WorldWideScience

Sample records for outage forecasting system

  1. Outage information system

    International Nuclear Information System (INIS)

    Svengren, Haakan; Meyer, Brita Diskerud

    2005-09-01

    Today's control room systems are designed to operate during power operation, and there is clearly a need for a system to support control room personnel in automatically supervising the status of the plant during the outage period. In order to improve the supervision of Nuclear Power Plants during outages, three prototypes of the Outage Information system have been designed by the Halden Project, one for PWR and two for BWR. The Outage Information System is presented on a large screen, centrally placed in the control room. There will be a PC connected to manage the system. By using signals from the process as input to logic diagrams reflecting the plant's Safety Technical Specifications, the system automatically is supervising that requirements in Safety Technical Specifications are fulfilled during all plant states of the outage period. The system also automatically gives an overview of the status of safety systems and electrical bus bars. Alarm will occur if a requirement in the Safety Technical Specifications is not fulfilled or if a component planned to be ready for operation, is inoperable. In addition, selected measurements being important during the outage period are presented on the large screen. Which measurements and in which way the values will be presented, depends on the plant's control room design and work practice. (Author)

  2. Lightning-generated whistler waves observed by probes on the Communication/Navigation Outage Forecast System satellite at low latitudes

    Science.gov (United States)

    Holzworth, R. H.; McCarthy, M. P.; Pfaff, R. F.; Jacobson, A. R.; Willcockson, W. L.; Rowland, D. E.

    2011-06-01

    Direct evidence is presented for a causal relationship between lightning and strong electric field transients inside equatorial ionospheric density depletions. In fact, these whistler mode plasma waves may be the dominant electric field signal within such depletions. Optical lightning data from the Communication/Navigation Outage Forecast System (C/NOFS) satellite and global lightning location information from the World Wide Lightning Location Network are presented as independent verification that these electric field transients are caused by lightning. The electric field instrument on C/NOFS routinely measures lightning-related electric field wave packets or sferics, associated with simultaneous measurements of optical flashes at all altitudes encountered by the satellite (401-867 km). Lightning-generated whistler waves have abundant access to the topside ionosphere, even close to the magnetic equator.

  3. An Overview of Scientific and Space Weather Results from the Communication/Navigation Outage Forecasting System (C/NOFS) Mission

    Science.gov (United States)

    Pfaff, R.; de la Beaujardiere, O.; Hunton, D.; Heelis, R.; Earle, G.; Strauss, P.; Bernhardt, P.

    2012-01-01

    The Communication/Navigation Outage Forecasting System (C/NOFS) Mission of the Air Force Research Laboratory is described. C/NOFS science objectives may be organized into three categories: (1) to understand physical processes active in the background ionosphere and thermosphere in which plasma instabilities grow; (2) to identify mechanisms that trigger or quench the plasma irregularities responsible for signal degradation; and (3) to determine how the plasma irregularities affect the propagation of electromagnetic waves. The satellite was launched in April, 2008 into a low inclination (13 deg), elliptical (400 x 850 km) orbit. The satellite sensors measure the following parameters in situ: ambient and fluctuating electron densities, AC and DC electric and magnetic fields, ion drifts and large scale ion composition, ion and electron temperatures, and neutral winds. C/NOFS is also equipped with a GPS occultation receiver and a radio beacon. In addition to the satellite sensors, complementary ground-based measurements, theory, and advanced modeling techniques are also important parts of the mission. We report scientific and space weather highlights of the mission after nearly four years in orbit

  4. Predicting Power Outages Using Multi-Model Ensemble Forecasts

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

    2017-12-01

    Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

  5. Outage capacity of multicarrier systems

    KAUST Repository

    Yilmaz, Ferkan; Alouini, Mohamed-Slim

    2010-01-01

    The probability density function and the cumulative distribution function of the product of shifted Gamma variates are obtained in terms of the generalized Fox's H function. Using these new results, the exact outage capacity of multi carrier transmission through a slow Nakagami-m fading channel is presented. Moreover, it is shown that analytical and simulation results are in perfect agreement. © 2009 IEEE.

  6. Outage capacity of multicarrier systems

    KAUST Repository

    Yilmaz, Ferkan

    2010-01-01

    The probability density function and the cumulative distribution function of the product of shifted Gamma variates are obtained in terms of the generalized Fox\\'s H function. Using these new results, the exact outage capacity of multi carrier transmission through a slow Nakagami-m fading channel is presented. Moreover, it is shown that analytical and simulation results are in perfect agreement. © 2009 IEEE.

  7. Integrated outage management: Leveraging utility system assets including GIS and AMR for optimum outage response

    Energy Technology Data Exchange (ETDEWEB)

    Finamore, E. P.

    2004-02-01

    The control of electrical system outages is discussed. The principal argument advanced is that traditional stand-alone methods of outage response will no longer get the job done without utility companies integrating their outage management systems with other system assets such as GIS (geographic information system) and AMR (advanced metering systems). Many meter reading systems, while primarily supporting customer billing, can also provide outage alarm and some are also capable of service restoration notification, which is an invaluable benefit to service operators since it obviates the need for verifying system restoration by labour-intensive on-site visits or customer call-backs. If successfully leveraged, optimization of all utility assets and improvements in labour productivity can results in improved outage management performance gains without affecting performance in other areas.

  8. Line outage contingency analysis including the system islanding ...

    African Journals Online (AJOL)

    The optimally ordered sparse [Bʹ], [Bʺ] matrices for the integrated system are used for load flow analysis to determine modified values of voltage phase angles [d] and bus voltages [V] to determine the over loading effect on the remaining lines due to outage of a selected line outage contingency. In case of over loading in ...

  9. Outage Analysis of Asymmetric RF-FSO Systems

    KAUST Repository

    Ansari, Imran Shafique; Abdallah, Mohamed M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2017-01-01

    In this work, the outage performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) channels cascaded with free-space optical (FSO) links is presented. The RF links are modeled by the Rayleigh fading

  10. Outage performance of cognitive radio systems with Improper Gaussian signaling

    KAUST Repository

    Amin, Osama

    2015-06-14

    Improper Gaussian signaling has proved its ability to improve the achievable rate of the systems that suffer from interference compared with proper Gaussian signaling. In this paper, we first study impact of improper Gaussian signaling on the performance of the cognitive radio system by analyzing the outage probability of both the primary user (PU) and the secondary user (SU). We derive exact expression of the SU outage probability and upper and lower bounds for the PU outage probability. Then, we design the SU signal by adjusting its transmitted power and the circularity coefficient to minimize the SU outage probability while maintaining a certain PU quality-of-service. Finally, we evaluate the proposed bounds and adaptive algorithms by numerical results.

  11. Line outage contingency analysis including the system islanding scenario

    Energy Technology Data Exchange (ETDEWEB)

    Hazarika, D.; Bhuyan, S. [Assam Engineering College, Jalukbari, Guwahati 781013 (India); Chowdhury, S.P. [Jadavpur University, Jadavpur, Kolkata 700 032 (India)

    2006-05-15

    The paper describes an algorithm for determining the line outage contingency of a line taking into account of line over load effect in remaining lines and subsequent tripping of over loaded line(s) leading to possible system split or islanding of a power system. The optimally ordered sparse [B'], [B'] matrices for the integrated system are used for load flow analysis to determine modified values of voltage phase angles [{delta}] and bus voltages [V] to determine the over loading effect on the remaining lines due to outage of a selected line outage contingency. In case of over loading in remaining line(s), the over loaded lines are removed from the system and a topology processor is used to find the islands. A fast decoupled load flow (FDLF) analysis is carried out for finding out the system variables for the islanded (or single island) system by incorporating appropriate modification in the [B'] and [B'] matrices of the integrated system. Line outage indices based on line overload, loss of load, loss of generation and static voltage stability are computed to indicate severity of a line outage of a selected line. (author)

  12. Efficient Simulation of the Outage Probability of Multihop Systems

    KAUST Repository

    Ben Issaid, Chaouki; Alouini, Mohamed-Slim; Tempone, Raul

    2017-01-01

    In this paper, we present an efficient importance sampling estimator for the evaluation of the outage probability of multihop systems with amplify-and-forward channel state-information-assisted. The proposed estimator is endowed with the bounded relative error property. Simulation results show a significant reduction in terms of number of simulation runs compared to naive Monte Carlo.

  13. Efficient Simulation of the Outage Probability of Multihop Systems

    KAUST Repository

    Ben Issaid, Chaouki

    2017-10-23

    In this paper, we present an efficient importance sampling estimator for the evaluation of the outage probability of multihop systems with amplify-and-forward channel state-information-assisted. The proposed estimator is endowed with the bounded relative error property. Simulation results show a significant reduction in terms of number of simulation runs compared to naive Monte Carlo.

  14. Does Your Domestic Photovoltaic Energy System Survive Grid Outages?

    Directory of Open Access Journals (Sweden)

    Marijn R. Jongerden

    2016-09-01

    Full Text Available Domestic renewable energy systems, including photovoltaic energy generation, as well as local storage, are becoming increasingly popular and economically feasible, but do come with a wide range of options. Hence, it can be difficult to match their specification to specific customer’s needs. Next to the usage-specific demand profiles and location-specific production profiles, local energy storage through the use of batteries is becoming increasingly important, since it allows one to balance variations in production and demand, either locally or via the grid. Moreover, local storage can also help to ensure a continuous energy supply in the presence of grid outages, at least for a while. Hybrid Petri net (HPN models allow one to analyze the effect of different battery management strategies on the continuity of such energy systems in the case of grid outages. The current paper focuses on one of these strategies, the so-called smart strategy, that reserves a certain percentage of the battery capacity to be only used in case of grid outages. Additionally, we introduce a new strategy that makes better use of the reserved backup capacity, by reducing the demand in the presence of a grid outage through a prioritization mechanism. This new strategy, called power-save, only allows the essential (high-priority demand to draw from the battery during power outages. We show that this new strategy outperforms previously-proposed strategies through a careful analysis of a number of scenarios and for a selection of survivability measures, such as minimum survivability per day, number of survivable hours per day, minimum survivability per year and various survivability quantiles.

  15. Outage Analysis of Asymmetric RF-FSO Systems

    KAUST Repository

    Ansari, Imran Shafique

    2017-03-20

    In this work, the outage performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) channels cascaded with free-space optical (FSO) links is presented. The RF links are modeled by the Rayleigh fading distribution and the FSO links are modeled by Malaga (M) turbulence distribution. The FSO links account for pointing errors and both types of detection techniques (i.e. heterodyne detection as well as intensity modulation/direct detection (IM/DD)). Transmit diversity is applied at the source, selection combining is applied at the destination, and the relay is equipped with single RF receive antenna and single aperture for relaying the information over FSO links. With this model, a new exact closed-form expression is derived for the outage probability of the end-to- end signal-to-noise ratio of such communication systems in terms of the Meijer\\'s G function under fixed amplify-and-forward relay scheme. All new analytical results are verified via computer-based Monte-Carlo simulations and are illustrated by some selected numerical results.

  16. Asymmetric Hardware Distortions in Receive Diversity Systems: Outage Performance Analysis

    KAUST Repository

    Javed, Sidrah; Amin, Osama; Ikki, Salama S.; Alouini, Mohamed-Slim

    2017-01-01

    This paper studies the impact of asymmetric hardware distortion (HWD) on the performance of receive diversity systems using linear and switched combining receivers. The asymmetric attribute of the proposed model motivates the employment of improper Gaussian signaling (IGS) scheme rather than the traditional proper Gaussian signaling (PGS) scheme. The achievable rate performance is analyzed for the ideal and non-ideal hardware scenarios using PGS and IGS transmission schemes for different combining receivers. In addition, the IGS statistical characteristics are optimized to maximize the achievable rate performance. Moreover, the outage probability performance of the receive diversity systems is analyzed yielding closed form expressions for both PGS and IGS based transmission schemes. HWD systems that employ IGS is proven to efficiently combat the self interference caused by the HWD. Furthermore, the obtained analytic expressions are validated through Monte-Carlo simulations. Eventually, non-ideal hardware transceivers degradation and IGS scheme acquired compensation are quantified through suitable numerical results.

  17. Asymmetric Hardware Distortions in Receive Diversity Systems: Outage Performance Analysis

    KAUST Repository

    Javed, Sidrah

    2017-02-22

    This paper studies the impact of asymmetric hardware distortion (HWD) on the performance of receive diversity systems using linear and switched combining receivers. The asymmetric attribute of the proposed model motivates the employment of improper Gaussian signaling (IGS) scheme rather than the traditional proper Gaussian signaling (PGS) scheme. The achievable rate performance is analyzed for the ideal and non-ideal hardware scenarios using PGS and IGS transmission schemes for different combining receivers. In addition, the IGS statistical characteristics are optimized to maximize the achievable rate performance. Moreover, the outage probability performance of the receive diversity systems is analyzed yielding closed form expressions for both PGS and IGS based transmission schemes. HWD systems that employ IGS is proven to efficiently combat the self interference caused by the HWD. Furthermore, the obtained analytic expressions are validated through Monte-Carlo simulations. Eventually, non-ideal hardware transceivers degradation and IGS scheme acquired compensation are quantified through suitable numerical results.

  18. Outage performance of cognitive radio systems with Improper Gaussian signaling

    KAUST Repository

    Amin, Osama; Abediseid, Walid; Alouini, Mohamed-Slim

    2015-01-01

    design the SU signal by adjusting its transmitted power and the circularity coefficient to minimize the SU outage probability while maintaining a certain PU quality-of-service. Finally, we evaluate the proposed bounds and adaptive algorithms by numerical

  19. Underlay Cognitive Radio Systems with Improper Gaussian Signaling: Outage Performance Analysis

    KAUST Repository

    Amin, Osama

    2016-03-29

    Improper Gaussian signaling has the ability over proper (conventional) Gaussian signaling to improve the achievable rate of systems that suffer from interference. In this paper, we study the impact of using improper Gaussian signaling on the performance limits of the underlay cognitive radio system by analyzing the achievable outage probability of both the primary user (PU) and secondary user (SU). We derive the exact outage probability expression of the SU and construct upper and lower bounds of the PU outage probability which results in formulating an approximate expression of the PU outage probability. This allows us to design the SU signal by adjusting its transmitted power and the circularity coefficient to minimize the SU outage probability while maintaining a certain PU quality-of-service. Finally, we evaluate the derived expressions for both the SU and the PU and the corresponding adaptive algorithms by numerical results.

  20. Underlay Cognitive Radio Systems with Improper Gaussian Signaling: Outage Performance Analysis

    KAUST Repository

    Amin, Osama; Abediseid, Walid; Alouini, Mohamed-Slim

    2016-01-01

    Improper Gaussian signaling has the ability over proper (conventional) Gaussian signaling to improve the achievable rate of systems that suffer from interference. In this paper, we study the impact of using improper Gaussian signaling on the performance limits of the underlay cognitive radio system by analyzing the achievable outage probability of both the primary user (PU) and secondary user (SU). We derive the exact outage probability expression of the SU and construct upper and lower bounds of the PU outage probability which results in formulating an approximate expression of the PU outage probability. This allows us to design the SU signal by adjusting its transmitted power and the circularity coefficient to minimize the SU outage probability while maintaining a certain PU quality-of-service. Finally, we evaluate the derived expressions for both the SU and the PU and the corresponding adaptive algorithms by numerical results.

  1. Failed fuel rod detection system and computerized manipulator during outages

    International Nuclear Information System (INIS)

    Boehm, H.H.; Foerch, H.

    1984-01-01

    During regular outages spent fuel assemblies need to be replaced and relocated within the core. Defective fuel rods in particular fuel assemblies have to be removed from further service and before delivery of such faulty fuel assemblies to a reprocessing plant. The system which Brown Boveri Reaktor GmbH and Krautkraemer have developed in the Federal Republic of Germany is capable of directly locating the defective rods in a proper fuel assembly. Inspection times are comparable to those of standard sipping methods, with the advantages of immediately available results and direct identification of the defective fuel rods. During the repair of fuel assemblies this system allows withdrawal of individual defective rods. With the sipping method all the fuel rods of a defective fuel assembly need to be removed and inspected by eddy current testing. During steam generator inspection and repair personnel are exposed to ample radiation. A remotely controlled, computerized manipulator was used to significantly reduce the radiation dose by automating steps in the procedures; at the same time inspection and repair times were reduced. The main features of the manipulator are a rigid component construction of the leg and two arms, and a resolver control for horizontal and vertical motion that enables rapid and accurate access to a desired tube (author)

  2. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  3. Outages planning

    International Nuclear Information System (INIS)

    Blanquer, N.

    2010-01-01

    The reason of a nuclear power plant outage seems easy. Replace 1/3 of the total core fuel inside reactor for a new, store the old one in a pool and shuffle the rest 2/3 in other positions in the core to optimize fuel burn up. Also is needed to make the preventive, corrective and conservative maintenance, the selected design changes and the regulatory and technical requirements for equipment and systems. To make the plant outage strategy for all the above pack with nuclear safety not challenged is the objective of this article for the Spanish Nuclear Society magazine. (Author)

  4. International outage coding system for nuclear power plants. Results of a co-ordinated research project

    International Nuclear Information System (INIS)

    2004-05-01

    The experience obtained in each individual plant constitutes the most relevant source of information for improving its performance. However, experience of the level of the utility, country and worldwide is also extremely valuable, because there are limitations to what can be learned from in-house experience. But learning from the experience of others is admittedly difficult, if the information is not harmonized. Therefore, such systems should be standardized and applicable to all types of reactors satisfying the needs of the broad set of nuclear power plant operators worldwide and allowing experience to be shared internationally. To cope with the considerable amount of information gathered from nuclear power plants worldwide, it is necessary to codify the information facilitating the identification of causes of outages, systems or component failures. Therefore, the IAEA established a sponsored Co-ordinated Research Project (CRP) on the International Outage Coding System to develop a general, internationally applicable system of coding nuclear power plant outages, providing worldwide nuclear utilities with a standardized tool for reporting outage information. This TECDOC summarizes the results of this CRP and provides information for transformation of the historical outage data into the new coding system, taking into consideration the existing systems for coding nuclear power plant events (WANO, IAEA-IRS and IAEA PRIS) but avoiding duplication of efforts to the maximum possible extent

  5. Climate Forecast System

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

  6. Power Outages

    Science.gov (United States)

    ... Publications Emergency Alerts Preparedness Portal Preparedness Messaging Calendar Social Media Preparedness Toolkits Preparedness News Languages About Us Build a Kit Close Search Enter Search Term(s): Main Content Home Be Informed Power Outages Power Outages Extended power outages may impact ...

  7. Forecasting in Complex Systems

    Science.gov (United States)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  8. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer

    2016-02-26

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

  9. Prediction of power system frequency response after generator outages using neural nets

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M B; Popovic, D P [Electrotechnicki Inst. ' Nikola Tesla' , Belgrade (Yugoslavia); Sobajic, D J; Pao, Y -H [Case Western Reserve Univ., Cleveland, OH (United States)

    1993-09-01

    A new methodology is presented for estimating the frequency behaviour of power systems necessary for an indication of under-frequency load shedding in steady-state security assessment. It is well known that large structural disturbances such as generator tripping or load outages can initiate cascading outages, system separation into islands, and even the complete breakup. The approach provides a fairly accurate method of estimating the system average frequency response without making simplifications or neglecting non-linearities and small time constants in the equations of generating units, voltage regulators and turbines. The efficiency of the new procedure is demonstrated using the New England power system model for a series of characteristic perturbations. The validity of the proposed approach is verified by comparison with the simulation of short-term dynamics including effects of control and automatic devices. (author)

  10. Outage and Capacity Performance Evaluation of Distributed MIMO Systems over a Composite Fading Channel

    Directory of Open Access Journals (Sweden)

    Wenjie Peng

    2014-01-01

    Full Text Available The exact closed-form expressions regarding the outage probability and capacity of distributed MIMO (DMIMO systems over a composite fading channel are derived. This is achieved firstly by using a lognormal approximation to a gamma-lognormal distribution when a mobile station (MS in the cell is in a fixed position, and the so-called maximum ratio transmission/selected combining (MRT-SC and selected transmission/maximum ratio combining (ST-MRC schemes are adopted in uplink and downlink, respectively. Then, based on a newly proposed nonuniform MS cell distribution model, which is more consistent with the MS cell hotspot distribution in an actual communication environment, the average outage probability and capacity formulas are further derived. Finally, the accuracy of the approximation method and the rationality of the corresponding theoretical analysis regarding the system performance are proven and illustrated by computer simulations.

  11. Decision support system for outage management and automated crew dispatch

    Science.gov (United States)

    Kang, Ning; Mousavi, Mirrasoul

    2018-01-23

    A decision support system is provided for utility operations to assist with crew dispatch and restoration activities following the occurrence of a disturbance in a multiphase power distribution network, by providing a real-time visualization of possible location(s). The system covers faults that occur on fuse-protected laterals. The system uses real-time data from intelligent electronics devices coupled with other data sources such as static feeder maps to provide a complete picture of the disturbance event, guiding the utility crew to the most probable location(s). This information is provided in real-time, reducing restoration time and avoiding more costly and laborious fault location finding practices.

  12. Does Your Domestic Photovoltaic Energy System Survive Grid Outages?

    NARCIS (Netherlands)

    Jongerden, M.R.; Hüls, Jannik; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.

    2016-01-01

    Domestic renewable energy systems, including photovoltaic energy generation, as well as local storage, are becoming increasingly popular and economically feasible, but do come with a wide range of options. Hence, it can be difficult to match their specification to specific customer’s needs. Next to

  13. Black Sea coastal forecasting system

    Directory of Open Access Journals (Sweden)

    A. I. Kubryakov

    2012-03-01

    Full Text Available The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

  14. Outage performance of two-way DF relaying systems with a new relay selection metric

    KAUST Repository

    Hyadi, Amal

    2012-04-01

    This paper investigates a new constrained relay selection scheme for two-way relaying systems where two end terminals communicate simultaneously via a relay. The introduced technique is based on the maximization of the weighted sum rate of both users. To evaluate the performance of the proposed system, the outage probability is derived in a general case (where an arbitrary channel is considered), and then over independently but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. The analytical results are verified through simulations. © 2012 IEEE.

  15. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  16. Outage Analysis of Practical FSO/RF Hybrid System With Adaptive Combining

    KAUST Repository

    Rakia, Tamer

    2015-08-01

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless transmission. We present and analyze a transmission scheme for the hybrid FSO/RF communication system based on adaptive combining. Specifically, only FSO link is active as long as the instantaneous signal-to-noise ratio (SNR) at the FSO receiver is above a certain threshold level. When it falls below this threshold level, the RF link is activated along with the FSO link and the signals from the two links are combined at the receiver using a dual-branch maximal ratio combiner. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed hybrid system is obtained. This CDF expression is used to study the system outage performance. Numerical examples are presented to compare the outage performance of the proposed hybrid FSO/RF system with that of the FSO-only and RF-only systems. © 1997-2012 IEEE.

  17. Placement of Synchronized Measurements for Power System Observability during Cascaded Outages

    Science.gov (United States)

    Thirugnanasambandam, Venkatesh; Jain, Trapti

    2017-11-01

    Cascaded outages often result in power system islanding followed by a blackout and therefore considered as a severe disturbance. Maintaining the observability of each island may help in taking proper control actions to preserve the stability of individual islands thus, averting system collapse. With this intent, a strategy for placement of synchronized measurements, which can be obtained from phasor measurement units (PMU), has been proposed in this paper to keep the system observable during cascaded outages also. Since, all the cascaded failures may not lead to islanding situations, therefore, failures leading to islanding as well as non-islanding situations have been considered. A topology based algorithm has been developed to identify the islanding/non-islanding condition created by a particular cascaded event. Additional contingencies such as single line loss and single PMU failure have also been considered after the occurrence of cascaded events. The proposed method is further extended to incorporate the measurement redundancy, which is desirable for a reliable state estimation. The proposed scheme is tested on IEEE 14-bus, IEEE 30-bus and a practical Indian 246-bus networks. The numerical results ensure the observability of the power system under system intact as well as during cascaded islanding and non-islanding disturbances.

  18. LIDAR AND INS FUSION IN PERIODS OF GPS OUTAGES FOR MOBILE LASER SCANNING MAPPING SYSTEMS

    Directory of Open Access Journals (Sweden)

    I. Klein

    2012-09-01

    Full Text Available Mobile laser scanning systems are becoming an increasingly popular means to obtain 3D coverage on a large scale. To perform the mapping, the exact position of the vehicle must be known throughout the trajectory. Exact position is achieved via integration of Global Positioning Systems (GPS and Inertial Navigation Systems (INS. Yet, in urban environments, cases of complete or even partial GPS outages may occur leaving the navigation solution to rely only on the INS. The INS navigation solution degrades with time as the Inertial Measurement Unit (IMU measurements contains noise, which permeates into the navigation equations. Degradation of the position determination leads to loss of data in such segments. To circumvent such drift and its effects, we propose fusing INS with lidar data by using building edges. This detection of edges is then translated into position data, which is used as an aiding to the INS. It thereby enables the determination of the vehicle position with a satisfactory level accuracy, sufficient to perform the laser-scanning based mapping in those outage periods.

  19. Evaluation of mean time between forced outage for reactor protection system using RBD and failure rate

    International Nuclear Information System (INIS)

    Lee, D. Y.; Park, J. H.; Hwang, I. K.; Cha, K. H.; Choi, J. K.; Lee, K. Y.; Park, J. K.

    2001-01-01

    The design life of nuclear power plants (NPPs) under recent construction is about fifty to sixty years. However, the duration that equipments of control systems operate without failures is at most five to ten years. Design for diversity and adequate maintenance strategy are required for NPP protection system in order to use the control equipment which has shorter life time than the design life of NPP. Fault Tree Analysis (FTA) technique, which has been applied to Probabilistics Safety Analysis (PSA), has been introduced to quantitatively evaluate the reliability of NPP I and C systems. The FTA, however, cannot properly consider the effect of maintenance. In this work, we have reviewed quantitative reliability evaluation techniques using the reliability block diagram and failure rates and applied it to the evaluation of mean time between forced outage for reactor protection system

  20. Outage probability of dual-hop FSO fixed gain relay transmission systems

    KAUST Repository

    Zedini, Emna

    2016-12-24

    In this paper, we analyze the end-to-end performance of dual-hop free-space optical (FSO) fixed gain relaying systems in the presence of atmospheric turbulence as well as pointing errors. More specifically, an exact closed-form expression for the outage probability is presented in terms of the bivariate Fox\\'s H function that accounts for both heterodyne detection as well as intensity modulation with direct detection. At high signal-to-noise ratio (SNR) regime, we provide very tight asymptotic result for this performance metric in terms of simple elementary functions. By using dual-hop FSO relaying, we demonstrate a better system performance as compared to the single FSO link. Numerical and Monte-Carlo simulation results are provided to verify the accuracy of the newly proposed results, and a perfect agreement is observed.

  1. Air traffic control : good progress on interim replacement for outage-plagued system, but risks can be further reduced

    Science.gov (United States)

    1996-10-01

    Certain air traffic control(ATC) centers experienced a series of major outages, : some of which were caused by the Display Channel Complex or DCC-a mainframe : computer system that processes radar and other data into displayable images on : controlle...

  2. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  3. Coastal risk forecast system

    Science.gov (United States)

    Sabino, André; Poseiro, Pedro; Rodrigues, Armanda; Reis, Maria Teresa; Fortes, Conceição J.; Reis, Rui; Araújo, João

    2018-03-01

    The run-up and overtopping by sea waves are two of the main processes that threaten coastal structures, leading to flooding, destruction of both property and the environment, and harm to people. To build early warning systems, the consequences and associated risks in the affected areas must be evaluated. It is also important to understand how these two types of spatial information integrate with sensor data sources and the risk assessment methodology. This paper describes the relationship between consequences and risk maps, their role in risk management and how the HIDRALERTA system integrates both aspects in its risk methodology. It describes a case study for Praia da Vitória Port, Terceira Island, Azores, Portugal, showing that the main innovations in this system are twofold: it represents the overtopping flow and consequent flooding, which are critical for coastal and port areas protected by maritime structures, and it works also as a risk assessment tool, extremely important for long-term planning and decision-making. Moreover, the implementation of the system considers possible known variability issues, enabling changes in its behaviour as needs arise. This system has the potential to become a useful tool for the management of coastal and port areas, due to its capacity to effectively issue warnings and assess risks.

  4. Coastal risk forecast system

    Science.gov (United States)

    Sabino, André; Poseiro, Pedro; Rodrigues, Armanda; Reis, Maria Teresa; Fortes, Conceição J.; Reis, Rui; Araújo, João

    2018-04-01

    The run-up and overtopping by sea waves are two of the main processes that threaten coastal structures, leading to flooding, destruction of both property and the environment, and harm to people. To build early warning systems, the consequences and associated risks in the affected areas must be evaluated. It is also important to understand how these two types of spatial information integrate with sensor data sources and the risk assessment methodology. This paper describes the relationship between consequences and risk maps, their role in risk management and how the HIDRALERTA system integrates both aspects in its risk methodology. It describes a case study for Praia da Vitória Port, Terceira Island, Azores, Portugal, showing that the main innovations in this system are twofold: it represents the overtopping flow and consequent flooding, which are critical for coastal and port areas protected by maritime structures, and it works also as a risk assessment tool, extremely important for long-term planning and decision-making. Moreover, the implementation of the system considers possible known variability issues, enabling changes in its behaviour as needs arise. This system has the potential to become a useful tool for the management of coastal and port areas, due to its capacity to effectively issue warnings and assess risks.

  5. Outage management

    International Nuclear Information System (INIS)

    Anonymous

    2006-01-01

    Since constructing Japan's first PWR plant, Mihama Unit 1, MHI has been working to upgrade its technologies. The ongoing goal is to provide PWR nuclear power plants with levels of reliability, safety, economy operation and maintainability unparalleled in the world market. To fulfill its obligations and responsibility as an integrated plant manufacturer in the nuclear industry, MHI keeps a close eye on every facility, component, device and sub-component from the viewpoint of its customers. Backed by its rich experience and advanced technology, MHI continues to enhance the safety, reliability and economy of nuclear plants introducing improvements at every level. MHI continues to develop and improve diagnostic and inspection technologies based on its more than 30 years of experience in inspection and servicing the major and auxiliary facilities within nuclear power plants. MHI secures the integrity of components by developing and deploying technologies to minimize the wear of components and to repair and replace parts either degraded by age or unduly susceptible to wear. MHI backs its development of these technologies with its comprehensive technical capabilities in the design of remote operation equipment and electro mechanics as well as its expertise in basic technologies such as welding and machining. Mitsubishi Heavy Industries, Ltd. is not only a PWR plant constructor, but also offers complete outage support and component services. In partnership with our customers, MHI is helping to reduce outage duration, radiation exposure and costs, by providing its state of the art engineering knowledge, advanced non-destructive examination, inspection, maintenance and repair technologies mentioned above. MHI is performing large equipment refurbishment such as Steam Generator Replacement, Reactor Vessel Head Replacement, LP/HP turbine replacement, and recently completed the first Core Internal Replacement in the world. The following activities are part of the outage

  6. Global Forecast System (GFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and...

  7. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  8. Major outage trends in light water reactors. Interim report

    International Nuclear Information System (INIS)

    Burns, E.T.

    1978-04-01

    The report is a summary of the major outages which occurred in light water reactor plants during the period January 1971 through June 1977. Only those outages greater than 100 hours duration (exclusive of refueling outages) are included in the report. The trends in outages related to various reactor systems and components are presented as a function of plant age, and alternatively, calendar year. The principal contributors to major outages are ranked by their effect on the overall outage time for PWRs and BWRs. In addition, the outage history of each operating nuclear plant greater than 150 MWe is presented, along with a brief summary of those outages greater than two months duration

  9. Outage and ser performance of spectrum sharing system with TAS/MRC

    KAUST Repository

    Khan, Fahd Ahmed

    2013-06-01

    Capacity of the secondary network degrades due to the interference constraint from the primary network. The secondary network capacity can be enhanced by means of spatial diversity, that can be achieved by adding multiple antennas on the terminals. In this paper, the performance of a multiple-input multiple-output (MIMO) secondary link with transmit antenna selection (TAS) at the transmitter and maximum ratio combining (MRC) at the receiver is analysed. A peak transmit power constraint is considered in addition to the interference power constraint. For a Rayleigh faded channel, closed-form expression for the outage probability of a MIMO cognitive system (MIMO-CS) with TAS/MRC is derived. In addition, closed-form expressions of the moment generating function and the symbol error rate are also obtained. The performance of this system is analyzed for asymptotic regimes and it is shown that TAS/MRC in a MIMO-CS achieves a generalized diversity order of nTnR, where nT and nR are the number of transmit and receive antennas, respectively. Numerical results are also presented to corroborate the derived analytical results. © 2013 IEEE.

  10. Secrecy Outage of Max-Min TAS Scheme in MIMO-NOMA Systems

    KAUST Repository

    Lei, Hongjiang

    2018-04-09

    This paper considers a secure non-orthogonal multiple access system, where confidential messages are transmitted from a base station to multiple legitimate destinations and wiretapped by multiple illegitimate receivers. It is assumed that all the channels experience Nakagami-m fading model and all the nodes are equipped with multiple antennas, respectively. Both non-colluding and colluding eavesdroppers are respectively considered. Max-min (MM) transmit antenna selection (TAS) strategy is adopted to improve the secrecy performance of the target system, in which both users in user paring are considered simultaneously. In particular, closed-form expressions for the cumulative distribution function of the signal-to-interference-noise ratio at the legitimate user are derived firstly. Then we obtain the exact and asymptotic analytical results in a closed form for the secrecy outage probability of MM TAS scheme. Monte-Carlo simulation results are presented to corroborate the correctness of the analysis. The results show that the secrecy diversity order is zero and non-zero for fixed and dynamic power allocations, respectively.

  11. Application of 4-Face Fuel Visual Inspection System during Outage in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Shin, J. C.; Kim, J. I.; Choi, C. B.; Kim, Y. C.; Kang, C. B.

    2008-01-01

    Recently, as a measure to reduce an outage duration in nuclear power plants (NPPs), a four-face fuel visual inspection system (4-FFVIS) built in 4 cameras was introduced by Ahlberg Electronics, Sweden. The 4- FFVIS is used to inspect the external appearance of irradiated fuel assemblies in order to confirm their integrity against mechanical defects and foreign materials. Until now, however, a typical one-face fuel inspection system(1-FFVIS) has been world-widely utilized in NPPs. The 1-FFVIS requires four turns with 90 degree to inspect every face of the fuel assembly, causing a relatively long inspecting time. But the 4- FFVIS allow us to inspect every face of the fuel assembly at the same time. The inspection time with the 4-FFVIS may be less than two minutes per fuel assembly, whereas that with the 1-FFVIS is about six minutes per fuel assembly. In viewpoint of this merit, the 4-FFVIS is expected to be world-widely used in the near future. In this paper, the technical requirements necessary to develop the 4-FFVIS as well as some improvements to complement the current 4-FFVIS are described

  12. Secrecy Outage of Max-Min TAS Scheme in MIMO-NOMA Systems

    KAUST Repository

    Lei, Hongjiang; Zhang, Jianming; Park, Kihong; Xu, Peng; Zhang, Zufan; Pan, Gaofeng; Alouini, Mohamed-Slim

    2018-01-01

    This paper considers a secure non-orthogonal multiple access system, where confidential messages are transmitted from a base station to multiple legitimate destinations and wiretapped by multiple illegitimate receivers. It is assumed that all the channels experience Nakagami-m fading model and all the nodes are equipped with multiple antennas, respectively. Both non-colluding and colluding eavesdroppers are respectively considered. Max-min (MM) transmit antenna selection (TAS) strategy is adopted to improve the secrecy performance of the target system, in which both users in user paring are considered simultaneously. In particular, closed-form expressions for the cumulative distribution function of the signal-to-interference-noise ratio at the legitimate user are derived firstly. Then we obtain the exact and asymptotic analytical results in a closed form for the secrecy outage probability of MM TAS scheme. Monte-Carlo simulation results are presented to corroborate the correctness of the analysis. The results show that the secrecy diversity order is zero and non-zero for fixed and dynamic power allocations, respectively.

  13. Distributed power-line outage detection based on wide area measurement system.

    Science.gov (United States)

    Zhao, Liang; Song, Wen-Zhan

    2014-07-21

    In modern power grids, the fast and reliable detection of power-line outages is an important functionality, which prevents cascading failures and facilitates an accurate state estimation to monitor the real-time conditions of the grids. However, most of the existing approaches for outage detection suffer from two drawbacks, namely: (i) high computational complexity; and (ii) relying on a centralized means of implementation. The high computational complexity limits the practical usage of outage detection only for the case of single-line or double-line outages. Meanwhile, the centralized means of implementation raises security and privacy issues. Considering these drawbacks, the present paper proposes a distributed framework, which carries out in-network information processing and only shares estimates on boundaries with the neighboring control areas. This novel framework relies on a convex-relaxed formulation of the line outage detection problem and leverages the alternating direction method of multipliers (ADMM) for its distributed solution. The proposed framework invokes a low computational complexity, requiring only linear and simple matrix-vector operations. We also extend this framework to incorporate the sparse property of the measurement matrix and employ the LSQRalgorithm to enable a warm start, which further accelerates the algorithm. Analysis and simulation tests validate the correctness and effectiveness of the proposed approaches.

  14. Method for Evaluation of Outage Probability on Random Access Channel in Mobile Communication Systems

    Science.gov (United States)

    Kollár, Martin

    2012-05-01

    In order to access the cell in all mobile communication technologies a so called random-access procedure is used. For example in GSM this is represented by sending the CHANNEL REQUEST message from Mobile Station (MS) to Base Transceiver Station (BTS) which is consequently forwarded as an CHANNEL REQUIRED message to the Base Station Controller (BSC). If the BTS decodes some noise on the Random Access Channel (RACH) as random access by mistake (so- called ‘phantom RACH') then it is a question of pure coincidence which èstablishment cause’ the BTS thinks to have recognized. A typical invalid channel access request or phantom RACH is characterized by an IMMEDIATE ASSIGNMENT procedure (assignment of an SDCCH or TCH) which is not followed by sending an ESTABLISH INDICATION from MS to BTS. In this paper a mathematical model for evaluation of the Power RACH Busy Threshold (RACHBT) in order to guaranty in advance determined outage probability on RACH is described and discussed as well. It focuses on Global System for Mobile Communications (GSM) however the obtained results can be generalized on remaining mobile technologies (ie WCDMA and LTE).

  15. A Wind Forecasting System for Energy Application

    Science.gov (United States)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated

  16. Sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage.

    Science.gov (United States)

    Weng, Falu; Liu, Mingxin; Mao, Weijie; Ding, Yuanchun; Liu, Feifei

    2018-05-10

    The problem of sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage is investigated in this paper. The objective of designing controllers is to guarantee the stability and anti-disturbance performance of the closed-loop systems while some sensor outages happen. Firstly, based on matrix transformation, the state-space model of structural systems with sensor outages and uncertainties appearing in the mass, damping and stiffness matrices is established. Secondly, by considering most of those earthquakes or strong winds happen in a very short time, and it is often the peak values make the structures damaged, the finite-time stability analysis method is introduced to constrain the state responses in a given time interval, and the H-infinity stability is adopted in the controller design to make sure that the closed-loop system has a prescribed level of disturbance attenuation performance during the whole control process. Furthermore, all stabilization conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using the LMI Toolbox. Finally, numerical examples are given to demonstrate the effectiveness of the proposed theorems. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Integrated outages increase Surry's availability

    International Nuclear Information System (INIS)

    Harms, S.R.; Downs, J.L.

    1995-01-01

    This article describes how, through Virginia Power's and Westinghouse's goal-oriented planning philosophy, teamwork and commitment, average outage duration has decreased significantly. During the past 10 years Virginia Power and its nuclear steam supply system (NSSS) services vendor, Westinghouse Electric Corp., have developed a working partnership with one goal in mind: increasing the availability and capacity factors of the North Anna and Surry nuclear power stations while driving down the operating costs of the plants. The outage integration program, steam generator maintenance agreement (SGMA), and integrated radiological services program form the core of this relationship and helped Virginia Power complete one of the most successful outages in Surry Power Station's operating history

  18. Darlington Station outage - a maintenance perspective

    International Nuclear Information System (INIS)

    Plourde, J.; Marczak, J.; Stone, M.; Myers, R.; Sutton, K.

    1997-01-01

    Ontario Hydro's Darlington Nuclear Generating Station (4x881MW(e)net) has carried out its first station outage since full commercial operation. The outage presented challenges to the organization in terms of outage planning, support, management, and safe execution within the constraints of schedule, budget and resources. This paper will focus on the success of the outage maintenance program, identifying the major work programs - a vacuum structure and containment outage, an emergency service water system outage, an emergency coolant injection system outage, intake channel inspections, low pressure service water inspections, and significant outage maintenance work on each of the four reactor units. Planning for the outage was initiated early in anticipation of this important milestone in the station's life. Detailed safety reviews - nuclear, radiation, and conventional - were conducted in support of the planned maintenance program. System lineup and work protection were provided by the Station Operator work group. Work protection permitry was initiated well in advance of the outage. Station maintenance staff resources were bolstered in support of the outage to ensure program execution could be maintained within the schedule. Training programs were in place to ensure that expectations were clear and that high standards would be maintained. Materials management issues in support of maintenance activities were given high priority to ensure no delays to the planned work. Station management review and monitoring in preparation for and during the outage ensured that staff priorities remained focused. Lessons learned from the outage execution are being formalized in maintenance procedures and outage management procedures, and shared with the nuclear community. (author)

  19. Driving for shorter outages

    International Nuclear Information System (INIS)

    Tritch, S.

    1996-01-01

    Nuclear plant outages are necessary to complete activities that cannot be completed during the operating cycle, such as steam generator inspection and testing, refueling, installing modifications, and performing maintenance tests. The time devoted to performing outages is normally the largest contributor to plant unavailability. Similarly, outage costs are a sizable portion of the total plant budget. The scope and quality of work done during outages directly affects operating reliability and the number of unplanned outages. Improved management and planning of outages enhances the margin of safety during the outage and results in increased plant reliability. The detailed planning and in-depth preparation that has become a necessity for driving shorter outage durations has also produced safer outages and improved post-outage reliability. Short outages require both plant and vendor management to focus on all aspects of the outage. Short outage durations, such as 26 days at South Texas or 29 days at North Anna, require power plant inter-department and intra-department teamwork and communication and vendor participation. In this paper shorter and safer outage at the 3-loop plants in the United States are explained. (J.P.N.)

  20. Outages of electric power supply resulting from cable failures Boston Edison Company system

    Energy Technology Data Exchange (ETDEWEB)

    None

    1980-07-01

    Factual data are provided regarding 5 electric power supply interruptions that occurred in the Boston Metropolitan area during April to June, 1979. Common to all of these outages was the failure of an underground cable as the initiating event, followed by multiple equipment failures. There was significant variation in the voltage ratings and types of cables which failed. The investigation was unable to delineate a single specific Boston Edison design operating or maintenance practice that could be cited as the cause of the outages. After reviewing the investigative report the following actions were recommended: the development and implementation of a plan to eliminate the direct current cable network; develop a network outage restoration plan; regroup primary feeder cables wherever possible to minimize the number of circuits in manholes, and to separate feeders to high load density areas; develop a program to detect incipient cable faults; evaluate the separation of the north and south sections of Back Bay network into separate networks; and, as a minimum, install the necessary facilities to make it possible to re-energize one section without interfering with the other; and re-evaluate the cathodic protection scheme where necessary. (LCL)

  1. Toward a Marine Ecological Forecasting System

    Science.gov (United States)

    2010-06-01

    coral bleaching , living resource distribution, and pathogen progression). An operational ecological forecasting system depends upon the assimilation of...space scales (e.g., harmful algal blooms, dissolved oxygen concentration (hypoxia), water quality/beach closures, coral bleaching , living resource...advance. Two beaches in Lake Michigan have been selected for initial implementation. Forecasting Coral Bleaching in relation to Ocean Temperatures

  2. The Invasive Species Forecasting System

    Science.gov (United States)

    Schnase, John; Most, Neal; Gill, Roger; Ma, Peter

    2011-01-01

    The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these

  3. Cooperative AF Relaying in Spectrum-Sharing Systems: Outage Probability Analysis under Co-Channel Interferences and Relay Selection

    KAUST Repository

    Xia, Minghua

    2012-11-01

    For cooperative amplify-and-forward (AF) relaying in spectrum-sharing wireless systems, secondary users share spectrum resources originally licensed to primary users to communicate with each other and, thus, the transmit power of secondary transmitters is strictly limited by the tolerable interference powers at primary receivers. Furthermore, the received signals at a relay and at a secondary receiver are inevitably interfered by the signals from primary transmitters. These co-channel interferences (CCIs) from concurrent primary transmission can significantly degrade the performance of secondary transmission. This paper studies the effect of CCIs on outage probability of the secondary link in a spectrum-sharing environment. In particular, in order to compensate the performance loss due to CCIs, the transmit powers of a secondary transmitter and its relaying node are respectively optimized with respect to both the tolerable interference powers at the primary receivers and the CCIs from the primary transmitters. Moreover, when multiple relays are available, the technique of opportunistic relay selection is exploited to further improve system performance with low implementation complexity. By analyzing lower and upper bounds on the outage probability of the secondary system, this study reveals that it is the tolerable interference powers at primary receivers that dominate the system performance, rather than the CCIs from primary transmitters. System designers will benefit from this result in planning and designing next-generation broadband spectrum-sharing systems.

  4. Flood Forecasting in River System Using ANFIS

    International Nuclear Information System (INIS)

    Ullah, Nazrin; Choudhury, P.

    2010-01-01

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  5. A global flash flood forecasting system

    Science.gov (United States)

    Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

    2016-04-01

    The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

  6. Dust forecasting system in JMA

    International Nuclear Information System (INIS)

    Mikami, M; Tanaka, T Y; Maki, T

    2009-01-01

    JMAs dust forecasting information, which is based on a GCM dust model, is presented through the JMA website coupled with nowcast information. The website was updated recently and JMA and MOE joint 'KOSA' website was open from April 2008. Data assimilation technique will be introduced for improvement of the 'KOSA' information.

  7. Global Ensemble Forecast System (GEFS) [2.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  8. Outages planning; Planificacion de recargas

    Energy Technology Data Exchange (ETDEWEB)

    Blanquer, N.

    2010-07-01

    The reason of a nuclear power plant outage seems easy. Replace 1/3 of the total core fuel inside reactor for a new, store the old one in a pool and shuffle the rest 2/3 in other positions in the core to optimize fuel burn up. Also is needed to make the preventive, corrective and conservative maintenance, the selected design changes and the regulatory and technical requirements for equipment and systems. To make the plant outage strategy for all the above pack with nuclear safety not challenged is the objective of this article for the Spanish Nuclear Society magazine. (Author)

  9. FORMASY : forecasting and recruitment in manpower systems

    NARCIS (Netherlands)

    Wessels, J.; van Nunen, J.A.E.E.

    1975-01-01

    In this paper the tools are developed for forecasting and recruitment planning in a graded manpower system. Basic features of the presented approach are: - the system contains several grades or job categories in which the employees stay for a certain time before being promoted or leaving the system,

  10. Forecasting systemic impact in financial networks

    NARCIS (Netherlands)

    Hautsch, N.; Schaumburg, J.; Schienle, M.

    2014-01-01

    We propose a methodology for forecasting the systemic impact of financial institutions in interconnected systems. Utilizing a five-year sample including the 2008/9 financial crisis, we demonstrate how the approach can be used for the timely systemic risk monitoring of large European banks and

  11. Cycle 7 outage experience

    International Nuclear Information System (INIS)

    Gadeken, A.D.

    1986-03-01

    The scheduled 58-day refueling outage in preparation for the seventh operating cycle of the Fast Flux Test Facility (FFTF) was successfully completed three days ahead of schedule. The planning and execution of the outage was greatly aided by Project/2 automated scheduling capabilities. For example, the use of ''maintenance windows'' and resource loading capabilities was particularly effective. The value of the planning process was demonstrated by the smooth transition into the outage phase after an early shutdown and set the stage for our best outage to date

  12. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) Precipitation Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time...

  13. FORMASY : forecasting and recruitment in manpower systems

    NARCIS (Netherlands)

    Wessels, J.; van Nunen, J.A.E.E.

    1976-01-01

    In this paper the tools are developed for forecasting and recruitment planning in a eraded manpower system. Basic features of the presented approach arc: - the system contains several &fades or job catea:ories in which the employees slay for a certain time before being promoted or leaving the

  14. Review of Paks outage results 1990

    International Nuclear Information System (INIS)

    Lukacs, P.; Zsoldos, F.; Kiss, Z.

    1991-01-01

    The year 1990 was not the most successful from an outage point of view at the Paks Nuclear Power Plant in Hungary -there were one or two long delays. Work at unit 4 had a delay of 10 days because of an error made during assembling the reactor vessel. While the outage of unit 3 was running, a feedwater pipe hanger problem was discovered - several hangers were found displaced from the right position. A general inspection of the affected system was required and this took about 11 days. Information about each outage is presented on diagrams, making comparison easier. These diagrams give information about deviations from the outage plan, about work hours performed during outages, and about collective exposure. (author)

  15. Outage scheduling and implementation

    International Nuclear Information System (INIS)

    Allison, J.E.; Segall, P.; Smith, R.R.

    1986-01-01

    Successful preparation and implementation of an outage schedule and completion of scheduled and emergent work within an identified critical path time frame is a result of careful coordination by Operations, Work Control, Maintenance, Engineering, Planning and Administration and others. At the Fast Flux Test Facility (FFTF) careful planning has been responsible for meeting all scheduled outage critical paths

  16. FORECAST MANAGEMENT FOR THE ECONOMIC SYSTEM

    OpenAIRE

    Dragoº MICU; Cosmin LEFTER

    2011-01-01

    Existing turbulences in the economic environment assume a more responsible involvement from the manager’s behalf in the management process thus determing them to use adequate forms of managemet. In this context, this paper highlights the necessity of implementing management forecasting systems in the economic environment.

  17. Grid-connected photovoltaic (PV) systems with batteries storage as solution to electrical grid outages in Burkina Faso

    International Nuclear Information System (INIS)

    Abdoulaye, D; Koalaga, Z; Zougmore, F

    2012-01-01

    This paper deals with a key solution for power outages problem experienced by many African countries and this through grid-connected photovoltaic (PV) systems with batteries storage. African grids are characterized by an insufficient power supply and frequent interruptions. Due to this fact, users who especially use classical grid-connected photovoltaic systems are unable to profit from their installation even if there is sun. In this study, we suggest the using of a grid-connected photovoltaic system with batteries storage as a solution to these problems. This photovoltaic system works by injecting the surplus of electricity production into grid and can also deliver electricity as a stand-alone system with all security needed. To achieve our study objectives, firstly we conducted a survey of a real situation of one African electrical grid, the case of Burkina Faso (SONABEL: National Electricity Company of Burkina). Secondly, as study case, we undertake a sizing, a modeling and a simulation of a grid-connected PV system with batteries storage for the LAME laboratory at the University of Ouagadougou. The simulation shows that the proposed grid-connected system allows users to profit from their photovoltaic installation at any time even if the public electrical grid has some failures either during the day or at night.

  18. Road icing forecasting and detecting system

    Science.gov (United States)

    Xu, Hongke; Zheng, Jinnan; Li, Peiqi; Wang, Qiucai

    2017-05-01

    Regard for the facts that the low accuracy and low real-time of the artificial observation to determine the road icing condition, and it is difficult to forecast icing situation, according to the main factors influencing the road-icing, and the electrical characteristics reflected by the pavement ice layer, this paper presents an innovative system, that is, ice-forecasting of the highway's dangerous section. The system bases on road surface water salinity measurements and pavement temperature measurement to calculate the freezing point of water and temperature change trend, and then predicts the occurrence time of road icing; using capacitance measurements to verdict the road surface is frozen or not; This paper expounds the method of using single chip microcomputer as the core of the control system and described the business process of the system.

  19. Nuclear power plant outages

    International Nuclear Information System (INIS)

    1998-01-01

    The Finnish Radiation and Nuclear Safety Authority (STUK) controls nuclear power plant safety in Finland. In addition to controlling the design, construction and operation of nuclear power plants, STUK also controls refuelling and repair outages at the plants. According to section 9 of the Nuclear Energy Act (990/87), it shall be the licence-holder's obligation to ensure the safety of the use of nuclear energy. Requirements applicable to the licence-holder as regards the assurance of outage safety are presented in this guide. STUK's regulatory control activities pertaining to outages are also described

  20. Nuclear safety risk control in the outage of CANDU unit

    International Nuclear Information System (INIS)

    Wu Mingliang; Zheng Jianhua

    2014-01-01

    Nuclear fuel remains in the core during the outage of CANDU unit, but there are still nuclear safety risks such as reactor accidental criticality, fuel element failure due to inability to properly remove residual heat. Furthermore, these risks are aggravated by the weakening plant system configuration and multiple cross operations during the outage. This paper analyzes the phases where there are potential nuclear safety risks on the basis of the typical critical path arrangement of the outage of Qinshan NPP 3 and introduces a series of CANDU-specific risk control measures taken during the past plant outages to ensure nuclear safety during the unit outage. (authors)

  1. WNP-2 outage safety review methodology

    International Nuclear Information System (INIS)

    Chiang, Albert; Fu, James

    2004-01-01

    A practical and versatile method was developed in the flow chart and checklist forms to show the defense-in-depth for various key safety functions of a nuclear power plant during shutdown. Using four different colors (green, yellow, orange, and red) for indication of levels of defense-in-depth is visually impressive, easy to understand, and was adopted by the outage management personnel as a convenient reference tool for maintenance activity planning before the outage, and schedule changes during the outage. This paper describes the method and its application at Washington Public Power Supply System's Nuclear Project 2 (WNP-2). (author)

  2. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-11-01

    This single page document is the November 1, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the production reactor.

  3. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-10-01

    This single page document is the October 1, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the Production Reactor.

  4. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-10-15

    This single page document is the October 15, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the Production Reactor.

  5. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-09-15

    This single page document is the September 15, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the Production Reactor.

  6. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-12-15

    This single page document is the December 16, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the Production reactor.

  7. Reactor outage schedule (tentative)

    Energy Technology Data Exchange (ETDEWEB)

    Walton, R.P.

    1969-12-01

    This single page document is the December 1, 1969 reactor refueling outage schedule for the Hanford Production Reactor. It also contains data on the amounts and types of fuels to be loaded and relocated in the Production reactor.

  8. Outage planning in Japan

    International Nuclear Information System (INIS)

    Nedderman, John.

    1997-01-01

    Nuclear plant operators in Japan are constrained to keep refuelling and maintenance outages to a minimum by the regulation limiting operating cycles to no longer than 13 months. Outage planning by two contrasting operators is described. Hokkaido Electric, which operates only one plant, Tomari, with two PWRs, plans to reduce outage time from the present 65 days in two stages. Detailed review of previous outage schedules has shown that a reduction to 59 days should be achievable by careful planning without any fundamental changes. The second reduction to 49 days will require such measures as relaxing water purity standards, rescheduling fuel unloading and loading shifts and speeding up eddy current testing of primary equipment by using steam generator nozzle dams. Kansai Electric, operating 11 PWRs at three plants, has scope for reducing outages at all of its units using a range of measures. Steam generator replacement in the seven oldest reactors, completed in July 1997, is by far the most significant of these and is expected to save 64 days repair time in a previous average outage time of 131 days. (UK)

  9. Applying of forecasting at decision making in power systems

    International Nuclear Information System (INIS)

    Sapundjiev, G.

    2007-01-01

    The problems concerning forecast and decision making are analyzed. The typical tasks arising in the forecasting process of the power systems with hierarchical structure formulated and brought to formal description

  10. North American Mesoscale Forecast System (NAM) [12 km

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The North American Mesoscale Forecast System (NAM) is one of the major regional weather forecast models run by the National Centers for Environmental Prediction...

  11. Global Forecast System (GFS) [0.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and...

  12. Radar Based Flow and Water Level Forecasting in Sewer Systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Rasmussen, Michael R.; Grum, M.

    2009-01-01

    This paper describes the first radar based forecast of flow and/or water level in sewer systems in Denmark. The rainfall is successfully forecasted with a lead time of 1-2 hours, and flow/levels are forecasted an additional ½-1½ hours using models describing the behaviour of the sewer system. Bot...

  13. Economic costs of electrical system instability and power outages caused by snakes on the Island of Guam

    Science.gov (United States)

    Fritts, T.H.

    2002-01-01

    The Brown Tree Snake, Boiga irregularis, is an introduced species on Guam where it causes frequent electrical power outages. The snake's high abundance, its propensity for climbing, and use of disturbed habitats all contribute to interruption of Guam's electrical service and the activities that depend on electrical power. Snakes have caused more than 1600 power outages in the 20-yr period of 1978–1997 and most recently nearly 200 outages per year. Single outages spanning the entire island and lasting 8 or more hours are estimated to cost in excess of $3,000,000 in lost productivity, but the costs of outages that involve only parts of the island or those of shorter durations are more difficult to quantify. Costs to the island's economy have exceeded $4.5 M $4.5M"> per year over a 7-yr period without considering repair costs, damage to electrical equipment, and lost revenues. Snakes pose the greatest problem on high voltage transmission lines, on transformers, and inside electrical substations.

  14. Real-time emergency forecasting technique for situation management systems

    Science.gov (United States)

    Kopytov, V. V.; Kharechkin, P. V.; Naumenko, V. V.; Tretyak, R. S.; Tebueva, F. B.

    2018-05-01

    The article describes the real-time emergency forecasting technique that allows increasing accuracy and reliability of forecasting results of any emergency computational model applied for decision making in situation management systems. Computational models are improved by the Improved Brown’s method applying fractal dimension to forecast short time series data being received from sensors and control systems. Reliability of emergency forecasting results is ensured by the invalid sensed data filtering according to the methods of correlation analysis.

  15. Flood forecasting and warning systems in Pakistan

    International Nuclear Information System (INIS)

    Ali Awan, Shaukat

    2004-01-01

    Meteorologically, there are two situations which may cause three types of floods in Indus Basin in Pakistan: i) Meteorological Situation for Category-I Floods when the seasonal low is a semi permanent weather system situated over south eastern Balochistan, south western Punjab, adjoining parts of Sindh get intensified and causes the moisture from the Arabian Sea to be brought up to upper catchments of Chenab and Jhelum rivers. (ii) Meteorological Situation for Category-11 and Category-111 Floods, which is linked with monsoon low/depression. Such monsoon systems originate in Bay of Bengal region and then move across India in general west/north westerly direction arrive over Rajasthan or any of adjoining states of India. Flood management in Pakistan is multi-functional process involving a number of different organizations. The first step in the process is issuance of flood forecast/warning, which is performed by Pakistan Meteorological Department (PMD) utilizing satellite cloud pictures and quantitative precipitation measurement radar data, in addition to the conventional weather forecasting facilities. For quantitative flood forecasting, hydrological data is obtained through the Provincial Irrigation Department and WAPDA. Furthermore, improved rainfall/runoff and flood routing models have been developed to provide more reliable and explicit flood information to a flood prone population.(Author)

  16. The Discriminant Analysis Flare Forecasting System (DAFFS)

    Science.gov (United States)

    Leka, K. D.; Barnes, Graham; Wagner, Eric; Hill, Frank; Marble, Andrew R.

    2016-05-01

    The Discriminant Analysis Flare Forecasting System (DAFFS) has been developed under NOAA/Small Business Innovative Research funds to quantitatively improve upon the NOAA/SWPC flare prediction. In the Phase-I of this project, it was demonstrated that DAFFS could indeed improve by the requested 25% most of the standard flare prediction data products from NOAA/SWPC. In the Phase-II of this project, a prototype has been developed and is presently running autonomously at NWRA.DAFFS uses near-real-time data from NOAA/GOES, SDO/HMI, and the NSO/GONG network to issue both region- and full-disk forecasts of solar flares, based on multi-variable non-parametric Discriminant Analysis. Presently, DAFFS provides forecasts which match those provided by NOAA/SWPC in terms of thresholds and validity periods (including 1-, 2-, and 3- day forecasts), although issued twice daily. Of particular note regarding DAFFS capabilities are the redundant system design, automatically-generated validation statistics and the large range of customizable options available. As part of this poster, a description of the data used, algorithm, performance and customizable options will be presented, as well as a demonstration of the DAFFS prototype.DAFFS development at NWRA is supported by NOAA/SBIR contracts WC-133R-13-CN-0079 and WC-133R-14-CN-0103, with additional support from NASA contract NNH12CG10C, plus acknowledgment to the SDO/HMI and NSO/GONG facilities and NOAA/SWPC personnel for data products, support, and feedback. DAFFS is presently ready for Phase-III development.

  17. The distribution of wind power forecast errors from operational systems

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, Bri-Mathias; Ela, Erik; Milligan, Michael

    2011-07-01

    Wind power forecasting is one important tool in the integration of large amounts of renewable generation into the electricity system. Wind power forecasts from operational systems are not perfect, and thus, an understanding of the forecast error distributions can be important in system operations. In this work, we examine the errors from operational wind power forecasting systems, both for a single wind plant and for an entire interconnection. The resulting error distributions are compared with the normal distribution and the distribution obtained from the persistence forecasting model at multiple timescales. A model distribution is fit to the operational system forecast errors and the potential impact on system operations highlighted through the generation of forecast confidence intervals. (orig.)

  18. Nuclear outages: an approach to project controls

    International Nuclear Information System (INIS)

    Bryson, R.

    1985-01-01

    The annual budget for maintaining and operating a nuclear power plant has risen dramatically over the past 5 years. NRC-mandated plant improvements and outage related expenses are often cited to be the main contributors to these escalating budgets. Nuclear utilities have responded by developing programs to improve plant availability and outage costs through improved outage performance. Utilities recognize that for capital improvements the program to control costs does no begin with outage planning, but rather more appropriately up front during the engineering phase. To support their management objectives, utilities have been developing comprehensive project control systems for concurrently reducing capital expenditures, outage-related costs, and time. This paper provides an approach to project controls that, rather than using one all inclusive comprehensive system, requires five separate monitoring systems - one for each phase of an activity's life cycle. Through the integration of these discrete but interrelated systems, utility management acquires the necessary tools for comprehensive planning and control of their modification program and effective detailed monitoring for all outage-related activities

  19. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer; Yang, Hong-Chuan; Gebali, Fayez; Alouini, Mohamed-Slim

    2016-01-01

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non

  20. Cognitive Multiple-Antenna Network with Outage and Rate Margins at the Primary System

    DEFF Research Database (Denmark)

    Maham, Behrouz; Popovski, Petar

    2015-01-01

    In the common model for spectrum sharing, cognitive users can access the spectrum as long as the target performance in the legitimate primary system is not violated. In this paper, we consider a downlink primary multiple-inputsingle- output (MISO) system which operates under a controlled interfer...

  1. [Combined forecasting system of peritonitis outcome].

    Science.gov (United States)

    Lebedev, N V; Klimov, A E; Agrba, S B; Gaidukevich, E K

    To create a reliable system for assessing of severity and prediction of the outcome of peritonitis. Critical analysis of the systems for peritonitis severity assessment is presented. The study included outcomes of 347 patients who admitted at the Department of Faculty Surgery of Peoples' Friendship University of Russia in 2015-2016. The cause of peritonitis were destructive forms of acute appendicitis, cholecystitis, perforated gastroduodenal ulcer, various perforation of small and large intestines (including tumor). Combined forecasting system for peritonitis severity assessment is created. The system includes clinical, laboratory data, assessment of systemic inflammatory response (SIRS) and severity of organ failure (qSOFA). The authors focused on easily identifiable parameters which are available in virtually any surgical hospital. Threshold value (lethal outcome probability over 50%) is 8 scores in this system. Sensitivity, specificity and accuracy were 93.3, 99.7 and 98.9%, respectively according to ROC-curve that exceeds those parameters of MPI and APACHE II.

  2. Activities of maintenance and outage

    International Nuclear Information System (INIS)

    Gracia-Orellan, J. M.; Gonzalez, P. L.; Verdu, M. F.; Fernandez, J. A.

    2004-01-01

    Iberinco Nuclear Generation Department have wanted to promote service activities in nuclear power plants for years besides its dedication to engineering activities. for it, in 1997 Nuclear Services Management was created to complement engineering activities and to be able to make an offer for products and turn key services. People involved in this Management have an extensive experience in Services Area, so that all type of maintenance works are promoted, as well other services like dismantling, fallout management and new equipment's for nuclear power plants services. Iberinco's experience in Support Services in Nuclear Power Plants allows to answer effectively to special workers during operation cycle and outages periods. These activities have been made in spanish nuclear power plants and Angra I and II plants, both of them in Brazil. In this area we provide Technical Consulting Management and Supervision to develop the following activities: - Improvement Maintenance Programs based in PSA: Implantation of Maintenance Rule in the plants. - Supervision and Assembly of design modifications in structures, systems and components. - Fulfilment of efficiency tests, inspection and turbo-group modification. - Noise and vibrations analysis. - Valves and rotative equipment calculations and diagnosis tests. Iberinco develop these outage activities itself or as contractors coordinator under its management. A lot of them have been working with Iberinco for many years and have a great experience in the Service Area they are developing. In this article, the main outage activities developed for Iberinco are detailed. (Author)

  3. Outage performance of two-way DF relaying systems with a new relay selection metric

    KAUST Repository

    Hyadi, Amal; Benjillali, Mustapha; Alouini, Mohamed-Slim

    2012-01-01

    This paper investigates a new constrained relay selection scheme for two-way relaying systems where two end terminals communicate simultaneously via a relay. The introduced technique is based on the maximization of the weighted sum rate of both

  4. The Red Sea Modeling and Forecasting System

    KAUST Repository

    Hoteit, Ibrahim

    2015-04-01

    Despite its importance for a variety of socio-economical and political reasons and the presence of extensive coral reef gardens along its shores, the Red Sea remains one of the most under-studied large marine physical and biological systems in the global ocean. This contribution will present our efforts to build advanced modeling and forecasting capabilities for the Red Sea, which is part of the newly established Saudi ARAMCO Marine Environmental Research Center at KAUST (SAMERCK). Our Red Sea modeling system compromises both regional and nested costal MIT general circulation models (MITgcm) with resolutions varying between 8 km and 250 m to simulate the general circulation and mesoscale dynamics at various spatial scales, a 10-km resolution Weather Research Forecasting (WRF) model to simulate the atmospheric conditions, a 4-km resolution European Regional Seas Ecosystem Model (ERSEM) to simulate the Red Sea ecosystem, and a 1-km resolution WAVEWATCH-III model to simulate the wind driven surface waves conditions. We have also implemented an oil spill model, and a probabilistic dispersion and larval connectivity modeling system (CMS) based on a stochastic Lagrangian framework and incorporating biological attributes. We are using the models outputs together with available observational data to study all aspects of the Red Sea circulations. Advanced monitoring capabilities are being deployed in the Red Sea as part of the SAMERCK, comprising multiple gliders equipped with hydrographical and biological sensors, high frequency (HF) surface current/wave mapping, buoys/ moorings, etc, complementing the available satellite ocean and atmospheric observations and Automatic Weather Stations (AWS). The Red Sea models have also been equipped with advanced data assimilation capabilities. Fully parallel ensemble-based Kalman filtering (EnKF) algorithms have been implemented with the MITgcm and ERSEM for assimilating all available multivariate satellite and in-situ data sets. We

  5. The Red Sea Modeling and Forecasting System

    KAUST Repository

    Hoteit, Ibrahim; Gopalakrishnan, Ganesh; Latif, Hatem; Toye, Habib; Zhan, Peng; Kartadikaria, Aditya R.; Viswanadhapalli, Yesubabu; Yao, Fengchao; Triantafyllou, George; Langodan, Sabique; Cavaleri, Luigi; Guo, Daquan; Johns, Burt

    2015-01-01

    Despite its importance for a variety of socio-economical and political reasons and the presence of extensive coral reef gardens along its shores, the Red Sea remains one of the most under-studied large marine physical and biological systems in the global ocean. This contribution will present our efforts to build advanced modeling and forecasting capabilities for the Red Sea, which is part of the newly established Saudi ARAMCO Marine Environmental Research Center at KAUST (SAMERCK). Our Red Sea modeling system compromises both regional and nested costal MIT general circulation models (MITgcm) with resolutions varying between 8 km and 250 m to simulate the general circulation and mesoscale dynamics at various spatial scales, a 10-km resolution Weather Research Forecasting (WRF) model to simulate the atmospheric conditions, a 4-km resolution European Regional Seas Ecosystem Model (ERSEM) to simulate the Red Sea ecosystem, and a 1-km resolution WAVEWATCH-III model to simulate the wind driven surface waves conditions. We have also implemented an oil spill model, and a probabilistic dispersion and larval connectivity modeling system (CMS) based on a stochastic Lagrangian framework and incorporating biological attributes. We are using the models outputs together with available observational data to study all aspects of the Red Sea circulations. Advanced monitoring capabilities are being deployed in the Red Sea as part of the SAMERCK, comprising multiple gliders equipped with hydrographical and biological sensors, high frequency (HF) surface current/wave mapping, buoys/ moorings, etc, complementing the available satellite ocean and atmospheric observations and Automatic Weather Stations (AWS). The Red Sea models have also been equipped with advanced data assimilation capabilities. Fully parallel ensemble-based Kalman filtering (EnKF) algorithms have been implemented with the MITgcm and ERSEM for assimilating all available multivariate satellite and in-situ data sets. We

  6. Framatome ANP outage optimization support solutions

    International Nuclear Information System (INIS)

    Bombail, Jean Paul

    2003-01-01

    Over the last several years, leading plant operators have demonstrated that availability factors can be improved while safety and reliability can be enhanced on a long-term basis and operating costs reduced. Outage optimization is the new term being used to describe these long-term initiatives through which a variety of measures aimed at shortening scheduled plant outages have been developed and successfully implemented by these leaders working with their service providers who were introducing new technologies and process improvements. Following the leaders, all operators now have ambitious outage optimization plans and the median and average outage duration are decreasing world-wide. Future objectives are even more stringent and must include plant upgrades and component replacements being performed for life extension of plant operation. Outage optimization covers a broad range of activities from modifications of plant systems to faster cool down rates to human behavior improvements. It has been proven to reduce costs, avoid unplanned outages and thus support plant availability and help to ensure the utility's competitive position in the marketplace

  7. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

  8. A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Chengshi Tian

    2018-03-01

    Full Text Available Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids.

  9. Outage preparation milestones - A tool to improve planned outage performance

    International Nuclear Information System (INIS)

    Laplatney, Jere; Hwang, Euiyoub

    2006-01-01

    Sustainable development of Nuclear Energy depends heavily on excellent performance of the existing fleet which in turn depend heavily on the performance of planned outages. Nuclear Power Plants who have successfully undertaken outage optimization projects have demonstrated than an effective Outage Preparation Milestone program is a key component of their improvement programs. This paper will provide background into the field of 'Outage Optimization' including the philosophy, general approach, and results obtained in the U. S. industry. The significant safety improvements afforded by properly implementing outage improvement programs will be explained. Some specific examples of outage improvements will be given including the adoption of a strong Outage Preparation Milestone Program. The paper will then describe the attributes of an effective Outage Preparation Milestone Program and list a set of specific key milestones. The key milestones are defined and the reasons for each are explained. Suggested due dates for each key milestone relative to the outage start date are provided. Successful implementation of an Outage Preparation Milestone program depends heavily upon the management tools and methods used to assure that the organization meets the milestones on time and in a quality fashion. These include methods to handle cases where milestones are not met - either partially or fully. KHNP is investigating implementing an improved Outage Preparation Milestone program for its fleet of reactors as part of its overall program to improve its performance of planned outages

  10. Hybrid ellipsoidal fuzzy systems in forecasting regional electricity loads

    Energy Technology Data Exchange (ETDEWEB)

    Pai, Ping-Feng [Department of Information Management, National Chi Nan University, 1 University Road, Puli, Nantou 545, Taiwan (China)

    2006-09-15

    Because of the privatization of electricity in many countries, load forecasting has become one of the most crucial issues in the planning and operations of electric utilities. In addition, accurate regional load forecasting can provide the transmission and distribution operators with more information. The hybrid ellipsoidal fuzzy system was originally designed to solve control and pattern recognition problems. The main objective of this investigation is to develop a hybrid ellipsoidal fuzzy system for time series forecasting (HEFST) and apply the proposed model to forecast regional electricity loads in Taiwan. Additionally, a scaled conjugate gradient learning method is employed in the supervised learning phase of the HEFST model. Subsequently, numerical data taken from the existing literature is used to demonstrate the forecasting performance of the HEFST model. Simulation results reveal that the proposed model has better forecasting performance than the artificial neural network model and the regression model. Thus, the HEFST model is a valid and promising alternative for forecasting regional electricity loads. (author)

  11. Development and validation of a regional coupled forecasting system for S2S forecasts

    Science.gov (United States)

    Sun, R.; Subramanian, A. C.; Hoteit, I.; Miller, A. J.; Ralph, M.; Cornuelle, B. D.

    2017-12-01

    Accurate and efficient forecasting of oceanic and atmospheric circulation is essential for a wide variety of high-impact societal needs, including: weather extremes; environmental protection and coastal management; management of fisheries, marine conservation; water resources; and renewable energy. Effective forecasting relies on high model fidelity and accurate initialization of the models with observed state of the ocean-atmosphere-land coupled system. A regional coupled ocean-atmosphere model with the Weather Research and Forecasting (WRF) model and the MITGCM ocean model coupled using the ESMF (Earth System Modeling Framework) coupling framework is developed to resolve mesoscale air-sea feedbacks. The regional coupled model allows oceanic mixed layer heat and momentum to interact with the atmospheric boundary layer dynamics at the mesoscale and submesoscale spatiotemporal regimes, thus leading to feedbacks which are otherwise not resolved in coarse resolution global coupled forecasting systems or regional uncoupled forecasting systems. The model is tested in two scenarios in the mesoscale eddy rich Red Sea and Western Indian Ocean region as well as mesoscale eddies and fronts of the California Current System. Recent studies show evidence for air-sea interactions involving the oceanic mesoscale in these two regions which can enhance predictability on sub seasonal timescale. We will present results from this newly developed regional coupled ocean-atmosphere model for forecasts over the Red Sea region as well as the California Current region. The forecasts will be validated against insitu observations in the region as well as reanalysis fields.

  12. Incorporating wind generation forecast uncertainty into power system operation, dispatch, and unit commitment procedures

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jiam; Subbarao, Krishnappa [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

    2010-07-01

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the ''flying-brick'' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors. (orig.)

  13. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  14. Regularized forecasting of chaotic dynamical systems

    International Nuclear Information System (INIS)

    Bollt, Erik M.

    2017-01-01

    While local models of dynamical systems have been highly successful in terms of using extensive data sets observing even a chaotic dynamical system to produce useful forecasts, there is a typical problem as follows. Specifically, with k-near neighbors, kNN method, local observations occur due to recurrences in a chaotic system, and this allows for local models to be built by regression to low dimensional polynomial approximations of the underlying system estimating a Taylor series. This has been a popular approach, particularly in context of scalar data observations which have been represented by time-delay embedding methods. However such local models can generally allow for spatial discontinuities of forecasts when considered globally, meaning jumps in predictions because the collected near neighbors vary from point to point. The source of these discontinuities is generally that the set of near neighbors varies discontinuously with respect to the position of the sample point, and so therefore does the model built from the near neighbors. It is possible to utilize local information inferred from near neighbors as usual but at the same time to impose a degree of regularity on a global scale. We present here a new global perspective extending the general local modeling concept. In so doing, then we proceed to show how this perspective allows us to impose prior presumed regularity into the model, by involving the Tikhonov regularity theory, since this classic perspective of optimization in ill-posed problems naturally balances fitting an objective with some prior assumed form of the result, such as continuity or derivative regularity for example. This all reduces to matrix manipulations which we demonstrate on a simple data set, with the implication that it may find much broader context.

  15. The oceanic forecasting system near the Shimokita Peninsula, Japan

    International Nuclear Information System (INIS)

    In, Teiji; Nakayama, Tomoharu; Matsuura, Yasutaka; Shima, Shigeki; Ishikawa, Yoichi; Awaji, Toshiyuki; Kobayashi, Takuya; Kawamura, Hideyuki; Togawa, Orihiko; Toyoda, Takahiro

    2007-01-01

    The oceanic forecasting system off the Shimokita Peninsula was constructed. To evaluate the performance of this system, we carried out the hindcast experiment for the oceanic conditions in 2003. The results showed the system had good reproducibility. Especially, it was able to reproduce the feature of seasonal variation of the Tsugaru Warm Water (TWW). We expect it has enough performance in actual forecasting. (author)

  16. The GOCF/AWAP system - forecasting temperature extremes

    International Nuclear Information System (INIS)

    Fawcett, Robert; Hume, Timothy

    2010-01-01

    Gridded hourly temperature forecasts from the Bureau of Meteorology's Gridded Operational Consensus Forecasting (GOCF) system are combined in real time with the Australian Water Availability Project (AWAP) gridded daily temperature analyses to produce gridded daily maximum and minimum temperature forecasts with lead times from one to five days. These forecasts are compared against the historical record of AWAP daily temperature analyses (1911 to present), to identify regions where record or near-record temperatures are predicted to occur. This paper describes the GOCF/AWAP system, showing how the daily maximum and minimum temperature forecasts are prepared from the hourly forecasts, and how they are bias-corrected in real time using the AWAP analyses, against which they are subsequently verified. Using monthly climatologies of long-term daily mean, standard deviation and all-time highest and lowest on record, derived forecast products (for both maximum and minimum temperature) include ordinary and standardised anomalies, 'forecast - highest on record' and 'forecast - lowest on record'. Compensation for the climatological variation across the country is achieved in these last two products, which provide the necessary guidance as to whether or not record-breaking temperatures are expected, by expressing the forecast departure from the previous record in both 0 C and standard deviations.

  17. Reactor refurbishment in an outage environment

    International Nuclear Information System (INIS)

    Gowthorpe, P.; Hoare, R.

    2012-01-01

    Reactor life extension has typically been performed during specific refurbishment outages. These outages are long and costly due to the sheer complexity of the scope, not to mention the ever present discovery work. A scope of this size requires a huge labour force to execute, which poses significant challenges. The work is difficult to staff with qualified people able to execute the work smoothly and managing the required labour pool problematic. Cost and time overruns are inevitable in that environment. Reducing the cost and schedule is critical to the long term viability of reactor refurbishment projects. With planning, the total cost of the refurbishment can be reduced by managing the inspection and repairs during normal outages. Identifying what activities need to be done each outage for the life of the reactor and bringing the latest technology can make this viable. Tightly planned outages with a small well trained labour force will go a long way to reducing costs. The suite of services and tooling available to the utilities to manage their reactor integrity has improved significantly in recent years and continues to evolve. New feeder inspection technologies can provide improved inspection results for the complex feeder geometry. These improvements lead to more accurate wear rates and better predictions of component life. Feeders that need replacement based on improved inspection techniques can be replaced systematically during regular outages rather than specific refurbishment outages. Targeting areas rather than entire feeders reduces time, dose and cost. In cases where feeder replacement isn't feasible or where unpredicted wear is found, a feeder weld overlay process can be used. To manage the reactor work, new data systems are under development that allow for effective tracking of each activity performed and outcomes in a single package. (author)

  18. Forecasting the Performance of Agroforestry Systems

    Science.gov (United States)

    Luedeling, E.; Shepherd, K.

    2014-12-01

    Agroforestry has received considerable attention from scientists and development practitioners in recent years. It is recognized as a cornerstone of many traditional agricultural systems, as well as a new option for sustainable land management in currently treeless agricultural landscapes. Agroforestry systems are diverse, but most manifestations supply substantial ecosystem services, including marketable tree products, soil fertility, water cycle regulation, wildlife habitat and carbon sequestration. While these benefits have been well documented for many existing systems, projecting the outcomes of introducing new agroforestry systems, or forecasting system performance under changing environmental or climatic conditions, remains a substantial challenge. Due to the various interactions between system components, the multiple benefits produced by trees and crops, and the host of environmental, socioeconomic and cultural factors that shape agroforestry systems, mechanistic models of such systems quickly become very complex. They then require a lot of data for site-specific calibration, which presents a challenge for their use in new environmental and climatic domains, especially in data-scarce environments. For supporting decisions on the scaling up of agroforestry technologies, new projection methods are needed that can capture system complexity to an adequate degree, while taking full account of the fact that data on many system variables will virtually always be highly uncertain. This paper explores what projection methods are needed for supplying decision-makers with useful information on the performance of agroforestry in new places or new climates. Existing methods are discussed in light of these methodological needs. Finally, a participatory approach to performance projection is proposed that captures system dynamics in a holistic manner and makes probabilistic projections about expected system performance. This approach avoids the temptation to take

  19. Maintenance and Outage Management Assessment (MOMA)

    International Nuclear Information System (INIS)

    2005-01-01

    The competitive environment has significant implications for nuclear power plant (NPP) operations, which include, inter alia, the need for efficient use of resources and effective management of plant activities of maintenance and outages. The purpose of NPP maintenance and outages is to allow NPPs to use all those functions necessary for safe and reliable power production by keeping them available and adequate maintenance programme is essential. The maintenance programme covers all preventive and remedial measures, both administrative and technical, necessary to identify and mitigate degradation of a functioning system, structure or component, or restore the design functions of a failed system, structure or component to an acceptable level. In response to the needs of MSs, NPES (Nuclear Power Section, Division of Nuclear Power, IAEA) plans to strengthen its services. NPES services will not only continue to provide its 'traditional' products of publications of nuclear industrial best practices and technical implementation of TC projects on plant maintenance and outage management, but also be expanded to deliver, in a timely manner, technical support missions as requested by MSs for NPPs. One of many services is Maintenance and Outage Management Assessment (MOMA). The NPP can obtain support and assistance in assessment and optimisation of its maintenance program and/or outage management. It aims to help the NPP improve its performance of maintenance and outage in a competitive nuclear power business environment. The specific benefits of the assessment are as follows: a) disseminate nuclear industrial best practices on maintenance program and outage management in the world, b) benchmark, evaluate and optimise the approach of maintenance program and outage management and c) identify solutions to known problems at nuclear power plants, if any. MOMA is conducted at the request of NPPs of any IAEA Member States. MOMA consists in a technical mission/visit for 1-3 weeks by

  20. Contingency Analysis of Cascading Line Outage Events

    Energy Technology Data Exchange (ETDEWEB)

    Thomas L Baldwin; Magdy S Tawfik; Miles McQueen

    2011-03-01

    As the US power systems continue to increase in size and complexity, including the growth of smart grids, larger blackouts due to cascading outages become more likely. Grid congestion is often associated with a cascading collapse leading to a major blackout. Such a collapse is characterized by a self-sustaining sequence of line outages followed by a topology breakup of the network. This paper addresses the implementation and testing of a process for N-k contingency analysis and sequential cascading outage simulation in order to identify potential cascading modes. A modeling approach described in this paper offers a unique capability to identify initiating events that may lead to cascading outages. It predicts the development of cascading events by identifying and visualizing potential cascading tiers. The proposed approach was implemented using a 328-bus simplified SERC power system network. The results of the study indicate that initiating events and possible cascading chains may be identified, ranked and visualized. This approach may be used to improve the reliability of a transmission grid and reduce its vulnerability to cascading outages.

  1. The Delft-FEWS flow forecasting system

    NARCIS (Netherlands)

    Werner, M.; Schellekens, J.; Gijsbers, P.; van Dijk, M.; van den Akker, O.; Heynert, K.

    2013-01-01

    Since its introduction in 2002/2003, the current generation of the Delft-FEWS operational forecasting platform has found application in over forty operational centres. In these it is used to link data and models in real time, producing forecasts on a daily basis. In some cases it forms a building

  2. Hybrid Intrusion Forecasting Framework for Early Warning System

    Science.gov (United States)

    Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

    Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

  3. The Stevens Integrated Maritime Surveillance Forecast System: Expansion and Enhancement

    National Research Council Canada - National Science Library

    Bruno, Michael S; Blumberg, Alan F

    2006-01-01

    .... In the long-term, the observation and modeling systems will be linked in a unique fashion, whereby the model forecast system will be enhanced by data assimilation, and the observing system will...

  4. Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System

    Directory of Open Access Journals (Sweden)

    Hugo Carrão

    2018-06-01

    Full Text Available Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated. Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily present in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half-yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. In the near term, the largest advances in the prediction of meteorological drought for Latin

  5. On the Required Number of Antennas in a Point-to-Point Large-but-Finite MIMO System: Outage-Limited Scenario

    KAUST Repository

    Makki, Behrooz

    2016-03-22

    This paper investigates the performance of the point-To-point multiple-input-multiple-output (MIMO) systems in the presence of a large but finite numbers of antennas at the transmitters and/or receivers. Considering the cases with and without hybrid automatic repeat request (HARQ) feedback, we determine the minimum numbers of the transmit/receive antennas, which are required to satisfy different outage probability constraints. Our results are obtained for different fading conditions and the effect of the power amplifiers efficiency/feedback error probability on the performance of the MIMO-HARQ systems is analyzed. Then, we use some recent results on the achievable rates of finite block-length codes, to analyze the effect of the codewords lengths on the system performance. Moreover, we derive closed-form expressions for the asymptotic performance of the MIMO-HARQ systems when the number of antennas increases. Our analytical and numerical results show that different outage requirements can be satisfied with relatively few transmit/receive antennas. © 1972-2012 IEEE.

  6. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

    Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  7. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    2003-01-01

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  8. Primary Water Chemistry Control during a Planned Outage at Bruce Power

    International Nuclear Information System (INIS)

    Ma, Guoping; Nashiem, Rod; Matheson, Shane; Yabar, Berman; Harper, Bill; Roberts, John G.

    2012-09-01

    Bruce Power has developed a comprehensive outage water chemistry program, which includes both primary and secondary chemistry requirements during planned outages. The purpose of the program is to emphasize the chemistry requirements during outages and subsequent start-ups in order to maintain the integrity of the systems, minimise activity transport and radiation fields, reduce the Carbon-14 release, and to ensure that the requirements are integrated with the outage management program. Prior to a planned outage, Station Chemical Technical Sections identify outage chemistry requirements to Operations and Outage Planning and ensure that work necessary to correct system chemistry issues is within outage work scope. The outage water chemistry program provides direction for establishing alternative sampling locations as demanded by the system configuration during the outage and identifies outage prerequisites for nuclear system purification capabilities. These requirements are contained in an outage checklist. The paper mainly highlights the primary water chemistry issues and chemistry control strategies during planned outages and discusses challenges and successes. (authors)

  9. Outage reduction of Hamaoka NPS

    International Nuclear Information System (INIS)

    Hida, Shigeru; Anma, Minoru

    1999-01-01

    In the Hamaoka nuclear power plant, we have worked on the outage reduction since 1993. In those days, the outage length in Hamaoka was 80 days or more, and was largely far apart from excellent results of European and American plants about the 30days. A concrete strategy to achieve the reduction process is the extension of working hours, the changing work schedule control unit for every hour, the equipment improvements, and the improvements of work environments, etc. We executed them one by one reflecting results. As a result, we achieved the outage for 57 days in 1995. Starting from this, we acquired the further outage reduction one by one and achieved the outage for 38 days in 1997 while maintaining safety and reliability of the plant. We advance these strategies further and we will aim at the achievement of the 30·35 days outage in the future. (author)

  10. Diablo Canyon refueling outage program

    International Nuclear Information System (INIS)

    McLane, W.B.; Irving, T.L.

    1991-01-01

    Management of outages has become one of the most talked about subjects in the nuclear power industry in the past several years. Many utilities do not perform refueling outages very well or in the past have had some outages that they would not like to repeat and in some cases do not even like to think about. With the growing cost of energy and the demands placed on utilities to improve capacity factors, it is very easy for management to focus on shortening refueling outage durations as a prime objective in improving overall corporate performance. So it is with Pacific Gas and Electric Company and the Diablo Canyon power plant. A review of their refueling outage performance reflects a utility that is responding to the nuclear industry's call for improved outage performance

  11. Climate Forecast System Reforecast (CFSR), for 1981 to 2011

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NCEP Climate Forecast System Reanalysis (CFSR) was designed and executed as a global, high resolution, coupled atmosphere-ocean-land surface-sea ice system to...

  12. Mid-term report on Renewable Energy Forecasting System

    International Nuclear Information System (INIS)

    Brand, A.J.; Hegberg, T.; Van der Borg, N.J.C.M.; Kok, J.K.; Van Selow, E.R.; Kamphuis, I.G.; De Noord, M.; Van Sambeek, E.J.W.

    2001-04-01

    The most important conclusions on the economical and technical feasibility of renewable energy forecasting systems are presented, next to recommendations to be followed in order to introduce such a system in the Dutch electricity market. 11 refs

  13. Outage time reduction in GKN II without loss of safety

    International Nuclear Information System (INIS)

    Sturm, J.

    1999-01-01

    GKN II is a 1340 MWE 4-loop pressurised water reactor from Siemens KONVOI type, located in the south of Germany. It was originally connected to the grid at the end of 1988. Commercial operation under utility responsibility started at the second half of 1989. The first outage was performed in 1990. Beginning from this date, the outage duration was contiguously reduced from 33 days to 15 days in 1996. In 1998, two refueling and maintenance outages were performed, each with a duration of 7 days. Key planning factors to achieve these results are: A well adapted planning organisation with an outage manager and an outage planning team. An effective long term planning. This means the combination of work with a long duration every 4 or 8 years. No longlasting work in the years in between. Main work only on one safety train per year. Optimisation and standardisation of the shutdown and the startup sequence. The real change of reactor states have been modified, compared to the vendor recommendations. An tests are assigned to plant conditions, where they are most effective and are less time critical. Small modifications in the plant, mainly on the auxiliary systems, to speedup some sequences. Extreme detailed planning of maintenance and periodic tests. Each work/test can be found in a detailed schedule with a dedicated time widow. Optimized tools to perform the detailed planning and to implement the feedback of experience from former outages. Optimized tools for maintenance and handlings of heavy equipment on the critical path. Optimized tools to perform periodic tests. Key factors during outage are: Permanent control of the schedules with an updated 3-day program. Best and permanent information with this 3-day program of all people that are involved. Fast reaction on delays. Outage managers permanent on site. Gain in safety during shutdown states, with reduced outage duration: It has to be proven, that short outages don't lead to faster and less accurate work. It can be

  14. ALARA database value in future outage work planning and dose management

    Energy Technology Data Exchange (ETDEWEB)

    Miller, D.W.; Green, W.H. [Clinton Power Station Illinois Power Co., IL (United States)

    1995-03-01

    ALARA database encompassing job-specific duration and man-rem plant specific information over three refueling outages represents an invaluable tool for the outage work planner and ALARA engineer. This paper describes dose-management trends emerging based on analysis of three refueling outages at Clinton Power Station. Conclusions reached based on hard data available from a relational database dose-tracking system is a valuable tool for planning of future outage work. The system`s ability to identify key problem areas during a refueling outage is improving as more outage comparative data becomes available. Trends over a three outage period are identified in this paper in the categories of number and type of radiation work permits implemented, duration of jobs, projected vs. actual dose rates in work areas, and accuracy of outage person-rem projection. The value of the database in projecting 1 and 5 year station person-rem estimates is discussed.

  15. An Assessment of the Subseasonal Forecast Performance in the Extended Global Ensemble Forecast System (GEFS)

    Science.gov (United States)

    Sinsky, E.; Zhu, Y.; Li, W.; Guan, H.; Melhauser, C.

    2017-12-01

    Optimal forecast quality is crucial for the preservation of life and property. Improving monthly forecast performance over both the tropics and extra-tropics requires attention to various physical aspects such as the representation of the underlying SST, model physics and the representation of the model physics uncertainty for an ensemble forecast system. This work focuses on the impact of stochastic physics, SST and the convection scheme on forecast performance for the sub-seasonal scale over the tropics and extra-tropics with emphasis on the Madden-Julian Oscillation (MJO). A 2-year period is evaluated using the National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS). Three experiments with different configurations than the operational GEFS were performed to illustrate the impact of the stochastic physics, SST and convection scheme. These experiments are compared against a control experiment (CTL) which consists of the operational GEFS but its integration is extended from 16 to 35 days. The three configurations are: 1) SPs, which uses a Stochastically Perturbed Physics Tendencies (SPPT), Stochastic Perturbed Humidity (SHUM) and Stochastic Kinetic Energy Backscatter (SKEB); 2) SPs+SST_bc, which uses a combination of SPs and a bias-corrected forecast SST from the NCEP Climate Forecast System Version 2 (CFSv2); and 3) SPs+SST_bc+SA_CV, which combines SPs, a bias-corrected forecast SST and a scale aware convection scheme. When comparing to the CTL experiment, SPs shows substantial improvement. The MJO skill has improved by about 4 lead days during the 2-year period. Improvement is also seen over the extra-tropics due to the updated stochastic physics, where there is a 3.1% and a 4.2% improvement during weeks 3 and 4 over the northern hemisphere and southern hemisphere, respectively. Improvement is also seen when the bias-corrected CFSv2 SST is combined with SPs. Additionally, forecast performance enhances when the scale aware

  16. ALARA database value in future outage work planning and dose management

    International Nuclear Information System (INIS)

    Miller, D.W.; Green, W.H.

    1995-01-01

    ALARA database encompassing job-specific duration and man-rem plant specific information over three refueling outages represents an invaluable tool for the outage work planner and ALARA engineer. This paper describes dose-management trends emerging based on analysis of three refueling outages at Clinton Power Station. Conclusions reached based on hard data available from a relational database dose-tracking system is a valuable tool for planning of future outage work. The system's ability to identify key problem areas during a refueling outage is improving as more outage comparative data becomes available. Trends over a three outage period are identified in this paper in the categories of number and type of radiation work permits implemented, duration of jobs, projected vs. actual dose rates in work areas, and accuracy of outage person-rem projection. The value of the database in projecting 1 and 5 year station person-rem estimates is discussed

  17. System of the Wind Wave Operational Forecast by the Black Sea Marine Forecast Center

    Directory of Open Access Journals (Sweden)

    Yu.B. Ratner

    2017-10-01

    Full Text Available System of the wind wave operational forecast in the Black Sea based on the SWAN (Simulating Waves Nearshore numerical spectral model is represented. In the course of the system development the SWAN model was adapted to take into account the features of its operation at the Black Sea Marine Forecast Center. The model input-output is agreed with the applied nomenclature and the data representation formats. The user interface for rapid access to simulation results was developed. The model adapted to wave forecast in the Black Sea in a quasi-operational mode, is validated for 2012–2015. Validation of the calculation results was carried out for all five forecasting terms based on the analysis of two-dimensional graphs of the wave height distribution derived from the data of prognostic calculations and remote measurements obtained with the altimeter installed on the Jason-2 satellite. Calculation of the statistical characteristics of the deviations between the wave height prognostic values and the data of their measurements from the Jason-2 satellite, as well as a regression analysis of the relationship between the forecasted and measured wave heights was additionally carried out. A comparison of the results obtained with the similar results reported in the works of other authors published in 2009–2016 showed their satisfactory compliance with each other. The forecasts carried out by the authors for the Black Sea as well as those obtained for the other World Ocean regions show that the current level of numerical methods for sea wave forecasting is in full compliance with the requirements of specialists engaged in studying and modeling the state of the ocean and the atmosphere, as well as the experts using these results for solving applied problems.

  18. An Electrical Energy Consumption Monitoring and Forecasting System

    Directory of Open Access Journals (Sweden)

    J. L. Rojas-Renteria

    2016-10-01

    Full Text Available Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.

  19. Wave energy potential: A forecasting system for the Mediterranean basin

    International Nuclear Information System (INIS)

    Carillo, Adriana; Sannino, Gianmaria; Lombardi, Emanuele

    2015-01-01

    ENEA is performing ocean wave modeling activities with the aim of both characterizing the Italian sea energy resource and providing the information necessary for the experimental at sea and operational phases of energy converters. Therefore a forecast system of sea waves and of the associated energy available has been developed and has been operatively running since June 2013. The forecasts are performed over the entire Mediterranean basin and, at a higher resolution, over ten sub-basins around the Italian coasts. The forecast system is here described along with the validation of the wave heights, performed by comparing them with the measurements from satellite sensors. [it

  20. Human-model hybrid Korean air quality forecasting system.

    Science.gov (United States)

    Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

    2016-09-01

    The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the

  1. Climate Forecast System Reanalysis (CFSR), for 1979 to 2011

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NCEP Climate Forecast System Reanalysis (CFSR) was initially completed for the 31-year period from 1979 to 2009, in January 2010. The CFSR was designed and...

  2. NOAA/NCEP Global Forecast System (GFS) Atmospheric Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — U.S. National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) numerical weather...

  3. Elements of a coastal ocean forecasting system for India

    Digital Repository Service at National Institute of Oceanography (India)

    Shetye, S.R.; Radhakrishnan, K.

    After about four decades of investment in infrastructure for ocean research, an appropriate initiative for India now would be to build a coastal ocean forecasting system to support the country's myriad activities in its Exclusive Economic Zone...

  4. Climate Forecast System Version 2 (CFSv2) Operational Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  5. An experimental system for flood risk forecasting at global scale

    Science.gov (United States)

    Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

    2016-12-01

    Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

  6. Pricing power outages in the Netherlands

    Energy Technology Data Exchange (ETDEWEB)

    Baarsma, Barbara E.; Hop, J. Peter [SEO Economic Research/University of Amsterdam, Amsterdam (Netherlands)

    2009-09-15

    In most Western countries, the power grid provides electricity more than 99% of the time. To maintain reliability at such high levels, energy companies have to continually invest in electric transmission- and distribution systems. Since customers of electricity cannot switch from one distribution network to another, no economic incentive exists that matches the supplied reliability to customer preferences. Either under- or over-investment in reliability may thus result. In order to introduce market-like incentives, the Dutch Energy Regulator introduced a regulatory system based on the (perceived) costs of power outages. An essential ingredient of the regulation is the cost of a power outage of a particular duration (i.e., 1 minute). This paper measures these outage cost by using conjoint analysis. We find that the social cost of the present Dutch level of reliability - that is, one outage of two hours every four years - is EUR2.80 on average for every household, and EUR33.10 on average for every SME firm. The total costs to Dutch society are almost EUR50 million. (author)

  7. Continental and global scale flood forecasting systems

    NARCIS (Netherlands)

    Emerton, Rebecca E.; Stephens, Elisabeth M.; Pappenberger, Florian; Pagano, Thomas P.; Weerts, A.H.; Wood, A.; Salamon, Peter; Brown, James D.; Hjerdt, Niclas; Donnelly, Chantal; Baugh, Calum A.; Cloke, Hannah L.

    2016-01-01

    Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not

  8. SOFT project: a new forecasting system based on satellite data

    Science.gov (United States)

    Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

  9. Impact of onsite solar generation on system load demand forecast

    International Nuclear Information System (INIS)

    Kaur, Amanpreet; Pedro, Hugo T.C.; Coimbra, Carlos F.M.

    2013-01-01

    Highlights: • We showed the impact onsite solar generation on system demand load forecast. • Forecast performance degrades by 9% and 3% for 1 h and 15 min forecast horizons. • Error distribution for onsite case is best characterized as t-distribution. • Relation between error, solar penetration and solar variability is characterized. - Abstract: Net energy metering tariffs have encouraged the growth of solar PV in the distribution grid. The additional variability associated with weather-dependent renewable energy creates new challenges for power system operators that must maintain and operate ancillary services to balance the grid. To deal with these issues power operators mostly rely on demand load forecasts. Electric load forecast has been used in power industry for a long time and there are several well established load forecasting models. But the performance of these models for future scenario of high renewable energy penetration is unclear. In this work, the impact of onsite solar power generation on the demand load forecast is analyzed for a community that meets between 10% and 15% of its annual power demand and 3–54% of its daily power demand from a solar power plant. Short-Term Load Forecasts (STLF) using persistence, machine learning and regression-based forecasting models are presented for two cases: (1) high solar penetration and (2) no penetration. Results show that for 1-h and 15-min forecasts the accuracy of the models drops by 9% and 3% with high solar penetration. Statistical analysis of the forecast errors demonstrate that the error distribution is best characterized as a t-distribution for the high penetration scenario. Analysis of the error distribution as a function of daily solar penetration for different levels of variability revealed that the solar power variability drives the forecast error magnitude whereas increasing penetration level has a much smaller contribution. This work concludes that the demand forecast error distribution

  10. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  11. Waste Information Management System with Integrated Transportation Forecast Data

    International Nuclear Information System (INIS)

    Upadhyay, H.; Quintero, W.; Shoffner, P.; Lagos, L.

    2009-01-01

    The Waste Information Management System with Integrated Transportation Forecast Data was developed to support the Department of Energy (DOE) mandated accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to site waste treatment and disposal were potential critical path issues under the accelerated schedules. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of waste that would be generated by the DOE sites over the next 40 years. Each local DOE site has historically collected, organized, and displayed site waste forecast information in separate and unique systems. However, waste and shipment information from all sites needed a common application to allow interested parties to understand and view the complete complex-wide picture. The Waste Information Management System with Integrated Transportation Forecast Data allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and inter-modal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, has deployed the web-based forecast and transportation system and is responsible for updating the waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. (authors)

  12. The Henetus wave forecast system in the Adriatic Sea

    Directory of Open Access Journals (Sweden)

    L. Bertotti

    2011-11-01

    Full Text Available We describe the Henetus wave forecast system in the Adriatic Sea. Operational since 1996, the system is continuously upgraded, especially through the correction of the input ECMWF wind fields. As these fields are of progressively improved quality with the increasing resolution of the meteorological model, the correction needs to be correspondingly updated. This ensures a practically constant quality of the Henetus results in the Adriatic Sea since 1996. After suitable and extended validation of the quality of the results at different forecast ranges, the operational range has been recently extended to five days. The Henetus results are used also to improve the tidal forecast on the Venetian coasts and the Venice lagoon, particularly during the most severe events. Extensive statistics on the model performance are provided, both as analysis and forecast, by comparing the model results versus both satellite and buoy data.

  13. Demonstrating the value of larger ensembles in forecasting physical systems

    Directory of Open Access Journals (Sweden)

    Reason L. Machete

    2016-12-01

    Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

  14. Nuclear Plant Integrated Outage Management

    International Nuclear Information System (INIS)

    Gerstberger, C. R.; Coulehan, R. J.; Tench, W. A.

    1992-01-01

    This paper is a discussion of an emerging concept for improving nuclear plant outage performance - integrated outage management. The paper begins with an explanation of what the concept encompasses, including a scope definition of the service and descriptions of the organization structure, various team functions, and vendor/customer relationships. The evolvement of traditional base scope services to the integrated outage concept is addressed and includes discussions on changing customer needs, shared risks, and a partnership approach to outages. Experiences with concept implementation from a single service in 1984 to the current volume of integrated outage management presented in this paper. We at Westinghouse believe that the operators of nuclear power plants will continue to be aggressively challenged in the next decade to improve the operating and financial performance of their units. More and more customers in the U. S. are looking towards integrated outage as the way to meet these challenges of the 1990s, an arrangement that is best implemented through a long-term partnering with a single-source supplier of high quality nuclear and turbine generator outage services. This availability, and other important parameters

  15. Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

    2016-12-01

    The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

  16. 35/30 outage improvement project

    International Nuclear Information System (INIS)

    Clewett, L.

    2011-01-01

    Outage performance is a significant contributor to the business plan at Bruce Power. A process improvement initiative commenced in 2010-11 to improve outage efficiency and predictability. 12 teams (over 200 people) participated in improvement identification in four areas: Organizational Engagement; Outage Scope; Resources; and, Critical Outage Execution. Out of over 550 initiatives identified, 200 are being incorporated into the Outage Improvement Initiative. Key deliverables include: Development of a long-range 'fleet-level' business strategy to integrate outage duration, outage improvements and unit refurbishments; Development of a 35 day outage schedule template; Determining optimal outage organization to perform outages on an 8-unit site; Improved schedule adherence and productivity; Process to integrate scope needs to support life-cycle and long-range outage needs improvement while meeting near term and regulatory requirements; Consistent methodology in planning of outages to front-end load the high risk work into the outage schedule; Consistent baseline by senior leaders for the expectations of milestone ownership and completion; Consistent framework for milestone compliance and preparation; Communication strategy to educate personnel on the importance of the outage program and nuclear safety, business goals, and budget; and, Suite of metrics based upon industry benchmarks. The Outage Improvement Initiative has a goal of 35 day outages every 30 months. This potentially represents considerable savings to the Bruce Power business plan, both direct revenue savings attributed to reduced outage duration, as well as incremental outage cost savings. Other improvements from the initiative will include personnel radiation exposure and equipment reliability due to decreased outage duration and adherence to scoping, assessing and long lead part milestones. This presentation will describe the outage improvement initiatives to achieve a goal of consistent 35 day outages

  17. 35/30 outage improvement project

    Energy Technology Data Exchange (ETDEWEB)

    Clewett, L. [Bruce Power, Tiverton, Ontario (Canada)

    2011-07-01

    Outage performance is a significant contributor to the business plan at Bruce Power. A process improvement initiative commenced in 2010-11 to improve outage efficiency and predictability. 12 teams (over 200 people) participated in improvement identification in four areas: Organizational Engagement; Outage Scope; Resources; and, Critical Outage Execution. Out of over 550 initiatives identified, 200 are being incorporated into the Outage Improvement Initiative. Key deliverables include: Development of a long-range 'fleet-level' business strategy to integrate outage duration, outage improvements and unit refurbishments; Development of a 35 day outage schedule template; Determining optimal outage organization to perform outages on an 8-unit site; Improved schedule adherence and productivity; Process to integrate scope needs to support life-cycle and long-range outage needs improvement while meeting near term and regulatory requirements; Consistent methodology in planning of outages to front-end load the high risk work into the outage schedule; Consistent baseline by senior leaders for the expectations of milestone ownership and completion; Consistent framework for milestone compliance and preparation; Communication strategy to educate personnel on the importance of the outage program and nuclear safety, business goals, and budget; and, Suite of metrics based upon industry benchmarks. The Outage Improvement Initiative has a goal of 35 day outages every 30 months. This potentially represents considerable savings to the Bruce Power business plan, both direct revenue savings attributed to reduced outage duration, as well as incremental outage cost savings. Other improvements from the initiative will include personnel radiation exposure and equipment reliability due to decreased outage duration and adherence to scoping, assessing and long lead part milestones. This presentation will describe the outage improvement initiatives to achieve a goal of consistent 35 day

  18. Short-Term Wind Speed Forecasting for Power System Operations

    KAUST Repository

    Zhu, Xinxin

    2012-04-01

    The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.

  19. Ensemble Bayesian forecasting system Part I: Theory and algorithms

    Science.gov (United States)

    Herr, Henry D.; Krzysztofowicz, Roman

    2015-05-01

    The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of

  20. The Betting Odds Rating System: Using soccer forecasts to forecast soccer.

    Science.gov (United States)

    Wunderlich, Fabian; Memmert, Daniel

    2018-01-01

    Betting odds are frequently found to outperform mathematical models in sports related forecasting tasks, however the factors contributing to betting odds are not fully traceable and in contrast to rating-based forecasts no straightforward measure of team-specific quality is deducible from the betting odds. The present study investigates the approach of combining the methods of mathematical models and the information included in betting odds. A soccer forecasting model based on the well-known ELO rating system and taking advantage of betting odds as a source of information is presented. Data from almost 15.000 soccer matches (seasons 2007/2008 until 2016/2017) are used, including both domestic matches (English Premier League, German Bundesliga, Spanish Primera Division and Italian Serie A) and international matches (UEFA Champions League, UEFA Europe League). The novel betting odds based ELO model is shown to outperform classic ELO models, thus demonstrating that betting odds prior to a match contain more relevant information than the result of the match itself. It is shown how the novel model can help to gain valuable insights into the quality of soccer teams and its development over time, thus having a practical benefit in performance analysis. Moreover, it is argued that network based approaches might help in further improving rating and forecasting methods.

  1. Sea Level Forecasts Aggregated from Established Operational Systems

    Directory of Open Access Journals (Sweden)

    Andy Taylor

    2017-08-01

    Full Text Available A system for providing routine seven-day forecasts of sea level observable at tide gauge locations is described and evaluated. Forecast time series are aggregated from well-established operational systems of the Australian Bureau of Meteorology; although following some adjustments these systems are only quasi-complimentary. Target applications are routine coastal decision processes under non-extreme conditions. The configuration aims to be relatively robust to operational realities such as version upgrades, data gaps and metadata ambiguities. Forecast skill is evaluated against hourly tide gauge observations. Characteristics of the bias correction term are demonstrated to be primarily static in time, with time varying signals showing regional coherence. This simple approach to exploiting existing complex systems can offer valuable levels of skill at a range of Australian locations. The prospect of interpolation between observation sites and exploitation of lagged-ensemble uncertainty estimates could be meaningfully pursued. Skill characteristics define a benchmark against which new operational sea level forecasting systems can be measured. More generally, an aggregation approach may prove to be optimal for routine sea level forecast services given the physically inhomogeneous processes involved and ability to incorporate ongoing improvements and extensions of source systems.

  2. Maintenance, outages and chemistry really can be compatible

    International Nuclear Information System (INIS)

    Roberts, J.G.; Deaconescu, R.

    2006-01-01

    'Full text:' In their address to the Canadian Nuclear Society, Bruce Power's Chemistry Design staff will describe how maintenance and outages can impact negatively on chemistry control and asset protection. Considerations of material impacts and material condition have significant influences on the approach to, and control of, chemistry. This applies equally to operation as it does during unit and/or system outages. Ideas will be presented as to how to facilitate making maintenance, outages and chemistry compatible. It will be shown how the lack of such an approach can lead to disastrous results. (author)

  3. Maintenance, outages and chemistry really can be compatible

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, J.G.; Deaconescu, R. [Bruce Power, Tiverton, Ontario (Canada)

    2006-07-01

    'Full text:' In their address to the Canadian Nuclear Society, Bruce Power's Chemistry Design staff will describe how maintenance and outages can impact negatively on chemistry control and asset protection. Considerations of material impacts and material condition have significant influences on the approach to, and control of, chemistry. This applies equally to operation as it does during unit and/or system outages. Ideas will be presented as to how to facilitate making maintenance, outages and chemistry compatible. It will be shown how the lack of such an approach can lead to disastrous results. (author)

  4. Short-term load forecasting of power system

    Science.gov (United States)

    Xu, Xiaobin

    2017-05-01

    In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

  5. System for forecasting a reactor power distribution

    International Nuclear Information System (INIS)

    Motoda, Hiroshi; Nishizawa, Yasuo.

    1976-01-01

    Purpose: To dispense with frequent running of detector in a BWR type reactor and permit calculation of the prevailing value and forecast value of power distribution in a specified region in an on-line basis. Constitution: The prevailing power distribution P sub(OZ) (where Z indicates a position in the axial direction) at a given position is estimated by prevailing power distribution estimating means, and the average prevailing power distribution Q sub(OZ) in the core is estimated while making correction of a primary neutron distribution model by core average characteristic measuring means. Then, the estimated core average power distribution Q sub(Z) after alteration of the core flow rate or alteration of Xe concentration is estimated by core average power distribution estimating means. At this time, a forecast power distribution P sub(Z) in a specified region after alteration of the flow rate or alteration of the Xe concentration is calculated on the basis of a relation P sub(Z) = (Q sub(Z)/Q sub(OZ)) by using P sub(OZ), Q sub(OZ) and Q sub(Z). The above calculations are carried out in a short period of time by using a process computer. (Ikeda, J.)

  6. Outage optimization - the US experience and approach

    International Nuclear Information System (INIS)

    LaPlatney, J.

    2007-01-01

    Sustainable development of Nuclear Energy depends heavily on excellent performance of the existing fleet which in turn depends heavily on the performance of planned outages. Some reactor fleets, for example Finland and Germany, have demonstrated sustained good outage performance from their start of commercial operation. Others, such as the US, have improved performance over time. The principles behind a successful outage optimization process are: -) duration is not sole measure of outage success, -) outage work must be performed safely, -) scope selection must focus on improving plant material condition to improve reliability, -) all approved outage work must be completed, -) work must be done cost effectively, -) post-outage plant reliability is a key measure of outage success, and -) outage lessons learned must be effectively implemented to achieve continuous improvement. This approach has proven its superiority over simple outage shortening, and has yielded good results in the US fleet over the past 15 years

  7. Management techniques that keep outages on schedule

    International Nuclear Information System (INIS)

    Taylor, R.B.

    1987-01-01

    During the immature operation of the Pickering Units 5 through 8, significant numbers of outages have been required to deal with warranty inspections and equipment problems. Techniques have been developed to ensure that outages are properly planned and managed so that outage time is minimized, overtime is minimized, and capacity factor is maximized, while ensuring that personnel safety is not compromised. Successful outage planning and execution requires the commitment of many on-station and off-station resources groups. Coordination of all of these groups is required both before and during the outage to ensure outage time is not lost due to unavailability of men or equipment at the time they are required. This paper details the control processes that must be used prior to, during, and after an outage to ensure that time is not lost unnecessarily during outages. Successful outage management at Pickering Nuclear Generating Station can be subdivided into three stages; preoutage planning, outage execution, and postoutage review

  8. Photovoltaics (PV System Energy Forecast on the Basis of the Local Weather Forecast: Problems, Uncertainties and Solutions

    Directory of Open Access Journals (Sweden)

    Kristijan Brecl

    2018-05-01

    Full Text Available When integrating a photovoltaic system into a smart zero-energy or energy-plus building, or just to lower the electricity bill by rising the share of the self-consumption in a private house, it is very important to have a photovoltaic power energy forecast for the next day(s. While the commercially available forecasting services might not meet the household prosumers interests due to the price or complexity we have developed a forecasting methodology that is based on the common weather forecast. Since the forecasted meteorological data does not include the solar irradiance information, but only the weather condition, the uncertainty of the results is relatively high. However, in the presented approach, irradiance is calculated from discrete weather conditions and with correlation of forecasted meteorological data, an RMS error of 65%, and a R2 correlation factor of 0.85 is feasible.

  9. The process of NPP refuelling outage analysis and follow-up

    International Nuclear Information System (INIS)

    Nemec, T.; Savli, S.; Cernilogar Radez, M.; Persic, A.; Pecek, V.; Stritar, A.

    2007-01-01

    Following the outages in 2004 and 2006, the Slovenian Nuclear Safety Administration (SNSA) has started with the practice of independent outage analysis in a form of an internal report. It includes a comparison of performed activities against the planned time schedule of activities, evaluation of design modifications implementation and analysis of significant events. The main result of the outage analysis is a list of recommendations and some open issues that have been identified. These findings are the basis for development of an action plan for SNSA activities until the next outage, aimed at eliminating deficiencies found out during the outage and further improving outage activities. The established system of outage supervision together with the final analysis and long term action plan represents an effective continuous safety supervision process, by which the regulatory body independently contributes to the higher level of safety culture both at the licensee and among its own staff. (author)

  10. PCBA demand forecasting using an evolving Takagi-Sugeno system

    NARCIS (Netherlands)

    van Rooijen, M.; Almeida, R.J.; Kaymak, U.

    2016-01-01

    This paper investigates the use of using an evolving fuzzy system for printed circuit board (PCBA) demand forecasting. The algorithm is based on the evolving Takagi-Sugeno (eTS) fuzzy system, which has the ability to incorporate new patterns by changing its internal structure in an on-line fashion.

  11. Development and demonstration of techniques for reducing occupational radiation doses during refueling outages. Tasks 7A/7B. Advanced outage management and radiation exposure control

    International Nuclear Information System (INIS)

    1985-03-01

    Objectives of Tasks 7A and 7B were to develop and demonstrate computer based systems to assist plant management and staff in utilizing information more effectively to reduce occupational exposures received as a result of refueling outages, and to shorten the duration of the outage. The Advanced Outage Management (AOM) Tool (Task 7A) is an automated outage planning system specifically designed to meet the needs of nuclear plant outage management. The primary objective of the AOM tool is to provide a computerized system that can manipulate the information typically associated with outage planning and scheduling to furnish reports and schedules that more accurately project the future course of the outage. The Radiation Exposure Control (REC) Tool (Task 7B) is a computerized personnel radiation exposure accounting and management system designed to enable nuclear plant management to project and monitor total personnel radiation exposure on a real-time basis. The two systems were designed to operate on the same computer system and interface through a common database that enables information sharing between plant organizations not typically interfaced. This interfacing provides outage planners with a means of incorporating occupational radiation exposure as a factor for making decisions on the course of an outage

  12. Optimal Control and Forecasting of Complex Dynamical Systems

    CERN Document Server

    Grigorenko, Ilya

    2006-01-01

    This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance. The theory presented here can be efficiently applied to various problems, such as the determination of the optimal shape of a laser pulse to induce certain excitations in quantum systems, the optimal design of nanostructured materials and devices, or the control of chaotic systems and minimization of the forecast error for a given forecasting model (for example, artificial neural networks). Starting from a brief review of the history of variational calcul

  13. Exact Outage Probability of Dual-Hop CSI-Assisted AF Relaying Over Nakagami-m Fading Channels

    KAUST Repository

    Xia, Minghua; Aissa, Sonia; Wu, Yik-Chung

    2012-01-01

    to evaluate the outage performance of the system under study. The analytical results of outage probability coincide exactly with Monte-Carlo simulation results and outperform the previously reported upper bounds in the low and medium SNR regions.

  14. Operational Forecasting and Warning systems for Coastal hazards in Korea

    Science.gov (United States)

    Park, Kwang-Soon; Kwon, Jae-Il; Kim, Jin-Ah; Heo, Ki-Young; Jun, Kicheon

    2017-04-01

    Coastal hazards caused by both Mother Nature and humans cost tremendous social, economic and environmental damages. To mitigate these damages many countries have been running the operational forecasting or warning systems. Since 2009 Korea Operational Oceanographic System (KOOS) has been developed by the leading of Korea Institute of Ocean Science and Technology (KIOST) in Korea and KOOS has been operated in 2012. KOOS is consists of several operational modules of numerical models and real-time observations and produces the basic forecasting variables such as winds, tides, waves, currents, temperature and salinity and so on. In practical application systems include storm surges, oil spills, and search and rescue prediction models. In particular, abnormal high waves (swell-like high-height waves) have occurred in the East coast of Korea peninsula during winter season owing to the local meteorological condition over the East Sea, causing property damages and the loss of human lives. In order to improve wave forecast accuracy even very local wave characteristics, numerical wave modeling system using SWAN is established with data assimilation module using 4D-EnKF and sensitivity test has been conducted. During the typhoon period for the prediction of sever waves and the decision making support system for evacuation of the ships, a high-resolution wave forecasting system has been established and calibrated.

  15. CORRECTION OF FORECASTS OF INTERRELATED CURRENCY PAIRS IN TERMS OF SYSTEMS OF BALANCE RATIOS

    OpenAIRE

    Gertsekovich D. A.

    2015-01-01

    In this paper the problem of exchange rates forecast is logically considered a) traditionally as a task of forecast on the base of «stand-alone» equations of autoregression for each currency pair and b) as a result of forecast correction of autoregression equations system on the base of boundary conditions of balance ratios systems. As a criterion for quality of forecast constructed with empirical models we take the sum of deficiency quadrates of forecasts estimated for deductive currency pai...

  16. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) 0-10cm Soil-Moisture Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near...

  17. Forecasting of Processes in Complex Systems for Real-World Problems

    Czech Academy of Sciences Publication Activity Database

    Pelikán, Emil

    2014-01-01

    Roč. 24, č. 6 (2014), s. 567-589 ISSN 1210-0552 Institutional support: RVO:67985807 Keywords : complex systems * data assimilation * ensemble forecasting * forecasting * global solar radiation * judgmental forecasting * multimodel forecasting * pollution Subject RIV: IN - Informatics, Computer Science Impact factor: 0.479, year: 2014

  18. A Sensitivity Study of Human Errors in Optimizing Surveillance Test Interval (STI) and Allowed Outage Time (AOT) of Standby Safety System

    International Nuclear Information System (INIS)

    Chung, Dae Wook; Shin, Won Ky; You, Young Woo; Yang, Hui Chang

    1998-01-01

    In most cases, the surveillance test intervals (STIs), allowed outage times (AOTS) and testing strategies of safety components in nuclear power plant are prescribed in plant technical specifications. And, in general, it is required that standby safety system shall be redundant (i.e., composed of multiple components) and these components are tested by either staggered test strategy or sequential test strategy. In this study, a linear model is presented to incorporate the effects of human errors associated with test into the evaluation of unavailability. The average unavailabilities of 1/4, 2/4 redundant systems are computed considering human error and testing strategy. The adverse effects of test on system unavailability, such as component wear and test-induced transient have been modelled. The final outcome of this study would be the optimized human error domain from 3-D human error sensitivity analysis by selecting finely classified segment. The results of sensitivity analysis show that the STI and AOT can be optimized provided human error probability is maintained within allowable range. (authors)

  19. Towards a medium-range coastal station fog forecasting system

    CSIR Research Space (South Africa)

    Landman, S

    2013-09-01

    Full Text Available -1 29th Annual conference of South African Society for Atmospheric Sciences (SASAS) 2013 http://sasas.ukzn.ac.za/homepage.aspx Towards a Medium-Range Coastal Station Fog Forecasting System Stephanie Landman*1, Estelle Marx1, Willem A. Landman2...

  20. A short-term ensemble wind speed forecasting system for wind power applications

    Science.gov (United States)

    Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

    2011-12-01

    This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

  1. Optimization of safety equipment outages improves safety

    International Nuclear Information System (INIS)

    Cepin, Marko

    2002-01-01

    Testing and maintenance activities of safety equipment in nuclear power plants are an important potential for risk and cost reduction. An optimization method is presented based on the simulated annealing algorithm. The method determines the optimal schedule of safety equipment outages due to testing and maintenance based on minimization of selected risk measure. The mean value of the selected time dependent risk measure represents the objective function of the optimization. The time dependent function of the selected risk measure is obtained from probabilistic safety assessment, i.e. the fault tree analysis at the system level and the fault tree/event tree analysis at the plant level, both extended with inclusion of time requirements. Results of several examples showed that it is possible to reduce risk by application of the proposed method. Because of large uncertainties in the probabilistic safety assessment, the most important result of the method may not be a selection of the most suitable schedule of safety equipment outages among those, which results in similarly low risk. But, it may be a prevention of such schedules of safety equipment outages, which result in high risk. Such finding increases the importance of evaluation speed versus the requirement of getting always the global optimum no matter if it is only slightly better that certain local one

  2. Analyzing Effect of System Inertia on Grid Frequency Forecasting Usnig Two Stage Neuro-Fuzzy System

    Science.gov (United States)

    Chourey, Divyansh R.; Gupta, Himanshu; Kumar, Amit; Kumar, Jitesh; Kumar, Anand; Mishra, Anup

    2018-04-01

    Frequency forecasting is an important aspect of power system operation. The system frequency varies with load-generation imbalance. Frequency variation depends upon various parameters including system inertia. System inertia determines the rate of fall of frequency after the disturbance in the grid. Though, inertia of the system is not considered while forecasting the frequency of power system during planning and operation. This leads to significant errors in forecasting. In this paper, the effect of inertia on frequency forecasting is analysed for a particular grid system. In this paper, a parameter equivalent to system inertia is introduced. This parameter is used to forecast the frequency of a typical power grid for any instant of time. The system gives appreciable result with reduced error.

  3. Outage management: A case study

    International Nuclear Information System (INIS)

    Haber, S.B.; Barriere, M.T.; Roberts, K.H.

    1992-01-01

    Outage management issues identified from a field study conducted at a two-unit commercial pressurized water reactor (PWR), when one unit was in a refueling outage and the other unit was at full power operation, are the focus of this paper. The study was conduced as part of the US Nuclear Regulatory Commission's (NRC) organizational factors research program, and therefore the issues to be addressed are from an organizational perspective. Topics discussed refer to areas identified by the NRC as critical for safety during shutdown operations, including outage planning and control, personnel stress, and improvements in training and procedures. Specifically, issues in communication, management attention, involvement and oversight, administrative processes, organizational culture, and human resources relevant to each of the areas are highlighted by example from field data collection. Insights regarding future guidance in these areas are presented based upon additional data collection subsequent to the original study

  4. The control of reactor outages

    International Nuclear Information System (INIS)

    Bouget, Y.H.; Berteloot, J.M.

    1995-01-01

    The 1985-1992 period was marked by a continuous decay in French reactors operation. This situation has led the Committee for Outages Mastery to take steps for the improvement of nuclear power plants availability. The control of reactor outages requires an integrated vision of the safety, duration, dosimetry, costs and security aspects and a perfect management of contractors. The paper describes the methodology used for the management and the maintenance of the French PWR reactors stock. A detailed schedule of maintenance tasks with dose estimations is now required from each site to anticipate and optimize the duration of outages. Thanks to this action, a significant reduction of the maintenance costs is observed for the 1992-1995 period. (J.S.). 2 figs

  5. Outage costs: who should pay?

    International Nuclear Information System (INIS)

    Stivison, D.V.

    1986-01-01

    Decisions affecting the Three Mile Island-1 and -2 reactors illustrate new an stricter standards which apply to how regulator will allocate the costs of outages. The rule allows outages for normal refueling and other normal shutdowns if return to the power grid is assured. TMI-1 was removed from the rate base one year after the accident, and was readmitted only after achieving full power in 1986. A reasonableness standard based on an analysis of the outage and utility responses is the basis for deciding for or against removal. The author cites cases in which unreasonable actions caused the Nuclear Regulatory Commission to charge utility management with imprudence. New safety standards will force utilities to reduce employee error, equipment failure, and management weakness. 19 references

  6. Streamflow Forecasting Using Nuero-Fuzzy Inference System

    Science.gov (United States)

    Nanduri, U. V.; Swain, P. C.

    2005-12-01

    The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A

  7. Navy Mobility Fuels Forecasting System. Phase I report

    Energy Technology Data Exchange (ETDEWEB)

    Davis, R.M.; Hadder, G.R.; Singh, S.P.N.; Whittle, C.

    1985-07-01

    The Department of the Navy (DON) requires an improved capability to forecast mobility fuel availability and quality. The changing patterns in fuel availability and quality are important in planning the Navy's Mobility Fuels R and D Program. These changes come about primarily because of the decline in the quality of crude oil entering world markets as well as the shifts in refinery capabilities domestically and worldwide. The DON requested ORNL's assistance in assembling and testing a methodology for forecasting mobility fuel trends. ORNL reviewed and analyzed domestic and world oil reserve estimates, production and price trends, and recent refinery trends. Three publicly available models developed by the Department of Energy were selected as the basis of the Navy Mobility Fuels Forecasting System. The system was used to analyze the availability and quality of jet fuel (JP-5) that could be produced on the West Coast of the United States under an illustrative business-as-usual and a world oil disruption scenario in 1990. Various strategies were investigated for replacing the lost JP-5 production. This exercise, which was strictly a test case for the forecasting system, suggested that full recovery of lost fuel production could be achieved by relaxing the smoke point specifications or by increasing the refiners' gate price for the jet fuel. A more complete analysis of military mobility fuel trends is currently under way.

  8. Interval forecasting of cyber-attacks on industrial control systems

    Science.gov (United States)

    Ivanyo, Y. M.; Krakovsky, Y. M.; Luzgin, A. N.

    2018-03-01

    At present, cyber-security issues of industrial control systems occupy one of the key niches in a state system of planning and management Functional disruption of these systems via cyber-attacks may lead to emergencies related to loss of life, environmental disasters, major financial and economic damage, or disrupted activities of cities and settlements. There is then an urgent need to develop protection methods against cyber-attacks. This paper studied the results of cyber-attack interval forecasting with a pre-set intensity level of cyber-attacks. Interval forecasting is the forecasting of one interval from two predetermined ones in which a future value of the indicator will be obtained. For this, probability estimates of these events were used. For interval forecasting, a probabilistic neural network with a dynamic updating value of the smoothing parameter was used. A dividing bound of these intervals was determined by a calculation method based on statistical characteristics of the indicator. The number of cyber-attacks per hour that were received through a honeypot from March to September 2013 for the group ‘zeppo-norcal’ was selected as the indicator.

  9. The status of the Hanaro class 4 power outage

    International Nuclear Information System (INIS)

    Hyungkyoo, K.; Hoansung, J.; Jongsup, W.

    2004-01-01

    Electric power is essential for all industrial plant. All who use electric power desire a perfect frequency, voltage stability, and reliability all the time. But this cannot be realized in practice because of the many causes of a power supply disturbance that are beyond the control of the utility. Since the first criticality of the Hanaro research reactor, the major reasons for reactor trips were system malfunctions and inexperienced operators in the initial stage of its operation. As Hanaro is stabilizing, the power supply outage becomes the major reason for a reactor trip. This paper describes the status of power supply outages. This paper deals with not only the outages which have an effect on Hanaro operation but also the reasons for the Hanaro class-4 power outages. The class-4 power is a commercial power which supplies the load centers and the large motors such as primary cooling pumps and secondary cooling pumps. Even if a class-4 power outage occurs, Hanaro is safe because of the reactor cooling by natural convection and the flywheel effect of the primary cooling pumps. The analysis of the characteristics and the trends of the outages can provide clues to how the outages can be minimized and what the impact of the outages are on the operation. For the site-wide class-4 power, the latest failure rate has been 2.36 per year and the mean time to repair is 23,78 minutes for the exponentially weighted mowing average. The unavailability of the Class-4 power is 1.5 10 -4

  10. Improving refueling outages through partnership

    International Nuclear Information System (INIS)

    Mercado, Angelo L.

    2004-01-01

    This paper describes an approach to reduce nuclear plant outage duration and cost through partnership. Partnership is defined as a long-term commitment between the utility and the vendor with the objective of achieving shared business goals by maximizing the effectiveness of each party's resources. The elements of an effective partnership are described. Specific examples are given as to how partnership has worked in the effective performance of refueling outages. To gain the full benefits of a partnership, both parties must agree to share information, define the scope early, communicate goals and expectations, and identify boundaries for technical ownership. (author)

  11. Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

    Science.gov (United States)

    Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

    2015-01-01

    A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

  12. On Outage Performance of Spectrum-Sharing Communication over M-Block Fading

    KAUST Repository

    Alabbasi, AbdulRahman

    2015-12-06

    In this paper, we consider a cognitive radio system in which a block-fading channel is assumed. Each transmission frame consists of M blocks and each block undergoes a different channel gain. Instantaneous channel state information about the interference links remains unknown to the primary and secondary users. We minimize the secondary user\\'s targeted outage probability over the block-fading channels. To protect the primary user, a statistical constraint on its targeted outage probability is enforced. The secondary user\\'s targeted outage region and the corresponding optimal power are derived. We also propose two sub-optimal power strategies and derive compact expressions for the corresponding outage probabilities. These probabilities are shown to be asymptotic lower and upper bounds on the outage probability. Utilizing these bounds, we derive the exact diversity order of the secondary user outage probability. Selected numerical results are presented to characterize the system\\'s behavior.

  13. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    Energy Technology Data Exchange (ETDEWEB)

    Hoff, Thomas Hoff [Clean Power Research, L.L.C., Napa, CA (United States); Kankiewicz, Adam [Clean Power Research, L.L.C., Napa, CA (United States)

    2016-02-26

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP) forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest

  14. Real-time drought forecasting system for irrigation managment

    Science.gov (United States)

    Ceppi, Alessandro; Ravazzani, Giovanni; Corbari, Chiara; Masseroni, Daniele; Meucci, Stefania; Pala, Francesca; Salerno, Raffaele; Meazza, Giuseppe; Chiesa, Marco; Mancini, Marco

    2013-04-01

    In recent years frequent periods of water scarcity have enhanced the need to use water more carefully, even in in European areas traditionally rich of water such as the Po Valley. In dry periods, the problem of water shortage can be enhanced by conflictual use of water such as irrigation, industrial and power production (hydroelectric and thermoelectric). Further, over the last decade the social perspective on this issue is increasing due to climate change and global warming scenarios which come out from the last IPCC Report. The increased frequency of dry periods has stimulated the improvement of irrigation and water management. In this study we show the development and implementation of the real-time drought forecasting system Pre.G.I., an Italian acronym that stands for "Hydro-Meteorological forecast for irrigation management". The system is based on ensemble prediction at long range (30 days) with hydrological simulation of water balance to forecast the soil water content in every parcel over the Consorzio Muzza basin. The studied area covers 74,000 ha in the middle of the Po Valley, near the city of Lodi. The hydrological ensemble forecasts are based on 20 meteorological members of the non-hydrostatic WRF model with 30 days as lead-time, provided by Epson Meteo Centre, while the hydrological model used to generate the soil moisture and water table simulations is the rainfall-runoff distributed FEST-WB model, developed at Politecnico di Milano. The hydrological model was validated against measurements of latent heat flux and soil moisture acquired by an eddy-covariance station. Reliability of the forecasting system and its benefits was assessed on some cases-study occurred in the recent years.

  15. Wolsong Unit 1 restart chemistry procedures during retubing outage

    International Nuclear Information System (INIS)

    Yun, Hyunran; Lee, Sarang; Moon, Yunyong; Kim, Seoyul

    2015-01-01

    Lay-up is aimed at protecting systems from degradation during outage, mainly by minimizing corrosion and particularly, when the outage is longer than 16 weeks. Due to the intrinsic design of CANDU reactors, their horizontal fuel channels should be replaced for another service life time. This poster presents the lay-up guidelines and methods recommended for re-tubing outage based on the first re-tubing operation made in Korea (at the Wolsung Unit 1). It is shown that dry lay-up with specific gas blanket was the sole choice for the primary heat transfer system, the moderator system and the steam cycle system while wet lay-up under circulation was recommended for the end shield cooling system and the liquid zone control system. The water filled part of steam generators, of the liquid zone control system and of the end shield cooling system was maintained normal

  16. East Asian winter monsoon forecasting schemes based on the NCEP's climate forecast system

    Science.gov (United States)

    Tian, Baoqiang; Fan, Ke; Yang, Hongqing

    2017-12-01

    The East Asian winter monsoon (EAWM) is the major climate system in the Northern Hemisphere during boreal winter. In this study, we developed two schemes to improve the forecasting skill of the interannual variability of the EAWM index (EAWMI) using the interannual increment prediction method, also known as the DY method. First, we found that version 2 of the NCEP's Climate Forecast System (CFSv2) showed higher skill in predicting the EAWMI in DY form than not. So, based on the advantage of the DY method, Scheme-I was obtained by adding the EAWMI DY predicted by CFSv2 to the observed EAWMI in the previous year. This scheme showed higher forecasting skill than CFSv2. Specifically, during 1983-2016, the temporal correlation coefficient between the Scheme-I-predicted and observed EAWMI was 0.47, exceeding the 99% significance level, with the root-mean-square error (RMSE) decreased by 12%. The autumn Arctic sea ice and North Pacific sea surface temperature (SST) are two important external forcing factors for the interannual variability of the EAWM. Therefore, a second (hybrid) prediction scheme, Scheme-II, was also developed. This scheme not only involved the EAWMI DY of CFSv2, but also the sea-ice concentration (SIC) observed the previous autumn in the Laptev and East Siberian seas and the temporal coefficients of the third mode of the North Pacific SST in DY form. We found that a negative SIC anomaly in the preceding autumn over the Laptev and the East Siberian seas could lead to a significant enhancement of the Aleutian low and East Asian westerly jet in the following winter. However, the intensity of the winter Siberian high was mainly affected by the third mode of the North Pacific autumn SST. Scheme-I and Scheme-II also showed higher predictive ability for the EAWMI in negative anomaly years compared to CFSv2. More importantly, the improvement in the prediction skill of the EAWMI by the new schemes, especially for Scheme-II, could enhance the forecasting skill of

  17. Forecasting Hurricane Tracks Using a Complex Adaptive System

    National Research Council Canada - National Science Library

    Lear, Matthew R

    2005-01-01

    Forecast hurricane tracks using a multi-model ensemble that consists of linearly combining the individual model forecasts have greatly reduced the average forecast errors when compared to individual...

  18. A Complex Adaptive System Approach to Forecasting Hurricane Tracks

    National Research Council Canada - National Science Library

    Lear, Matthew R

    2005-01-01

    Forecast hurricane tracks using a multi-model ensemble that consists of linearly combining the individual model forecasts have greatly reduced the average forecast errors when compared to individual...

  19. A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

    Science.gov (United States)

    Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

    2017-04-01

    Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of

  20. Forecasting and recruitment in graded manpower systems

    NARCIS (Netherlands)

    van Nunen, J.A.E.E.; Wessels, J.

    1977-01-01

    In this paper a generalized Markov model is introduced to describe the dynamic behaviour of an individual employee in a graded Manpower system. Characteristics like the employee's grade, his educational level, his age and the time spent in his actual grade, can be incorporated in the Markov model.

  1. Optimal Power Flow for Distribution Systems under Uncertain Forecasts: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Dall' Anese, Emiliano; Baker, Kyri; Summers, Tyler

    2016-12-01

    The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.

  2. Cooperative AF Relaying in Spectrum-Sharing Systems: Outage Probability Analysis under Co-Channel Interferences and Relay Selection

    KAUST Repository

    Xia, Minghua; Aissa, Sonia

    2012-01-01

    For cooperative amplify-and-forward (AF) relaying in spectrum-sharing wireless systems, secondary users share spectrum resources originally licensed to primary users to communicate with each other and, thus, the transmit power of secondary

  3. A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

    Science.gov (United States)

    Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

    2017-12-01

    The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

  4. Design and implementation of ticket price forecasting system

    Science.gov (United States)

    Li, Yuling; Li, Zhichao

    2018-05-01

    With the advent of the aviation travel industry, a large number of data mining technologies have been developed to increase profits for airlines in the past two decades. The implementation of the digital optimization strategy leads to price discrimination, for example, similar seats on the same flight are purchased at different prices, depending on the time of purchase, the supplier, and so on. Price fluctuations make the prediction of ticket prices have application value. In this paper, a combination of ARMA algorithm and random forest algorithm is proposed to predict the price of air ticket. The experimental results show that the model is more reliable by comparing the forecasting results with the actual results of each price model. The model is helpful for passengers to buy tickets and to save money. Based on the proposed model, using Python language and SQL Server database, we design and implement the ticket price forecasting system.

  5. Sales Forecasting System for Newspaper Distribution Companies in Turkey

    Directory of Open Access Journals (Sweden)

    Gencay İncesu

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE st1\\:*{behavior:url(#ieooui } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} Newspapers are like goods with a shelf life of one day and they have to be distributed daily basis to the sales points. A problem that most newspaper companies encounter daily is how to predict the right number of newspapers to print and distribute among distinct sales points. The aim is to predict newspaper demand as accurately as possible to meet customer need with minimum number of returns, missed sales and oversupply. This makes it necessary to develop a short-term forecasting system. The data taken from one of the largest distribution companies in Turkey is time dependent. Therefore, time series analysis is used to forecast newspaper circulation. In this paper, the newspaper sales system is examined for Turkey. Various types of forecasting techniques which are applicable to newspaper circulation planning are compared and a nonlinear approach for returns is applied.

  6. Anvil Forecast Tool in the Advanced Weather Interactive Processing System

    Science.gov (United States)

    Barrett, Joe H., III; Hood, Doris

    2009-01-01

    Meteorologists from the 45th Weather Squadron (45 WS) and National Weather Service Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the Lightning Launch Commit Criteria and Space Shuttle Flight Rules. As a result, the Applied Meteorology Unit (AMU) was tasked to create a graphical overlay tool for the Meteorological Interactive Data Display System (MIDDS) that indicates the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input. The tool creates a graphic depicting the potential location of thunderstorm anvils one, two, and three hours into the future. The locations are based on the average of the upper level observed or forecasted winds. The graphic includes 10 and 20 n mi standoff circles centered at the location of interest, as well as one-, two-, and three-hour arcs in the upwind direction. The arcs extend outward across a 30 sector width based on a previous AMU study that determined thunderstorm anvils move in a direction plus or minus 15 of the upper-level wind direction. The AMU was then tasked to transition the tool to the Advanced Weather Interactive Processing System (AWIPS). SMG later requested the tool be updated to provide more flexibility and quicker access to model data. This presentation describes the work performed by the AMU to transition the tool into AWIPS, as well as the subsequent improvements made to the tool.

  7. A multidisciplinary system for monitoring and forecasting Etna volcanic plumes

    Science.gov (United States)

    Coltelli, Mauro; Prestifilippo, Michele; Spata, Gaetano; Scollo, Simona; Andronico, Daniele

    2010-05-01

    One of the most active volcanoes in the world is Mt. Etna, in Italy, characterized by frequent explosive activity from the central craters and from fractures opened along the volcano flanks which, during the last years, caused several damages to aviation and forced the closure of the Catania International Airport. To give precise warning to the aviation authorities and air traffic controller and to assist the work of VAACs, a novel system for monitoring and forecasting Etna volcanic plumes, was developed at the Istituto Nazionale di Geofisica e Vulcanologia, sezione di Catania, the managing institution for the surveillance of Etna volcano. Monitoring is carried out using multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation geosynchronous satellite able to track the volcanic plume with a high time resolution, visual and thermal cameras used to monitor the explosive activity, three continuous wave X-band disdrometers which detect ash dispersal and fallout, sounding balloons used to evaluate the atmospheric fields, and finally field data collected after the end of the eruptive event needed to extrapolate important features of explosive activity. Forecasting is carried out daily using automatic procedures which download weather forecast data obtained by meteorological mesoscale models from the Italian Air Force national Meteorological Office and from the hydrometeorological service of ARPA-SIM; run four different tephra dispersal models using input parameters obtained by the analysis of the deposits collected after few hours since the eruptive event similar to 22 July 1998, 21-24 July 2001 and 2002-03 Etna eruptions; plot hazard maps on ground and in air and finally publish them on a web-site dedicated to the Italian Civil Protection. The system has been already tested successfully during several explosive events occurring at Etna in 2006, 2007 and 2008. These events produced eruption

  8. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le; Gu, Yingzhong; Zhu, Xinxin; Genton, Marc G.

    2014-01-01

    forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24

  9. Forecasting US renewables in the national energy modelling system

    International Nuclear Information System (INIS)

    Diedrich, R.; Petersik, T.W.

    2001-01-01

    The Energy information Administration (EIA) of the US Department of Energy (DOE) forecasts US renewable energy supply and demand in the context of overall energy markets using the National Energy Modelling System (NEMS). Renewables compete with other supply and demand options within the residential, commercial, industrial, transportation, and electricity sectors of the US economy. NEMS forecasts renewable energy for grid-connected electricity production within the Electricity Market Module (EM), and characterizes central station biomass, geothermal, conventional hydroelectric, municipal solid waste, solar thermal, solar photovoltaic, and wind-powered electricity generating technologies. EIA's Annual Energy Outlook 1998, projecting US energy markets, forecasts marketed renewables to remain a minor part of US energy production and consumption through to 2020. The USA is expected to remain primarily a fossil energy producer and consumer throughout the period. An alternative case indicates that biomass, wind, and to some extent geothermal power would likely increase most rapidly if the US were to require greater use of renewables for power supply, though electricity prices would increase somewhat. (author)

  10. Forecasting system predicts presence of sea nettles in Chesapeake Bay

    Science.gov (United States)

    Brown, Christopher W.; Hood, Raleigh R.; Li, Zhen; Decker, Mary Beth; Gross, Thomas F.; Purcell, Jennifer E.; Wang, Harry V.

    Outbreaks of noxious biota, which occur in both aquatic and terrestrial systems, can have considerable negative economic impacts. For example, an increasing frequency of harmful algal blooms worldwide has negatively affected the tourism industry in many regions. Such impacts could be mitigated if the conditions that give rise to these outbreaks were known and could be monitored. Recent advances in technology and communications allow us to continuously measure and model many environmental factors that are responsible for outbreaks of certain noxious organisms. A new prototype ecological forecasting system predicts the likelihood of occurrence of the sea nettle (Chrysaora quinquecirrha), a stinging jellyfish, in the Chesapeake Bay.

  11. Power Outage - 16 October

    CERN Multimedia

    2014-01-01

    At 19:03 last night, a fire in an 18kV circuit breaker in building 212 led to a blackout on the Meyrin site. The CERN fire brigade rapidly brought the fire under control and power was restored by 22:25. Many CERN systems were affected and have been brought back in to service overnight, this work will continue through the day.

  12. Outage management philosophies at Oconee nuclear station

    International Nuclear Information System (INIS)

    Bond, R.T.

    1991-01-01

    At Oconee the biggest single factor in improving availability and cutting cost per kilowatt-hour is reducing outage lengths. This must be accomplished without compromising the quality of the work that must be performed during these outages. Oconee has completed 35 refueling outages and has gained considerable experience in outage management. Since 1984, outage costs and durations have consistently been reduced while continuing to improve capacity factors. The last 6 refueling outages were 43, 42, 45, 42, 41, and 44 days, respectively. The capacity factors for these units between refueling outages are 98, 94, 96, 98, and 98%, respectively. The average cost of outages has been less than $12 million. It is believed that success cannot be attributed to any one factor by itself but is a compilation of many factors, all complementing each other. It is also believed, however, that there are four key areas that represent philosophies and can be given most of the credit for successful outages: planning, experience, teamwork, and outage management

  13. Nuclear power plant outage optimisation strategy

    International Nuclear Information System (INIS)

    2002-10-01

    Competitive environment for electricity generation has significant implications for nuclear power plant operations, including among others the need of efficient use of resources, effective management of plant activities such as on-line maintenance and outages. Nuclear power plant outage management is a key factor for good, safe and economic nuclear power plant performance which involves many aspects: plant policy, co-ordination of available resources, nuclear safety, regulatory and technical requirements and, all activities and work hazards, before and during the outage. This technical publication aims to communicate these practices in a way they can be used by operators and utilities in the Member States of the IAEA. It intends to give guidance to outage managers, operating staff and to the local industry on planning aspects, as well as examples and strategies experienced from current plants in operation on the optimization of outage period. This report discusses the plant outage strategy and how this strategy is actually implemented. The main areas identified as most important for outage optimization by the utilities and government organizations participating in this report are: organization and management; outage planning and preparation, outage execution, safety outage review, and counter measures to avoid extension of outages and to easier the work in forced outages. This report was based on discussions and findings by the authors of the annexes and the participants of an Advisory Group Meeting on Determinant Causes for Reducing Outage Duration held in June 1999 in Vienna. The report presents the consensus of these experts regarding best common or individual good practices that can be used at nuclear power plants with the aim to optimize

  14. Knowledge to Action - Understanding Natural Hazards-Induced Power Outage Scenarios for Actionable Disaster Responses

    Science.gov (United States)

    Kar, B.; Robinson, C.; Koch, D. B.; Omitaomu, O.

    2017-12-01

    The Sendai Framework for Disaster Risk Reduction 2015-2030 identified the following four priorities to prevent and reduce disaster risks: i) understanding disaster risk; ii) strengthening governance to manage disaster risk; iii) investing in disaster risk reduction for resilience and; iv) enhancing disaster preparedness for effective response, and to "Build Back Better" in recovery, rehabilitation and reconstruction. While forecasting and decision making tools are in place to predict and understand future impacts of natural hazards, the knowledge to action approach that currently exists fails to provide updated information needed by decision makers to undertake response and recovery efforts following a hazard event. For instance, during a tropical storm event advisories are released every two to three hours, but manual analysis of geospatial data to determine potential impacts of the event tends to be time-consuming and a post-event process. Researchers at Oak Ridge National Laboratory have developed a Spatial Decision Support System that enables real-time analysis of storm impact based on updated advisory. A prototype of the tool that focuses on determining projected power outage areas and projected duration of outages demonstrates the feasibility of integrating science with decision making for emergency management personnel to act in real time to protect communities and reduce risk.

  15. AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

    Science.gov (United States)

    Reale, O.; Lau, W.K.; Susskind, J.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Rosenburg, R.; Fuentes, M.

    2009-01-01

    Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

  16. The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

    Science.gov (United States)

    Reynolds, David; Rasch, William; Kozlowski, Daniel; Burks, Jason; Zavodsky, Bradley; Bernardet, Ligia; Jankov, Isidora; Albers, Steve

    2014-01-01

    The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near-realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9-km horizontal grid spacing. The ensemble has eight members, all employing WRF-ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012-2013 and 2013-2014 winters. A smaller domain covering just the West Coast was created to minimize band-width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short-term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6-hr QPF along with the ExREF mean 6-hr QPF so the forecasters can build confidence in the use of the

  17. Multiplexed FBG Monitoring System for Forecasting Coalmine Water Inrush Disaster

    Directory of Open Access Journals (Sweden)

    B. Liu

    2012-01-01

    Full Text Available This paper presents a novel fiber-Bragg-grating- (FBG- based system which can monitor and analyze multiple parameters such as temperature, strain, displacement, and seepage pressure simultaneously for forecasting coalmine water inrush disaster. The sensors have minimum perturbation on the strain field. And the seepage pressure sensors adopt a drawbar structure and employ a corrugated diaphragm to transmit seepage pressure to the axial strain of FBG. The pressure sensitivity is 20.20 pm/KPa, which is 6E3 times higher than that of ordinary bare FBG. The FBG sensors are all preembedded on the roof of mining area in coalmine water inrush model test. Then FBG sensing network is set up applying wavelength-division multiplexing (WDM technology. The experiment is carried out by twelve steps, while the system acquires temperature, strain, displacement, and seepage pressure signals in real time. The results show that strain, displacement, and seepage pressure monitored by the system change significantly before water inrush occurs, and the strain changes firstly. Through signal fusion analyzed it can be concluded that the system provides a novel way to forecast water inrush disaster successfully.

  18. An Operational Coastal Forecasting System in Galicia (NW Spain)

    Science.gov (United States)

    Balseiro, C. F.; Carracedo, P.; Pérez, E.; Pérez, V.; Taboada, J.; Venacio, A.; Vilasa, L.

    2009-09-01

    The Galician coast (NW Iberian Peninsula coast) and mainly the Rias Baixas (southern Galician rias) are one of the most productive ecosystems in the world, supporting a very active fishing and aquiculture industry. This high productivity lives together with a high human pressure and an intense maritime traffic, which means an important environmental risk. Besides that, Harmful Algae Blooms (HAB) are common in this area, producing important economical losses in aquiculture. In this context, the development of an Operational Hydrodynamic Ocean Forecast System is the first step to the development of a more sophisticated Ocean Integrated Decision Support Tool. A regional oceanographic forecasting system in the Galician Coast has been developed by MeteoGalicia (the Galician regional meteorological agency) inside ESEOO project to provide forecasts on currents, sea level, water temperature and salinity. This system is based on hydrodynamic model MOHID, forced with the operational meteorological model WRF, supported daily at MeteoGalicia . Two grid meshes are running nested at different scales, one of ~2km at the shelf scale and the other one with a resolution of 500 m at the rias scale. ESEOAT (Puertos del Estado) model provide salinity and temperature fields which are relaxed at all depth along the open boundary of the regional model (~6km). Temperature and salinity initial fields are also obtained from this application. Freshwater input from main rivers are included as forcing in MOHID model. Monthly mean discharge data from gauge station have been provided by Aguas de Galicia. Nowadays a coupling between an hydrological model (SWAT) and the hydrodynamic one are in development with the aim to verify the impact of the rivers discharges. The system runs operationally daily, providing two days of forecast. First model verifications had been performed against Puertos del Estado buoys and Xunta de Galicia buoys network along the Galician coast. High resolution model results

  19. Short-Term Wind Speed Forecasting for Power System Operations

    KAUST Repository

    Zhu, Xinxin; Genton, Marc G.

    2012-01-01

    some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss

  20. The course of a true outage never ran so smooth

    International Nuclear Information System (INIS)

    Harberts, Craig

    1994-01-01

    In order to improve the performance of outages at San Onofre Nuclear Generating Station in California, the working structure of the entire organisation has had to be radically altered, in order to bring San Onofre up to standard with other nuclear plants known to be performing well. Working systems were simplified and efficiency improved. Personnel needed to be remotivated to work cooperatively and the outage budget process was revised to include input from all relevant organizations, historical costs and benchmark information from other plants that performed well. Finally, the decision making and teamwork culture has altered radically at San Onofre over the last decade. (UK)

  1. Traffic congestion forecasting model for the INFORM System. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  2. A nowcast-forecast information system for PWS

    International Nuclear Information System (INIS)

    Thomas, G.L.; Cox, W.

    2000-01-01

    The development of the Prince William Sound Oil Spill Recovery Institute's (ORI) nowcast-forecast information system was discussed. OSRI addresses oil spill response and prevention research and development in the Arctic and subArctic. A realistic electronic model of the ecosystem was a much needed tool for efficient prioritization of oil spill technologies. The OSRI Sound Ecosystem Assessment (SEA) research program focused on developing a physical-biological model that consisted of static and biological resources that change over long time periods. This includes bathymetry, shoreline type, and substrate-dependent vegetation. It also focused on developing a model of dynamic properties such as wind, weather, plankton, and wildlife populations that undergo significant changes on annual or shorter time scales. The nowcast information system is a long-term development project which uses the Princeton ocean model (POM), a static runoff model, a network of weather and water observation stations, an Intranet which allows the observational data to run in near-real time and an Internet home page. It will contribute to sustaining the natural resources of coastal areas. It was concluded that the nowcast-forecast information system has short-term applications to oil spill prevention and response and long-term applications to the natural resources at risk to spills. 33 refs

  3. A quality assessment of the MARS crop yield forecasting system for the European Union

    Science.gov (United States)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  4. Better Forecasting for Better Planning: A Systems Approach.

    Science.gov (United States)

    Austin, W. Burnet

    Predictions and forecasts are the most critical features of rational planning as well as the most vulnerable to inaccuracy. Because plans are only as good as their forecasts, current planning procedures could be improved by greater forecasting accuracy. Economic factors explain and predict more than any other set of factors, making economic…

  5. Advances in electric power and energy systems load and price forecasting

    CERN Document Server

    2017-01-01

    A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

  6. Using adaptive network based fuzzy inference system to forecast regional electricity loads

    International Nuclear Information System (INIS)

    Ying, L.-C.; Pan, M.-C.

    2008-01-01

    Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

  7. Using adaptive network based fuzzy inference system to forecast regional electricity loads

    Energy Technology Data Exchange (ETDEWEB)

    Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

    2008-02-15

    Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

  8. A national-scale seasonal hydrological forecast system: development and evaluation over Britain

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2017-09-01

    Full Text Available Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts from the GloSea5 model (1996 to 2009 are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region. Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 % in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows, whereas for the 3-month ahead lead time, GloSea5 forecasts account for  ∼ 70

  9. Management strategies for nuclear power plant outages

    International Nuclear Information System (INIS)

    2006-01-01

    More competitive energy markets have significant implications for nuclear power plant operations, including, among others, the need for more efficient use of resources and effective management of plant activities such as on-line maintenance and outages. Outage management is a key factor for safe, reliable and economic plant performance and involves many aspects: plant policy, coordination of available resources, nuclear safety, regulatory and technical requirements, and all activities and work hazards, before and during the outage. The IAEA has produced this report on nuclear power plant outage management strategies to provide both a summary and an update of a follow-up to a series of technical documents related to practices regarding outage management and cost effective maintenance. The aim of this publication is to identify good practices in outage management: outage planning and preparation, outage execution and post-outage review. As in in the related technical documents, this report aims to communicate these practices in such a way that they can be used by operating organizations and regulatory bodies in Member States. The report was prepared as part of an IAEA project on continuous process improvement. The objective of this project is to increase Member State capabilities in improving plant performance and competitiveness through the utilization of proven engineering and management practices developed and transferred by the IAEA

  10. Operational water management of Rijnland water system and pilot of ensemble forecasting system for flood control

    Science.gov (United States)

    van der Zwan, Rene

    2013-04-01

    The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water

  11. Operational air quality forecasting system for Spain: CALIOPE

    Science.gov (United States)

    Baldasano, J. M.; Piot, M.; Jorba, O.; Goncalves, M.; Pay, M.; Pirez, C.; Lopez, E.; Gasso, S.; Martin, F.; García-Vivanco, M.; Palomino, I.; Querol, X.; Pandolfi, M.; Dieguez, J. J.; Padilla, L.

    2009-12-01

    The European Commission (EC) and the United States Environmental Protection Agency (US-EPA) have shown great concerns to understand the transport and dynamics of pollutants in the atmosphere. According to the European directives (1996/62/EC, 2002/3/EC, 2008/50/EC), air quality modeling, if accurately applied, is a useful tool to understand the dynamics of air pollutants, to analyze and forecast the air quality, and to develop programs reducing emissions and alert the population when health-related issues occur. The CALIOPE project, funded by the Spanish Ministry of the Environment, has the main objective to establish an air quality forecasting system for Spain. A partnership of four research institutions composes the CALIOPE project: the Barcelona Supercomputing Center (BSC), the center of investigation CIEMAT, the Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC) and the CEAM Foundation. CALIOPE will become the official Spanish air quality operational system. This contribution focuses on the recent developments and implementation of the integrated modelling system for the Iberian Peninsula (IP) and Canary Islands (CI) with a high spatial and temporal resolution (4x4 sq. km for IP and 2x2 sq. km for CI, 1 hour), namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM. The HERMES04 emission model has been specifically developed as a high-resolution (1x1 sq. km, 1 hour) emission model for Spain. It includes biogenic and anthropogenic emissions such as on-road and paved-road resuspension production, power plant generation, ship and plane traffic, airports and ports activities, industrial and agricultural sectors as well as domestic and commercial emissions. The qualitative and quantitative evaluation of the model was performed for a reference year (2004) using data from ground-based measurement networks. The products of the CALIOPE system will provide 24h and 48h forecasts for O3, NO2, SO2, CO, PM10 and PM2.5 at surface level. An operational evaluation system has been developed

  12. Flood forecasting within urban drainage systems using NARX neural network.

    Science.gov (United States)

    Abou Rjeily, Yves; Abbas, Oras; Sadek, Marwan; Shahrour, Isam; Hage Chehade, Fadi

    2017-11-01

    Urbanization activity and climate change increase the runoff volumes, and consequently the surcharge of the urban drainage systems (UDS). In addition, age and structural failures of these utilities limit their capacities, and thus generate hydraulic operation shortages, leading to flooding events. The large increase in floods within urban areas requires rapid actions from the UDS operators. The proactivity in taking the appropriate actions is a key element in applying efficient management and flood mitigation. Therefore, this work focuses on developing a flooding forecast system (FFS), able to alert in advance the UDS managers for possible flooding. For a forecasted storm event, a quick estimation of the water depth variation within critical manholes allows a reliable evaluation of the flood risk. The Nonlinear Auto Regressive with eXogenous inputs (NARX) neural network was chosen to develop the FFS as due to its calculation nature it is capable of relating water depth variation in manholes to rainfall intensities. The campus of the University of Lille is used as an experimental site to test and evaluate the FFS proposed in this paper.

  13. Planning and management of outages in nuclear power plants

    International Nuclear Information System (INIS)

    Sica, G.F.; Fusari, W.; Reginelli, A.

    1984-01-01

    At present the Ente Nazionale per l'Energia Elettrica (ENEL) operates three nuclear power plants, only one of which belongs to the new generation, i.e. the Caorso Nuclear Power Plant which has been in commercial operation since December 1981. Outage planning, implementation and analysis are very important in order to minimize the shutdown time and thus improve plant availability, which is of particular importance for a large nuclear power plant. Such activities are very complicated because of the large number of jobs that have to be performed in accordance with detailed written procedures and which have to be properly documented and controlled. Large off-site resources are required which have to be accurately interfaced with on-site staff. The ENEL is making a great effort to define both the administrative and technical aspects of refuelling outages. As outage planning requires the availability and handling of a large amount of data and information, a maintenance information system that has been widely used in conventional plants was applied, with some modifications made especially for the Caorso Nuclear Power Plant. After two years the following results have been achieved: a large number of raw and processed data are now available, the first refuelling outage was carried out with few problems and according to schedule, and the second refuelling outage, based on the experience of the first, required somewhat less preparation and is developing well even though many special activities have had to be scheduled. The ENEL believes that the efforts made in the planning and management areas will pay off in terms of the short duration, smoothness and economy of further outages, both for Caorso and for future plants. (author)

  14. An independent system operator's perspective on operational ramp forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Porter, G. [New Brunswick System Operator, Fredericton, NB (Canada)

    2010-07-01

    One of the principal roles of the power system operator is to select the most economical resources to reliably supply electric system power needs. Operational wind power production forecasts are required by system operators in order to understand the impact of ramp event forecasting on dispatch functions. A centralized dispatch approach can contribute to a more efficient use of resources that traditional economic dispatch methods. Wind ramping events can have a significant impact on system reliability. Power systems can have constrained or robust transmission systems, and may also be islanded or have large connections to neighbouring systems. Power resources can include both flexible and inflexible generation resources. Wind integration tools must be used by system operators to improve communications and connections with wind power plants. Improved wind forecasting techniques are also needed. Sensitivity to forecast errors is dependent on current system conditions. System operators require basic production forecasts, probabilistic forecasts, and event forecasts. Forecasting errors were presented as well as charts outlining the implications of various forecasts. tabs., figs.

  15. MOCASSIM - an operational forecast system for the Portuguese coastal waters.

    Science.gov (United States)

    Vitorino, J.; Soares, C.; Almeida, S.; Rusu, E.; Pinto, J.

    2003-04-01

    An operational system for the forecast of oceanographic conditions off the Portuguese coast is presently being implemented at Instituto Hidrográfico (IH), in the framework of project MOCASSIM. The system is planned to use a broad range of observations provided both from IH observational networks (wave buoys, tidal gauges) and programs (hydrographic surveys, moorings) as well as from external sources. The MOCASSIM system integrates several numerical models which, combined, are intended to cover the relevant physical processes observed in the geographical areas of interest. At the present stage of development the system integrates a circulation module and a wave module. The circulation module is based on the Harvard Ocean Prediction System (HOPS), a primitive equation model formulated under the rigid lid assumption, which includes a data assimilation module. The wave module is based on the WaveWatch3 (WW3) model, which provides wave conditions in the North Atlantic basin, and on the SWAN model which is used to improve the wave forecasts on coastal or other specific areas of interest. The models use the meteorological forcing fields of a limited area model (ALADIN model) covering the Portuguese area, which are being provided in the framework of a close colaboration with Instituto de Meteorologia. Although still under devellopment, the MOCASSIM system has already been used in several operationnal contexts. These included the operational environmental assessment during both national and NATO navy exercises and, more recently, the monitoring of the oceanographic conditions in the NW Iberian area affected by the oil spill of MV "Prestige". The system is also a key component of ongoing research on the oceanography of the Portuguese continental margin, which is presently being conducted at IH in the framework of national and European funded projects.

  16. Search for new ternary Al, Ga or In containing phases using information forecasting system

    International Nuclear Information System (INIS)

    Kiseleva, N.N.; Burkhanov, G.S.

    1989-01-01

    Automated system of search for regularities in the formation of crystal phases and forecasting of new compounds with required properties, comprising data base on the properties of ternary inorganic compounds and cybernetic forecasting system, has been developed. General principles of operation of the developed information-forecasting system are considered. Efficiency of the system operation is shown, using as an example the search for new ternary compounds with aluminium, gallium and indium, crystallized in ZrNiAl, TiNiSi, ThCr 2 Si 2 , CaAl 2 Si 2 structural types. Results of the above-mentioned phases forecasting are shown

  17. Management of planned unit outages

    International Nuclear Information System (INIS)

    Brune, W.

    1984-01-01

    Management of planned unit outages at the Bruno Leuschner Nuclear Power Plant is based on the experience gained with Soviet PWR units of the WWER type over a period of more than 50 reactor-years. For PWR units, planned outages concentrate almost exclusively on annual refuellings and major maintenance of the power plant facilities involved. Planning of such major maintenance work is based on a standardized basic network plan and a catalogue of standardized maintenance and inspection measures. From these, an overall maintenance schedule of the unit and partial process plans of the individual main components are derived (manually or by computer) and, in the temporal integration of major maintenance at every unit, fixed starting times and durations are determined. More than 75% of the maintenance work at the Bruno Leuschner Nuclear Power Plant is carried out by the plant's own maintenance personnel. Large-scale maintenance of every unit is controlled by a special project head. He is assisted by commissioners, each of whom is responsible for his own respective item. A daily control report is made. The organizational centre is a central office which works in shifts around the clock. All maintenance orders and reports of completion pass through this office; thus, the overall maintenance schedule can be corrected daily. To enforce the proposed operational strategy, suitable accompanying technical measures are required with respect to effective facility monitoring and technical diagnosis, purposeful improvement of particularly sensitive components and an increase in the effectiveness of maintenance work by special technologies and devices. (author)

  18. Verification of Global Radiation Forecasts from the Ensemble Prediction System at DMI

    DEFF Research Database (Denmark)

    Lundholm, Sisse Camilla

    To comply with an increasing demand for sustainable energy sources, a solar heating unit is being developed at the Technical University of Denmark. To make optimal use — environmentally and economically —, this heating unit is equipped with an intelligent control system using forecasts of the heat...... consumption of the house and the amount of available solar energy. In order to make the most of this solar heating unit, accurate forecasts of the available solar radiation are esstential. However, because of its sensitivity to local meteorological conditions, the solar radiation received at the surface...... of the Earth can be highly fluctuating and challenging to forecast accurately. To comply with the accuracy requirements to forecasts of both global, direct, and diffuse radiation, the uncertainty of these forecasts is of interest. Forecast uncertainties can become accessible by running an ensemble of forecasts...

  19. Operational flood forecasting system of Umbria Region "Functional Centre

    Science.gov (United States)

    Berni, N.; Pandolfo, C.; Stelluti, M.; Ponziani, F.; Viterbo, A.

    2009-04-01

    The hydrometeorological alert office (called "Decentrate Functional Centre" - CFD) of Umbria Region, in central Italy, is the office that provides technical tools able to support decisions when significant flood/landslide events occur, furnishing 24h support for the whole duration of the emergency period, according to the national directive DPCM 27 February 2004 concerning the "Operating concepts for functional management of national and regional alert system during flooding and landslide events for civil protection activities purposes" that designs, within the Italian Civil Defence Emergency Management System, a network of 21 regional Functional Centres coordinated by a central office at the National Civil Protection Department in Rome. Due to its "linking" role between Civil Protection "real time" activities and environmental/planning "deferred time" ones, the Centre is in charge to acquire and collect both real time and quasi-static data: quantitative data from monitoring networks (hydrometeorological stations, meteo radar, ...), meteorological forecasting models output, Earth Observation data, hydraulic and hydrological simulation models, cartographic and thematic GIS data (vectorial and raster type), planning studies related to flooding areas mapping, dam managing plans during flood events, non instrumental information from direct control of "territorial presidium". A detailed procedure for the management of critical events was planned, also in order to define the different role of various authorities and institutions involved. Tiber River catchment, of which Umbria region represents the main upper-medium portion, includes also regional trans-boundary issues very important to cope with, especially for what concerns large dam behavior and management during heavy rainfall. The alert system is referred to 6 different warning areas in which the territory has been divided into and based on a threshold system of three different increasing critical levels according

  20. Seasonal and Local Characteristics of Lightning Outages of Power Distribution Lines in Hokuriku Area

    Science.gov (United States)

    Sugimoto, Hitoshi; Shimasaki, Katsuhiko

    The proportion of the lightning outages in all outages on Japanese 6.6kV distribution lines is high with approximately 20 percent, and then lightning protections are very important for supply reliability of 6.6kV lines. It is effective for the lightning performance to apply countermeasures in order of the area where a large number of the lightning outages occur. Winter lightning occurs in Hokuriku area, therefore it is also important to understand the seasonal characteristics of the lightning outages. In summer 70 percent of the lightning outages on distribution lines in Hokuriku area were due to sparkover, such as power wire breakings and failures of pole-mounted transformers. However, in winter almost half of lightning-damaged equipments were surge arrester failures. The number of the lightning outages per lightning strokes detected by the lightning location system (LLS) in winter was 4.4 times larger than that in summer. The authors have presumed the occurrence of lightning outages from lightning stroke density, 50% value of lightning current and installation rate of lightning protection equipments and overhead ground wire by multiple regression analysis. The presumed results suggest the local difference in the lightning outages.

  1. Use of collaboration software to improve nuclear power plant outage management

    Energy Technology Data Exchange (ETDEWEB)

    Germain, Shawn

    2015-02-01

    Nuclear Power Plant (NPP) refueling outages create some of the most challenging activities the utilities face in both tracking and coordinating thousands of activities in a short period of time. Other challenges, including nuclear safety concerns arising from atypical system configurations and resource allocation issues, can create delays and schedule overruns, driving up outage costs. Today the majority of the outage communication is done using processes that do not take advantage of advances in modern technologies that enable enhanced communication, collaboration and information sharing. Some of the common practices include: runners that deliver paper-based requests for approval, radios, telephones, desktop computers, daily schedule printouts, and static whiteboards that are used to display information. Many gains have been made to reduce the challenges facing outage coordinators; however; new opportunities can be realized by utilizing modern technological advancements in communication and information tools that can enhance the collective situational awareness of plant personnel leading to improved decision-making. Ongoing research as part of the Light Water Reactor Sustainability Program (LWRS) has been targeting NPP outage improvement. As part of this research, various applications of collaborative software have been demonstrated through pilot project utility partnerships. Collaboration software can be utilized as part of the larger concept of Computer-Supported Cooperative Work (CSCW). Collaborative software can be used for emergent issue resolution, Outage Control Center (OCC) displays, and schedule monitoring. Use of collaboration software enables outage staff and subject matter experts (SMEs) to view and update critical outage information from any location on site or off.

  2. Financial forecasts accuracy in Brazil's social security system.

    Directory of Open Access Journals (Sweden)

    Carlos Patrick Alves da Silva

    Full Text Available Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government's proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.

  3. Financial forecasts accuracy in Brazil's social security system.

    Science.gov (United States)

    Silva, Carlos Patrick Alves da; Puty, Claudio Alberto Castelo Branco; Silva, Marcelino Silva da; Carvalho, Solon Venâncio de; Francês, Carlos Renato Lisboa

    2017-01-01

    Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government's proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.

  4. Financial forecasts accuracy in Brazil’s social security system

    Science.gov (United States)

    2017-01-01

    Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts. PMID:28859172

  5. Flow Forecasting in Drainage Systems with Extrapolated Radar Rainfall Data and Auto Calibration on Flow Observations

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Grum, M.; Rasmussen, Michael R.

    2011-01-01

    Forecasting of flows, overflow volumes, water levels, etc. in drainage systems can be applied in real time control of drainage systems in the future climate in order to fully utilize system capacity and thus save possible construction costs. An online system for forecasting flows and water levels......-calibrated on flow measurements in order to produce the best possible forecast for the drainage system at all times. The system shows great potential for the implementation of real time control in drainage systems and forecasting flows and water levels.......Forecasting of flows, overflow volumes, water levels, etc. in drainage systems can be applied in real time control of drainage systems in the future climate in order to fully utilize system capacity and thus save possible construction costs. An online system for forecasting flows and water levels...... in a small urban catchment has been developed. The forecast is based on application of radar rainfall data, which by a correlation based technique, is extrapolated with a lead time up to two hours. The runoff forecast in the drainage system is based on a fully distributed MOUSE model which is auto...

  6. Rough Precipitation Forecasts based on Analogue Method: an Operational System

    Science.gov (United States)

    Raffa, Mario; Mercogliano, Paola; Lacressonnière, Gwendoline; Guillaume, Bruno; Deandreis, Céline; Castanier, Pierre

    2017-04-01

    In the framework of the Climate KIC partnership, has been funded the project Wat-Ener-Cast (WEC), coordinated by ARIA Technologies, having the goal to adapt, through tailored weather-related forecast, the water and energy operations to the increased weather fluctuation and to climate change. The WEC products allow providing high quality forecast suited in risk and opportunities assessment dashboard for water and energy operational decisions and addressing the needs of sewage/water distribution operators, energy transport & distribution system operators, energy manager and wind energy producers. A common "energy water" web platform, able to interface with newest smart water-energy IT network have been developed. The main benefit by sharing resources through the "WEC platform" is the possibility to optimize the cost and the procedures of safety and maintenance team, in case of alerts and, finally to reduce overflows. Among the different services implemented on the WEC platform, ARIA have developed a product having the goal to support sewage/water distribution operators, based on a gradual forecast information system ( at 48hrs/24hrs/12hrs horizons) of heavy precipitation. For each fixed deadline different type of operation are implemented: 1) 48hour horizon, organisation of "on call team", 2) 24 hour horizon, update and confirm the "on call team", 3) 12 hour horizon, secure human resources and equipment (emptying storage basins, pipes manipulations …). More specifically CMCC have provided a statistical downscaling method in order to provide a "rough" daily local precipitation at 24 hours, especially when high precipitation values are expected. This statistical technique consists of an adaptation of analogue method based on ECMWF data (analysis and forecast at 24 hours). One of the most advantages of this technique concerns a lower computational burden and budget compared to running a Numerical Weather Prediction (NWP) model, also if, of course it provides only this

  7. Online updating procedures for a real-time hydrological forecasting system

    International Nuclear Information System (INIS)

    Kahl, B; Nachtnebel, H P

    2008-01-01

    Rainfall-runoff-models can explain major parts of the natural runoff pattern but never simulate the observed hydrograph exactly. Reasons for errors are various sources of uncertainties embedded in the model forecasting system. Errors are due to measurement errors, the selected time period for calibration and validation, the parametric uncertainty and the model imprecision. In on-line forecasting systems forecasted input data is used which additionally generates a major uncertainty for the hydrological forecasting system. Techniques for partially compensating these uncertainties are investigated in the recent study in a medium sized catchment in the Austrian part of the Danube basin. The catchment area is about 1000 km2. The forecasting system consists of a semi-distributed continuous rainfall-runoff model that uses quantitative precipitation and temperature forecasts. To provide adequate system states at the beginning of the forecasting period continuous simulation is required, especially in winter. In this study two online updating methods are used and combined for enhancing the runoff forecasts. The first method is used for updating the system states at the beginning of the forecasting period by changing the precipitation input. The second method is an autoregressive error model, which is used to eliminate systematic errors in the model output. In combination those two methods work together well as each method is more effective in different runoff situations.

  8. The Role of Occupational Health and Safety in Complex Outage Services to NPPs

    International Nuclear Information System (INIS)

    Rozman, A.; Androjna, A.

    2010-01-01

    Meeting outage schedules in NPPs which are increasingly demanding, apart from all other aspects, introduces a new perspective on occupational health and safety (OHS). Not only is the OHS a constituent part of a plant's overall outage management, it above all dictates paramount objectives to outage service providers. The paper reviews the impacts of reductions of outage durations on OHS and presents related experience of the leading Slovenian outage services provider, NUMIP d.o.o. over the last ten years. The company is now getting prepared for its 12th outage at Krsko NPP in 2010, and has not have recorded a major injury so far, even though these projects engaged over 450 people at a time on-site. To achieve such results, a lot of emphasis is being put onto OHS management prior to and during outages. A certified OHSAS 18001 system has been established and implemented to further support preparation and execution of NUMIP's outage activities at Krsko NPP, and also for other projects. An effective continuous improvement system is built into the project, providing for implementation of lessons learned from domestic and foreign plants. To illustrate the topic in more detail, a case on a Seismic protection of polar crane project is presented. It took place in the 2009 Outage and has certainly been one of the most demanding projects from the OHS point of view for NUMIP so far. The paper aims at contributing to a better understanding of the role of effective management of OHS on the side of a service provider, and, consequently, in the overall outage success of a plant.(author).

  9. Outage risk reduction at Diablo Canyon

    International Nuclear Information System (INIS)

    Burnett, Tobias W.T.; Eugene Newman, C.

    2004-01-01

    A formal risk reduction program was conducted at the Diablo Canyon Nuclear Generating plant as part of EPRI's Outage Risk Assessment and Management Program. The program began with a probabilistic and deterministic assessment of the frequency of core coolant boiling and core uncovery during shutdown operations. This step identified important contributors to risk, periods of high vulnerability, and potential mechanisms for reducing risk. Next, recovery strategies were evaluated and procedures, training, and outage schedules modified. Twelve risk reduction enhancements were developed and implemented. These enhancements and their impact are described in this paper. These enhancements reduced the calculated risk of core uncovery by about a factor of four for a refueling outage without lengthening the outage schedule; increased the outage efficiency, contributing to completing 11 days ahead of schedule; and helped to earn the highest achievable SALP rating from the NRC. (author)

  10. Using Quantile Regression to Extend an Existing Wind Power Forecasting System with Probabilistic Forecasts

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Madsen, Henrik; Nielsen, Torben Skov

    2006-01-01

    speed (due to the non-linearity of the power curve) and the forecast horizon. With respect to the predictability of the actual meteorological situation a number of explanatory variables are considered, some inspired by the literature. The article contains an overview of related work within the field...

  11. An Intelligent Decision Support System for Workforce Forecast

    Science.gov (United States)

    2011-01-01

    growth. Brown (1999) developed a model to forecast dental workforce size and mix (by sex) for the first twenty years of the twenty first century in...forecasted competencies required to deliver needed dental services. Labor market signaling approaches based workforce forecasting model was presented...techniques viz. algebra, calculus or probability theory, (Law and Kelton, 1991). Simulation processes, same as conducting experiments on computers, deals

  12. Seasonal prediction for Southern Africa: Maximising the skill from forecast systems

    CSIR Research Space (South Africa)

    Landman, WA

    2012-06-01

    Full Text Available /system development started in early 1990s ? SAWS, UCT, UP, Wits (statistical forecast systems) ? South African Long-Lead Forecast Forum ? SARCOF started in 1997 ? consensus through discussions ? Late 1990s ? started to use AGCMs and post-processing ? At SAWS... Reg1 Reg2 Reg3 Reg4 Reg5 Reg6 Reg7 Reg8 Regions RO C ar ea s Below-Normal Near-Normal Above-Normal Operational Forecast Skill From CONSENSUS discussions Verification over 7 years of consensus forecast production New objective multi...

  13. Natural gas demand forecast system based on the application of artificial neural networks

    International Nuclear Information System (INIS)

    Sanfeliu, J.M.; Doumanian, J.E.

    1997-01-01

    Gas Natural BAN, as a distribution gas company since 1993 in the north and west area of Buenos Aires Argentina, with 1,000,000 customers, had to develop a gas demand forecast system which should comply with the following basic requirements: Be able to do reliable forecasts with short historical information (2 years); Distinguish demands in areas of different characteristics, i.e. mainly residential, mainly industrial; Self-learning capability. To accomplish above goals, Gas Natural BAN chose in view of its own necessities, an artificial intelligence application (neural networks). 'SANDRA', the gas demand forecast system for gas distribution used by Gas Natural BAN, has the following features: Daily gas demand forecast, Hourly gas demand forecast and Breakdown of both forecast for each of the 3 basic zones in which the distribution area of Gas Natural BAN is divided. (au)

  14. CORRECTION OF FORECASTS OF INTERRELATED CURRENCY PAIRS IN TERMS OF SYSTEMS OF BALANCE RATIOS

    Directory of Open Access Journals (Sweden)

    Gertsekovich D. A.

    2015-03-01

    Full Text Available In this paper the problem of exchange rates forecast is logically considered a traditionally as a task of forecast on the base of «stand-alone» equations of autoregression for each currency pair and b as a result of forecast correction of autoregression equations system on the base of boundary conditions of balance ratios systems. As a criterion for quality of forecast constructed with empirical models we take the sum of deficiency quadrates of forecasts estimated for deductive currency pairs. Practical approval confirmed that deductive models meet common requirements, provide accepted precision, show resistance to initial data and are free from series of deficiency of one index. However, extreme forecast errors tell that practical application of the approach offered needs further improvement.

  15. Areva: experiences in outage services

    International Nuclear Information System (INIS)

    Wiemeier, R.; Mueller, N.; Blanco, I. J.

    2010-01-01

    As the world leader in the nuclear industry, Areva is firmly committed to the safe and reliable operation of the Spanish nuclear power plants. Following this commitment, Areva has established the subsidiary Areva NP Services Spain as a local platform to provide nuclear services for the Spanish nuclear power plants. being integrated and supported by the global Areva Group, Areva NP Services Spain is able to offer services solutions to all customers demands while maintaining close and sustainable relationships with them. This integration also allows the Spanish personnel of Areva to employ their skills by working in multinational teams in international projects. This article will present the capacities, and the most important recent national and international project performed by Areva NP Services Spain in the field of outage services. (Author)

  16. Comparison of two new short-term wind-power forecasting systems

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Rosado, Ignacio J. [Department of Electrical Engineering, University of Zaragoza, Zaragoza (Spain); Fernandez-Jimenez, L. Alfredo [Department of Electrical Engineering, University of La Rioja, Logrono (Spain); Monteiro, Claudio; Sousa, Joao; Bessa, Ricardo [FEUP, Fac. Engenharia Univ. Porto (Portugal)]|[INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

    2009-07-15

    This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction model; and electric power-generation registers from the SCADA system of the wind farm. Both systems are described in detail and the forecasting results compared, revealing great similarities, although the proposed structures of the two systems are different. The forecast horizon for both systems is 72 h, allowing the use of the forecasted values in electric market operations, as diary and intra-diary power generation bid offers, and in wind-farm maintenance planning. (author)

  17. Inferential, non-parametric statistics to assess the quality of probabilistic forecast systems

    NARCIS (Netherlands)

    Maia, A.H.N.; Meinke, H.B.; Lennox, S.; Stone, R.C.

    2007-01-01

    Many statistical forecast systems are available to interested users. To be useful for decision making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and its statistical manifestation have been firmly established, the forecasts must

  18. Mediterranea Forecasting System: a focus on wave-current coupling

    Science.gov (United States)

    Clementi, Emanuela; Delrosso, Damiano; Pistoia, Jenny; Drudi, Massimiliano; Fratianni, Claudia; Grandi, Alessandro; Pinardi, Nadia; Oddo, Paolo; Tonani, Marina

    2016-04-01

    The Mediterranean Forecasting System (MFS) is a numerical ocean prediction system that produces analyses, reanalyses and short term forecasts for the entire Mediterranean Sea and its Atlantic Ocean adjacent areas. MFS became operational in the late 90's and has been developed and continuously improved in the framework of a series of EU and National funded programs and is now part of the Copernicus Marine Service. The MFS is composed by the hydrodynamic model NEMO (Nucleus for European Modelling of the Ocean) 2-way coupled with the third generation wave model WW3 (WaveWatchIII) implemented in the Mediterranean Sea with 1/16 horizontal resolution and forced by ECMWF atmospheric fields. The model solutions are corrected by the data assimilation system (3D variational scheme adapted to the oceanic assimilation problem) with a daily assimilation cycle, using a background error correlation matrix varying seasonally and in different sub-regions of the Mediterranean Sea. The focus of this work is to present the latest modelling system upgrades and the related achieved improvements. In order to evaluate the performance of the coupled system a set of experiments has been built by coupling the wave and circulation models that hourly exchange the following fields: the sea surface currents and air-sea temperature difference are transferred from NEMO model to WW3 model modifying respectively the mean momentum transfer of waves and the wind speed stability parameter; while the neutral drag coefficient computed by WW3 model is passed to NEMO that computes the turbulent component. In order to validate the modelling system, numerical results have been compared with in-situ and remote sensing data. This work suggests that a coupled model might be capable of a better description of wave-current interactions, in particular feedback from the ocean to the waves might assess an improvement on the prediction capability of wave characteristics, while suggests to proceed toward a fully

  19. Study of Arkansas Nuclear One-1 13th refueling outage

    International Nuclear Information System (INIS)

    Hashiba, Takashi

    1997-01-01

    Recently performance of nuclear power plants in the USA has improved remarkably. Their average automatic shutdown rate has been sharply dropping, although it is still higher than that in Japan, and their average capacity factor has become higher than that in Japan in recent years. One of the main contributors is an extension of the operational period, and another is a shortening of refueling-outage time. It is considerably difficult to have accomplished both the improvement of plant reliability and shortening of refueling-outage time because their refueling outage corresponds to our periodical inspection which is central to maintenance activities in Japanese plants. In order to learn how they have been achieved, a visit to Arkansas Nuclear One-1 (ANO-1) which obtained the top-class result of SALP (Systematic Assessment of Licensee Performance) performed by the Nuclear Regulatory Commission was planned and study of their 13th refueling outage was carried out. Their achievements result from performance-base maintenance and on-line maintenance, based on a proper preventive maintenance program, and untiring efforts of efficiency improvement, represented by the introduction of several on-line systems. And the reason behind this is severe competition concerning power generation cost reduction. (author)

  20. Study of Arkansas Nuclear One-1 13th refueling outage

    Energy Technology Data Exchange (ETDEWEB)

    Hashiba, Takashi [Institute of Nuclear Safety System Inc., Seika, Kyoto (Japan)

    1997-09-01

    Recently performance of nuclear power plants in the USA has improved remarkably. Their average automatic shutdown rate has been sharply dropping, although it is still higher than that in Japan, and their average capacity factor has become higher than that in Japan in recent years. One of the main contributors is an extension of the operational period, and another is a shortening of refueling-outage time. It is considerably difficult to have accomplished both the improvement of plant reliability and shortening of refueling-outage time because their refueling outage corresponds to our periodical inspection which is central to maintenance activities in Japanese plants. In order to learn how they have been achieved, a visit to Arkansas Nuclear One-1 (ANO-1) which obtained the top-class result of SALP (Systematic Assessment of Licensee Performance) performed by the Nuclear Regulatory Commission was planned and study of their 13th refueling outage was carried out. Their achievements result from performance-base maintenance and on-line maintenance, based on a proper preventive maintenance program, and untiring efforts of efficiency improvement, represented by the introduction of several on-line systems. And the reason behind this is severe competition concerning power generation cost reduction. (author)

  1. Development of an Adaptive Forecasting System: A Case Study of a PC Manufacturer in South Korea

    Directory of Open Access Journals (Sweden)

    Chihyun Jung

    2016-03-01

    Full Text Available We present a case study of the development of an adaptive forecasting system for a leading personal computer (PC manufacturer in South Korea. It is widely accepted that demand forecasting for products with short product life cycles (PLCs is difficult, and the PLC of a PC is generally very short. The firm has various types of products, and the volatile demand patterns differ by product. Moreover, we found that different departments have different requirements when it comes to the accuracy, point-of-time and range of the forecasts. We divide the demand forecasting process into three stages depending on the requirements and purposes. The systematic forecasting process is then introduced to improve the accuracy of demand forecasting and to meet the department-specific requirements. Moreover, a newly devised short-term forecasting method is presented, which utilizes the long-term forecasting results of the preceding stages. We evaluate our systematic forecasting methods based on actual sales data from the PC manufacturer, where our forecasting methods have been implemented.

  2. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  3. The Eruption Forecasting Information System (EFIS) database project

    Science.gov (United States)

    Ogburn, Sarah; Harpel, Chris; Pesicek, Jeremy; Wellik, Jay; Pallister, John; Wright, Heather

    2016-04-01

    The Eruption Forecasting Information System (EFIS) project is a new initiative of the U.S. Geological Survey-USAID Volcano Disaster Assistance Program (VDAP) with the goal of enhancing VDAP's ability to forecast the outcome of volcanic unrest. The EFIS project seeks to: (1) Move away from relying on the collective memory to probability estimation using databases (2) Create databases useful for pattern recognition and for answering common VDAP questions; e.g. how commonly does unrest lead to eruption? how commonly do phreatic eruptions portend magmatic eruptions and what is the range of antecedence times? (3) Create generic probabilistic event trees using global data for different volcano 'types' (4) Create background, volcano-specific, probabilistic event trees for frequently active or particularly hazardous volcanoes in advance of a crisis (5) Quantify and communicate uncertainty in probabilities A major component of the project is the global EFIS relational database, which contains multiple modules designed to aid in the construction of probabilistic event trees and to answer common questions that arise during volcanic crises. The primary module contains chronologies of volcanic unrest, including the timing of phreatic eruptions, column heights, eruptive products, etc. and will be initially populated using chronicles of eruptive activity from Alaskan volcanic eruptions in the GeoDIVA database (Cameron et al. 2013). This database module allows us to query across other global databases such as the WOVOdat database of monitoring data and the Smithsonian Institution's Global Volcanism Program (GVP) database of eruptive histories and volcano information. The EFIS database is in the early stages of development and population; thus, this contribution also serves as a request for feedback from the community.

  4. Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

    Science.gov (United States)

    Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

    2016-12-01

    Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

  5. Nuclear Power Plant Outage Optimization Strategy. 2016 Edition

    International Nuclear Information System (INIS)

    2016-10-01

    This publication is an update of IAEA-TECDOC-1315, Nuclear Power Plant Outage Optimisation Strategy, which was published in 2002, and aims to communicate good outage management practices in a manner that can be used by operators and utilities in Member States. Nuclear power plant outage management is a key factor for safe and economic nuclear power plant performance. This publication discusses plant outage strategy and how this strategy is actually implemented. The main areas that are important for outage optimization that were identified by the utilities and government organizations participating in this report are: 1) organization and management; 2) outage planning and preparation; 3) outage execution; 4) safety outage review; and 5) counter measures to avoid the extension of outages and to facilitate the work in forced outages. Good outage management practices cover many different areas of work and this publication aims to communicate these good practices in a way that they can be used effectively by operators and utilities

  6. Forecasting of Hourly Photovoltaic Energy in Canarian Electrical System

    Science.gov (United States)

    Henriquez, D.; Castaño, C.; Nebot, R.; Piernavieja, G.; Rodriguez, A.

    2010-09-01

    The Canarian Archipelago face similar problems as most insular region lacking of endogenous conventional energy resources and not connected to continental electrical grids. A consequence of the "insular fact" is the existence of isolated electrical systems that are very difficult to interconnect due to the considerable sea depths between the islands. Currently, the Canary Islands have six isolated electrical systems, only one utility generating most of the electricity (burning fuel), a recently arrived TSO (REE) and still a low implementation of Renewable Energy Resources (RES). The low level of RES deployment is a consequence of two main facts: the weakness of the stand-alone grids (from 12 MW in El Hierro up to only 1 GW in Gran Canaria) and the lack of space to install RES systems (more than 50% of the land protected due to environmental reasons). To increase the penetration of renewable energy generation, like solar or wind energy, is necessary to develop tools to manage them. The penetration of non manageable sources into weak grids like the Canarian ones causes a big problem to the grid operator. There are currently 104 MW of PV connected to the islands grids (Dec. 2009) and additional 150 MW under licensing. This power presents a serious challenge for the operation and stability of the electrical system. ITC, together with the local TSO (Red Eléctrica de España, REE) started in 2008 and R&D project to develop a PV energy prediction tool for the six Canarian Insular electrical systems. The objective is to supply reliable information for hourly forecast of the generation dispatch programme and to predict daily solar radiation patterns, in order to help program spinning reserves. ITC has approached the task of weather forecasting using different numerical model (MM5 and WRF) in combination with MSG (Meteosat Second Generation) images. From the online data recorded at several monitored PV plants and meteorological stations, PV nominal power and energy produced

  7. A production throughput forecasting system in an automated hard disk drive test operation using GRNN

    Energy Technology Data Exchange (ETDEWEB)

    Samattapapong, N.; Afzulpurkar, N.

    2016-07-01

    The goal of this paper is to develop a pragmatic system of a production throughput forecasting system for an automated test operation in a hard drive manufacturing plant. The accurate forecasting result is necessary for the management team to response to any changes in the production processes and the resources allocations. In this study, we design a production throughput forecasting system in an automated test operation in hard drive manufacturing plant. In the proposed system, consists of three main stages. In the first stage, a mutual information method was adopted for selecting the relevant inputs into the forecasting model. In the second stage, a generalized regression neural network (GRNN) was implemented in the forecasting model development phase. Finally, forecasting accuracy was improved by searching the optimal smoothing parameter which selected from comparisons result among three optimization algorithms: particle swarm optimization (PSO), unrestricted search optimization (USO) and interval halving optimization (IHO). The experimental result shows that (1) the developed production throughput forecasting system using GRNN is able to provide forecasted results close to actual values, and to projected the future trends of production throughput in an automated hard disk drive test operation; (2) An IHO algorithm performed as superiority appropriate optimization method than the other two algorithms. (3) Compared with current forecasting system in manufacturing, the results show that the proposed system’s performance is superior to the current system in prediction accuracy and suitable for real-world application. The production throughput volume is a key performance index of hard disk drive manufacturing systems that need to be forecast. Because of the production throughput forecasting result is useful information for management team to respond to any changing in production processes and resources allocation. However, a practically forecasting system for

  8. A Weather Analysis and Forecasting System for Baja California, Mexico

    Science.gov (United States)

    Farfan, L. M.

    2006-05-01

    The weather of the Baja California Peninsula, part of northwestern Mexico, is mild and dry most of the year. However, during the summer, humid air masses associated with tropical cyclones move northward in the eastern Pacific Ocean. Added features that create a unique meteorological situation include mountain ranges along the spine of the peninsula, warm water in the Gulf of California, and the cold California Current in the Pacific. These features interact with the environmental flow to induce conditions that play a role in the occurrence of localized, convective systems during the approach of tropical cyclones. Most of these events occur late in the summer, generating heavy precipitation, strong winds, lightning, and are associated with significant property damage to the local populations. Our goal is to provide information on the characteristics of these weather systems by performing an analysis of observations derived from a regional network. This includes imagery from radar and geostationary satellite, and data from surface stations. A set of real-time products are generated in our research center and are made available to a broad audience (researchers, students, and business employees) by using an internet site. Graphical products are updated anywhere from one to 24 hours and includes predictions from numerical models. Forecasts are derived from an operational model (GFS) and locally generated simulations based on a mesoscale model (MM5). Our analysis and forecasting system has been in operation since the summer of 2005 and was used as a reference for a set of discussions during the development of eastern Pacific tropical cyclones. This basin had 15 named storms and none of them made landfall on the west coast of Mexico; however, four systems were within 800 km from the area of interest, resulting in some convective activity. During the whole season, a group of 30 users from our institution, government offices, and local businesses received daily information

  9. An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

    Directory of Open Access Journals (Sweden)

    F. Anctil

    2009-11-01

    Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

    In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

  10. Crime Forecasting System (An exploratory web-based approach

    Directory of Open Access Journals (Sweden)

    Yaseen Ahmed Meenai

    2011-08-01

    Full Text Available With the continuous rise in crimes in some big cities of the world like Karachi and the increasing complexity of these crimes, the difficulties the law enforcing agencies are facing in tracking down and taking out culprits have increased manifold. To help cut back the crime rate, a Crime Forecasting System (CFS can be used which uses historical information maintained by the local Police to help them predict crime patterns with the support of a huge and self-updating database. This system operates to prevent crime, helps in apprehending criminals, and to reduce disorder. This system is also vital in helping the law enforcers in forming a proactive approach by helping them in identifying early warning signs, take timely and necessary actions, and eventually help stop crime before it actually happens. It will also be beneficial in maintaining an up to date database of criminal suspects includes information on arrest records, communication with police department, associations with other known suspects, and membership in gangs/activist groups. After exploratory analysis of the online data acquired from the victims of these crimes, a broad picture of the scenario can be analyzed. The degree of vulnerability of an area at some particular moment can be highlighted by different colors aided by Google Maps. Some statistical diagrams have also been incorporated. The future of CFS can be seen as an information engine for the analysis, study and prediction of crimes.

  11. The application of hybrid artificial intelligence systems for forecasting

    Science.gov (United States)

    Lees, Brian; Corchado, Juan

    1999-03-01

    The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

  12. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Tian; Chernyakhovskiy, Ilya; Brancucci Martinez-Anido, Carlo

    2016-04-01

    This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  13. Space-time wind speed forecasting for improved power system dispatch

    KAUST Repository

    Zhu, Xinxin; Genton, Marc G.; Gu, Yingzhong; Xie, Le

    2014-01-01

    direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast

  14. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    International Nuclear Information System (INIS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Chenwei, Nie; Dong, Ren

    2014-01-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps

  15. Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing

    NARCIS (Netherlands)

    Candogan Yossef, N.; Winsemius, H.C.; Weerts, A.; Van Beek, R.; Bierkens, M.F.P.

    2013-01-01

    We investigate the relative contributions of initial conditions (ICs) and meteorological forcing (MF) to the skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCRaster Global Water Balance. Potential improvement in forecasting skill through

  16. Flood forecasting and early warning system for Dungun River Basin

    International Nuclear Information System (INIS)

    Hafiz, I; Sidek, L M; Basri, H; Fukami, K; Hanapi, M N; Livia, L; Nor, M D

    2013-01-01

    Floods can bring such disasters to the affected dweller due to loss of properties, crops and even deaths. The damages to properties and crops by the severe flooding are occurred due to the increase in the economic value of the properties as well as the extent of the flood. Flood forecasting and warning system is one of the examples of the non-structural measures which can give early warning to the affected people. People who live near the flood-prone areas will be warned so that they can evacuate themselves and their belongings before the arrival of the flood. This can considerably reduce flood loss and damage and above all, the loss of human lives. Integrated Flood Analysis System (IFAS) model is a runoff analysis model converting rainfall into runoff for a given river basin. The simulation can be done using either ground or satellite-based rainfall to produce calculated discharge within the river. The calculated discharge is used to generate the flood inundation map within the catchment area for the selected flood event using Infowork RS.

  17. Outage performance analysis of underlay cognitive RF and FSO wireless channels

    KAUST Repository

    Ansari, Imran Shafique; Abdallah, Mohamed M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2014-01-01

    In this work, the outage performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) channel cascaded with a free-space optical (FSO) link is presented. For the RF link, an underlay cognitive network

  18. A Unified Simulation Approach for the Fast Outage Capacity Evaluation over Generalized Fading Channels

    KAUST Repository

    Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul

    2016-01-01

    The outage capacity (OC) is among the most important performance metrics of communication systems over fading channels. The evaluation of the OC, when equal gain combining (EGC) or maximum ratio combining (MRC) diversity techniques are employed

  19. The Stevens Integrated Maritime Surveillance Forecast System: Expansion and Enhancement

    National Research Council Canada - National Science Library

    Bruno, Michael S; Blumberg, Alan F

    2006-01-01

    ... for the real-time assessment of ocean, weather, environmental, and vessel traffic conditions throughout the New York Harbor region, and the forecast of conditions in the near and long-term and under specific threat scenarios...

  20. Reliabilty worth: Development of a relationship with outage magnitude, duration and frequency

    International Nuclear Information System (INIS)

    Turner, F.P.P.; Katrichak, A.M.; Dwyer, A.; Edwards, D.; Ibrahim, A.

    1994-01-01

    British Columbia Hydro's Worth Project Team was founded to determine values for reliability for reference in evaluation of investment and operating decisions. Work to date has produced key preliminary values for specific outages and concepts for the shape of the relationship between value and these determinates of reliability worth, frequency, magnitude and duration. These values and concepts are described. The values are developed through an iterative, trial and refinement approach. The approach incorporates direct input from customers, common sense and judgement, and micro- and macro-economic concepts. Reliability worth values for reduced or prevented outages are presented for residential, commercial, small industrial and mixed sectors and various outage durations. Reliability worth values were obtained through customer surveys. Limitations of the reliability worth value are numerous and are listed. Study of cost vs magnitude of interruption using microeconomic models has shown that costly system improvements to reduce the possibility of widespread outages may not be justified. The case of exceptionally large area outages (blackouts) is examined. The cost vs frequency relationship was examined in terms of the economic concept of utility or satisfaction. Different loss/frequency characteristics are demonstrated for different customer classes. Customer value for reduced outage duration is expressed in a curve with flatter slope than that for eliminated outages. 2 refs., 6 figs

  1. San Onofre - the evolution of outage management

    International Nuclear Information System (INIS)

    Slagle, K.A.

    1993-01-01

    With the addition of units 2 and 3 to San Onofre nuclear station in 1983 and 1984, it became evident that a separate group was needed to manage outages. Despite early establishment of a division to handle outages, it was a difficult journey to make the changes to achieve short outages. Early organizational emphasis was on developing an error-free operating environment and work culture. This is difficult for a relatively large organization at a three-unit site. The work processes and decision styles were designed to be very deliberate with many checks and balances. The organization leadership and accountability were focused in the traditional operations, maintenance, and engineering divisions. Later, our organization emphasis shifted to achieving engineering excellence. With a sound foundation of operating and engineering excellence, our organizational focus has turned to achieving quality outages. This means accomplishing the right work in a shorter duration and having the units run until the next refueling

  2. Refueling outage data collection and analysis

    International Nuclear Information System (INIS)

    Harshaw, K.; Quilliam, J.; Brinsfield, W.; Jeffries, J.

    1993-07-01

    This report summarizes the results of an EPRI project to compile an industry generic refueling outage database applicable to alternate (non-full-power) modes of shutdown conditions at nuclear power plants. The project team evaluated five outages at two BWR plants. They obtained data primarily from control room logs, outage schedules, incident reports, and licensee event reports. The team organized the data by outage segment and time line. Due to its small sample size, this study produced no conclusive results related to initiating event frequencies, equipment failure rates, or human reliability estimates during shutdown conditions. However, it pointed out the problems of brief or inconsistent recordkeeping. A too brief record results in difficulty determining if the root cause of an event was mechanical or the result of human performance. Retrieval of data can be difficult and labor-intensive. There is a clear need for better, more comprehensive documentation

  3. The Impact of Distributed Generation Systems in the Load Forecasting

    OpenAIRE

    Benedicto Llorens, Juan Manuel

    2009-01-01

    Projecte fet en col.laboració amb l'Instituto Superior Tecnico. Universidade Técnica de Lisboa Load forecasting is vitally important for the electric industry in the deregulated economy. It has many applications including energy purchasing and generation, load switching, contract evaluation and infrastructure development. Because of this, a large variety of mathematical methods have been developed for load forecasting. In addition, the large-scale integration of wind power, now...

  4. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

    Science.gov (United States)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  5. Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

    2017-11-01

    Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias

  6. Hydro-economic assessment of hydrological forecasting systems

    Science.gov (United States)

    Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

    2012-01-01

    SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

  7. Siemens capabilities to perform detailed fuel inspections during short outages

    International Nuclear Information System (INIS)

    Knecht, K.; Reparaz, A.

    1999-01-01

    Fuel inspection data are used to support development activities such as corrosion resistant cladding and advanced fuel assembly designs that will reach higher burnups. Increased inspection efforts are necessary to optimize fuel management and performance strategies. Additionally, there is an increasing trend to reduce outage time in Germany and abroad. Siemens has recently developed several timesaving systems for rapid inspection of fuel assemblies and core components. Siemens' focus in developing these systems has been to obtain data in reduced reactor outage time while increasing both the volume and the quality of the measured data. Mast sipping for PWRs is used for identifying leaking fuel assemblies and allows early detection of leaks during downloading of the fuel assemblies from the reactor. An In-Core sipping system for BWRs based on a hood technique to allow testing a full core within 16 hours is under development. (authors)

  8. Partnership - its contribution to outage success

    International Nuclear Information System (INIS)

    Gill, K.S.; Kirton-Darling, F.; Robinson, F.T.

    1996-01-01

    An innovative approach to developing the teamwork between the power station and the outage contractor has been pioneered over the past three years at the Bradwell nuclear power station in the UK, which houses two Magnox reactors. Magnox Electric and Rolls-Royce Nuclear Engineering Services are now undertaking their third outage under a partnership contract which has provided significant benefits to both parties. (Author)

  9. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  10. Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

    Science.gov (United States)

    Prive, N. C.; Errico, Ronald M.

    2015-01-01

    The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

  11. ECMWF seasonal forecast system 3 and its prediction of sea surface temperature

    Energy Technology Data Exchange (ETDEWEB)

    Stockdale, Timothy N.; Anderson, David L.T.; Balmaseda, Magdalena A.; Ferranti, Laura; Mogensen, Kristian; Palmer, Timothy N.; Molteni, Franco; Vitart, Frederic [ECMWF, Reading (United Kingdom); Doblas-Reyes, Francisco [ECMWF, Reading (United Kingdom); Institut Catala de Ciencies del Clima (IC3), Barcelona (Spain)

    2011-08-15

    The latest operational version of the ECMWF seasonal forecasting system is described. It shows noticeably improved skill for sea surface temperature (SST) prediction compared with previous versions, particularly with respect to El Nino related variability. Substantial skill is shown for lead times up to 1 year, although at this range the spread in the ensemble forecast implies a loss of predictability large enough to account for most of the forecast error variance, suggesting only moderate scope for improving long range El Nino forecasts. At shorter ranges, particularly 3-6 months, skill is still substantially below the model-estimated predictability limit. SST forecast skill is higher for more recent periods than earlier ones. Analysis shows that although various factors can affect scores in particular periods, the improvement from 1994 onwards seems to be robust, and is most plausibly due to improvements in the observing system made at that time. The improvement in forecast skill is most evident for 3-month forecasts starting in February, where predictions of NINO3.4 SST from 1994 to present have been almost without fault. It is argued that in situations where the impact of model error is small, the value of improved observational data can be seen most clearly. Significant skill is also shown in the equatorial Indian Ocean, although predictive skill in parts of the tropical Atlantic are relatively poor. SST forecast errors can be especially high in the Southern Ocean. (orig.)

  12. Looking toward to the next-generation space weather forecast system. Comments former a former space weather forecaster

    International Nuclear Information System (INIS)

    Tomita, Fumihiko

    1999-01-01

    In the 21st century, man's space-based activities will increase significantly and many kinds of space utilization technologies will assume a vital role in the infrastructure, creating new businesses, securing the global environment, contributing much to human welfare in the world. Communications Research Laboratory (CRL) has been contributing to the safety of human activity in space and to the further understanding of the solar terrestrial environment through the study of space weather, including the upper atmosphere, magnetosphere, interplanetary space, and the sun. The next-generation Space Weather Integrated Monitoring System (SWIMS) for future space activities based on the present international space weather forecasting system is introduced in this paper. (author)

  13. An Operational Short-Term Forecasting System for Regional Hydropower Management

    Science.gov (United States)

    Gronewold, A.; Labuhn, K. A.; Calappi, T. J.; MacNeil, A.

    2017-12-01

    The Niagara River is the natural outlet of Lake Erie and drains four of the five Great lakes. The river is used to move commerce and is home to both sport fishing and tourism industries. It also provides nearly 5 million kilowatts of hydropower for approximately 3.9 million homes. Due to a complex international treaty and the necessity of balancing water needs for an extensive tourism industry, the power entities operating on the river require detailed and accurate short-term river flow forecasts to maximize power output. A new forecast system is being evaluated that takes advantage of several previously independent components including the NOAA Lake Erie operational Forecast System (LEOFS), a previously developed HEC-RAS model, input from the New York Power Authority(NYPA) and Ontario Power Generation (OPG) and lateral flow forecasts for some of the tributaries provided by the NOAA Northeast River Forecast Center (NERFC). The Corps of Engineers updated the HEC-RAS model of the upper Niagara River to use the output forcing from LEOFS and a planned Grass Island Pool elevation provided by the power entities. The entire system has been integrated at the NERFC; it will be run multiple times per day with results provided to the Niagara River Control Center operators. The new model helps improve discharge forecasts by better accounting for dynamic conditions on Lake Erie. LEOFS captures seiche events on the lake that are often several meters of displacement from still water level. These seiche events translate into flow spikes that HEC-RAS routes downstream. Knowledge of the peak arrival time helps improve operational decisions at the Grass Island Pool. This poster will compare and contrast results from the existing operational flow forecast and the new integrated LEOFS/HEC-RAS forecast. This additional model will supply the Niagara River Control Center operators with multiple forecasts of flow to help improve forecasting under a wider variety of conditions.

  14. Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  15. Comparison of short-term rainfall forecasts for modelbased flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Ahm, Malte; Nielsen, Jesper Ellerbek

    2013-01-01

    Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times....

  16. Outage Probability Analysis of FSO Links over Foggy Channel

    KAUST Repository

    Esmail, Maged Abdullah; Fathallah, Habib; Alouini, Mohamed-Slim

    2017-01-01

    Outdoor Free space optic (FSO) communication systems are sensitive to atmospheric impairments such as turbulence and fog, in addition to being subject to pointing errors. Fog is particularly severe because it induces an attenuation that may vary from few dBs up to few hundreds of dBs per kilometer. Pointing errors also distort the link alignment and cause signal fading. In this paper, we investigate and analyze the FSO systems performance under fog conditions and pointing errors in terms of outage probability. We then study the impact of several effective communication mitigation techniques that can improve the system performance including multi-hop, transmit laser selection (TLS) and hybrid RF/FSO transmission. Closed-form expressions for the outage probability are derived and practical and comprehensive numerical examples are suggested to assess the obtained results. We found that the FSO system has limited performance that prevents applying FSO in wireless microcells that have a 500 m minimum cell radius. The performance degrades more when pointing errors appear. Increasing the transmitted power can improve the performance under light to moderate fog. However, under thick and dense fog the improvement is negligible. Using mitigation techniques can play a major role in improving the range and outage probability.

  17. Outage Probability Analysis of FSO Links over Foggy Channel

    KAUST Repository

    Esmail, Maged Abdullah

    2017-02-22

    Outdoor Free space optic (FSO) communication systems are sensitive to atmospheric impairments such as turbulence and fog, in addition to being subject to pointing errors. Fog is particularly severe because it induces an attenuation that may vary from few dBs up to few hundreds of dBs per kilometer. Pointing errors also distort the link alignment and cause signal fading. In this paper, we investigate and analyze the FSO systems performance under fog conditions and pointing errors in terms of outage probability. We then study the impact of several effective communication mitigation techniques that can improve the system performance including multi-hop, transmit laser selection (TLS) and hybrid RF/FSO transmission. Closed-form expressions for the outage probability are derived and practical and comprehensive numerical examples are suggested to assess the obtained results. We found that the FSO system has limited performance that prevents applying FSO in wireless microcells that have a 500 m minimum cell radius. The performance degrades more when pointing errors appear. Increasing the transmitted power can improve the performance under light to moderate fog. However, under thick and dense fog the improvement is negligible. Using mitigation techniques can play a major role in improving the range and outage probability.

  18. Short-Term State Forecasting-Based Optimal Voltage Regulation in Distribution Systems: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Rui; Jiang, Huaiguang; Zhang, Yingchen

    2017-05-17

    A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.

  19. Evaluation of the Plant-Craig stochastic convection scheme in an ensemble forecasting system

    Science.gov (United States)

    Keane, R. J.; Plant, R. S.; Tennant, W. J.

    2015-12-01

    The Plant-Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic element only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant-Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant-Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

  20. Wave ensemble forecast system for tropical cyclones in the Australian region

    Science.gov (United States)

    Zieger, Stefan; Greenslade, Diana; Kepert, Jeffrey D.

    2018-05-01

    Forecasting of waves under extreme conditions such as tropical cyclones is vitally important for many offshore industries, but there remain many challenges. For Northwest Western Australia (NW WA), wave forecasts issued by the Australian Bureau of Meteorology have previously been limited to products from deterministic operational wave models forced by deterministic atmospheric models. The wave models are run over global (resolution 1/4∘) and regional (resolution 1/10∘) domains with forecast ranges of + 7 and + 3 day respectively. Because of this relatively coarse resolution (both in the wave models and in the forcing fields), the accuracy of these products is limited under tropical cyclone conditions. Given this limited accuracy, a new ensemble-based wave forecasting system for the NW WA region has been developed. To achieve this, a new dedicated 8-km resolution grid was nested in the global wave model. Over this grid, the wave model is forced with winds from a bias-corrected European Centre for Medium Range Weather Forecast atmospheric ensemble that comprises 51 ensemble members to take into account the uncertainties in location, intensity and structure of a tropical cyclone system. A unique technique is used to select restart files for each wave ensemble member. The system is designed to operate in real time during the cyclone season providing + 10-day forecasts. This paper will describe the wave forecast components of this system and present the verification metrics and skill for specific events.

  1. Outage probability of distributed beamforming with co-channel interference

    KAUST Repository

    Yang, Liang

    2012-03-01

    In this letter, we consider a distributed beamforming scheme (DBF) in the presence of equal-power co-channel interferers for both amplify-and-forward and decode-and-forward relaying protocols over Rayleigh fading channels. We first derive outage probability expressions for the DBF systems. We then present a performance analysis for a scheme relying on source selection. Numerical results are finally presented to verify our analysis. © 2011 IEEE.

  2. Radar Based Flow and Water Level Forecasting in Sewer Systems:a danisk case study

    OpenAIRE

    Thorndahl, Søren; Rasmussen, Michael R.; Grum, M.; Neve, S. L.

    2009-01-01

    This paper describes the first radar based forecast of flow and/or water level in sewer systems in Denmark. The rainfall is successfully forecasted with a lead time of 1-2 hours, and flow/levels are forecasted an additional ½-1½ hours using models describing the behaviour of the sewer system. Both radar data and flow/water level model are continuously updated using online rain gauges and online in-sewer measurements, in order to make the best possible predictions. The project show very promis...

  3. Analysis of T101 outage radiation dose

    International Nuclear Information System (INIS)

    Li, Zhonghua

    2008-01-01

    Full text: Collective radiation dose during outage is about 80% of annual collective radiation dose at nuclear power plants (NPPs). T 101 Outage is the first four-year outage of Unit 1 at Tianwan Nuclear Power Station (TNPS) and thorough overhaul was undergone for the 105-day's duration. Therefore, T 101 Outage has significant reference meaning to reducing collective radiation dose at TNPS. This paper collects the radiation dose statistics during T 101 Outage and analyses the radiation dose distribution according to tasks, work kinds and varying trend of the collective radiation dose etc., comparing with other similar PWRs in the world. Based on the analysis this paper attempts to find out the major factors in collective radiation dose during T 101 Outage. The major positive factor is low radiation level at workplace, which profits from low content of Co in reactor construction materials, optimised high-temperature p H value of the primary circuit coolant within the tight range and reactor operation without trips within the first fuel cycle. One of the most negative factors is long outage duration and many person-hours spent in the radiological controlled zone, caused by too many tasks and inefficient work. So besides keeping good performance of reducing radioactive sources, it should be focused on how to improve implementation of work management including work selection, planning and scheduling, work preparation, work implementation, work assessment and feedback, which can lead to reduced numbers of workers needed to perform a task, of person-hours spent in the radiological controlled zone. Moreover, this leads to reduce occupational exposures in an ALARA fashion. (author)

  4. Advanced Test Reactor outage risk assessment

    International Nuclear Information System (INIS)

    Thatcher, T.A.; Atkinson, S.A.

    1997-01-01

    Beginning in 1997, risk assessment was performed for each Advanced Test Reactor (ATR) outage aiding the coordination of plant configuration and work activities (maintenance, construction projects, etc.) to minimize the risk of reactor fuel damage and to improve defense-in-depth. The risk assessment activities move beyond simply meeting Technical Safety Requirements to increase the awareness of risk sensitive configurations, to focus increased attention on the higher risk activities, and to seek cost-effective design or operational changes that reduce risk. A detailed probabilistic risk assessment (PRA) had been performed to assess the risk of fuel damage during shutdown operations including heavy load handling. This resulted in several design changes to improve safety; however, evaluation of individual outages had not been performed previously and many risk insights were not being utilized in outage planning. The shutdown PRA provided the necessary framework for assessing relative and absolute risk levels and assessing defense-in-depth. Guidelines were written identifying combinations of equipment outages to avoid. Screening criteria were developed for the selection of work activities to receive review. Tabulation of inherent and work-related initiating events and their relative risk level versus plant mode has aided identification of the risk level the scheduled work involves. Preoutage reviews are conducted and post-outage risk assessment is documented to summarize the positive and negative aspects of the outage with regard to risk. The risk for the outage is compared to the risk level that would result from optimal scheduling of the work to be performed and to baseline or average past performance

  5. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L

    2004-01-01

    .... The results of this forecasting system would provide real-time information to the National Hurricane Center during the tropical cyclone season in the Atlantic for establishing improved advisories...

  6. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L; Cardone, Vincent J; Cox, Andrew T; Augustus, Ellsworth H; Colonnese, Christopher P

    2003-01-01

    .... The results of this forecasting system would provide real-time information to the National Hurricane Center during the tropical cyclone season in the Atlantic for establishing improved advisories...

  7. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L

    2005-01-01

    .... The results of this forecasting system would provide real-time information to the National Hurricane Center during the tropical cyclone season in the Atlantic for establishing improved advisories...

  8. Performance of the ocean state forecast system at Indian National Centre for Ocean Information Services

    Digital Repository Service at National Institute of Oceanography (India)

    Nair, T.M.B.; Sirisha, P.; Sandhya, K.G.; Srinivas, K.; SanilKumar, V.; Sabique, L.; Nherakkol, A.; KrishnaPrasad, B.; RakhiKumari; Jeyakumar, C.; Kaviyazhahu, K.; RameshKumar, M.; Harikumar, R.; Shenoi, S.S.C.; Nayak, S.

    The reliability of the operational Ocean State Forecast system at the Indian National Centre for Ocean Information Services (INCOIS) during tropical cyclones that affect the coastline of India is described in this article. The performance...

  9. COAWST Forecast System : USGS : US East Coast and Gulf of Mexico (Experimental)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Experimental forecast model product from the USGS Coupled Ocean Atmosphere Wave Sediment-Transport (COAWST) modeling system. Data required to drive the modeling...

  10. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L

    2005-01-01

    The long-term goal of this partnership is to establish an operational forecasting system of the wind field and resulting waves and surge impacting the coastline during the approach and landfall of tropical cyclones...

  11. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L; Cardone, Vincent J; Cox, Andrew T

    2006-01-01

    ... of tropical cyclones The results of this forecasting system would provide real-time information to the National Hurricane Center during the tropical cyclone season in the Atlantic for establishing improved...

  12. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L

    2004-01-01

    The long-term goal of this partnership is to establish an operational forecasting system of the wind field and resulting waves and surge impacting the coastline during the approach and landfall of tropical cyclones...

  13. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones

    National Research Council Canada - National Science Library

    Graber, Hans C; Donelan, Mark A; Brown, Michael G; Slinn, Donald N; Hagen, Scott C; Thompson, Donald R; Jensen, Robert E; Black, Peter G; Powell, Mark D; Guiney, John L; Cardone, Vincent J; Cox, Andrew T; Augustus, Ellsworth H; Colonnese, Christopher P

    2003-01-01

    The long-term goal of this partnership is to establish an operational forecasting system of the wind field and resulting waves and surge impacting the coastline during the approach and landfall of tropical cyclones...

  14. The impact of implementing a demand forecasting system into a low-income country's supply chain.

    Science.gov (United States)

    Mueller, Leslie E; Haidari, Leila A; Wateska, Angela R; Phillips, Roslyn J; Schmitz, Michelle M; Connor, Diana L; Norman, Bryan A; Brown, Shawn T; Welling, Joel S; Lee, Bruce Y

    2016-07-12

    To evaluate the potential impact and value of applications (e.g. adjusting ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country's vaccine supply chain with different levels of population change to urban areas. Using our software, HERMES, we generated a detailed discrete event simulation model of Niger's entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. Demand forecasting systems have the potential to greatly improve vaccine demand fulfilment, and decrease logistics cost/dose when implemented with storage and transportation increases. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements. Copyright

  15. Outage analysis of opportunistic decode-and-forward relaying

    KAUST Repository

    Tourki, Kamel

    2010-09-01

    In this paper, we investigate a dual-hop opportunistic decode-and-forward relaying scheme where the source may or not be able to communicate directly with the destination. We first derive statistics based on exact probability density function (PDF) of each hop. Then, the PDFs are used to determine closed-form outage probability expression for a transmission rate R. Furthermore, we evaluate the asymptotic outage performance and the diversity order is deduced. Unlike existing works where the analysis focused on high signal-to-noise ratio (SNR) regime, such results are important to enable the designers to take decisions regarding practical systems that operate at low SNR regime. We show that performance simulation results coincide with our analytical results under practical assumption of unbalanced hops. © 2010 IEEE.

  16. AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

    Science.gov (United States)

    Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

    2011-01-01

    A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

  17. Global Ocean Forecast System 3.1 Validation Test

    Science.gov (United States)

    2017-05-04

    the relative skill of one analysis region with another. 49 An ice score card similar to the ocean score card has not yet been refined, so...the water column. GOFS nowcasts/forecasts the ocean’s “ weather ”, which includes the three-dimensional ocean temperature, salinity and current...42 4.0 SUMMARY, SCORE CARDS AND RECOMMENDATIONS ..................................................... 46

  18. A New Coastal Flood Forecasting System for the Netherlands

    NARCIS (Netherlands)

    De Kleermaeker, S.; Verlaan, M.; Kroos, J.; Zijl, F.

    2012-01-01

    The North Sea is one of the busiest seas in the world with dense ship traffic, fisheries, wind farming, recreation and many other activities. All these activities depend on the ‘marine weather’. Accurate forecasts of waves, currents and sea level are crucial for operational management and for

  19. Space-time wind speed forecasting for improved power system dispatch

    KAUST Repository

    Zhu, Xinxin

    2014-02-27

    To support large-scale integration of wind power into electric energy systems, state-of-the-art wind speed forecasting methods should be able to provide accurate and adequate information to enable efficient, reliable, and cost-effective scheduling of wind power. Here, we incorporate space-time wind forecasts into electric power system scheduling. First, we propose a modified regime-switching, space-time wind speed forecasting model that allows the forecast regimes to vary with the dominant wind direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast models. This, in turn, leads to cost-effective scheduling of system-wide wind generation. Potential economic benefits arise from the system-wide generation of cost savings and from the ancillary service cost savings. We illustrate the economic benefits using a test system in the northwest region of the United States. Compared with persistence and autoregressive models, our model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars annually in regions with high wind penetration, such as Texas and the Pacific northwest. © 2014 Sociedad de Estadística e Investigación Operativa.

  20. Development of an Adaptable Display and Diagnostic System for the Evaluation of Tropical Cyclone Forecasts

    Science.gov (United States)

    Kucera, P. A.; Burek, T.; Halley-Gotway, J.

    2015-12-01

    NCAR's Joint Numerical Testbed Program (JNTP) focuses on the evaluation of experimental forecasts of tropical cyclones (TCs) with the goal of developing new research tools and diagnostic evaluation methods that can be transitioned to operations. Recent activities include the development of new TC forecast verification methods and the development of an adaptable TC display and diagnostic system. The next generation display and diagnostic system is being developed to support evaluation needs of the U.S. National Hurricane Center (NHC) and broader TC research community. The new hurricane display and diagnostic capabilities allow forecasters and research scientists to more deeply examine the performance of operational and experimental models. The system is built upon modern and flexible technology that includes OpenLayers Mapping tools that are platform independent. The forecast track and intensity along with associated observed track information are stored in an efficient MySQL database. The system provides easy-to-use interactive display system, and provides diagnostic tools to examine forecast track stratified by intensity. Consensus forecasts can be computed and displayed interactively. The system is designed to display information for both real-time and for historical TC cyclones. The display configurations are easily adaptable to meet the needs of the end-user preferences. Ongoing enhancements include improving capabilities for stratification and evaluation of historical best tracks, development and implementation of additional methods to stratify and compute consensus hurricane track and intensity forecasts, and improved graphical display tools. The display is also being enhanced to incorporate gridded forecast, satellite, and sea surface temperature fields. The presentation will provide an overview of the display and diagnostic system development and demonstration of the current capabilities.

  1. Improving Arctic Sea Ice Edge Forecasts by Assimilating High Horizontal Resolution Sea Ice Concentration Data into the US Navy’s Ice Forecast Systems

    Science.gov (United States)

    2016-06-13

    1735-2015 © Author(s) 2015. CC Attribution 3.0 License. Improving Arctic sea ice edge forecasts by assimilating high horizontal resolution sea ice...concentration data into the US Navy’s ice forecast systems P. G. Posey1, E. J. Metzger1, A. J. Wallcraft1, D. A. Hebert1, R. A. Allard1, O. M. Smedstad2...error within the US Navy’s operational sea ice forecast systems gained by assimilating high horizontal resolution satellite-derived ice concentration

  2. Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

    Science.gov (United States)

    Radziukynas, V.; Klementavičius, A.

    2016-04-01

    The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011) and planned wind power capacities (the year 2023).

  3. Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

    Directory of Open Access Journals (Sweden)

    Radziukynas V.

    2016-04-01

    Full Text Available The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011 and planned wind power capacities (the year 2023.

  4. Forecast products from the Gulf of Mexico created by the NOAA Harmful Algal Bloom Operational Forecast System (HAB-OFS) from 2007-09-10 to the present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection contains outputs from the NOAA Harmful Algal Bloom Operational Forecast System (HAB-OFS) in the form of bulletin documents beginning on 2007-09-10....

  5. Outage Analysis of Spectrum-Sharing over M-Block Fading with Sensing Information

    KAUST Repository

    Alabbasi, Abdulrahman

    2016-07-13

    Future wireless technologies, such as, 5G, are expected to support real-time applications with high data throughput, e.g., holographic meetings. From a bandwidth perspective, cognitive radio is a promising technology to enhance the system’s throughput via sharing the licensed spectrum. From a delay perspective, it is well known that increasing the number of decoding blocks will improve the system robustness against errors, while increasing the delay. Therefore, optimally allocating the resources to determine the tradeoff of tuning the length of decoding blocks while sharing the spectrum is a critical challenge for future wireless systems. In this work, we minimize the targeted outage probability over the block-fading channels while utilizing the spectrum-sharing concept. The secondary user’s outage region and the corresponding optimal power are derived, over twoblocks and M-blocks fading channels. We propose two suboptimal power strategies and derive the associated asymptotic lower and upper bounds on the outage probability with tractable expressions. These bounds allow us to derive the exact diversity order of the secondary user’s outage probability. To further enhance the system’s performance, we also investigate the impact of including the sensing information on the outage problem. The outage problem is then solved via proposing an alternating optimization algorithm, which utilizes the verified strict quasiconvex structure of the problem. Selected numerical results are presented to characterize the system’s behavior and show the improvements of several sharing concepts.

  6. Estimating the Propagation of Interdependent Cascading Outages with Multi-Type Branching Processes

    Energy Technology Data Exchange (ETDEWEB)

    Qi, Junjian; Ju, Wenyun; Sun, Kai

    2016-01-01

    In this paper, the multi-type branching process is applied to describe the statistics and interdependencies of line outages, the load shed, and isolated buses. The offspring mean matrix of the multi-type branching process is estimated by the Expectation Maximization (EM) algorithm and can quantify the extent of outage propagation. The joint distribution of two types of outages is estimated by the multi-type branching process via the Lagrange-Good inversion. The proposed model is tested with data generated by the AC OPA cascading simulations on the IEEE 118-bus system. The largest eigenvalues of the offspring mean matrix indicate that the system is closer to criticality when considering the interdependence of different types of outages. Compared with empirically estimating the joint distribution of the total outages, good estimate is obtained by using the multitype branching process with a much smaller number of cascades, thus greatly improving the efficiency. It is shown that the multitype branching process can effectively predict the distribution of the load shed and isolated buses and their conditional largest possible total outages even when there are no data of them.

  7. Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay

    Science.gov (United States)

    Garzon, Juan L.; Ferreira, Celso M.; Padilla-Hernandez, Roberto

    2018-01-01

    Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.

  8. Commercial operation and outage experience of ABWR at Kashiwazaki-Kariwa units Nos. 6 and 7

    International Nuclear Information System (INIS)

    Anahara, N.; Yamada, M.; Kataoka, H.

    2000-01-01

    Kashiwazaki-Kariwa Nuclear Power Station Units Nos. 6 and 7, the world's first ABWRs (Advanced Boiling Water Reactor), started commercial operation on November 7, 1996 and July 2, 1997, respectively, and continued their commercial operation with a high capacity factor, low occupational radiation exposure and radioactive waste. Units 6 and 7 were in their 3rd cycle operation until 25th April 1999 and 1st November 1999, respectively. Thermal efficiency was 35.4-35.8% (design thermal efficiency: 34.5%) during these period, demonstrating better performance than that of BWR-5 (design thermal efficiency: 33.4%). Nos. 6 and 7 have experienced 2 annual outages. The first outage of unit No. 6 started on November 20, 1997 and was completed within 61 days (including 6 New Year holidays), and the second outage started on March 13, 1999 and was completed within 44 days. The first annual outage of unit No. 7 started on May 27, 1998, earlier than it would normally have been, to avoid an annual outage during the summer, and was completed within 55 days, and the second outage started on September 18th, 1999 and was completed within 45 days, All annual outages were carried out within a very short time period without any severe malfunctions, including newly designed ABWR systems and equipment. As the first outage in Japan, 55 days is a very short period, despite the fact that the Nos. 6 and 7 are the first ABWRs in the world and the largest capacity units in Japan. The total occupational radiation exposure of No. 6 was 300 man-mSv (1st outage) and 331 man-mSv (2nd outage). That of Unit 7 was 153 man-mSv (1st outage) Those of unit No. 6 were at the same level as those of unit No. 3, which is the latest design 1100MW(e) BWR-5. That of unit No. 7 was the lowest ever at Kashiwazaki-Kariwa nuclear power station. The drums of radioactive waste discharged during the annual outage numbered 54 (1st outage) for No. 6 and 62 (1st outage) for No. 7, which was less than the design target of 100

  9. Incorporating Forecast Uncertainty in Utility Control Center

    Energy Technology Data Exchange (ETDEWEB)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

    2014-07-09

    Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

  10. Upgrading BWR training simulators for annual outage operation training

    International Nuclear Information System (INIS)

    Yamakabe, K.; Nakajima, A.; Shiyama, H.; Noji, K.; Okabe, N.; Murata, F.

    2006-01-01

    Based upon the recently developed quality assurance program by the Japanese electric companies, BWR Operator Training Center (BTC) identified the needs to enhance operators' knowledge and skills for operations tasks during annual outage, and started to develop a dedicated operator training course specialized for them. In this paper, we present the total framework of the training course for annual outage operations and the associated typical three functions of our full-scope simulators specially developed and upgraded to conduct the training; namely, (1) Simulation model upgrade for the flow and temperature behavior concerning residual heat removal (RHR) system with shutdown cooling mode, (2) Addition of malfunctions for DC power supply equipment, (3) Simulation model upgrade for water filling operation for reactor pressurization (future development). We have implemented a trial of the training course by using the upgraded 800MW full-scope training simulator with functions (1) and (2) above. As the result of this trial, we are confident that the developed training course is effective for enhancing operators' knowledge and skills for operations tasks during annual outage. (author)

  11. Improved Weather Forecasting for the Dynamic Scheduling System of the Green Bank Telescope

    Science.gov (United States)

    Henry, Kari; Maddalena, Ronald

    2018-01-01

    The Robert C Byrd Green Bank Telescope (GBT) uses a software system that dynamically schedules observations based on models of vertical weather forecasts produced by the National Weather Service (NWS). The NWS provides hourly forecasted values for ~60 layers that extend into the stratosphere over the observatory. We use models, recommended by the Radiocommunication Sector of the International Telecommunications Union, to derive the absorption coefficient in each layer for each hour in the NWS forecasts and for all frequencies over which the GBT has receivers, 0.1 to 115 GHz. We apply radiative transfer models to derive the opacity and the atmospheric contributions to the system temperature, thereby deriving forecasts applicable to scheduling radio observations for up to 10 days into the future. Additionally, the algorithms embedded in the data processing pipeline use historical values of the forecasted opacity to calibrate observations. Until recently, we have concentrated on predictions for high frequency (> 15 GHz) observing, as these need to be scheduled carefully around bad weather. We have been using simple models for the contribution of rain and clouds since we only schedule low-frequency observations under these conditions. In this project, we wanted to improve the scheduling of the GBT and data calibration at low frequencies by deriving better algorithms for clouds and rain. To address the limitation at low frequency, the observatory acquired a Radiometrics Corporation MP-1500A radiometer, which operates in 27 channels between 22 and 30 GHz. By comparing 16 months of measurements from the radiometer against forecasted system temperatures, we have confirmed that forecasted system temperatures are indistinguishable from those measured under good weather conditions. Small miss-calibrations of the radiometer data dominate the comparison. By using recalibrated radiometer measurements, we looked at bad weather days to derive better models for forecasting the

  12. Partnership - the heart of integrated outage management

    International Nuclear Information System (INIS)

    Robinson, F.T.

    1995-01-01

    Changes in the power generating industry continue apace. The effects of privatisation are widely visible: nowhere more so than in the growing national and international competition facing the generators around the world. A successful, long-term marriage between generator and contractor on power station outage management offers significant scope for cost reduction, shortening annual plant downtime and generating more megawatts, all within a safety environment of continuous improvement. Working in close partnership, Nuclear Electric and Rolls-Royce Nuclear Engineering Services have remodelled the whole contractor/client strategy. The new discipline, known as integrated outage management and partnering, is already producing shorter outage periods at Bradwell, a Magnox Station in Essex. (author)

  13. A Novel Hydro-information System for Improving National Weather Service River Forecast System

    Science.gov (United States)

    Nan, Z.; Wang, S.; Liang, X.; Adams, T. E.; Teng, W. L.; Liang, Y.

    2009-12-01

    A novel hydro-information system has been developed to improve the forecast accuracy of the NOAA National Weather Service River Forecast System (NWSRFS). An MKF-based (Multiscale Kalman Filter) spatial data assimilation framework, together with the NOAH land surface model, is employed in our system to assimilate satellite surface soil moisture data to yield improved evapotranspiration. The latter are then integrated into the distributed version of the NWSRFS to improve its forecasting skills, especially for droughts, but also for disaster management in general. Our system supports an automated flow into the NWSRFS of daily satellite surface soil moisture data, derived from the TRMM Microwave Imager (TMI) and Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), and the forcing information of the North American Land Data Assimilation System (NLDAS). All data are custom processed, archived, and supported by the NASA Goddard Earth Sciences Data Information and Services Center (GES DISC). An optional data fusing component is available in our system, which fuses NEXRAD Stage III precipitation data with the NLDAS precipitation data, using the MKF-based framework, to provide improved precipitation inputs. Our system employs a plug-in, structured framework and has a user-friendly, graphical interface, which can display, in real-time, the spatial distributions of assimilated state variables and other model-simulated information, as well as their behaviors in time series. The interface can also display watershed maps, as a result of the integration of the QGIS library into our system. Extendibility and flexibility of our system are achieved through the plug-in design and by an extensive use of XML-based configuration files. Furthermore, our system can be extended to support multiple land surface models and multiple data assimilation schemes, which would further increase its capabilities. Testing of the integration of the current system into the NWSRFS is

  14. Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

    Science.gov (United States)

    Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

    2015-04-01

    The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful

  15. Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

    Science.gov (United States)

    Wu, Qi

    2010-03-01

    Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

  16. Benchmark Report on Key Outage Attributes: An Analysis of Outage Improvement Opportunities and Priorities

    Energy Technology Data Exchange (ETDEWEB)

    Germain, Shawn St. [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Farris, Ronald [Idaho National Laboratory (INL), Idaho Falls, ID (United States)

    2014-09-01

    Advanced Outage Control Center (AOCC), is a multi-year pilot project targeted at Nuclear Power Plant (NPP) outage improvement. The purpose of this pilot project is to improve management of NPP outages through the development of an AOCC that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This report documents the results of a benchmarking effort to evaluate the transferability of technologies demonstrated at Idaho National Laboratory and the primary pilot project partner, Palo Verde Nuclear Generating Station. The initial assumption for this pilot project was that NPPs generally do not take advantage of advanced technology to support outage management activities. Several researchers involved in this pilot project have commercial NPP experience and believed that very little technology has been applied towards outage communication and collaboration. To verify that the technology options researched and demonstrated through this pilot project would in fact have broad application for the US commercial nuclear fleet, and to look for additional outage management best practices, LWRS program researchers visited several additional nuclear facilities.

  17. Pathways to designing and running an operational flood forecasting system: an adventure game!

    Science.gov (United States)

    Arnal, Louise; Pappenberger, Florian; Ramos, Maria-Helena; Cloke, Hannah; Crochemore, Louise; Giuliani, Matteo; Aalbers, Emma

    2017-04-01

    In the design and building of an operational flood forecasting system, a large number of decisions have to be taken. These include technical decisions related to the choice of the meteorological forecasts to be used as input to the hydrological model, the choice of the hydrological model itself (its structure and parameters), the selection of a data assimilation procedure to run in real-time, the use (or not) of a post-processor, and the computing environment to run the models and display the outputs. Additionally, a number of trans-disciplinary decisions are also involved in the process, such as the way the needs of the users will be considered in the modelling setup and how the forecasts (and their quality) will be efficiently communicated to ensure usefulness and build confidence in the forecasting system. We propose to reflect on the numerous, alternative pathways to designing and running an operational flood forecasting system through an adventure game. In this game, the player is the protagonist of an interactive story driven by challenges, exploration and problem-solving. For this presentation, you will have a chance to play this game, acting as the leader of a forecasting team at an operational centre. Your role is to manage the actions of your team and make sequential decisions that impact the design and running of the system in preparation to and during a flood event, and that deal with the consequences of the forecasts issued. Your actions are evaluated by how much they cost you in time, money and credibility. Your aim is to take decisions that will ultimately lead to a good balance between time and money spent, while keeping your credibility high over the whole process. This game was designed to highlight the complexities behind decision-making in an operational forecasting and emergency response context, in terms of the variety of pathways that can be selected as well as the timescale, cost and timing of effective actions.

  18. Evaluation and Quality Control for the Copernicus Seasonal Forecast Systems

    Science.gov (United States)

    Manubens, N.; Hunter, A.; Bedia, J.; Bretonnière, P. A.; Bhend, J.; Doblas-Reyes, F. J.

    2017-12-01

    The EU funded Copernicus Climate Change Service (C3S) will provide authoritative information about past, current and future climate for a wide range of users, from climate scientists to stakeholders from a wide range of sectors including insurance, energy or transport. It has been recognized that providing information about the products' quality and provenance is paramount to establish trust in the service and allow users to make best use of the available information. This presentation outlines the work being conducted within the Quality Assurance for Multi-model Seasonal Forecast Products project (QA4Seas). The aim of QA4Seas is to develop a strategy for the evaluation and quality control (EQC) of the multi-model seasonal forecasts provided by C3S. First, we present the set of guidelines the data providers must comply with, ensuring the data is fully traceable and harmonized across data sets. Second, we discuss the ongoing work on defining a provenance and metadata model that is able to encode such information, and that can be extended to describe the steps followed to obtain the final verification products such as maps and time series of forecast quality measures. The metadata model is based on the Resource Description Framework W3C standard, being thus extensible and reusable. It benefits from widely adopted vocabularies to describe data provenance and workflows, as well as from expert consensus and community-support for the development of the verification and downscaling specific ontologies. Third, we describe the open source software being developed to generate fully reproducible and certifiable seasonal forecast products, which also attaches provenance and metadata information to the verification measures and enables the user to visually inspect the quality of the C3S products. QA4Seas is seeking collaboration with similar initiatives, as well as extending the discussion to interested parties outside the C3S community to share experiences and establish global

  19. Decadal Prediction Skill in the GEOS-5 Forecast System

    Science.gov (United States)

    Ham, Yoo-Geun; Rienecker, Michele M.; Suarez, Max J.; Vikhliaev, Yury; Zhao, Bin; Marshak, Jelena; Vernieres, Guillaume; Schubert, Siegfried D.

    2013-01-01

    A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office's (GMAO's) GEOS-5 Atmosphere-Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multivariate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO's atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean Atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 percent improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the sub-polar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

  20. Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region

    International Nuclear Information System (INIS)

    Han, S.-R.; Guikema, Seth D.; Quiring, Steven M.; Lee, Kyung-Ho; Rosowsky, David; Davidson, Rachel A.

    2009-01-01

    Hurricanes have caused severe damage to the electric power system throughout the Gulf coast region of the US, and electric power is critical to post-hurricane disaster response as well as to long-term recovery for impacted areas. Managing power outage risk and preparing for post-storm recovery efforts requires accurate methods for estimating the number and location of power outages. This paper builds on past work on statistical power outage estimation models to develop, test, and demonstrate a statistical power outage risk estimation model for the Gulf Coast region of the US. Previous work used binary hurricane-indicator variables representing particular hurricanes in order to achieve a good fit to the past data. To use these models for predicting power outages during future hurricanes, one must implicitly assume that an approaching hurricane is similar to the average of the past hurricanes. The model developed in this paper replaces these indicator variables with physically measurable variables, enabling future predictions to be based on only well-understood characteristics of hurricanes. The models were developed using data about power outages during nine hurricanes in three states served by a large, investor-owned utility company in the Gulf Coast region

  1. Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

    Science.gov (United States)

    Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

    2011-12-01

    This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

  2. Outages 1999 and 2000, investments in safety and long-term operation of NE Krsko

    International Nuclear Information System (INIS)

    Sirola, P.; Krajnc, J.; Androjna, F.

    1999-01-01

    Plant outage is an important part of nuclear power plant operation. During that time the conditions are established for the performance of specific activities, such as refueling, tests, inspections, preventive and corrective maintenance and modifications, that are intended to confirm proper condition and availability of safety and other important components and improve overall plant safety and reliability. It is well know that in Nuclear Power Plant Krsko (Nuklearna elektrarna Krsko NEK) during Outage 2000 new Steam Generators (SGs) will be placed in service, while Outage '99 was used for preparatory works. But the importance of those two outages is even greater, because they are implementing a broad number of improvements and establishing a basis for long-term plant operation. Outage '99 required very detailed planning to assure a good control over the outage activities and operational plant systems necessary for safe shutdown. Numerous activities took place in a relatively narrow space in the Reactor Building. Some of these activities will have a big significance for the future. The article treats the status update and summarizes the specifics and importance of the mentioned activities to long-term plant safe and reliable operation.(author)

  3. Guidelines for Implementation of an Advanced Outage Control Center to Improve Outage Coordination, Problem Resolution, and Outage Risk Management

    Energy Technology Data Exchange (ETDEWEB)

    St. Germain, Shawn W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Farris, Ronald K. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Whaley, April M. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Medema, Heather D. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Gertman, David I. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2014-09-01

    This research effort is a part of the Light-Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by Department of Energy (DOE) and performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants. The LWRS program serves to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The purpose of this research is to improve management of nuclear power plant (NPP) outages through the development of an advanced outage control center (AOCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This technical report for industry implementation outlines methods and considerations for the establishment of an AOCC. This report provides a process for implementation of a change management plan, evaluation of current outage processes, the selection of technology, and guidance for the implementation of the selected technology. Methods are presented for both adoption of technologies within an existing OCC and for a complete OCC replacement, including human factors considerations for OCC design and setup.

  4. An Operational System for Surveillance and Ecological Forecasting of West Nile Virus Outbreaks

    Science.gov (United States)

    Wimberly, M. C.; Davis, J. K.; Vincent, G.; Hess, A.; Hildreth, M. B.

    2017-12-01

    Mosquito-borne disease surveillance has traditionally focused on tracking human cases along with the abundance and infection status of mosquito vectors. For many of these diseases, vector and host population dynamics are also sensitive to climatic factors, including temperature fluctuations and the availability of surface water for mosquito breeding. Thus, there is a potential to strengthen surveillance and predict future outbreaks by monitoring environmental risk factors using broad-scale sensor networks that include earth-observing satellites. The South Dakota Mosquito Information System (SDMIS) project combines entomological surveillance with gridded meteorological data from NASA's North American Land Data Assimilation System (NLDAS) to generate weekly risk maps for West Nile virus (WNV) in the north-central United States. Critical components include a mosquito infection model that smooths the noisy infection rate and compensates for unbalanced sampling, and a human infection model that combines the entomological risk estimates with lagged effects of meteorological variables from the North American Land Data Assimilation System (NLDAS). Two types of forecasts are generated: long-term forecasts of statewide risk extending through the entire WNV season, and short-term forecasts of the geographic pattern of WNV risk in the upcoming week. Model forecasts are connected to public health actions through decision support matrices that link predicted risk levels to a set of phased responses. In 2016, the SDMIS successfully forecast an early start to the WNV season and a large outbreak of WNV cases following several years of low transmission. An evaluation of the 2017 forecasts will also be presented. Our experiences with the SDMIS highlight several important lessons that can inform future efforts at disease early warning. These include the value of integrating climatic models with recent observations of infection, the critical role of automated workflows to facilitate

  5. Sample Results from MCU Solids Outage

    Energy Technology Data Exchange (ETDEWEB)

    Peters, T.; Washington, A.; Oji, L.; Coleman, C.; Poirier, M.

    2014-09-22

    Savannah River National Laboratory (SRNL) has received several solid and liquid samples from MCU in an effort to understand and recover from the system outage starting on April 6, 2014. SRNL concludes that the presence of solids in the Salt Solution Feed Tank (SSFT) is the likely root cause for the outage, based upon the following discoveries: A solids sample from the extraction contactor #1 proved to be mostly sodium oxalate; A solids sample from the scrub contactor#1 proved to be mostly sodium oxalate; A solids sample from the Salt Solution Feed Tank (SSFT) proved to be mostly sodium oxalate; An archived sample from Tank 49H taken last year was shown to contain a fine precipitate of sodium oxalate; A solids sample from ; A liquid sample from the SSFT was shown to have elevated levels of oxalate anion compared to the expected concentration in the feed. Visual inspection of the SSFT indicated the presence of precipitated or transferred solids, which were likely also in the Salt Solution Receipt Tank (SSRT). The presence of the solids coupled with agitation performed to maintain feed temperature resulted in oxalate solids migration through the MCU system and caused hydraulic issues that resulted in unplanned phase carryover from the extraction into the scrub, and ultimately the strip contactors. Not only did this carryover result in the Strip Effluent (SE) being pushed out of waste acceptance specification, but it resulted in the deposition of solids into several of the contactors. At the same time, extensive deposits of aluminosilicates were found in the drain tube in the extraction contactor #1. However it is not known at this time how the aluminosilicate solids are related to the oxalate solids. The solids were successfully cleaned out of the MCU system. However, future consideration must be given to the exclusion of oxalate solids into the MCU system. There were 53 recommendations for improving operations recently identified. Some additional considerations or

  6. A seasonal agricultural drought forecast system for food-insecure regions of East Africa

    Science.gov (United States)

    Shukla, Shraddhanand; McNally, Amy; Husak, Gregory; Funk, Christopher C.

    2014-01-01

     The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall

  7. Verification of an ensemble prediction system for storm surge forecast in the Adriatic Sea

    Science.gov (United States)

    Mel, Riccardo; Lionello, Piero

    2014-12-01

    In the Adriatic Sea, storm surges present a significant threat to Venice and to the flat coastal areas of the northern coast of the basin. Sea level forecast is of paramount importance for the management of daily activities and for operating the movable barriers that are presently being built for the protection of the city. In this paper, an EPS (ensemble prediction system) for operational forecasting of storm surge in the northern Adriatic Sea is presented and applied to a 3-month-long period (October-December 2010). The sea level EPS is based on the HYPSE (hydrostatic Padua Sea elevation) model, which is a standard single-layer nonlinear shallow water model, whose forcings (mean sea level pressure and surface wind fields) are provided by the ensemble members of the ECMWF (European Center for Medium-Range Weather Forecasts) EPS. Results are verified against observations at five tide gauges located along the Croatian and Italian coasts of the Adriatic Sea. Forecast uncertainty increases with the predicted value of the storm surge and with the forecast lead time. The EMF (ensemble mean forecast) provided by the EPS has a rms (root mean square) error lower than the DF (deterministic forecast), especially for short (up to 3 days) lead times. Uncertainty for short lead times of the forecast and for small storm surges is mainly caused by uncertainty of the initial condition of the hydrodynamical model. Uncertainty for large lead times and large storm surges is mainly caused by uncertainty in the meteorological forcings. The EPS spread increases with the rms error of the forecast. For large lead times the EPS spread and the forecast error substantially coincide. However, the EPS spread in this study, which does not account for uncertainty in the initial condition, underestimates the error during the early part of the forecast and for small storm surge values. On the contrary, it overestimates the rms error for large surge values. The PF (probability forecast) of the EPS

  8. A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF)

    International Nuclear Information System (INIS)

    Papaioannou, A; Anastasiadis, A; Sandberg, I; Tsiropoula, G; Tziotziou, K; Georgoulis, M K; Jiggens, P; Hilgers, A

    2015-01-01

    Solar Energetic Particles (SEPs) result from intense solar eruptive events such as solar flares and coronal mass ejections (CMEs) and pose a significant threat for both personnel and infrastructure in space conditions. In this work, we present FORSPEF (Forecasting Solar Particle Events and Flares), a novel dual system, designed to perform forecasting of SEPs based on forecasting of solar flares, as well as independent SEP nowcasting. An overview of flare and SEP forecasting methods of choice is presented. Concerning SEP events, we make use for the first time of the newly re-calibrated GOES proton data within the energy range 6.0-243 MeV and we build our statistics on an extensive time interval that includes roughly 3 solar cycles (1984-2013). A new comprehensive catalogue of SEP events based on these data has been compiled including solar associations in terms of flare (magnitude, location) and CME (width, velocity) characteristics. (paper)

  9. Sub-seasonal prediction over East Asia during boreal summer using the ECCC monthly forecasting system

    Science.gov (United States)

    Liang, Ping; Lin, Hai

    2018-02-01

    A useful sub-seasonal forecast is of great societal and economical value in the highly populated East Asian region, especially during boreal summer when frequent extreme events such as heat waves and persistent heavy rainfalls occur. Despite recent interest and development in sub-seasonal prediction, it is still unclear how skillful dynamical forecasting systems are in East Asia beyond 2 weeks. In this study we evaluate the sub-seasonal prediction over East Asia during boreal summer in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC).Results show that the climatological intra-seasonal oscillation (CISO) of East Asian summer monsoonis reasonably well captured. Statistically significant forecast skill of 2-meter air temperature (T2m) is achieved for all lead times up to week 4 (days 26-32) over East China and Northeast Asia, which is consistent with the skill in 500 hPa geopotential height (Z500). Significant forecast skill of precipitation, however, is limited to the week of days 5-11. Possible sources of predictability on the sub-seasonal time scale are analyzed. The weekly mean T2m anomaly over East China is found to be linked to an eastward propagating extratropical Rossby wave from the North Atlantic across Europe to East Asia. The Madden-Julian Oscillation (MJO) and El Nino-Southern Oscillation (ENSO) are also likely to influence the forecast skill of T2m at the sub-seasonal timescale over East Asia.

  10. An Experimental Real-Time Ocean Nowcast/Forecast System for Intra America Seas

    Science.gov (United States)

    Ko, D. S.; Preller, R. H.; Martin, P. J.

    2003-04-01

    An experimental real-time Ocean Nowcast/Forecast System has been developed for the Intra America Seas (IASNFS). The area of coverage includes the Caribbean Sea, the Gulf of Mexico and the Straits of Florida. The system produces nowcast and up to 72 hours forecast the sea level variation, 3D ocean current, temperature and salinity fields. IASNFS consists an 1/24 degree (~5 km), 41-level sigma-z data-assimilating ocean model based on NCOM. For daily nowcast/forecast the model is restarted from previous nowcast. Once model is restarted it continuously assimilates the synthetic temperature/salinity profiles generated by a data analysis model called MODAS to produce nowcast. Real-time data come from satellite altimeter (GFO, TOPEX/Poseidon, ERS-2) sea surface height anomaly and AVHRR sea surface temperature. Three hourly surface heat fluxes, including solar radiation, wind stresses and sea level air pressure from NOGAPS/FNMOC are applied for surface forcing. Forecasts are produced with available NOGAPS forecasts. Once the nowcast/forecast are produced they are distributed through the Internet via the updated web pages. The open boundary conditions including sea surface elevation, transport, temperature, salinity and currents are provided by the NRL 1/8 degree Global NCOM which is operated daily. An one way coupling scheme is used to ingest those boundary conditions into the IAS model. There are 41 rivers with monthly discharges included in the IASNFS.

  11. A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

    Directory of Open Access Journals (Sweden)

    S. Davolio

    2008-02-01

    Full Text Available The precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF, conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast.

    The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines. These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines.

    The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision.

  12. Standard plants, standard outages: the EdF approach

    International Nuclear Information System (INIS)

    Miron, J.L.

    1991-01-01

    At the end of 1990 Electricite de France had carried out a total of 350 PWR refuelling outages. Although the French units are standardized the routine of the outages are not all the same. The major influences on outages were: setting up new organizations to apply quality assurance regulations; improving systematic experience feedback; incorporating modifications in the outage schedules; assumilation of computerized maintenance management by the sites. (author)

  13. Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

    Science.gov (United States)

    Manukalo, V.

    2012-12-01

    Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of

  14. Residential outage cost estimation: Hong Kong

    International Nuclear Information System (INIS)

    Woo, C.K.; Ho, T.; Shiu, A.; Cheng, Y.S.; Horowitz, I.; Wang, J.

    2014-01-01

    Hong Kong has almost perfect electricity reliability, the result of substantial investments ultimately financed by electricity consumers who may be willing to accept lower reliability in exchange for lower bills. But consumers with high outage costs are likely to reject the reliability reduction. Our ordered-logit regression analysis of the responses by 1876 households to a telephone survey conducted in June 2013 indicates that Hong Kong residents exhibit a statistically-significant preference for their existing service reliability and rate. Moreover, the average residential cost estimate for a 1-h outage is US$45 (HK$350), topping the estimates reported in 10 of the 11 studies published in the last 10 years. The policy implication is that absent additional compelling evidence, Hong Kong should not reduce its service reliability. - Highlights: • Use a contingent valuation survey to obtain residential preferences for reliability. • Use an ordered logit analysis to estimate Hong Kong's residential outage costs. • Find high outage cost estimates that imply high reliability requirements. • Conclude that sans new evidence, Hong Kong should not reduce its reliability

  15. Hybrid Cascading Outage Analysis of Extreme Events with Optimized Corrective Actions

    Energy Technology Data Exchange (ETDEWEB)

    Vallem, Mallikarjuna R.; Vyakaranam, Bharat GNVSR; Holzer, Jesse T.; Samaan, Nader A.; Makarov, Yuri V.; Diao, Ruisheng; Huang, Qiuhua; Ke, Xinda

    2017-10-19

    Power system are vulnerable to extreme contingencies (like an outage of a major generating substation) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Some cascading outages are seen within minutes following a major contingency, which may not be captured exclusively using the dynamic simulation of the power system. The utilities plan for contingencies either based on dynamic or steady state analysis separately which may not accurately capture the impact of one process on the other. We address this gap in cascading outage analysis by developing Dynamic Contingency Analysis Tool (DCAT) that can analyze hybrid dynamic and steady state behavior of the power system, including protection system models in dynamic simulations, and simulating corrective actions in post-transient steady state conditions. One of the important implemented steady state processes is to mimic operator corrective actions to mitigate aggravated states caused by dynamic cascading. This paper presents an Optimal Power Flow (OPF) based formulation for selecting corrective actions that utility operators can take during major contingency and thus automate the hybrid dynamic-steady state cascading outage process. The improved DCAT framework with OPF based corrective actions is demonstrated on IEEE 300 bus test system.

  16. Qinshan CANDU NPP outage performance improvement through benchmarking

    International Nuclear Information System (INIS)

    Jiang Fuming

    2005-01-01

    With the increasingly fierce competition in the deregulated Energy Market, the optimization of outage duration has become one of the focal points for the Nuclear Power Plant owners around the world. People are seeking various ways to shorten the outage duration of NPP. Great efforts have been made in the Light Water Reactor (LWR) family with the concept of benchmarking and evaluation, which great reduced the outage duration and improved outage performance. The average capacity factor of LWRs has been greatly improved over the last three decades, which now is close to 90%. CANDU (Pressurized Heavy Water Reactor) stations, with its unique feature of on power refueling, of nuclear fuel remaining in the reactor all through the planned outage, have given raise to more stringent safety requirements during planned outage. In addition, the above feature gives more variations to the critical path of planned outage in different station. In order to benchmarking again the best practices in the CANDU stations, Third Qinshan Nuclear Power Company (TQNPC) have initiated the benchmarking program among the CANDU stations aiming to standardize the outage maintenance windows and optimize the outage duration. The initial benchmarking has resulted the optimization of outage duration in Qinshan CANDU NPP and the formulation of its first long-term outage plan. This paper describes the benchmarking works that have been proven to be useful for optimizing outage duration in Qinshan CANDU NPP, and the vision of further optimize the duration with joint effort from the CANDU community. (authors)

  17. Cell outage compensation in LTE networks: Algorithms and performance assessment

    NARCIS (Netherlands)

    Amirijoo, M.; Jorguseski, L.; Litjens, R.; Schmelz, L.C.

    2011-01-01

    Cell outage compensation is a self-healing function and as such part of the Self-Organising Networks concept for mobile wireless networks. It aims at mitigating the degradation of coverage, capacity and service quality caused by a cell or site level outage. Upon detection of such an outage, cell

  18. Forecasting and observability: critical technologies for system operations with high PV penetration

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    – Photovoltaics (ETIP PV) reviews the different use cases for these technologies, their current status, and the need for future developments. Power system operations require a real-time view of PV production for managing power reserves and for feeding shortterm forecasts. They also require forecasts on all......Forecasting and monitoring technologies for photovoltaics are required on different spatial and temporal scales by multiple actors, from the owners of PV systems to transmission system operators. In this paper the Grid integration working group of the European Technology and Innovation Platform...... timescales from the short (for dispatching purposes), where statistical models work best, to the very long (for infrastructure planning), where physics-based models are more accurate. Power system regulations are driving the development of these techniques. This application also provides a good basis...

  19. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  20. The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts

    Directory of Open Access Journals (Sweden)

    J. C. Bartholmes

    2009-02-01

    Full Text Available Since 2005 the European Flood Alert System (EFAS has been producing probabilistic hydrological forecasts in pre-operational mode at the Joint Research Centre (JRC of the European Commission. EFAS aims at increasing preparedness for floods in trans-national European river basins by providing medium-range deterministic and probabilistic flood forecasting information, from 3 to 10 days in advance, to national hydro-meteorological services.

    This paper is Part 2 of a study presenting the development and skill assessment of EFAS. In Part 1, the scientific approach adopted in the development of the system has been presented, as well as its basic principles and forecast products. In the present article, two years of existing operational EFAS forecasts are statistically assessed and the skill of EFAS forecasts is analysed with several skill scores. The analysis is based on the comparison of threshold exceedances between proxy-observed and forecasted discharges. Skill is assessed both with and without taking into account the persistence of the forecasted signal during consecutive forecasts.

    Skill assessment approaches are mostly adopted from meteorology and the analysis also compares probabilistic and deterministic aspects of EFAS. Furthermore, the utility of different skill scores is discussed and their strengths and shortcomings illustrated. The analysis shows the benefit of incorporating past forecasts in the probability analysis, for medium-range forecasts, which effectively increases the skill of the forecasts.

  1. Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2018-02-01

    Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.

  2. Enhancing Community Based Early Warning Systems in Nepal with Flood Forecasting Using Local and Global Models

    Science.gov (United States)

    Dugar, Sumit; Smith, Paul; Parajuli, Binod; Khanal, Sonu; Brown, Sarah; Gautam, Dilip; Bhandari, Dinanath; Gurung, Gehendra; Shakya, Puja; Kharbuja, RamGopal; Uprety, Madhab

    2017-04-01

    Operationalising effective Flood Early Warning Systems (EWS) in developing countries like Nepal poses numerous challenges, with complex topography and geology, sparse network of river and rainfall gauging stations and diverse socio-economic conditions. Despite these challenges, simple real-time monitoring based EWSs have been in place for the past decade. A key constraint of these simple systems is the very limited lead time for response - as little as 2-3 hours, especially for rivers originating from steep mountainous catchments. Efforts to increase lead time for early warning are focusing on imbedding forecasts into the existing early warning systems. In 2016, the Nepal Department of Hydrology and Meteorology (DHM) piloted an operational Probabilistic Flood Forecasting Model in major river basins across Nepal. This comprised a low data approach to forecast water levels, developed jointly through a research/practitioner partnership with Lancaster University and WaterNumbers (UK) and the International NGO Practical Action. Using Data-Based Mechanistic Modelling (DBM) techniques, the model assimilated rainfall and water levels to generate localised hourly flood predictions, which are presented as probabilistic forecasts, increasing lead times from 2-3 hours to 7-8 hours. The Nepal DHM has simultaneously started utilizing forecasts from the Global Flood Awareness System (GLoFAS) that provides streamflow predictions at the global scale based upon distributed hydrological simulations using numerical ensemble weather forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). The aforementioned global and local models have already affected the approach to early warning in Nepal, being operational during the 2016 monsoon in the West Rapti basin in Western Nepal. On 24 July 2016, GLoFAS hydrological forecasts for the West Rapti indicated a sharp rise in river discharge above 1500 m3/sec (equivalent to the river warning level at 5 meters) with 53

  3. Validation of the CME Geomagnetic forecast alerts under COMESEP alert system

    Science.gov (United States)

    Dumbovic, Mateja; Srivastava, Nandita; Khodia, Yamini; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

    2017-04-01

    An automated space weather alert system has been developed under the EU FP7 project COMESEP (COronal Mass Ejections and Solar Energetic Particles: http://comesep.aeronomy.be) to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. COMESEP alert system uses automated detection tool CACTus to detect potentially threatening CMEs, drag-based model (DBM) to predict their arrival and CME geo-effectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, DBM calculates its arrival time at Earth and CGFT calculates its geomagnetic risk level. Geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geo-effectiveness, as well as an estimate of the geomagnetic-storm duration. We present the evaluation of the CME risk level forecast with COMESEP alert system based on a study of geo-effective CMEs observed during 2014. The validation of the forecast tool is done by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of DBM and CGFT (self standing tools available at Hvar Observatory website: http://oh.geof.unizg.hr). The results implicate that the success rate of the forecast is higher with human intervention and using more advanced tools. This work has received funding from the European Commission FP7 Project COMESEP (263252). We acknowledge the support of Croatian Science Foundation under the project 6212 „Solar and Stellar Variability".

  4. Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

    Science.gov (United States)

    Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

    2013-04-01

    The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of

  5. The Santos Basin Ocean Observing System: From R&D to Operational Regional Forecasts

    Science.gov (United States)

    Da Rocha Fragoso, M.; Moore, A. M.; dos Santos, F. A.; Marques Da Cruz, L.; Carvalho, G. V.; Soares, F.

    2016-02-01

    Santos Basin is located on the Southwestern Brazilian Ocean Basin and comprises the main offshore oil reserves of Brazil. The exploration and production activities on its ocean are growing in accelerated pace, which means that oil spill contingency and search & rescue operations are likely to be more frequent. Therefore, ocean current reliable nowcasts and forecasts has become even more important for this region. The Santos Basin Ocean Observing System was designed as an R&D project and its main objective was to establish and maintain a systematic oceanographic data collection for this region in order to study its ocean dynamics and improve regional ocean forecast through data assimilation. In the first three years of the project surface drifters, profiling floats and gliders were deployed to measure and monitor mainly the Brazil Current Western Boundary System, a highly unstable baroclinic current system, that present several meanders and mesoscale eddies activities. Throughout the development of the project, the team involved was able to learn how to operate the equipment, treat the collected data and use it to assimilate on the Regional Ocean Modeling System (ROMS). After performing a one-year 4DVAR assimilation cycle (Fragoso et al., 2015) in which the forecasting skill was assessed, the system was considered mature enough to start producing ocean circulation forecasts for Santos Basin. It is the first time in Brazil that a regional ocean model using a 4DVAR data assimilation scheme was used to produce high resolution operational ocean current forecasts. This paper describes all the components of this forecasting system, its main results and discoveries with special focus on the Brazil Current System Transport and mesocale eddies dynamics and statistics.

  6. Multi-platform operational validation of the Western Mediterranean SOCIB forecasting system

    Science.gov (United States)

    Juza, Mélanie; Mourre, Baptiste; Renault, Lionel; Tintoré, Joaquin

    2014-05-01

    The development of science-based ocean forecasting systems at global, regional, and local scales can support a better management of the marine environment (maritime security, environmental and resources protection, maritime and commercial operations, tourism, ...). In this context, SOCIB (the Balearic Islands Coastal Observing and Forecasting System, www.socib.es) has developed an operational ocean forecasting system in the Western Mediterranean Sea (WMOP). WMOP uses a regional configuration of the Regional Ocean Modelling System (ROMS, Shchepetkin and McWilliams, 2005) nested in the larger scale Mediterranean Forecasting System (MFS) with a spatial resolution of 1.5-2km. WMOP aims at reproducing both the basin-scale ocean circulation and the mesoscale variability which is known to play a crucial role due to its strong interaction with the large scale circulation in this region. An operational validation system has been developed to systematically assess the model outputs at daily, monthly and seasonal time scales. Multi-platform observations are used for this validation, including satellite products (Sea Surface Temperature, Sea Level Anomaly), in situ measurements (from gliders, Argo floats, drifters and fixed moorings) and High-Frequency radar data. The validation procedures allow to monitor and certify the general realism of the daily production of the ocean forecasting system before its distribution to users. Additionally, different indicators (Sea Surface Temperature and Salinity, Eddy Kinetic Energy, Mixed Layer Depth, Heat Content, transports in key sections) are computed every day both at the basin-scale and in several sub-regions (Alboran Sea, Balearic Sea, Gulf of Lion). The daily forecasts, validation diagnostics and indicators from the operational model over the last months are available at www.socib.es.

  7. Outage planning in nuclear power plants. A paradigm shift from an external towards an integrated project planning tool

    Energy Technology Data Exchange (ETDEWEB)

    Rosemann, Andreas [Gesellschaft fuer integrierte Systemplanung (GIS) mbH, Weinheim (Germany)

    2014-07-01

    Latest demands on nuclear plant inspections are the ongoing actualisation of the outage plan on the basis of the current work progress and current events as well as the permanent access to the current planning status and work process of all people involved in the outage. Modern EAM systems (EAM: Enterprise Application Management) made up ground on established project planning tools with regard to functionalities for scheduling work orders. A shift towards an integrated planning in the EAM system increases the efficiency in the outage planning and improves the communication of current states of planning. (orig.)

  8. Outage planning in nuclear power plants. A paradigm shift from an external towards an integrated project planning tool

    International Nuclear Information System (INIS)

    Rosemann, Andreas

    2014-01-01

    Latest demands on nuclear plant inspections are the ongoing actualisation of the outage plan on the basis of the current work progress and current events as well as the permanent access to the current planning status and work process of all people involved in the outage. Modern EAM systems (EAM: Enterprise Application Management) made up ground on established project planning tools with regard to functionalities for scheduling work orders. A shift towards an integrated planning in the EAM system increases the efficiency in the outage planning and improves the communication of current states of planning. (orig.)

  9. An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games

    Science.gov (United States)

    Mailhot, J.; Milbrandt, J. A.; Giguère, A.; McTaggart-Cowan, R.; Erfani, A.; Denis, B.; Glazer, A.; Vallée, M.

    2014-01-01

    Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM-LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.

  10. COST ES0602: towards a European network on chemical weather forecasting and information systems

    Directory of Open Access Journals (Sweden)

    J. Kukkonen

    2009-04-01

    Full Text Available The COST ES0602 action provides a forum for benchmarking approaches and practices in data exchange and multi-model capabilities for chemical weather forecasting and near real-time information services in Europe. The action includes approximately 30 participants from 19 countries, and its duration is from 2007 to 2011 (http://www.chemicalweather.eu/. Major efforts have been dedicated in other actions and projects to the development of infrastructures for data flow. We have therefore aimed for collaboration with ongoing actions towards developing near real-time exchange of input data for air quality forecasting. We have collected information on the operational air quality forecasting models on a regional and continental scale in a structured form, and inter-compared and evaluated the physical and chemical structure of these models. We have also constructed a European chemical weather forecasting portal that includes links to most of the available chemical weather forecasting systems in Europe. The collaboration also includes the examination of the case studies that have been organized within COST-728, in order to inter-compare and evaluate the models against experimental data. We have also constructed an operational model forecasting ensemble. Data from a representative set of regional background stations have been selected, and the operational forecasts for this set of sites will be inter-compared and evaluated. The Action has investigated, analysed and reviewed existing chemical weather information systems and services, and will provide recommendations on best practices concerning the presentation and dissemination of chemical weather information towards the public and decision makers.

  11. Short-Term Forecasting of Electric Energy Generation for a Photovoltaic System

    Directory of Open Access Journals (Sweden)

    Dinh V.T.

    2018-01-01

    Full Text Available This article presents a short-term forecast of electric energy output of a photovoltaic (PV system towards Tomsk city, Russia climate variations (module temperature and solar irradiance. The system is located at Institute of Non-destructive Testing, Tomsk Polytechnic University. The obtained results show good agreement between actual data and prediction values.

  12. Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system

    Science.gov (United States)

    Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic

    2014-01-01

    The finite resolution of general circulation models of the coupled atmosphere–ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere–ocean climate system in operational forecast mode, and the latest seasonal forecasting system—System 4—has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981–2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden–Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid

  13. Exploring the applicability of future air quality predictions based on synoptic system forecasts

    International Nuclear Information System (INIS)

    Yuval; Broday, David M.; Alpert, Pinhas

    2012-01-01

    For a given emissions inventory, the general levels of air pollutants and the spatial distribution of their concentrations are determined by the physiochemical state of the atmosphere. Apart from the trivial seasonal and daily cycles, most of the variability is associated with the atmospheric synoptic scale. A simple methodology for assessing future levels of air pollutants' concentrations based on synoptic forecasts is presented. At short time scales the methodology is comparable and slightly better than persistence and seasonal forecasts at categorical classification of pollution levels. It's utility is shown for air quality studies at the long time scale of a changing climate scenario, where seasonality and persistence cannot be used. It is demonstrated that the air quality variability due to changes in the pollution emissions can be expected to be much larger than that associated with the effects of climatic changes. - Highlights: ► A method for short and long term air quality forecasts is introduced. ► The method is based on prediction of synoptic systems. ► The method beats simple benchmarks in short term forecasts. ► Assessment of future air pollution in a changing climate scenario is demonstrated. - Air quality in a changing climate scenario can be studied using air pollution predictions based on synoptic system forecasts.

  14. Demand forecasting for automotive sector in Malaysia by system dynamics approach

    International Nuclear Information System (INIS)

    Zulkepli, Jafri; Abidin, Norhaslinda Zainal; Fong, Chan Hwa

    2015-01-01

    In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars

  15. Future wind power forecast errors, need for regulating power, and costs in the Swedish system

    Energy Technology Data Exchange (ETDEWEB)

    Carlsson, Fredrik [Vattenfall Research and Development AB, Stockholm (Sweden). Power Technology

    2011-07-01

    Wind power is one of the renewable energy sources in the electricity system that grows most rapid in Sweden. There are however two market challenges that need to be addressed with a higher proportion of wind power - that is variability and predictability. Predictability is important since the spot market Nord Pool Spot requires forecasts of production 12 - 36 hours ahead. The forecast errors must be regulated with regulating power, which is expensive for the actors causing the forecast errors. This paper has investigated a number of scenarios with 10 - 55 TWh of wind power installed in the Swedish system. The focus has been on a base scenario with 10 TWh new wind power consisting of 3,5 GW new wind power and 1,5 GW already installed power, which gives 5 GW. The results show that the costs for the forecast errors will increase as more intermittent production is installed. However, the increase can be limited by for instance trading on intraday market or increase quality of forecasts. (orig.)

  16. Demand forecasting for automotive sector in Malaysia by system dynamics approach

    Energy Technology Data Exchange (ETDEWEB)

    Zulkepli, Jafri, E-mail: zhjafri@uum.edu.my; Abidin, Norhaslinda Zainal, E-mail: nhaslinda@uum.edu.my [School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah (Malaysia); Fong, Chan Hwa, E-mail: hfchan7623@yahoo.com [SWM Environment Sdn. Bhd.Level 17, Menara LGB, Taman Tun Dr. Ismail Kuala Lumpur (Malaysia)

    2015-12-11

    In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

  17. A system-theory-based model for monthly river runoff forecasting: model calibration and optimization

    Directory of Open Access Journals (Sweden)

    Wu Jianhua

    2014-03-01

    Full Text Available River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff forecasting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.

  18. Model-Aided Altimeter-Based Water Level Forecasting System in Mekong River

    Science.gov (United States)

    Chang, C. H.; Lee, H.; Hossain, F.; Okeowo, M. A.; Basnayake, S. B.; Jayasinghe, S.; Saah, D. S.; Anderson, E.; Hwang, E.

    2017-12-01

    Mekong River, one of the massive river systems in the world, has drainage area of about 795,000 km2 covering six countries. People living in its drainage area highly rely on resources given by the river in terms of agriculture, fishery, and hydropower. Monitoring and forecasting the water level in a timely manner, is urgently needed over the Mekong River. Recently, using TOPEX/Poseidon (T/P) altimetry water level measurements in India, Biancamaria et al. [2011] has demonstrated the capability of an altimeter-based flood forecasting system in Bangladesh, with RMSE from 0.6 - 0.8 m for lead times up to 5 days on 10-day basis due to T/P's repeat period. Hossain et al. [2013] further established a daily water level forecasting system in Bangladesh using observations from Jason-2 in India and HEC-RAS hydraulic model, with RMSE from 0.5 - 1.5 m and an underestimating mean bias of 0.25 - 1.25 m. However, such daily forecasting system relies on a collection of Jason-2 virtual stations (VSs) to ensure frequent sampling and data availability. Since the Mekong River is a meridional river with few number of VSs, the direct application of this system to the Mekong River becomes challenging. To address this problem, we propose a model-aided altimeter-based forecasting system. The discharge output by Variable Infiltration Capacity hydrologic model is used to reconstruct a daily water level product at upstream Jason-2 VSs based on the discharge-to-level rating curve. The reconstructed daily water level is then used to perform regression analysis with downstream in-situ water level to build regression models, which are used to forecast a daily water level. In the middle reach of the Mekong River from Nakhon Phanom to Kratie, a 3-day lead time forecasting can reach RMSE about 0.7 - 1.3 m with correlation coefficient around 0.95. For the lower reach of the Mekong River, the water flow becomes more complicated due to the reversal flow between the Tonle Sap Lake and the Mekong River

  19. Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

    Science.gov (United States)

    Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

    2016-01-01

    Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

  20. Excellence through outage planning and scheduling

    International Nuclear Information System (INIS)

    Ferriole, G.

    1987-01-01

    The Nuclear and Fossil Generation Division of Electricite de France (EdF) has been the largest nuclear plant operating utility in France since 1984. The size of the units, their standardization, and extensive operating experience were favorable parameters leading to the development of a very complete maintenance organization. Electricite de France believes in the importance of well-defined maintenance concepts. These maintenance concepts contribute to outage performance by requiring a careful consideration of work to be done and by defining the techniques and means of accomplishing this work. In addition to maintenance concepts and careful planning and scheduling, good outage management is achieved through the motivation and dedication of the people involved. It is the key to good operational results

  1. Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems

    Directory of Open Access Journals (Sweden)

    D. T. Yakupov

    2017-01-01

    Full Text Available The purpose of research – to identify the prospects for the use of neural network approach in relation to the tasks of economic forecasting of logistics performance, in particular of volume freight traffic in the transport system promiscuous regional freight traffic, as well as to substantiate the effectiveness of the use of artificial neural networks (ANN, as compared with the efficiency of traditional extrapolative methods of forecasting. The authors consider the possibility of forecasting to use ANN for these economic indicators not as an alternative to the traditional methods of statistical forecasting, but as one of the available simple means for solving complex problems.Materials and methods. When predicting the ANN, three methods of learning were used: 1 the Levenberg-Marquardt algorithm-network training stops when the generalization ceases to improve, which is shown by the increase in the mean square error of the output value; 2 Bayes regularization method - network training is stopped in accordance with the minimization of adaptive weights; 3 the method of scaled conjugate gradients, which is used to find the local extremum of a function on the basis of information about its values and gradient. The Neural Network Toolbox package is used for forecasting. The neural network model consists of a hidden layer of neurons with a sigmoidal activation function and an output neuron with a linear activation function, the input values of the dynamic time series, and the predicted value is removed from the output. For a more objective assessment of the prospects of the ANN application, the results of the forecast are presented in comparison with the results obtained in predicting the method of exponential smoothing.Results. When predicting the volumes of freight transportation by rail, satisfactory indicators of the verification of forecasting by both the method of exponential smoothing and ANN had been obtained, although the neural network

  2. Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

    2010-03-15

    The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

  3. Programming and organisation of unit outages

    International Nuclear Information System (INIS)

    Hadjidakis, Y.; Cezard, C.; Audierne, J.

    1997-01-01

    The unit outages are scheduled every 12 to 18 months for fuel reloading. The success of these shutdowns, with the whole of objectives (duration, dosimetry, costs), with maintaining the safety level, is an important stake for the competitiveness of the enterprise. In this article are described the planning, the experience return and the organisation of scheduled shutdowns which have contribute to the improvement of availability. (N.C.)

  4. Advanced Outage and Control Center: Strategies for Nuclear Plant Outage Work Status Capabilities

    Energy Technology Data Exchange (ETDEWEB)

    Gregory Weatherby

    2012-05-01

    The research effort is a part of the Light Water Reactor Sustainability (LWRS) Program. LWRS is a research and development program sponsored by the Department of Energy, performed in close collaboration with industry to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. The LWRS Program serves to help the US nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The Outage Control Center (OCC) Pilot Project was directed at carrying out the applied research for development and pilot of technology designed to enhance safe outage and maintenance operations, improve human performance and reliability, increase overall operational efficiency, and improve plant status control. Plant outage management is a high priority concern for the nuclear industry from cost and safety perspectives. Unfortunately, many of the underlying technologies supporting outage control are the same as those used in the 1980’s. They depend heavily upon large teams of staff, multiple work and coordination locations, and manual administrative actions that require large amounts of paper. Previous work in human reliability analysis suggests that many repetitive tasks, including paper work tasks, may have a failure rate of 1.0E-3 or higher (Gertman, 1996). With between 10,000 and 45,000 subtasks being performed during an outage (Gomes, 1996), the opportunity for human error of some consequence is a realistic concern. Although a number of factors exist that can make these errors recoverable, reducing and effectively coordinating the sheer number of tasks to be performed, particularly those that are error prone, has the potential to enhance outage efficiency and safety. Additionally, outage management requires precise coordination of work groups that do not always share similar objectives. Outage

  5. Long-term optimization of outage performance

    International Nuclear Information System (INIS)

    Huemmeler, Alexander; Jakobs, Norbert; Seifert, Siegfried

    2003-01-01

    Deregulation of the power markets and the accompanying pressure on electricity prices have forced all electric utilities to reduce their power generating costs in order to be able to hold their own in the new market environment. This has also particularly affected the operators of nuclear power plants since they have to compete against the lower power generating costs of fossil-fired combined-cycle power plants and, in Germany are faced with a difficult political climate. The areas identified as having the greatest cost-cutting potential were fuel costs, operating costs and measures to increase plant availability. The main objective behind increasing plant availability was not only to improve the already high standard of operational reliability and plant safety even further, but also to significantly shorten the downtime needed for annual refueling outages. A variety of measures aimed at shortening scheduled plant outages have thus been developed and successfully implemented by nuclear plant operators. At the same time, process improvements and new technologies have been introduced by the service providers. Both initiatives together have contributed towards substantially reducing outage time and cost. (author)

  6. Cost of Lightning Strike Related Outages of Visual Navigational Aids at Airports in the United States

    Science.gov (United States)

    Rakas, J.; Nikolic, M.; Bauranov, A.

    2017-12-01

    Lightning storms are a serious hazard that can cause damage to vital human infrastructure. In aviation, lightning strikes cause outages to air traffic control equipment and facilities that result in major disruptions in the network, causing delays and financial costs measured in the millions of dollars. Failure of critical systems, such as Visual Navigational Aids (Visual NAVAIDS), are particularly dangerous since NAVAIDS are an essential part of landing procedures. Precision instrument approach, an operation utilized during the poor visibility conditions, utilizes several of these systems, and their failure leads to holding patterns and ultimately diversions to other airports. These disruptions lead to both ground and airborne delay. Accurate prediction of these outages and their costs is a key prerequisite for successful investment planning. The air traffic management and control sector need accurate information to successfully plan maintenance and develop a more robust system under the threat of increasing lightning rates. To analyze the issue, we couple the Remote Monitoring and Logging System (RMLS) database and the Aviation System Performance Metrics (ASPM) databases to identify lightning-induced outages, and connect them with weather conditions, demand and landing runway to calculate the total delays induced by the outages, as well as the number of cancellations and diversions. The costs are then determined by calculating direct costs to aircraft operators and costs of passengers' time for delays, cancellations and diversions. The results indicate that 1) not all NAVAIDS are created equal, and 2) outside conditions matter. The cost of an outage depends on the importance of the failed system and the conditions that prevailed before, during and after the failure. The outage that occurs during high demand and poor weather conditions is more likely to result in more delays and higher costs.

  7. Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

    Science.gov (United States)

    Lowe, Rachel; Coelho, Caio AS; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

    2016-01-01

    Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001 PMID:26910315

  8. A space weather forecasting system with multiple satellites based on a self-recognizing network.

    Science.gov (United States)

    Tokumitsu, Masahiro; Ishida, Yoshiteru

    2014-05-05

    This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  9. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

    Directory of Open Access Journals (Sweden)

    Masahiro Tokumitsu

    2014-05-01

    Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  10. How individual traces and interactive timelines could support outage execution - Toward an outage historian concept

    International Nuclear Information System (INIS)

    Parfouru, S.; De-Beler, N.

    2012-01-01

    In the context of a project that is designing innovative ICT-based solutions for the organizational concept of outage management, we focus on the informational process of the OCR (Outage Control Room) underlying the execution of the outages. Informational process are based on structured and unstructured documents that have a key role in the collaborative processes and management of the outage. We especially track the structured and unstructured documents, electronically or not, from creation to sharing. Our analysis allows us to consider that the individual traces produced by an individual participant with a specific role could be multi-purpose and support sharing between participants without creating duplication of work. The ultimate goal is to be able to generate an outage historian, that is not just focused on highly structured information, which could be useful to improve the continuity of information between participants. We study the implementation of this approach through web technologies and social media tools to address this issue. We also investigate the issue of data access through interactive visualization timelines coupled with other modality's to assist users in the navigation and exploration of the proposed historian. (authors)

  11. A Prototype Regional GSI-based EnKF-Variational Hybrid Data Assimilation System for the Rapid Refresh Forecasting System: Dual-Resolution Implementation and Testing Results

    Science.gov (United States)

    Pan, Yujie; Xue, Ming; Zhu, Kefeng; Wang, Mingjun

    2018-05-01

    A dual-resolution (DR) version of a regional ensemble Kalman filter (EnKF)-3D ensemble variational (3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution (HR) deterministic background forecast with lower-resolution (LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/˜13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation (GSI) 3D variational (3DVar) analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar. Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.

  12. Adaptive neuro-fuzzy inference system for forecasting rubber milk production

    Science.gov (United States)

    Rahmat, R. F.; Nurmawan; Sembiring, S.; Syahputra, M. F.; Fadli

    2018-02-01

    Natural Rubber is classified as the top export commodity in Indonesia. Its high production leads to a significant contribution to Indonesia’s foreign exchange. Before natural rubber ready to be exported to another country, the production of rubber milk becomes the primary concern. In this research, we use adaptive neuro-fuzzy inference system (ANFIS) to do rubber milk production forecasting. The data presented here is taken from PT. Anglo Eastern Plantation (AEP), which has high data variance and range for rubber milk production. Our data will span from January 2009 until December 2015. The best forecasting result is 1,182% in term of Mean Absolute Percentage Error (MAPE).

  13. Virtual collection: a mode to forecast the utilization in information systems

    International Nuclear Information System (INIS)

    Rausch, J.C.

    1988-01-01

    A model to forescast the requests of documents was proposed and tested. The model was tested using the data from the Selective Dissemination of Information and Document Delivery services of the Nuclear Information Center (CIN) of the National Comission of Nuclear Energy (CNEN). The variable which were used to forecast the requests were identified and using the integration of the two systems and regression analysis techniques it was forecasted the documents of the so-called ''virtual collection''. The results obtained have shown the viability of the application of the model. (author) [pt

  14. Seasonal maximum temperature prediction skill over Southern Africa: 1- vs 2-tiered forecasting systems

    CSIR Research Space (South Africa)

    Lazenby, MJ

    2011-09-01

    Full Text Available TEMPERATURE PREDICTION SKILL OVER SOUTHERN AFRICA: 1- VS. 2-TIERED FORECASTING SYSTEMS Melissa J. Lazenby University of Pretoria, Private Bag X20, Pretoria, 0028, South Africa Willem A. Landman Council for Scientific and Industrial....J., Tyson, P.D. and Tennant, W.J., 2001. Retro-active skill of multi- tiered forecasts of summer rainfall over southern Africa. International Journal of Climatology, 21, 1- 19. Mason, S.J. and Graham, N.E., 2002. Areas beneath the relative operating...

  15. Approaches, techniques, and information technology systems in the restaurants and foodservice industry: a qualitative study in sales forecasting.

    OpenAIRE

    Green, Yvette N. J.; Weaver, Pamela A.

    2008-01-01

    This is a study of the approaches, techniques, and information technology systems utilized for restaurant sales forecasting in the full-service restaurant segment. Companies were examined using a qualitative research methods design and long interviews to gather information on approaches, techniques, and technology systems utilized in the sales forecasting process. The results of the interviews were presented along with ensuing discussion.

  16. Technical Note: The normal quantile transformation and its application in a flood forecasting system

    Directory of Open Access Journals (Sweden)

    K. Bogner

    2012-04-01

    Full Text Available The Normal Quantile Transform (NQT has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

  17. Outage Performance of Decode-and-Forward in Two-Way Relaying with Outdated CSI

    KAUST Repository

    Hyadi, Amal

    2015-01-07

    In this paper, we analyze the outage behavior of decode-and-forward relaying in the context of selective two-way cooperative systems. First, a new relay selection metric is proposed to take into consideration both transmission rates and instantaneous link conditions between cooperating nodes. Afterwards, the outage probability of the proposed system is derived for Nakagami-m fading channels in the case when perfect channel state information is available and then extended to the more realistic scenario where the available channel state information (CSI) is outdated due to fast fading. New expressions for the outage probability are obtained, and the impact of imperfect CSI on the performance is evaluated. Illustrative numerical results, Monte Carlo simulations, and comparisons with similar approaches are presented to assess the accuracy of our analytical derivations and confirm the performance gain of the proposed scheme.

  18. Outage performance of reactive cooperation in Nakagami-m fading channels

    KAUST Repository

    Benjillali, Mustapha

    2010-06-01

    In this paper, we investigate the outage performance of Decode-and-Forward with reactive relaying in dual-hop cooperetive Nakagaml-m fading links. The destination, based on the umque knowledge of local second hop channel state information, selects the best relay to increase the chances of cooperation when the direct link is also available. After deriving the exact distribution of the variables of interest, the outage probability of the system - with and without the direct link - is obtained in closed-form, and the ε-outage capacity is derived in the particular c.se wh.ere the channel model is reduced to a Rayleigh fading. Simulation results confirm the accuracy of our analysis for a large selection of system and fading parameters.

  19. Outage performance of Decode-and-Forward partial selection in Nakagami-m fading channels

    KAUST Repository

    Benjillali, Mustapha

    2010-01-01

    In this paper, we investigate the outage performance of Decode-and-Forward with partial selection relaying in dualhop cooperative Nakagami-m fading links. The source, based on the unique knowledge of local first hop channel state information, selects the best relay to increase the chances of successful decoding and hence the possibility of cooperation when the direct link is also available. After deriving the exact distribution of the sum of two gamma variates with the same shape parameter, the outage probability of the system-with and without the direct link-is obtained in closed-form. We also derive the ε-outage capacity in different particular cases, and the obtained results- when the channel model is reduced to a Rayleigh fading-are either new or correspond to those previously obtained in other works. Simulation results confirm the accuracy of our analysis for a large selection of system and fading parameters. © 2009 IEEE.

  20. NOAA Weather Radio - Viewing Outages

    Science.gov (United States)

    SAME Non-Zero All Hazards Logo Emergency Alert Description Event Codes Fact Sheet FAQ Organization COVERAGE County Coverage Listings State Coverage Listings NWR Station Search Maps SAME SAME Coding Using ALert SYSTEM EAS Description Event Codes EAS Fact Sheet GENERAL INFORMATION Receiver Information

  1. Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

    Science.gov (United States)

    Zhao, Yongxu; Chen, Yueyun; Mai, Zhiyuan

    2018-01-01

    In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

  2. Outage probability analysis of wireless sensor networks in the presence of channel fading and spatial correlation

    KAUST Repository

    Al-Murad, Tamim M.

    2011-07-01

    Evaluating the reliability of wireless sensor networks is becoming more important as theses networks are being used in crucial applications. The outage probability defined as the probability that the error in the system exceeds a maximum acceptable threshold has recently been used as a measure of the reliability of such systems. In this work we find the outage probability of wireless sensor network in different scenarios of distributed sensing where sensors\\' readings are affected by spatial correlation and in the presence of channel fading. © 2011 IEEE.

  3. Indicators for management of planned outages in nuclear power plants

    International Nuclear Information System (INIS)

    2006-04-01

    The outages considered within the scope of this publication are planned refuelling outages (PWR and BWR nuclear power plants) and planned outages associated with major maintenance, tests and inspections (PHWR and LWGR nuclear power plants). The IAEA has published some valuable reports providing guidance and assistance to operating organizations on outage management. This TECDOC outlines main issues to be considered in outage performance monitoring and provides guidance to operating organizations for the development and implementation of outage programmes which could enhance plant safety, reliability and economics. It also complements the series of reports published by the IAEA on outage management and on previous work related to performance indicators developed for monitoring different areas of plant operation, such as safety, production, reliability and economics. This publication is based upon the information presented at a technical meeting to develop a standardized set of outage indicators for outage optimization, which was organised in Vienna, 6-9 October 2003. At this meeting, case studies and good practices relating to performance indicator utilization in the process of planned outage management were presented and discussed

  4. Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

    Science.gov (United States)

    Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

    2016-01-01

    Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

  5. Forecasting short-term power prices in the Ontario Electricity Market (OEM) with a fuzzy logic based inference system

    International Nuclear Information System (INIS)

    Arciniegas, Alvaro I.; Arciniegas Rueda, Ismael E.

    2008-01-01

    The Ontario Electricity Market (OEM), which opened in May 2002, is relatively new and is still under change. In addition, the bidding strategies of the participants are such that the relationships between price and fundamentals are non-linear and dynamic. The lack of market maturity and high complexity hinders the use of traditional statistical methodologies (e.g., regression analysis) for price forecasting. Therefore, a flexible model is needed to achieve good forecasting in OEM. This paper uses a Takagi-Sugeno-Kang (TSK) fuzzy inference system in forecasting the one-day-ahead real-time peak price of the OEM. The forecasting results of TSK are compared with those obtained by traditional statistical and neural network based forecasting. The comparison suggests that TSK has considerable value in forecasting one-day-ahead peak price in OEM. (author)

  6. Enhancing Famine Early Warning Systems with Improved Forecasts, Satellite Observations and Hydrologic Simulations

    Science.gov (United States)

    Funk, C. C.; Verdin, J.; Thiaw, W. M.; Hoell, A.; Korecha, D.; McNally, A.; Shukla, S.; Arsenault, K. R.; Magadzire, T.; Novella, N.; Peters-Lidard, C. D.; Robjohn, M.; Pomposi, C.; Galu, G.; Rowland, J.; Budde, M. E.; Landsfeld, M. F.; Harrison, L.; Davenport, F.; Husak, G. J.; Endalkachew, E.

    2017-12-01

    Drought early warning science, in support of famine prevention, is a rapidly advancing field that is helping to save lives and livelihoods. In 2015-2017, a series of extreme droughts afflicted Ethiopia, Southern Africa, Eastern Africa in OND and Eastern Africa in MAM, pushing more than 50 million people into severe food insecurity. Improved drought forecasts and monitoring tools, however, helped motivate and target large and effective humanitarian responses. Here we describe new science being developed by a long-established early warning system - the USAID Famine Early Warning Systems Network (FEWS NET). FEWS NET is a leading provider of early warning and analysis on food insecurity. FEWS NET research is advancing rapidly on several fronts, providing better climate forecasts and more effective drought monitoring tools that are being used to support enhanced famine early warning. We explore the philosophy and science underlying these successes, suggesting that a modal view of climate change can support enhanced seasonal prediction. Under this modal perspective, warming of the tropical oceans may interact with natural modes of variability, like the El Niño-Southern Oscillation, to enhance Indo-Pacific sea surface temperature gradients during both El Niño and La Niña-like climate states. Using empirical data and climate change simulations, we suggest that a sequence of droughts may commence in northern Ethiopia and Southern Africa with the advent of a moderate-to-strong El Niño, and then continue with La Niña/West Pacific related droughts in equatorial eastern East Africa. Scientifically, we show that a new hybrid statistical-dynamic precipitation forecast system, the FEWS NET Integrated Forecast System (FIFS), based on reformulations of the Global Ensemble Forecast System weather forecasts and National Multi-Model Ensemble (NMME) seasonal climate predictions, can effectively anticipate recent East and Southern African drought events. Using cross-validation, we

  7. Maintaining a Local Data Integration System in Support of Weather Forecast Operations

    Science.gov (United States)

    Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

    2010-01-01

    Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) at Johnson Space Center in Houston, TX have used a local data integration system (LDIS) as part of their forecast and warning operations. The original LDIS was developed by NASA's Applied Meteorology Unit (AMU; Bauman et ai, 2004) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features

  8. Mid-term load forecasting of power systems by a new prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    Mid-term load forecasting (MTLF) becomes an essential tool for today power systems, mainly in those countries whose power systems operate in a deregulated environment. Among different kinds of MTLF, this paper focuses on the prediction of daily peak load for one month ahead. This kind of load forecast has many applications like maintenance scheduling, mid-term hydro thermal coordination, adequacy assessment, management of limited energy units, negotiation of forward contracts, and development of cost efficient fuel purchasing strategies. However, daily peak load is a nonlinear, volatile, and nonstationary signal. Besides, lack of sufficient data usually further complicates this problem. The paper proposes a new methodology to solve it, composed of an efficient data model, preforecast mechanism and combination of neural network and evolutionary algorithm as the hybrid forecast technique. The proposed methodology is examined on the EUropean Network on Intelligent TEchnologies (EUNITE) test data and Iran's power system. We will also compare our strategy with the other MTLF methods revealing its capability to solve this load forecast problem

  9. a system approach to the long term forecasting of the climat data in baikal region

    Science.gov (United States)

    Abasov, N.; Berezhnykh, T.

    2003-04-01

    optimal vectors of parameters obtained are tested on the examination (verifying) subsample. If the procedure is successful, the forecast is immediately made by integration of several best solutions. Peculiarities of forecasting extreme processes. Methods of long-term forecasting allow the sufficiently reliable forecasts to be made within the interval of xmin+Δ_1, xmax - Δ_2 (i.e. in the interval of medium values of indices). Meanwhile, in the intervals close to extreme ones, reliability of forecasts is substantially lower. While for medium values the statistics of the100-year sequence gives acceptable results owing to a sufficiently large number of revealed analogs that correspond to prognostic samples, for extreme values the situation is quite different, first of all by virtue of poverty of statistical data. Decreasing the values of Δ_1,Δ_2: Δ_1,Δ_2 rightarrow 0 (by including them into optimization parameters of the considered forecasting methods) could be one of the ways to improve reliability of forecasts. Partially, such an approach has been realized in the method of analog-similarity relations, giving the possibility to form a range of possible forecasted trajectories in two variants - from the minimum possible trajectory to the maximum possible one. Reliability of long-term forecasts. Both the methodology and the methods considered above have been realized as the information-forecasting system "GIPSAR". The system includes some tools implementing several methods of forecasting, analysis of initial and forecasted information, a developed database, a set of tools for verification of algorithms, additional information on the algorithms of statistical processing of sequences (sliding averaging, integral-difference curves, etc.), aids to organize input of initial information (in its various forms) as well as aids to draw up output prognostic documents. Risk management. The normal functioning of the Angara cascade is periodically interrupted by risks of two types

  10. MOSE: A Demonstrator for an Automatic Operational System for the Optical Turbulence Forecast for ESO Sites

    Science.gov (United States)

    Masciadri, Elena; Lascaux, F.; Turchi, A.; Fini, L.

    2017-09-01

    "Most of the observations performed with new-generation ground-based telescopes are employing the Service Mode. To optimize the flexible-scheduling of scientific programs and instruments, the optical turbulence (OT) forecast is a must, particularly when observations are supported by adaptive optics (AO) and Interferometry. Reliable OT forecast are crucial to optimize the usage of AO and interferometric facilities which is not possible when using only optical measurements. Numerical techniques are the best placed to achieve such a goal. The MOSE project (MOdeling ESO Sites), co-funded by ESO, aimed at proving the feasibility of the forecast of (1) all the classical atmospheric parameters (such as temperature, wind speed and direction, relative humidity) and (2) the optical turbulence i.e. the CN 2 profiles and all the main integrated astro-climatic parameters derived from the CN 2 (the seeing, the isoplanatic angle, the wavefront coherence time) above the two ESO sites of Cerro Paranal and Cerro Armazones. The proposed technique is based on the use of a non-hydrostatic atmospheric meso-scale model and a dedicated code for the optical turbulence. The final goal of the project aimed at implementing an automatic system for the operational forecasts of the aforementioned parameters to support the astronomical observations above the two sites. MOSE Phase A and B have been completed and a set of dedicated papers have been published on the topic. Model performances have been extensively quantified with several dedicated figures of merit and we proved that our tool is able to provide reliable forecasts of optical turbulence and atmospheric parameters with very satisfactory score of success. This should guarantee us to make a step ahead in the framework of the Service Mode of new generation telescopes. A conceptual design as well as an operational plan of the automatic system has been submitted to ESO as integral part of the feasibility study. We completed a negotiation with

  11. Thermal Hydraulic Assessment for Loss of SDCS Event During the Outage of CANDU Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jonghyun [Gnest, Inc. Taejon (Korea, Republic of); Lee, Kwangho; Oh, Haechol; Jun, Hwangyong [KEPRI, Taejon (Korea, Republic of)

    2006-07-01

    During the outage(overhaul) of the nuclear power plant, there are several operating states other than the full power state, that is 'Hot-Zero Power', 'Depressurized-Cooldown', and 'Partially Drained'. Until now safety assessment has not been done much for this operating state of CANDU type reactor worldwide. For the accuracy and confidence of PSA for the CANDU outage, the safety analysis is necessary. At the first stage, we analyzed the thermal hydraulic characteristics and safety of the postulated event of loss of shutdown cooling system (SDCS) during the partially drained state which is the longest one in the middle of outage period. As an analysis tool, this study uses the best estimate thermal hydraulic code, RELAP5/CANDU which was modified according to the CANDU specific characteristics and based on RELAP5.Mod3.

  12. Study on optimization of normal plant outage work plan for nuclear power plants

    International Nuclear Information System (INIS)

    Aoki, Takayuki; Kodama, Noriko; Takase, Kentaro; Miya, Kenzo

    2011-01-01

    This paper discusses maintenance optimization in maintenance implementation stage following maintenance planning stage in nuclear power plants and proposes a methodology to get an optimum maintenance work plan. As a result of consideration, the followings were obtained. (1) The quantitative evaluation methodology for optimizing maintenance work plan in nuclear power plants was developed. (2) Utilizing the above methodology, a simulation analysis of maintenance work planning for BWR's PLR and RHR systems in a normal plant outage was performed. Maintenance cost calculation in several cases was carried out on the condition of smoothening man loading over the plant outage schedule as much as possible. (3) As a result of the simulation, the economical work plans having a flat man loading over the plant outage schedule were obtained. (author)

  13. Outage planning in nuclear power plants. A paradigm shift from an external towards an integrated project planning tool

    Energy Technology Data Exchange (ETDEWEB)

    Rosemann, Andreas [Gesellschaft fuer integrierte Systemplanung (GiS) mbH, Weinheim (Germany)

    2014-05-15

    In nuclear power plants it is common to carry out the technical planning of the annual outage work orders in an Enterprise Application Management (EAM) system and to schedule the outage tasks in a project planning tool. The reason for this is historical: Former EAM systems did not (or just to some extend) offer the necessary functionalities to realise the scheduling of the outage; graphical support for the planning was not provided at all. Consequently, scheduling the annual outage was performed in a separate planning tool. Modern Enterprise Application Management (EAM) software builds on established project planning tools with respect to the functionalities and timing of work orders. As a standard they provide editable charts as well as a lot of functionalities which are required for scheduling the annual outage. The functional gap between the demanded planning functionalities and the functionalities provided by the EAM system has been significantly reduced. Depending on the deployed software itself it is possible to extend the EAM system with little effort (in comparison to the promising advantages) so that external project timing planning tools are not required any more. By shifting towards an integrated planning tool, efficiency in planning an outage as well as the quality of communication of the current planning status increases. Furthermore, the basis of information for work orders by the control room staff and therefore safety can be enhanced. (orig.)

  14. Outage planning in nuclear power plants. A paradigm shift from an external towards an integrated project planning tool

    International Nuclear Information System (INIS)

    Rosemann, Andreas

    2014-01-01

    In nuclear power plants it is common to carry out the technical planning of the annual outage work orders in an Enterprise Application Management (EAM) system and to schedule the outage tasks in a project planning tool. The reason for this is historical: Former EAM systems did not (or just to some extend) offer the necessary functionalities to realise the scheduling of the outage; graphical support for the planning was not provided at all. Consequently, scheduling the annual outage was performed in a separate planning tool. Modern Enterprise Application Management (EAM) software builds on established project planning tools with respect to the functionalities and timing of work orders. As a standard they provide editable charts as well as a lot of functionalities which are required for scheduling the annual outage. The functional gap between the demanded planning functionalities and the functionalities provided by the EAM system has been significantly reduced. Depending on the deployed software itself it is possible to extend the EAM system with little effort (in comparison to the promising advantages) so that external project timing planning tools are not required any more. By shifting towards an integrated planning tool, efficiency in planning an outage as well as the quality of communication of the current planning status increases. Furthermore, the basis of information for work orders by the control room staff and therefore safety can be enhanced. (orig.)

  15. Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System

    Directory of Open Access Journals (Sweden)

    Luca Massidda

    2017-12-01

    Full Text Available The balance between production and consumption in a smart grid with high penetration of renewable sources and in the presence of energy storage systems benefits from an accurate load prediction. A general approach to load forecasting is not possible because of the additional complication due to the increasing presence of distributed and usually unmeasured photovoltaic production. Various methods are proposed in the literature that can be classified into two classes: those that predict by separating the portion of load due to consumption habits from the part of production due to local weather conditions, and those that attempt to predict the load as a whole. The characteristic that should lead to a preference for one approach over another is obviously the percentage of penetration of distributed production. The study site discussed in this document is the grid of Borkum, an island located in the North Sea. The advantages in terms of reducing forecasting errors for the electrical load, which can be obtained by using weather information, are explained. In particular, when comparing the results of different approaches gradually introducing weather forecasts, it is clear that the correct functional dependency of production has to be taken into account in order to obtain maximum yield from the available information. Where possible, this approach can significantly improve the quality of the forecasts, which in turn can improve the balance of a network—especially if energy storage systems are in place.

  16. Development and testing of an innovative short-term large wind ramp forecasting system

    Energy Technology Data Exchange (ETDEWEB)

    Zack, J.W. [AWS Truepower LLC, Troy, NY (United States)

    2010-07-01

    This PowerPoint presentation discussed a ramp forecasting tool designed for use in a region of Texas with a high wind-generating capacity. Large system-wide ramps frequently occur in the region, and curtailments are common due to transmission constraints. The average hourly load of the power system is 32,101 MW. Wind power capacity in the region is 9382 MW. However, actual production rarely exceeds 6500 MW due to the curtailments. The short-term ramp forecasting tool was designed to aid in grid management decisions for the 0-6 hour ahead period as well as to address issues related to wind farm time series data and the lack of situational awareness information. The tool provided rapid updates for grid point wind analysis with feature detection and tracking algorithms and a rapid update cycle model. The tool also featured a suite of web-based applications that included deterministic ramp even forecasts, power production time series forecasts, and situational awareness products that are updated every 15 minutes. A performance evaluation study of the tool was provided. tabs., figs.

  17. A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

    Directory of Open Access Journals (Sweden)

    Laila A. Puntel

    2018-04-01

    Full Text Available Historically crop models have been used to evaluate crop yield responses to nitrogen (N rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1 evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages; (2 determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3 quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77 using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81. Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively. At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR in 62% of the cases examined (n = 31 with an average error range of ±38 kg N ha−1 (22% of the average N rate. Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather

  18. A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

    Science.gov (United States)

    Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Thorburn, Peter J.; Castellano, Michael J.; Moore, Kenneth J.; VanLoocke, Andrew; Heaton, Emily A.; Archontoulis, Sotirios V.

    2018-01-01

    Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years

  19. A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate.

    Science.gov (United States)

    Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Thorburn, Peter J; Castellano, Michael J; Moore, Kenneth J; VanLoocke, Andrew; Heaton, Emily A; Archontoulis, Sotirios V

    2018-01-01

    Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time ( R 2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity ( R 2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined ( n = 31) with an average error range of ±38 kg N ha -1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather

  20. Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona

    International Nuclear Information System (INIS)

    Maliszewski, Paul J.; Larson, Elisabeth K.; Perrings, Charles

    2012-01-01

    The sustainability of power infrastructures depends on their reliability. One test of the reliability of an infrastructure is its ability to function reliably in extreme environmental conditions. Effective planning for reliable electrical systems requires knowledge of unscheduled outage sources, including environmental and social factors. Despite many studies on the vulnerability of infrastructure systems, the effect of interacting environmental and infrastructural conditions on the reliability of urban residential power distribution remains an understudied problem. We model electric interruptions using outage data between the years of 2002 and 2005 across Phoenix, Arizona. Consistent with perceptions of increased exposure, overhead power lines positively correlate with unscheduled outages indicating underground cables are more resistant to failure. In the presence of overhead lines, the interaction between birds and vegetation as well as proximity to nearest desert areas and lakes are positive driving factors explaining much of the variation in unscheduled outages. Closeness to the nearest arterial road and the interaction between housing square footage and temperature are also significantly positive. A spatial error model was found to provide the best fit to the data. Resultant findings are useful for understanding and improving electrical infrastructure reliability. - Highlights: ► Unscheduled outages were related to interacting environmental and infrastructural conditions. ► Underground feeders are more resistant to failure. ► In the presence of overhead lines, birds, vegetation, and proximity to desert areas are positive driving factors. ► Proximity to arterial roads and a proxy for energy demand were significantly positive. ► Outages were most spatially dependent up to around 350 m.

  1. Control Room Tasks During Refueling in Ringhals 1 Nuclear Power Plant - Operator performance during refuelling outages

    International Nuclear Information System (INIS)

    Stroebeck, Einar; Olausson, Jesper; Van Gemst, Paul

    1998-01-01

    This paper discusses the performance and tasks of the operators in the control room during refuelling outages. Analyses of such events have, during the last years, shown that the risk for nuclear accidents is not negligible compared with the risk at higher reactor power levels. Some experts have the opinion that, due to mistakes during an outage, the risk for such accidents during the outage and other accidents later on during power operation is higher than in other plant situations. The high risk level is mainly a result of errors at maintenance actions and supervision of lining up of safety systems. Most of the control rooms in existing NPPs were designed more than 10 years ago. At that time the activities and the tasks for the operators were not very well understood. Procedures for refuelling and other activities during the outages were not described very well. Often the utility organisation for refuelling outages was not established at the start of the control room design. Experience from operation during many years has shown that the performance of operators can be improved in existing plant, and thus risks be reduced, by upgrading the control room. These issues have been studied as a part of the modernisation project for Ringhals 1, an ABB Atom BWR owned by Vattenfall AB in Sweden. The paper will describe the working model for upgrading the control room and important issues to take care of with respect to refuelling outages. The identified issues will be used as the input for improving control room philosophy and the individual technical systems. (authors)

  2. An advanced microcosting system for forecasting and managing radiology expenses

    International Nuclear Information System (INIS)

    Arenson, R.; Viale, R.; VanDerVoorde, F.

    1985-01-01

    The new prospective payment system encourages hospital cost containment and necessitates understanding actual cost for radiology procedures. The automated microcosting system described in this paper, utilizing data from the Radiology Information Management System, hospital expense reports, and payroll management reports, calculates an accurate unit cost for each procedure type. This data is very useful for cost control, enhancement of department efficiency, and planning

  3. Approach to shortening duration of nuclear plant refueling outage

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Yoshiharu; Nakanishi, Tooru [Mitsubishi Heavy Industries Ltd., Kobe (Japan). Kobe Shipyard and Machinery Works; Yoshihara, Seiichi; Kanbara, Masayuki; Yamanaka, Misao; Shimizu, Takeshi

    1998-07-01

    This paper summarizes the mission role of the MHI in-house project team for a shorter outage duration for PWR plants operating in Japan and its results. The major tasks of project team are benchmarking to develop outage performance goals, and develop recommendation packages for outage enhancement covering field procedures and tooling betterment. An optimization study for maintenance tasks was also carried out. This paper highlights the results of efforts the activities of the project team. (author)

  4. Forecast generation for real-time control of urban drainage systems using greybox modelling and radar rainfall

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2012-01-01

    We present stochastic flow forecasts to be used in a real-time control setup for urban drainage systems. The forecasts are generated using greybox models with rain gauge and radar rainfall observations as input. Predictions are evaluated as intervals rather than just mean values. We obtain...

  5. Radiological protection for the ANGRA 1 steam generator replacement outage

    International Nuclear Information System (INIS)

    Oliveira, Magno Jose de; Amaral, Marcos Antonio do; Minelli, Edson; Ferreira, William Alves

    2009-01-01

    The Angra 1 Nuclear Power Plant (NPP) is a Westinghouse two-loop plant with net output before its 1P16 Outage of 632 MWe, with the Old Steam Generators (OSG) type model D3, which were replaced by two new Steam Generators with feed water-ring system. Localized in Angra dos Reis, Rio de Janeiro - Brazil, Angra 1 started in commercial operation in 1985 and, from the beginning problems related to corrosion have appeared in the Inconel 600 alloy of the tubes. The corrosion problems indicated the necessity for a strong control of the tubes thicknesses and, after a time, the ELETRONUCLEAR decided to replace the OSG. In 2009, ELETRONUCLEAR initiated in January 24, the actions for the Steam Generators Replacement - SGR. During the SGR process, several controls were applied in field, which made possible to have no radiological accidents, no dose limits exceeded, and permitted to achieve a very good result in terms of Collective Dose. This paper describes the radiological controls applied for the Angra 1 Steam Generator Replacement Outage, the radiological protection team sizing and distribution and the obtained results. (author)

  6. Evaluation of allowed outage time using PRA results

    International Nuclear Information System (INIS)

    Johanson, G.

    1985-01-01

    In a probabilistic risk assessment (PRA) different measures of risk importance can be established. These measures can be used as a basis for further evaluation and determination of allowed outage time for specific components, within safety systems of a nuclear power plant. In order to optimize the allowed outage time (AOT) stipulated in the plant's Technical Specification it is necessary to create a methodology which could incorporate existing PRA data into a quantitative extrapolation. In order to evaluate the plant risk status due to AOT in a quantitative manner, the risk achievement worth is utilized. Risk achievement worth is defined as follows: to measure the worth of a feature, in achieving the present risk, one approach is to remove the feature and then determine how much the risk has increased. Thus, the risk achievement worth is formally defined to be the increase in risk if the feature were assumed not be there or to be failed. Another parameter of interest for this analysis is the shutdown risk increase. The shutdown risk achievement worth must be incorporated into the accident sequence risk achievement worth to arrive at an optimal set of plant specific AOTs

  7. APPROACH TO ASSESSING THE PREPAREDNESS OF HOSPITALS TO POWER OUTAGES

    Directory of Open Access Journals (Sweden)

    Lenka BREHOVSKÁ

    2017-06-01

    Full Text Available Within the secondary impacts of electricity blackouts, it is necessary to pay attention to facilities providing medical care for the population, namely the hospitals. Hospitals represent a key position in the provision of health care also in times of crisis. These facilities must provide constant care; it is therefore essential that the preparedness of such facilities is kept at a high level. The basic aim of this article is to analyse the preparedness of hospitals to power outages (power failures, blackouts within a pilot study. On that basis, a SWOT analysis is used to determine strengths and weaknesses of the system of preparedness of hospitals to power outages and solutions for better security of hospitals are defined. The sample investigated consists of four hospitals founded by the Regional Authority (hospitals Nos. 1-4 and one hospital founded by the Ministry of Health of the Czech Republic (hospital No. 5. The results of the study shows that most weaknesses of the preparedness of hospitals are represented by inadequately addressed reserves of fuel for the main backup power supply, poor knowledge of employees who are insufficiently retrained, and old backup power supplies (even 35 years in some cases.

  8. Predicting the Heat Consumption in District Heating Systems using Meteorological Forecasts

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg, orlov 31.07.2008; Madsen, Henrik

    that meteorological forecasts are available on-line. Such a service has recently been introduced by the Danish Meteorological Institute. However, actual meteorological forecasts has not been available for the work described here. Assuming the climate to be known the mean absolute relative prediction error for 72 hour......Methods for on-line prediction of heat consumption in district heating systems hour by hour for horizons up to 72 hours are considered in this report. Data from the district heating system Vestegnens Kraftvarmeselskab I/S is used in the investigation. During the development it has been assumed......, this is somewhat contrary to practice. The work presented is a demonstration of the value of the so called gray box approach where theoretical knowledge about the system under consideration is combined with information from measurements performed on the system in order to obtain a mathematical description...

  9. Maintaining a Local Data Integration System in Support of Weather Forecast Operations

    Science.gov (United States)

    Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

    2010-01-01

    Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LDIS) as part of their forecast and warning operations. Each has benefited from 3-dimensional analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive and complete understanding of evolving fine-scale weather features. Recent efforts have been undertaken to update the LDIS through the formal tasking process of NASA's Applied Meteorology Unit. The goals include upgrading LDIS with the latest version of ADAS, incorporating new sources of observational data, and making adjustments to shell scripts written to govern the system. A series of scripts run a complete modeling system consisting of the preprocessing step, the main model integration, and the post-processing step. The preprocessing step prepares the terrain, surface characteristics data sets, and the objective analysis for model initialization. Data ingested through ADAS include (but are not limited to) Level II Weather Surveillance Radar- 1988 Doppler (WSR-88D) data from six Florida radars, Geostationary Operational Environmental Satellites (GOES) visible and infrared satellite imagery, surface and upper air observations throughout Florida from NOAA's Earth System Research Laboratory/Global Systems Division

  10. Rate of recovery from perturbations as a means to forecast future stability of living systems.

    Science.gov (United States)

    Ghadami, Amin; Gourgou, Eleni; Epureanu, Bogdan I

    2018-06-18

    Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system's response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds.

  11. Reply to "Comment on 'Nonparametric forecasting of low-dimensional dynamical systems' ".

    Science.gov (United States)

    Berry, Tyrus; Giannakis, Dimitrios; Harlim, John

    2016-03-01

    In this Reply we provide additional results which allow a better comparison of the diffusion forecast and the "past-noise" forecasting (PNF) approach for the El Niño index. We remark on some qualitative differences between the diffusion forecast and PNF, and we suggest an alternative use of the diffusion forecast for the purposes of forecasting the probabilities of extreme events.

  12. Bingham Pump Outage Pits: Environmental information document

    International Nuclear Information System (INIS)

    Pekkala, R.O.; Jewell, C.E.; Holmes, W.G.; Marine, I.W.

    1987-03-01

    Seven waste sites known as the Bingham Pump Outage Pits located in areas of the Savannah River Plant (SRP) received solid waste containing an estimated 4 Ci of low-level radioactivity in 1957-1958. These sites were subsequently backfilled and have been inactive since that time. Most of the radioactivity at the Bingham Pump Outage Pits has been eliminated by radioactive decay. A total of approximately 1 Ci of activity (primarily 137 Cs and 90 Sr) is estimated to remain at the seven sites. The closure options considered for the Bingham Pump Outage Pits are waste removal and closure, no waste removal and closure, and no action. The predominant pathways for human exposure to chemical and/or radioactive constituents are through surface, subsurface, and atmospheric transport. Modeling calculations were made to determine the risks to human population via these general pathways for the three postulated closure options. An ecological assessment was conducted to predict the environmental impacts on aquatic and terrestrial biota. The relative costs for each of the closure options were estimated. Evaluation indicates that the relative human health risks for all closure options are small. The greatest public risk would occur after the waste site was released to unrestricted public use (assumed to occur in Year 2085) via the groundwater pathway to a well. The cost estimates show that the waste removal and closure option is the most expensive (89.6 million dollars). The cost of the no waste removal and the no action options is $800,000. 35 refs., 26 figs., 47 tabs

  13. FORECASTING AND ANALYSIS OF TRENDS IN AREA OF QUALITY MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Aleksandar Vujović

    2009-12-01

    Full Text Available This research presents chronology and trends in area of quality management system through nonconformities. The aim of the work is to forecast possible scenario to foresee activities for future period and time what will point out on critical indicators and on possible measures for improvement. Furthermore, research identifies advantages, disadvantages and possibilities, especially for production and service sectors. The work presents long-term research on quality management system and experience and knowledge that are obtained based on real indicators.

  14. An Automated Weather Research and Forecasting (WRF)-Based Nowcasting System: Software Description

    Science.gov (United States)

    2013-10-01

    14. ABSTRACT A Web service /Web interface software package has been engineered to address the need for an automated means to run the Weather Research...An Automated Weather Research and Forecasting (WRF)- Based Nowcasting System: Software Description by Stephen F. Kirby, Brian P. Reen, and...Based Nowcasting System: Software Description Stephen F. Kirby, Brian P. Reen, and Robert E. Dumais Jr. Computational and Information Sciences

  15. Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

    Science.gov (United States)

    Colarco, Peter; da Silva, Arlindo; Aquila, Valentina; Bian, Huisheng; Buchard, Virginie; Castellanos, Patricia; Darmenov, Anton; Follette-Cook, Melanie; Govindaraju, Ravi; Keller, Christoph; hide

    2017-01-01

    GEOS-5 is the Goddard Earth Observing System model. GEOS-5 is maintained by the NASA Global Modeling and Assimilation Office. Core development is within GMAO,Goddard Atmospheric Chemistry and Dynamics Laboratory, and with external partners. Primary GEOS-5 functions: Earth system model for studying climate variability and change, provide research quality reanalyses for supporting NASA instrument teams and scientific community, provide near-real time forecasts of meteorology,aerosols, and other atmospheric constituents to support NASA airborne campaigns.

  16. Unit availability not affected by extending outage cycles

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D.J.

    2003-03-01

    To improve their economic dispatch position, more and more plant owners are extending the intervals between major outages for boilers from one year to 18-24 months and for steam turbine up to 12 years. In many instances, extended outage cycles have resulted in no loss in availability or increases in forced outages. The article discusses outage scheduling at Tucson Electric Power's Springville coal-fired plant, the Panther Creek Energy Facility in Pennsylvania, and at Tennessee Valley Authority's coal-fired power plants. 1 fig.

  17. Outage Risk Assessment and Management (ORAM) technology to improve outage safety and economics

    International Nuclear Information System (INIS)

    Kalra, S.P.

    2004-01-01

    The Electric Power Research Institute (EPRI) has undertaken an aggressive program, called ORAM (Outage Risk Assessment and Management), to provide utilities with tools and technology to assist in managing risk during the planning and conduct of outages. The ORAM program consists of the following 6 steps: i) Perform utility surveys and visits on shutdown risk management needs, ii) Perform probabilistic shutdown safety assessments (PSSAs) to identify generic insights that can be incorporated into risk management guidelines and identify selected areas for the development of contingency actions, iii) Develop risk management guidelines (RMG's) that provide a systematic approach to the planning and conduct of outages from a safety perspective. Incorporate insights from the shutdown safety assessments and other operating experience into the RMG's. iv) Develop selected contingency actions including a thermalhydraulic tool kit to address higher risk time periods and activities identified in the shutdown safety assessments, v) Develop computer software that integrates all of the above capability into an easy to use tool for effective shutdown operation management for utilities, vi) Provide assistance in the transfer of this technology and the application of these tools. This paper briefly describes the technical approach and tools developed under EPRI's ORAM program and its applications for improving outage safety and economics. (author)

  18. Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

    Science.gov (United States)

    Singh, Sanjeev Kumar; Prasad, V. S.

    2018-02-01

    This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

  19. Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation

    Directory of Open Access Journals (Sweden)

    Dirk Cannon

    2017-06-01

    Full Text Available State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the resolved uncertainty associated with estimating the future large-scale atmospheric state is larger than the unresolved uncertainty associated with estimating the system-wide wind power response to a given large-scale state.The bounds of skilful ensemble forecast range are quantified for three leading global forecast systems. The power system of Great Britain (GB is used as an example because independent verifying data is available from National Grid. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time is found to be 6–8 days. The lower bound is found to be 1.4–2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5–5.5 days. The upper bound on this forecast range can only be extended by improving the global forecast system (outside the control of most users or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days.

  20. Information system of forecasting infrastructure development in tourism

    Directory of Open Access Journals (Sweden)

    Gats Bogdan

    2013-01-01

    Full Text Available Manuscript is devoted to the development of information system for tourist objects infrastructure growth and its practical implementation in form of information system using methods of fuzzy logic, theory of fractals and diffusion. Developed technology allows compute attractiveness of Carpathian region, structure, dynamics of the main tourist settlements Vorochta and Slavske, prospective territories for tourist business, growing strategies for region.

  1. Anvil Forecast Tool in the Advanced Weather Interactive Processing System (AWIPS)

    Science.gov (United States)

    Barrett, Joe H., III; Hood, Doris

    2009-01-01

    Launch Weather Officers (LWOs) from the 45th Weather Squadron (45 WS) and forecasters from the National Weather Service (NWS) Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violating the Lightning Launch Commit Criteria (LLCC) (Krider et al. 2006; Space Shuttle Flight Rules (FR), NASA/JSC 2004)). As a result, the Applied Meteorology Unit (AMU) developed a tool that creates an anvil threat corridor graphic that can be overlaid on satellite imagery using the Meteorological Interactive Data Display System (MIDDS, Short and Wheeler, 2002). The tool helps forecasters estimate the locations of thunderstorm anvils at one, two, and three hours into the future. It has been used extensively in launch and landing operations by both the 45 WS and SMG. The Advanced Weather Interactive Processing System (AWIPS) is now used along with MIDDS for weather analysis and display at SMG. In Phase I of this task, SMG tasked the AMU to transition the tool from MIDDS to AWIPS (Barrett et aI., 2007). For Phase II, SMG requested the AMU make the Anvil Forecast Tool in AWIPS more configurable by creating the capability to read model gridded data from user-defined model files instead of hard-coded files. An NWS local AWIPS application called AGRID was used to accomplish this. In addition, SMG needed to be able to define the pressure levels for the model data, instead of hard-coding the bottom level as 300 mb and the top level as 150 mb. This paper describes the initial development of the Anvil Forecast Tool for MIDDS, followed by the migration of the tool to AWIPS in Phase I. It then gives a detailed presentation of the Phase II improvements to the AWIPS tool.

  2. Forecasting E > 50-MeV Proton Events with the Proton Prediction System (PPS)

    Science.gov (United States)

    Kahler, S. W.; White, S. M.; Ling, A. G.

    2017-12-01

    Forecasting solar energetic (E > 10 MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (> 50 MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E > 50-MeV proton events > 1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986 to 2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all > M5 solar X-ray flares; (2) all > 200 sfu 8800-MHz bursts with associated > M5 flares; (3) all > 500 sfu 8800-MHz bursts; and (4) all > 5000 sfu 8800-MHz bursts. For X-ray flare inputs the forecasted event peak intensities and fluences are compared with observed values. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude.

  3. Electricity demand load forecasting of the Hellenic power system using an ARMA model

    Energy Technology Data Exchange (ETDEWEB)

    Pappas, S.Sp. [ASPETE - School of Pedagogical and Technological Education Department of Electrical Engineering Educators N. Heraklion, 141 21 Athens (Greece); Ekonomou, L.; Chatzarakis, G.E.; Skafidas, P.D. [ASPETE-School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece); Karampelas, P. [Hellenic American University, IT Department, 12 Kaplanon Str., 106 80 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24 100 Kalamata (Greece); Katsikas, S.K. [University of Piraeus, Department of Technology Education and Digital Systems, 150 Androutsou St., 18 532 Piraeus (Greece)

    2010-03-15

    Effective modeling and forecasting requires the efficient use of the information contained in the available data so that essential data properties can be extracted and projected into the future. As far as electricity demand load forecasting is concerned time series analysis has the advantage of being statistically adaptive to data characteristics compared to econometric methods which quite often are subject to errors and uncertainties in model specification and knowledge of causal variables. This paper presents a new method for electricity demand load forecasting using the multi-model partitioning theory and compares its performance with three other well established time series analysis techniques namely Corrected Akaike Information Criterion (AICC), Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The suitability of the proposed method is illustrated through an application to actual electricity demand load of the Hellenic power system, proving the reliability and the effectiveness of the method and making clear its usefulness in the studies that concern electricity consumption and electricity prices forecasts. (author)

  4. Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

    Science.gov (United States)

    Yi, J.; Choi, C.

    2014-12-01

    Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

  5. Wet snow hazard for power lines: a forecast and alert system applied in Italy

    Directory of Open Access Journals (Sweden)

    P. Bonelli

    2011-09-01

    Full Text Available Wet snow icing accretion on power lines is a real problem in Italy, causing failures on high and medium voltage power supplies during the cold season. The phenomenon is a process in which many large and local scale variables contribute in a complex way and not completely understood. A numerical weather forecast can be used to select areas where wet snow accretion has an high probability of occurring, but a specific accretion model must also be used to estimate the load of an ice sleeve and its hazard. All the information must be carefully selected and shown to the electric grid operator in order to warn him promptly.

    The authors describe a prototype of forecast and alert system, WOLF (Wet snow Overload aLert and Forecast, developed and applied in Italy. The prototype elaborates the output of a numerical weather prediction model, as temperature, precipitation, wind intensity and direction, to determine the areas of potential risk for the power lines. Then an accretion model computes the ice sleeves' load for different conductor diameters. The highest values are selected and displayed on a WEB-GIS application principally devoted to the electric operator, but also to more expert users. Some experimental field campaigns have been conducted to better parameterize the accretion model. Comparisons between real accidents and forecasted icing conditions are presented and discussed.

  6. Wet snow hazard for power lines: a forecast and alert system applied in Italy

    Science.gov (United States)

    Bonelli, P.; Lacavalla, M.; Marcacci, P.; Mariani, G.; Stella, G.

    2011-09-01

    Wet snow icing accretion on power lines is a real problem in Italy, causing failures on high and medium voltage power supplies during the cold season. The phenomenon is a process in which many large and local scale variables contribute in a complex way and not completely understood. A numerical weather forecast can be used to select areas where wet snow accretion has an high probability of occurring, but a specific accretion model must also be used to estimate the load of an ice sleeve and its hazard. All the information must be carefully selected and shown to the electric grid operator in order to warn him promptly. The authors describe a prototype of forecast and alert system, WOLF (Wet snow Overload aLert and Forecast), developed and applied in Italy. The prototype elaborates the output of a numerical weather prediction model, as temperature, precipitation, wind intensity and direction, to determine the areas of potential risk for the power lines. Then an accretion model computes the ice sleeves' load for different conductor diameters. The highest values are selected and displayed on a WEB-GIS application principally devoted to the electric operator, but also to more expert users. Some experimental field campaigns have been conducted to better parameterize the accretion model. Comparisons between real accidents and forecasted icing conditions are presented and discussed.

  7. The Use of Fuzzy Systems for Forecasting the Hardenability of Steel

    Directory of Open Access Journals (Sweden)

    Sitek W.

    2016-06-01

    Full Text Available The goal of the research carried out was to develop the fuzzy systems, allowing the determination of the Jominy hardenability curve based on the chemical composition of structural steels for quenching and tempering. Fuzzy system was created to calculate hardness of the steel, based on the alloying elements concentrations, and to forecast the hardenability curves. This was done based on information from the PN-EN 10083-3: 2008. Examples of hardenability curves calculated for exemplar steels were presented. Results of the research confirmed that fuzzy systems are a useful tool in evaluation the effect of alloying elements on the properties of materials compared to conventional methods. It has been demonstrated the practical usefulness of the developed models which allows forecasting the steels’ Jominy hardenability curve.

  8. Innovative Development and Forecast of BeiDou System

    Directory of Open Access Journals (Sweden)

    TAN Shusen

    2017-10-01

    Full Text Available Due to the strong demand for satellite applications and rapid development of new space technology,the cross-integration of space-based radio systems has become a trend.BeiDou system started from two satellites to build China's first generation satellite navigation and positioning system with the features of fast location reporting(RDSSand short message communication(MSSservice.Then BeiDou technology frame combined with RNSS continuous navigation and RDSS location report,was constructed in eight years,and the coverage in Asia-Pacific was completed.Through effective satellite radio frequency compatible design and international coordination,BeiDou system is the first radio satellite system which includes RNSS,RDSS,MSS three major services,approved by International Telecommunication Union(ITUin the world.This paper expounds the development process,technical frame,main features and prospect of BeiDou system with three major services and four key functions,in the concept of innovation and transcendence.

  9. Forecast analysis of the electricity supply-demand balance in France for summer 2013

    International Nuclear Information System (INIS)

    2013-05-01

    Under normal meteorological conditions, and notwithstanding localized risks associated with the vulnerability of certain regions, the forecast outlook for the electricity supply-demand balance in continental France shows no particular risk for the entire summer 2013 period. Special vigilance is maintained in the Provence-Alpes-Cote d'Azur region, given the risk of forest fires and potential outages affecting the dual 400 kV link from Toulon. This assessment is based on the assumption that forecast demand for summer 2013 will remain broadly stable as compared with summer 2012, given public economic indicators, but also that the forecast availability of the French generating fleet will increase by 1100 MW compared with summer 2012. This increased availability is based on information supplied by generators, and notably includes scheduled temporary outages of certain combined cycle gas turbines. Finally, growth in photovoltaic generation (3,700 MW of installed capacity currently in France) is continuing at a sustained pace, leading to a 700 MW increase in the mean availability rate for this generation technology as compared with summer 2012. Moreover, the substantial investments already made by RTE or currently in progress to develop its network (voltage support measures, Cotentin-Maine line, etc.) have had a very positive impact on the reliability of the power system. (authors)

  10. Outage Analysis and Optimization of SWIPT in Network-Coded Two-Way Relay Networks

    Directory of Open Access Journals (Sweden)

    Ruihong Jiang

    2017-01-01

    Full Text Available This paper investigates the outage performance of simultaneous wireless information and power transfer (SWIPT in network-coded two-way relay systems, where a relay first harvests energy from the signals transmitted by two sources and then uses the harvested energy to forward the received information to the two sources. We consider two transmission protocols, power splitting two-way relay (PS-TWR and time switching two-way relay (TS-TWR protocols. We present two explicit expressions for the system outage probability of the two protocols and further derive approximate expressions for them in high and low SNR cases. To explore the system performance limits, two optimization problems are formulated to minimize the system outage probability. Since the problems are nonconvex and have no known solution methods, a genetic algorithm- (GA- based algorithm is designed. Numerical and simulation results validate our theoretical analysis. It is shown that, by jointly optimizing the time assignment and SWIPT receiver parameters, a great performance gain can be achieved for both PS-TWR and TS-TWR. Moreover, the optimized PS-TWR always outperforms the optimized TS-TWR in terms of outage performance. Additionally, the effects of parameters including relay location and transmit powers are also discussed, which provide some insights for the SWIPT-enabled two-way relay networks.

  11. Outage analysis of blind cooperative diversity

    KAUST Repository

    Tourki, Kamel; Alouini, Mohamed-Slim

    2011-01-01

    Mobile users with single antennas can still take advantage of spatial diversity through cooperative space-time-encoded transmission. In this paper, we considered a scheme in which a relay chooses to cooperate only if its source-relay channel is of an acceptable quality, and we evaluate the usefulness of relaying when the source acts blindly and ignores the decision of the relays whether they may cooperate or not. In our study, we consider the regenerative relays in which the decisions to cooperate are based on a targeted end-to-end data rate R. We derived the end-to-end outage probability for a transmission rate R and a code rate ρ and look at a power allocation strategy between the source and the relays in order to minimize the end-to-end outage probability at the destination for high signal-to-noise ratio, by using the golden section search method. Performance results show that the computer simulations-based results coincide with our analytical results. Copyright © 2011 John Wiley & Sons, Ltd.

  12. Outage analysis of blind cooperative diversity

    KAUST Repository

    Tourki, Kamel

    2011-06-06

    Mobile users with single antennas can still take advantage of spatial diversity through cooperative space-time-encoded transmission. In this paper, we considered a scheme in which a relay chooses to cooperate only if its source-relay channel is of an acceptable quality, and we evaluate the usefulness of relaying when the source acts blindly and ignores the decision of the relays whether they may cooperate or not. In our study, we consider the regenerative relays in which the decisions to cooperate are based on a targeted end-to-end data rate R. We derived the end-to-end outage probability for a transmission rate R and a code rate ρ and look at a power allocation strategy between the source and the relays in order to minimize the end-to-end outage probability at the destination for high signal-to-noise ratio, by using the golden section search method. Performance results show that the computer simulations-based results coincide with our analytical results. Copyright © 2011 John Wiley & Sons, Ltd.

  13. Stock market modeling and forecasting a system adaptation approach

    CERN Document Server

    Zheng, Xiaolian

    2013-01-01

    Stock Market Modeling translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a stock market exhibits fast and slow dynamics corresponding to internal (such as company value and profitability) and external forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent.   The authors present work on both developed and developing markets ...

  14. Improvements in medium range weather forecasting system of India

    Indian Academy of Sciences (India)

    system is based on the latest Grid Statistical Interpolation (GSI) scheme and it has the provision to use most of .... ified Simplified-Arakawa Scheme (SAS) (Han and. Pan 2010). ..... Kim Y-J and Arakawa A 1995 Improvement of orographic gravity wave ... Yang F, Mitchell K, Hou Y-T, Dai Y, Deng X, Wang Z and. Liang X-Z ...

  15. Long forecast horizon to improve Real Time Control of urban drainage systems

    DEFF Research Database (Denmark)

    Courdent, Vianney Augustin Thomas; Vezzaro, Luca; Mikkelsen, Peter Steen

    2014-01-01

    Global Real Time Control (RTC) of urban drainage system is increasingly seen as cost-effective solution in order to respond to increasing performance demand (e.g. reduction of Combined Sewer Overflow, protection of sensitive areas as bathing water etc.). The Dynamic Overflow Risk Assessment (DORA......) strategy was developed to operate Urban Drainage Systems (UDS) in order to minimize the expected overflow risk by considering the water volume presently stored in the drainage network, the expected runoff volume based on a 2-hours radar forecast model and an estimated uncertainty of the runoff forecast....... However, such temporal horizon (1-2 hours) is relatively short when used for the operation of large storage facilities, which may require a few days to be emptied. This limits the performance of the optimization and control in reducing combined sewer overflow and in preparing for possible flooding. Based...

  16. Using ensemble weather forecast in a risk based real time optimization of urban drainage systems

    DEFF Research Database (Denmark)

    Courdent, Vianney Augustin Thomas; Vezzaro, Luca; Mikkelsen, Peter Steen

    2015-01-01

    Global Real Time Control (RTC) of urban drainage system is increasingly seen as cost-effective solution in order to respond to increasing performance demand (e.g. reduction of Combined Sewer Overflow, protection of sensitive areas as bathing water etc.). The Dynamic Overflow Risk Assessment (DORA......) strategy was developed to operate Urban Drainage Systems (UDS) in order to minimize the expected overflow risk by considering the water volume presently stored in the drainage network, the expected runoff volume based on a 2-hours radar forecast model and an estimated uncertainty of the runoff forecast....... However, such temporal horizon (1-2 hours) is relatively short when used for the operation of large storage facilities, which may require a few days to be emptied. This limits the performance of the optimization and control in reducing combined sewer overflow and in preparing for possible flooding. Based...

  17. Impact of forecast errors on expansion planning of power systems with a renewables target

    DEFF Research Database (Denmark)

    Pineda, Salvador; Morales González, Juan Miguel; Boomsma, Trine Krogh

    2015-01-01

    This paper analyzes the impact of production forecast errors on the expansion planning of a power system and investigates the influence of market design to facilitate the integration of renewable generation. For this purpose, we propose a programming modeling framework to determine the generation...... and transmission expansion plan that minimizes system-wide investment and operating costs, while ensuring a given share of renewable generation in the electricity supply. Unlike existing ones, this framework includes both a day-ahead and a balancing market so as to capture the impact of both production forecasts...... and the associated prediction errors. Within this framework, we consider two paradigmatic market designs that essentially differ in whether the day-ahead generation schedule and the subsequent balancing re-dispatch are co-optimized or not. The main features and results of the model set-ups are discussed using...

  18. Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

    Science.gov (United States)

    Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

    2014-12-01

    Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

  19. New tool for integration of wind power forecasting into power system operation

    DEFF Research Database (Denmark)

    Gubina, Andrej F.; Keane, Andrew; Meibom, Peter

    2009-01-01

    The paper describes the methodology that has been developed for transmission system operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling....... The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows...... for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules...

  20. Definition of Pluviometric Thresholds For A Real Time Flood Forecasting System In The Arno Watershed

    Science.gov (United States)

    Amadio, P.; Mancini, M.; Mazzetti, P.; Menduni, G.; Nativi, S.; Rabuffetti, D.; Ravazzani, G.; Rosso, R.

    The pluviometric flood forecasting thresholds are an easy method that helps river flood emergency management collecting data from limited area meteorologic model or telemetric raingauges. The thresholds represent the cumulated rainfall depth which generate critic discharge for a particular section. The thresholds were calculated for different sections of Arno river and for different antecedent moisture condition using the flood event distributed hydrologic model FEST. The model inputs were syntethic hietographs with different shape and duration. The system realibility has been verified by generating 500 year syntethic rainfall for 3 important subwatersheds of the studied area. A new technique to consider spatial variability of rainfall and soil properties effects on hydrograph has been investigated. The "Geomorphologic Weights" were so calculated. The alarm system has been implemented in a dedicated software (MIMI) that gets measured and forecast rainfall data from Autorità di Bacino and defines the state of the alert of the river sections.

  1. Improvement of availability of PWR nuclear plants through the reduction of the time required for refueling/maintenance outages

    International Nuclear Information System (INIS)

    Mayers, J.B.; Soth, L.G.

    1978-04-01

    The objective of the project, conducted by Commonwealth Research Corporation and Westinghouse Electric Corporation, is to identify improvements in procedures and equipment which will reduce the time required for refueling/maintenance outages at PWR nuclear power plants. The outage of Commonwealth Edison Zion Station Unit 1 in March through May of 1976 was evaluated to identify those items which caused delays and those work activities that offer the potential for significant improvements that could reduce the overall duration of the outage and achieve an improvement in the plant's availability for power production. Modifications in procedures have been developed and were evaluated during one or more outages in 1977. Conceptual designs have been developed for equipment modifications to the refueling system that could reduce the time required for the refueling portion of the outage. The purpose of the interim report is to describe those conceptual designs and to assess their impact upon future outages. Recommendations are included for the implementation of these equipment improvements in a continuation of this program as a demonstration of plant availability benefits that can be realized in PWR nuclear plants already in operation or under construction

  2. Braess's paradox in oscillator networks, desynchronization and power outage

    International Nuclear Information System (INIS)

    Witthaut, Dirk; Timme, Marc

    2012-01-01

    Robust synchronization is essential to ensure the stable operation of many complex networked systems such as electric power grids. Increasing energy demands and more strongly distributing power sources raise the question of where to add new connection lines to the already existing grid. Here we study how the addition of individual links impacts the emergence of synchrony in oscillator networks that model power grids on coarse scales. We reveal that adding new links may not only promote but also destroy synchrony and link this counter-intuitive phenomenon to Braess's paradox known for traffic networks. We analytically uncover its underlying mechanism in an elementary grid example, trace its origin to geometric frustration in phase oscillators, and show that it generically occurs across a wide range of systems. As an important consequence, upgrading the grid requires particular care when adding new connections because some may destabilize the synchronization of the grid—and thus induce power outages. (paper)

  3. Development of Improved Graphical Displays for an Advanced Outage Control Center, Employing Human Factors Principles for Outage Schedule Management

    Energy Technology Data Exchange (ETDEWEB)

    St Germain, Shawn Walter [Idaho National Lab. (INL), Idaho Falls, ID (United States); Farris, Ronald Keith [Idaho National Lab. (INL), Idaho Falls, ID (United States); Thomas, Kenneth David [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    The long-term viability of existing nuclear power plants in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are somewhat challenging to coordinate; therefore, finding ways to improve refueling outage performance, while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center (AOCC) project is a research and development (R&D) demonstration activity under the LWRS Program. LWRS is an R&D program that works closely with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current fleet of NPPs. As such, the LWRS Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, INL is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. The overall focus is on developing an AOCC with the following capabilities that enables plant and OCC staff to; Collaborate in real-time to address emergent issues; Effectively communicate outage status to all workers involved in the outage; Effectively communicate discovered conditions in the field to the OCC; Provide real-time work status; Provide automatic pending support notifications

  4. Development of Improved Graphical Displays for an Advanced Outage Control Center, Employing Human Factors Principles for Outage Schedule Management

    International Nuclear Information System (INIS)

    St Germain, Shawn Walter; Farris, Ronald Keith; Thomas, Kenneth David

    2015-01-01

    The long-term viability of existing nuclear power plants in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are somewhat challenging to coordinate; therefore, finding ways to improve refueling outage performance, while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center (AOCC) project is a research and development (R&D) demonstration activity under the LWRS Program. LWRS is an R&D program that works closely with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current fleet of NPPs. As such, the LWRS Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, INL is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. The overall focus is on developing an AOCC with the following capabilities that enables plant and OCC staff to; Collaborate in real-time to address emergent issues; Effectively communicate outage status to all workers involved in the outage; Effectively communicate discovered conditions in the field to the OCC; Provide real-time work status; Provide automatic pending support notifications

  5. Forest fire forecasting tool for air quality modelling systems

    International Nuclear Information System (INIS)

    San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Palacios, M.

    2015-01-01

    Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wild land fire spread and behavior are complex phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-Fire- Chem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

  6. Forest fire forecasting tool for air quality modelling systems

    Energy Technology Data Exchange (ETDEWEB)

    San Jose, R.; Perez, J.L.; Perez, L.; Gonzalez, R.M.; Pecci, J.; Palacios, M.

    2015-07-01

    Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wildland fire spread and behavior are complex Phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-FireChem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

  7. Forest fire forecasting tool for air quality modelling systems

    Energy Technology Data Exchange (ETDEWEB)

    San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Palacios, M.

    2015-07-01

    Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wild land fire spread and behavior are complex phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-Fire- Chem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

  8. Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

    Science.gov (United States)

    Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

    2009-04-01

    Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

  9. GEOS-5 Seasonal Forecast System: ENSO Prediction Skill and Bias

    Science.gov (United States)

    Borovikov, Anna; Kovach, Robin; Marshak, Jelena

    2018-01-01

    The GEOS-5 AOGCM known as S2S-1.0 has been in service from June 2012 through January 2018 (Borovikov et al. 2017). The atmospheric component of S2S-1.0 is Fortuna-2.5, the same that was used for the Modern-Era Retrospective Analysis for Research and Applications (MERRA), but with adjusted parameterization of moist processes and turbulence. The ocean component is the Modular Ocean Model version 4 (MOM4). The sea ice component is the Community Ice CodE, version 4 (CICE). The land surface model is a catchment-based hydrological model coupled to the multi-layer snow model. The AGCM uses a Cartesian grid with a 1 deg × 1.25 deg horizontal resolution and 72 hybrid vertical levels with the upper most level at 0.01 hPa. OGCM nominal resolution of the tripolar grid is 1/2 deg, with a meridional equatorial refinement to 1/4 deg. In the coupled model initialization, selected atmospheric variables are constrained with MERRA. The Goddard Earth Observing System integrated Ocean Data Assimilation System (GEOS-iODAS) is used for both ocean state and sea ice initialization. SST, T and S profiles and sea ice concentration were assimilated.

  10. An operational coupled wave-current forecasting system for the northern Adriatic Sea

    Science.gov (United States)

    Russo, A.; Coluccelli, A.; Deserti, M.; Valentini, A.; Benetazzo, A.; Carniel, S.

    2012-04-01

    Since 2005 an Adriatic implementation of the Regional Ocean Modeling System (AdriaROMS) is being producing operational short-term forecasts (72 hours) of some hydrodynamic properties (currents, sea level, temperature, salinity) of the Adriatic Sea at 2 km horizontal resolution and 20 vertical s-levels, on a daily basis. The main objective of AdriaROMS, which is managed by the Hydro-Meteo-Clima Service (SIMC) of ARPA Emilia Romagna, is to provide useful products for civil protection purposes (sea level forecasts, outputs to run other forecasting models as for saline wedge, oil spills and coastal erosion). In order to improve the forecasts in the coastal area, where most of the attention is focused, a higher resolution model (0.5 km, again with 20 vertical s-levels) has been implemented for the northern Adriatic domain. The new implementation is based on the Coupled-Ocean-Atmosphere-Wave-Sediment Transport Modeling System (COAWST)and adopts ROMS for the hydrodynamic and Simulating WAve Nearshore (SWAN) for the wave module, respectively. Air-sea fluxes are computed using forecasts produced by the COSMO-I7 operational atmospheric model. At the open boundary of the high resolution model, temperature, salinity and velocity fields are provided by AdriaROMS while the wave characteristics are provided by an operational SWAN implementation (also managed by SIMC). Main tidal components are imposed as well, derived from a tidal model. Work in progress is oriented now on the validation of model results by means of extensive comparisons with acquired hydrographic measurements (such as CTDs or XBTs from sea-truth campaigns), currents and waves acquired at observational sites (including those of SIMC, CNR-ISMAR network and its oceanographic tower, located off the Venice littoral) and satellite-derived wave-heights data. Preliminary results on the forecast waves denote how, especially during intense storms, the effect of coupling can lead to significant variations in the wave

  11. An operational wave forecasting system for the east coast of India

    Science.gov (United States)

    Sandhya, K. G.; Murty, P. L. N.; Deshmukh, Aditya N.; Balakrishnan Nair, T. M.; Shenoi, S. S. C.

    2018-03-01

    Demand for operational ocean state forecasting is increasing, owing to the ever-increasing marine activities in the context of blue economy. In the present study, an operational wave forecasting system for the east coast of India is proposed using unstructured Simulating WAves Nearshore model (UNSWAN). This modelling system uses very high resolution mesh near the Indian east coast and coarse resolution offshore, and thus avoids the necessity of nesting with a global wave model. The model is forced with European Centre for Medium-Range Weather Forecasts (ECMWF) winds and simulates wave parameters and wave spectra for the next 3 days. The spatial pictures of satellite data overlaid on simulated wave height show that the model is capable of simulating the significant wave heights and their gradients realistically. Spectral validation has been done using the available data to prove the reliability of the model. To further evaluate the model performance, the wave forecast for the entire year 2014 is evaluated against buoy measurements over the region at 4 waverider buoy locations. Seasonal analysis of significant wave height (Hs) at the four locations showed that the correlation between the modelled and observed was the highest (in the range 0.78-0.96) during the post-monsoon season. The variability of Hs was also the highest during this season at all locations. The error statistics showed clear seasonal and geographical location dependence. The root mean square error at Visakhapatnam was the same (0.25) for all seasons, but it was the smallest for pre-monsoon season (0.12 m and 0.17 m) for Puducherry and Gopalpur. The wind sea component showed higher variability compared to the corresponding swell component in all locations and for all seasons. The variability was picked by the model to a reasonable level in most of the cases. The results of statistical analysis show that the modelling system is suitable for use in the operational scenario.

  12. A Two-Dimensional Gridded Solar Forecasting System using Situation-Dependent Blending of Multiple Weather Models

    Science.gov (United States)

    Lu, S.; Hwang, Y.; Shao, X.; Hamann, H.

    2015-12-01

    Previously, we reported the application of a "weather situation" dependent multi-model blending approach to improve the forecast accuracy of solar irradiance and other atmospheric parameters. The approach uses machine-learning techniques to classify "weather situations" by a set of atmospheric parameters. The "weather situation" classification is location-dependent and each "weather situation" has characteristic forecast errors from a set of individual input numerical weather prediction (NWP) models. The input models are thus corrected or combined differently for different "weather situations" to minimize the overall forecast error. While the original implementation of the model-blending is applicable to only point-like locations having historical data of both measurements and forecasts, here we extend the approach to provide two-dimensional (2D) gridded forecasts. An experimental 2D forecasting system has been set up to provide gridded forecasts of solar irradiance (global horizontal irradiance), temperature, wind speed, and humidity for the contiguous United States (CONUS). Validation results show around 30% enhancement of 0 to 48 hour ahead solar irradiance forecast accuracy compared to the best input NWP model. The forecasting system may be leveraged by other site- or region-specific solar energy forecast products. To enable the 2D forecasting system, historical solar irradiance measurements from around 1,600 selected sites of the remote automated weather stations (RAWS) network have been employed. The CONUS was divided into smaller sub-regions, each containing a group of 10 to 20 RAWS sites. A group of sites, as classified by statistical analysis, have similar "weather patterns", i.e. the NWPs have similar "weather situation" dependent forecast errors for all sites in a group. The model-blending trained by the historical data from a group of sites is then applied for all locations in the corresponding sub-region. We discuss some key techniques developed for

  13. Evaluation of the Planned Outage Durations in EU-APR

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Byung Joon; Lee, Keun Sung [KHNP CRI, Daejeon (Korea, Republic of)

    2016-10-15

    EU-APR has been designed to comply with European Utility Requirements (EUR) and nuclear design requirements of the European countries. And it is modified and improved from its original design of APR1400. The whole duration varies depending on items for additional process. Refueling and regular maintenance outage is comprised of basic processes and Main turbine-generator outage includes dismantling inspection of main generator and high pressure turbine as a critical path in addition to basic processes. In-Service Inspection Outage includes Automatic ultrasonic inspection on the upper side/lower side of a nuclear reactor as a critical path in addition to basic processes. The planned outage durations of EU-APR are optimized according to the above results. And they are complied with EUR Requirement (EUR 2.2.7.2.2 B), respectively. In addition, outage duration can be reduced with improved operating technology and more maintenance friendly environment including betterment of filling, drain and ventilation.

  14. Evaluation of the Planned Outage Durations in EU-APR

    International Nuclear Information System (INIS)

    Jung, Byung Joon; Lee, Keun Sung

    2016-01-01

    EU-APR has been designed to comply with European Utility Requirements (EUR) and nuclear design requirements of the European countries. And it is modified and improved from its original design of APR1400. The whole duration varies depending on items for additional process. Refueling and regular maintenance outage is comprised of basic processes and Main turbine-generator outage includes dismantling inspection of main generator and high pressure turbine as a critical path in addition to basic processes. In-Service Inspection Outage includes Automatic ultrasonic inspection on the upper side/lower side of a nuclear reactor as a critical path in addition to basic processes. The planned outage durations of EU-APR are optimized according to the above results. And they are complied with EUR Requirement (EUR 2.2.7.2.2 B), respectively. In addition, outage duration can be reduced with improved operating technology and more maintenance friendly environment including betterment of filling, drain and ventilation

  15. Analysis of scrams and forced outages at boiling water reactors

    International Nuclear Information System (INIS)

    Earle, R.T.; Sullivan, W.P.; Miller, K.R.; Schwegman, W.J.

    1980-07-01

    This report documents the results of a study of scrams and forced outages at General Electric Boiling Water Reactors (BWRs) operating in the United States. This study was conducted for Sandia Laboratories under a Light Water Reactor Safety Program which it manages for the United States Department of Energy. Operating plant data were used to identify the causes of scrams and forced outages. Causes of scrams and forced outages have been summarized as a function of operating plant and plant age and also ranked according to the number of events per year, outage time per year, and outage time per event. From this ranking, identified potential improvement opportunities were evaluated to determine the associated benefits and impact on plant availability

  16. The Impact of Implementing a Demand Forecasting System into a Low-Income Country’s Supply Chain

    Science.gov (United States)

    Mueller, Leslie E.; Haidari, Leila A.; Wateska, Angela R.; Phillips, Roslyn J.; Schmitz, Michelle M.; Connor, Diana L.; Norman, Bryan A.; Brown, Shawn T.; Welling, Joel S.; Lee, Bruce Y.

    2016-01-01

    OBJECTIVE To evaluate the potential impact and value of applications (e.g., ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country’s vaccine supply chain with different levels of population change to urban areas. MATERIALS AND METHODS Using our software, HERMES, we generated a detailed discrete event simulation model of Niger’s entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. RESULTS Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. DISCUSSION The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. CONCLUSION Demand forecasting systems have the potential to greatly improve vaccine demand fulfillment, and decrease logistics cost/dose when implemented with storage and transportation increases direct vaccines. Simulation modeling can demonstrate the potential

  17. Factors Reducing Efficiency of the Operational Oceanographic Forecast Systems in the Arctic Basin

    Directory of Open Access Journals (Sweden)

    V.N. Belokopytov

    2017-04-01

    Full Text Available Reliability of the forecasted fields in the Arctic Basin is limited by a number of problems resulting, in the first turn, from lack of operational information. Due to the ice cover, satellite data on the sea level and the sea surface temperature is either completely not available or partially accessible in summer. The amount of CTD measuring systems functioning in the operational mode (3 – 5 probes is not sufficient. The number of the temperature-profiling buoys the probing depth of which is limited to 60 m, is not enough for the Arctic as well. Lack of spatial resolution of the available altimetry information (14 km, as compared to the Rossby radius in the Arctic Ocean (2 – 12 km, requires a thorough analysis of the forecasting system practical goals. The basic factor enhancing reliability of the oceanographic forecast consists in the fact that the key oceanographic regions, namely the eastern parts of the Norwegian and Greenland seas, the Barents Sea and the Chukchi Sea including the Bering Strait (where the Atlantic and Pacific waters flow in and transform, and the halocline structure is formed are partially or completely free of ice and significantly better provided with operational information.

  18. Prototypes of risk-based flood forecasting systems in the Netherlands and Italy

    Directory of Open Access Journals (Sweden)

    Bachmann D.

    2016-01-01

    Full Text Available Flood forecasting, warning and emergency response are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within emergency response. However, the information provided for decision support is often restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in current early warning and response systems. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. This paper presents the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. This paper presents the first results from two prototype applications of the new developed concept: The first prototype is applied to the Rotterdam area situated in the western part of the Netherlands. The second pilot study focusses on a rural area between the cities of Mantua and Ferrara along the Po river (Italy.

  19. The Simulations of Wildland Fire Smoke PM25 in the NWS Air Quality Forecasting Systems

    Science.gov (United States)

    Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

    2017-12-01

    The increase of wildland fire intensity and frequency in the United States (U.S.) has led to property loss, human fatality, and poor air quality due to elevated particulate matters and surface ozone concentrations. The NOAA/National Weather Service (NWS) built the National Air Quality Forecast Capability (NAQFC) based on the U.S. Environmental Protection Agency (EPA) Community Multi-scale Air Quality (CMAQ) Modeling System driven by the NCEP North American Mesoscale Forecast System meteorology to provide ozone and fine particulate matter (PM2.5) forecast guidance publicly. State and local forecasters use the NWS air quality forecast guidance to issue air quality alerts in their area. The NAQFC PM2.5 predictions include emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and wildland fires. The wildland fire emission inputs to the NAQFC is derived from the NOAA National Environmental Satellite, Data, and Information Service Hazard Mapping System fire and smoke detection product and the emission module of the U.S. Forest Service (USFS) BlueSky Smoke Modeling Framework. Wildland fires are unpredictable and can be ignited by natural causes such as lightning or be human-caused. It is extremely difficult to predict future occurrences and behavior of wildland fires, as is the available bio-fuel to be burned for real-time air quality predictions. Assumptions of future day's wildland fire behavior often have to be made from older observed wildland fire information. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that large errors in PM2.5 prediction can occur if fire smoke emissions are sometimes placed at the wrong location and/or time. A configuration of NAQFC CMAQ-system to re-run previous 24 hours, during which wildland fires were observed from satellites has been included recently. This study focuses on the effort performed to minimize the error in NAQFC PM2.5 predictions

  20. Downscaling modelling system for multi-scale air quality forecasting

    Science.gov (United States)

    Nuterman, R.; Baklanov, A.; Mahura, A.; Amstrup, B.; Weismann, J.

    2010-09-01

    Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -ɛ linear eddy-viscosity model, k - ɛ non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a

  1. The System of Inventory Forecasting in PT. XYZ by using the Method of Holt Winter Multiplicative

    Science.gov (United States)

    Shaleh, W.; Rasim; Wahyudin

    2018-01-01

    Problems at PT. XYZ currently only rely on manual bookkeeping, then the cost of production will swell and all investments invested to be less to predict sales and inventory of goods. If the inventory prediction of goods is to large, then the cost of production will swell and all investments invested to be less efficient. Vice versa, if the inventory prediction is too small it will impact on consumers, so that consumers are forced to wait for the desired product. Therefore, in this era of globalization, the development of computer technology has become a very important part in every business plan. Almost of all companies, both large and small, use computer technology. By utilizing computer technology, people can make time in solving complex business problems. Computer technology for companies has become an indispensable activity to provide enhancements to the business services they manage but systems and technologies are not limited to the distribution model and data processing but the existing system must be able to analyze the possibilities of future company capabilities. Therefore, the company must be able to forecast conditions and circumstances, either from inventory of goods, force, or profits to be obtained. To forecast it, the data of total sales from December 2014 to December 2016 will be calculated by using the method of Holt Winters, which is the method of time series prediction (Multiplicative Seasonal Method) it is seasonal data that has increased and decreased, also has 4 equations i.e. Single Smoothing, Trending Smoothing, Seasonal Smoothing and Forecasting. From the results of research conducted, error value in the form of MAPE is below 1%, so it can be concluded that forecasting with the method of Holt Winter Multiplicative.

  2. Elimination of maintenance outage and cost reduction by development of outage-free maintenance techniques

    International Nuclear Information System (INIS)

    Jakabe, Hideo; Maruyama, Yoshinaga

    1996-01-01

    The development program of KEPCO on outage-free maintenance techniques for distribution line work since 1984 is overviewed. It has succeeded in eliminating maintenance outages since 1989. The original aim was to improve customer satisfaction. However, in all, four benefits were realised through the development. These are cost reduction, securing of worker safety, improvement of customer service, and advancement of distribution techniques and morale in KEPCO. The introduction of robotic techniques for maintenance work and manipulator techniques for repair work is planned for further modernization. These new techniques are helping in both work safety and work efficiency improvement. Cost reduction and advancement of distribution line work techniques is also considered. (R.P.)

  3. Intercomparison of Operational Ocean Forecasting Systems in the framework of GODAE

    Science.gov (United States)

    Hernandez, F.

    2009-04-01

    One of the main benefits of the GODAE 10-year activity is the implementation of ocean forecasting systems in several countries. In 2008, several systems are operated routinely, at global or basin scale. Among them, the BLUElink (Australia), HYCOM (USA), MOVE/MRI.COM (Japan), Mercator (France), FOAM (United Kingdom), TOPAZ (Norway) and C-NOOFS (Canada) systems offered to demonstrate their operational feasibility by performing an intercomparison exercise during a three months period (February to April 2008). The objectives were: a) to show that operational ocean forecasting systems are operated routinely in different countries, and that they can interact; b) to perform in a similar way a scientific validation aimed to assess the quality of the ocean estimates, the performance, and forecasting capabilities of each system; and c) to learn from this intercomparison exercise to increase inter-operability and collaboration in real time. The intercomparison relies on the assessment strategy developed for the EU MERSEA project, where diagnostics over the global ocean have been revisited by the GODAE contributors. This approach, based on metrics, allow for each system: a) to verify if ocean estimates are consistent with the current general knowledge of the dynamics; and b) to evaluate the accuracy of delivered products, compared to space and in-situ observations. Using the same diagnostics also allows one to intercompare the results from each system consistently. Water masses and general circulation description by the different systems are consistent with WOA05 Levitus climatology. The large scale dynamics (tropical, subtropical and subpolar gyres ) are also correctly reproduced. At short scales, benefit of high resolution systems can be evidenced on the turbulent eddy field, in particular when compared to eddy kinetic energy deduced from satellite altimetry of drifter observations. Comparisons to high resolution SST products show some discrepancies on ocean surface

  4. Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

    Science.gov (United States)

    Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

    2018-05-01

    We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

  5. A Study on the Frequency of Initiating Event of OPR-1000 during Outage Periods

    Energy Technology Data Exchange (ETDEWEB)

    Hong Jae Beol; Jae, Moo Sung [Hanyang Univ., Seoul (Korea, Republic of)

    2013-10-15

    These sources of data did not reflect the latest event data which have occurred during the PWR outage to the frequencies of initiating event Electric Power Research Institute(EPRI) in USA collected the data of loss of decay heat removal during outage from 1989 to 2009 and published technical report. Domestic operating experiences for LOOP is gathered in Operational Performance Information System for Nuclear Power Plant(OPIS). To reduce conservatism and obtain completeness for LPSD PSA, those data should be collected and used to update the frequencies. The frequencies of LOSDC and LOOP are reevaluated using the data of EPRI and OPIS in this paper. Quantification is conducted to recalculate core damage frequency(CDF), since the rate is changed. The results are discussed below. To make an accurate estimate of the initiating events of LPSD PSA, the event data were collected and the frequencies of initiating events were updated using Bayesian approach. CDF was evaluated through quantification. Δ CDF is -40% and the dominant contributor is pressurizer PSV stuck open event. The most of the event data in EPRI TR were collected from US nuclear power plant industry. Those data are not enough to evaluate outage risk precisely. Therefore, to reduce conservatism and obtain completeness for LPSD PSA, the licensee event report and domestic data should be collected and reflected to the frequencies of the initiating events during outage.

  6. Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

    Science.gov (United States)

    Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

    1996-01-01

    The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the

  7. The NWRA Classification Infrastructure: description and extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

    Science.gov (United States)

    Leka, K. D.; Barnes, Graham; Wagner, Eric

    2018-04-01

    A classification infrastructure built upon Discriminant Analysis (DA) has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional DA, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.

  8. Forecast of energy demand in Colombia by means of a system of inference diffuse neuronal

    International Nuclear Information System (INIS)

    Medina Hurtado, Santiago; Garcia Aguado, Josefina

    2005-01-01

    This work two artificial intelligence techniques are used lo forecast the monthly demand of electric power in Colombia, the objective is determinate the error of the prediction and they can be compared later with other traditional models of forecast time series, an important decrease in the prediction errors, would bring economic benefits for all the agents that operate in the electric market. The artificial neural networks - RNA and Adaptative Neural Fuzzy Inference Systems - ANFIS are actually broadly used in forecast problems in many fields of the science and the technology with good performance, for our case these models were fed with explanatory variables of the demand. We used a RNA totally interconnected with forward propagation and three hidden layer, two learned algorithms were proved for the net find significantly different results in the prediction error as we as in the time of training. The ANFIS model used was of type Takawi - Sugeno of order zero and it was fed with the main components of the defined entrance variables. The results were compared by means of the function of error Root of the Mean Square Error RMSE and the Percentage of Error Mean Absolute (MAPE) we find a better performance of the RNA

  9. Application of Interval Type-2 Fuzzy Logic System in Short Term Load Forecasting on Special Days

    Directory of Open Access Journals (Sweden)

    Agus Dharma

    2011-05-01

    Full Text Available This paper presents the application of Interval Type-2 fuzzy logic systems (Interval Type-2 FLS in short term load forecasting (STLF on special days, study case in Bali Indonesia. Type-2 FLS is characterized by a concept called footprint of uncertainty (FOU that provides the extra mathematical dimension that equips Type-2 FLS with the potential to outperform their Type-1 counterparts. While a Type-2 FLS has the capability to model more complex relationships, the output of a Type-2 fuzzy inference engine needs to be type-reduced. Type reduction is used by applying the Karnik-Mendel (KM iterative algorithm. This type reduction maps the output of Type-2 FSs into Type-1 FSs then the defuzzification with centroid method converts that Type-1 reduced FSs into a number. The proposed method was tested with the actual load data of special days using 4 days peak load before special days and at the time of special day for the year 2002-2006. There are 20 items of special days in Bali that are used to be forecasted in the year 2005 and 2006 respectively. The test results showed an accurate forecasting with the mean average percentage error of 1.0335% and 1.5683% in the year 2005 and 2006 respectively.

  10. Application of hydrometeorological coupled European flood forecasting operational real time system in Yellow River Basin

    Directory of Open Access Journals (Sweden)

    Yi-qi Yan

    2009-12-01

    Full Text Available This study evaluated the application of the European flood forecasting operational real time system (EFFORTS to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin (from the Sanmenxia Reservoir to the Huayuankou Hydrological Station, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.

  11. A dynamic system to forecast ionospheric storm disturbances based on solar wind conditions

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    2005-06-01

    Full Text Available For the reliable performance of technologically advanced radio communications systems under geomagnetically disturbed conditions, the forecast and modelling of the ionospheric response during storms is a high priority. The ionospheric storm forecasting models that are currently in operation have shown a high degree of reliability during quiet conditions, but they have proved inadequate during storm events. To improve their prediction accuracy, we have to take advantage of the deeper understanding in ionospheric storm dynamics that is currently available, indicating a correlation between the Interplanetary Magnetic Field (IMF disturbances and the qualitative signature of ionospheric storm disturbances at middle latitude stations. In this paper we analyse observations of the foF2 critical frequency parameter from one mid-latitude European ionospheric station (Chilton in conjunction with observations of IMF parameters (total magnitude, Bt and Bz-IMF component from the ACE spacecraft mission for eight storm events. The determination of the time delay in the ionospheric response to the interplanetary medium disturbances leads to significant results concerning the forecast of the ionospheric storms onset and their development during the first 24 h. In this way the real-time ACE observations of the solar wind parameters may be used in the development of a real-time dynamic ionospheric storm model with adequate accuracy.

  12. Forecasting E > 50-MeV proton events with the proton prediction system (PPS)

    Science.gov (United States)

    Kahler, Stephen W.; White, Stephen M.; Ling, Alan G.

    2017-11-01

    Forecasting solar energetic (E > 10-MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (≥50-MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E ≥ 50-MeV proton events >1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986-2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all ≥M5 solar X-ray flares; (2) all ≥200 sfu 8800-MHz bursts with associated ≥M5 flares; (3) all ≥500 sfu 8800-MHz bursts; and (4) all ≥5000 sfu 8800-MHz bursts. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude, and argue that the longitude-dependence employed by PPS does not match modern observations. Use of the radio fluxes as the PPS driver tends to result in too many false alarms at the 500 sfu threshold, and misses more events than the soft X-ray predictor at the 5000 sfu threshold.

  13. Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS)

    Science.gov (United States)

    2016-09-01

    were downloaded from the University of Wyoming’s weather website (http://www.weather.uwyo.edu/upperair/sounding.html). An alternative site is the RAOB...Midwest US Amarillo, TX AMA 2016-01-02-12 37.12, –98.66 Dodge City, KS DDC and Lamont, OK LMN 2016-02-10-12 Norman, OK OUN...0-, 24-, 48-, 72-, or 96-h forecast from the same day, 1, 2, 3, or 4 days earlier, respectively. For example, for a 12 Coordinated Universal Time

  14. Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang; Zhang, Yingchen

    2016-11-14

    This paper proposes an approach for distribution system state forecasting, which aims to provide an accurate and high speed state forecasting with an optimal synchrophasor sensor placement (OSSP) based state estimator and an extreme learning machine (ELM) based forecaster. Specifically, considering the sensor installation cost and measurement error, an OSSP algorithm is proposed to reduce the number of synchrophasor sensor and keep the whole distribution system numerically and topologically observable. Then, the weighted least square (WLS) based system state estimator is used to produce the training data for the proposed forecaster. Traditionally, the artificial neural network (ANN) and support vector regression (SVR) are widely used in forecasting due to their nonlinear modeling capabilities. However, the ANN contains heavy computation load and the best parameters for SVR are difficult to obtain. In this paper, the ELM, which overcomes these drawbacks, is used to forecast the future system states with the historical system states. The proposed approach is effective and accurate based on the testing results.

  15. World-class outage performance of the Olkiluoto nuclear power plant

    International Nuclear Information System (INIS)

    Paavola, M.

    1998-01-01

    The production of the Olkiluoto power plant units covered 17% of the electricity consumption in Finland in 1997; the total share of nuclear energy was 27% of the electricity consumed in the country. Based on Finnish experience, nuclear energy is a safe, environmentally friendly and economic way to produce electricity provided that the plants and their personnel are well taken care of. TVO's policy is to keep the plant units in good condition and technically modern. This requires continuous investments in the plant. In maintenance, attention is paid to monitoring the condition of the plant and to preventive maintenance aiming at avoiding disturbances in production. TVO has chosen continuous development as the operational line develops the plant by annual investments and performs the necessary modifications during planned annual outages trying to avoid long production interruptions. The load factors of the Olkiluoto nuclear power plant have been high. The average load factor during the last decade was over 93%. The most significant single factor in the production deficits is the amount or electricity, which has not been produced because of the annual outages. Due to this, special attention has been paid to the performance of the annual outages. TVO aims at continuous development of the annual outage procedure. A centralized task management system makes it possible to perform simultaneously more tasks than before. The company has also invested in equipment and systems, which ease and speed up servicing. Normal outage length varies between 10 and 16 days. By keeping the plant units as modern as possible and in good condition we facilitate reaching TVO's target, which is also stated in TVO's slogan 'always 40 years lifetime'. (author)

  16. Forecasting in an integrated surface water-ground water system: The Big Cypress Basin, South Florida

    Science.gov (United States)

    Butts, M. B.; Feng, K.; Klinting, A.; Stewart, K.; Nath, A.; Manning, P.; Hazlett, T.; Jacobsen, T.

    2009-04-01

    The South Florida Water Management District (SFWMD) manages and protects the state's water resources on behalf of 7.5 million South Floridians and is the lead agency in restoring America's Everglades - the largest environmental restoration project in US history. Many of the projects to restore and protect the Everglades ecosystem are part of the Comprehensive Everglades Restoration Plan (CERP). The region has a unique hydrological regime, with close connection between surface water and groundwater, and a complex managed drainage network with many structures. Added to the physical complexity are the conflicting needs of the ecosystem for protection and restoration, versus the substantial urban development with the accompanying water supply, water quality and flood control issues. In this paper a novel forecasting and real-time modelling system is presented for the Big Cypress Basin. The Big Cypress Basin includes 272 km of primary canals and 46 water control structures throughout the area that provide limited levels of flood protection, as well as water supply and environmental quality management. This system is linked to the South Florida Water Management District's extensive real-time (SCADA) data monitoring and collection system. Novel aspects of this system include the use of a fully distributed and integrated modeling approach and a new filter-based updating approach for accurately forecasting river levels. Because of the interaction between surface- and groundwater a fully integrated forecast modeling approach is required. Indeed, results for the