Short term Braking Capability during Power Interruptions for Integrated Matrix Converter-Motor Drives

DEFF Research Database (Denmark)

Klumpner, Christian; Blaabjerg, Frede

2002-01-01

attractive. Sinusoidal input currents and bi-directional power flow are other advantages of the matrix converter but it is less immune to power grid disturbances compared to a standard ASD. In hoisting applications, short-term braking capability during a power outage is needed until the mechanical brake...... engages or to perform more effective a combined braking.This paper proposes a new method to provide short-term braking capability during a power outage for matrix converters. A braking chopper is needed in the clamp circuit, which allows for a drastically reduction of the capacitor size. The power flow...

Regime-based supervisory control to reduce power fluctuations from offshore wind power plants

DEFF Research Database (Denmark)

Barahona Garzón, Braulio; Cutululis, Nicolaos Antonio; Trombe, Pierre-Julien

2013-01-01

Wind power fluctuations, especially offshore, can pose challenges in the secure and stable operation of the power system. In modern large offshore wind farms, there are supervisory controls designed to reduce the power fluctuations. Their operation is limited due to the fact that they imply loss...... that consider different wind power regimes to derive control setpoints by using a Markov-Switching AutoRegressive model. We evaluate the performance versus measured data in terms of power ramp characteristics and energy efficiency....

Observation of short period fluctuation of CygX-1 with balloon

International Nuclear Information System (INIS)

Nakagawa, Michio; Sakurai, Takahisa; Uchida, Masayoshi

1977-01-01

CygX-1 presents very complex short period fluctuation of X-ray, therefore the hard X-ray was especially observed in 1972 and 1973 with large balloons, and the data were analyzed. This short period fluctuation and energy spectra of CygX-1 in the normal and flare time bands were compared. The observing apparatuses consisted of the 3 in diameter NaI detector and a high pressure proportional counter. The observing method is to turn the gondora alternately to the directions of source (ON) and background (OFF). As for the data analysis, the events at ON and OFF in the observation data in 1972 and 1973 were plotted for time interval. The background component is in agreement with Poisson's distribution, but source component is not. This difference for Poisson's distribution means the behavior of CygX-1. The power spectrum was analyzed, and the strong power density was observed at 5.4 x 10 -2 Hz in ON, but such power density was not observed in OFF. Accordingly this is presumed to be caused by CygX-1. The events for time interval in flare time are shown. The rise of about 2.9 σ exists at 80 msec. The count rates were compared for photon energy in the normal and flare times. The short period fluctuation of hard X-ray from CygX-1 deviates from Poisson's distribution and is different in the normal and flare times. (Nakai, Y.)

Evaluating the quality of scenarios of short-term wind power generation

DEFF Research Database (Denmark)

Pinson, Pierre; Girard, R.

2012-01-01

Scenarios of short-term wind power generation are becoming increasingly popular as input to multi-stage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benets from...... their use in decision-making. So far however, their verication is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verication tools, as well...... as diagnostic approaches based on event-based verication are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools....

A new ensemble model for short term wind power prediction

DEFF Research Database (Denmark)

Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

2012-01-01

As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

Dynamics of cyanobacterial bloom formation during short-term hydrodynamic fluctuation in a large shallow, eutrophic, and wind-exposed Lake Taihu, China.

Science.gov (United States)

Wu, Tingfeng; Qin, Boqiang; Zhu, Guangwei; Luo, Liancong; Ding, Yanqing; Bian, Geya

2013-12-01

Short-term hydrodynamic fluctuations caused by extreme weather events are expected to increase worldwide because of global climate change, and such fluctuations can strongly influence cyanobacterial blooms. In this study, the cyanobacterial bloom disappearance and reappearance in Lake Taihu, China, in response to short-term hydrodynamic fluctuations, was investigated by field sampling, long-term ecological records, high-frequency sensors and MODIS satellite images. The horizontal drift caused by the dominant easterly wind during the phytoplankton growth season was mainly responsible for cyanobacterial biomass accumulation in the western and northern regions of the lake and subsequent bloom formation over relatively long time scales. The cyanobacterial bloom changed slowly under calm or gentle wind conditions. In contrast, the short-term bloom events within a day were mainly caused by entrainment and disentrainment of cyanobacterial colonies by wind-induced hydrodynamics. Observation of a westerly event in Lake Taihu revealed that when the 30 min mean wind speed (flow speed) exceeded the threshold value of 6 m/s (5.7 cm/s), cyanobacteria in colonies were entrained by the wind-induced hydrodynamics. Subsequently, the vertical migration of cyanobacterial colonies was controlled by hydrodynamics, resulting in thorough mixing of algal biomass throughout the water depth and the eventual disappearance of surface blooms. Moreover, the intense mixing can also increase the chance for forming larger and more cyanobacterial colonies, namely, aggregation. Subsequently, when the hydrodynamics became weak, the cyanobacterial colonies continuously float upward without effective buoyancy regulation, and cause cyanobacterial bloom explosive expansion after the westerly. Furthermore, the results of this study indicate that the strong wind happening frequently during April and October can be an important cause of the formation and expansion of cyanobacterial blooms in Lake Taihu.

Profiling the regional wind power fluctuation in China

International Nuclear Information System (INIS)

Yu Dayang; Liang Jun; Han Xueshan; Zhao Jianguo

2011-01-01

As China starts to build 6 10-GW wind zones in 5 provinces by 2020, accommodating the wind electricity generated from these large wind zones will be a great challenge for the regional grids. Inadequate wind observing data hinders profiling the wind power fluctuations at the regional grid level. This paper proposed a method to assess the seasonal and diurnal wind power patterns based on the wind speed data from the NASA GEOS-5 DAS system, which provides data to the study of climate processes including the long-term estimates of meteorological quantities. The wind power fluctuations for the 6 largest wind zones in China are presented with both the capacity factor and the megawatt wind power output. The measured hourly wind output in a regional grid is compared to the calculating result to test the analyzing model. To investigate the offsetting effect of dispersed wind farms over large regions, the regional correlations of hourly wind power fluctuations are calculated. The result illustrates the different offsetting effects of minute and hourly fluctuations.

Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

Directory of Open Access Journals (Sweden)

Haixiang Zang

2016-01-01

Full Text Available Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EEMD, runs test (RT, and relevance vector machine (RVM. First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF components and residual (RES component by using EEMD. Next, we use the RT method to reconstruct the components and obtain three new components characterized by the fine-to-coarse order. Finally, we obtain the overall forecasting results (with preestablished confidence levels by superimposing the forecasting results of each new component. Our results show that, compared with existing methods, our proposed short-term interval forecasting method has less forecasting errors, narrower interval widths, and larger interval coverage percentages. Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.

Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm

OpenAIRE

BeomJun Park; Jin Hur

2017-01-01

Short-term wind power forecasting is a technique which tells system operators how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resources into the power grids, short-term wind power forecasting is becoming an important issue for grid integration analysis. The high reliability of wind power forecasting can contribute to the successful integration of wind generating resources into the power grids. To guarantee the reliability of forecas...

Analysing the Possible Ways for Short-Term Forcing Gas Turbine Engines in Auxiliary Power Unit

Directory of Open Access Journals (Sweden)

N. I. Trotskii

2016-01-01

Full Text Available Using a gas turbine energy unit as an example, the article discusses possible ways for forcing the short-term gas turbine engines (GTE. The introduction explains the need for forcing the air transport and marine GTE in specific driving conditions and offers the main methods. Then it analyzes the three main short-term forcing methods according to GTE power, namely: precompressor water injection, a short-term rise in temperature after the combustion chamber, and feeding an additional compressed air into combustion chamber from the reserve cylinders.The analysis of the water injection method to force a GTE presents the main provisions and calculation results of the cycle, as a function of engine power on the amount of water injected into compressor inlet. It is shown that with water injection into compressor inlet in an amount of 1% of the total airflow there is a 17% power increase in the compressor. It also lists the main implementation problems of this method and makes a comparison with the results of other studies on the water injection into compressor.Next, the article concerns the GTE short-term forcing method through the pre-turbine short-term increase in the gas temperature. The article presents the calculation results of the cycle as a function of the power and the fuel-flow rate on the gas temperature at the turbine inlet. It is shown that with increasing temperature by 80 degrees the engine power increases by 11.2% and requires 11% more fuel. In the analysis of this method arises an issue of thermal barrier coating on the blade surface. The article discusses the most common types of coatings and their main shortcomings. It lists the main challenges and some ways of their solving when using this method to implement the short-term forcing.The last method under consideration is GTE short-term forcing by feeding the compressed air into the combustion chamber from the additional reserve cylinders. It should be noted that this method is

Evaluating the quality of scenarios of short-term wind power generation

International Nuclear Information System (INIS)

Pinson, P.; Girard, R.

2012-01-01

Highlights: ► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate, diagnostic). ► Highlighting of the properties of current approaches to scenario generation. ► Guidelines for future evaluation/benchmark exercises. -- Abstract: Scenarios of short-term wind power generation are becoming increasingly popular as input to multistage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benefits from their use in decision-making. So far however, their verification is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verification tools, as well as diagnostic approaches based on event-based verification are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools.

Predicting short-term stock fluctuations by using processing fluency

Science.gov (United States)

Alter, Adam L.; Oppenheimer, Daniel M.

2006-01-01

Three studies investigated the impact of the psychological principle of fluency (that people tend to prefer easily processed information) on short-term share price movements. In both a laboratory study and two analyses of naturalistic real-world stock market data, fluently named stocks robustly outperformed stocks with disfluent names in the short term. For example, in one study, an initial investment of $1,000 yielded a profit of $112 more after 1 day of trading for a basket of fluently named shares than for a basket of disfluently named shares. These results imply that simple, cognitive approaches to modeling human behavior sometimes outperform more typical, complex alternatives. PMID:16754871

A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation

Directory of Open Access Journals (Sweden)

Yuan-Kang Wu

2014-01-01

Full Text Available The increasing use of solar power as a source of electricity has led to increased interest in forecasting its power output over short-time horizons. Short-term forecasts are needed for operational planning, switching sources, programming backup, reserve usage, and peak load matching. However, the output of a photovoltaic (PV system is influenced by irradiation, cloud cover, and other weather conditions. These factors make it difficult to conduct short-term PV output forecasting. In this paper, an experimental database of solar power output, solar irradiance, air, and module temperature data has been utilized. It includes data from the Green Energy Office Building in Malaysia, the Taichung Thermal Plant of Taipower, and National Penghu University. Based on the historical PV power and weather data provided in the experiment, all factors that influence photovoltaic-generated energy are discussed. Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output. They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm. Forecasting results show the high precision and efficiency of this combination model. Therefore, the proposed model is suitable for ensuring the stable operation of a photovoltaic generation system.

Evaluation of short-term tracer fluctuations in groundwater and soil air in a two year study

Science.gov (United States)

Jenner, Florian; Mayer, Simon; Aeschbach, Werner; Weissbach, Therese

2016-04-01

The application of gas tracers like noble gases (NGs), SF6 or CFCs in groundwater studies such as paleo temperature determination requires a detailed understanding of the dynamics of reactive and inert gases in the soil air with which the infiltrating water equilibrates. Due to microbial gas consumption and production, NG partial pressures in soil air can deviate from atmospheric air, an effect that could bias noble gas temperatures estimates if not taken into account. So far, such an impact on NG contents in groundwater has not been directly demonstrated. We provide the first long-term study of the above mentioned gas tracers and physical parameters in both the saturated and unsaturated soil zone, sampled continuously for more than two years near Mannheim (Germany). NG partial pressures in soil air correlate with soil moisture and the sum value of O2+CO2, with a maximal significant enhancement of 3-6% with respect to atmospheric air during summer time. Observed seasonal fluctuations result in a mass dependent fractionation of NGs in soil air. Concentrations of SF6 and CFCs in soil air are determined by corresponding fluctuations in local atmospheric air, caused by industrial emissions. Arising concentration peaks are damped with increasing soil depth. Shallow groundwater shows short-term NG fluctuations which are smoothed within a few meters below the water table. A correlation between NG contents of soil air and of groundwater is observable during strong recharge events. However, there is no evidence for a permanent influence of seasonal variations of soil air composition on shallow groundwater. Fluctuating NG contents in shallow groundwater are rather determined by variations of soil temperature and water table level. Our data gives evidence for a further temperature driven equilibration of groundwater with entrapped air bubbles within the topmost saturated zone, which permanently occurs even some years after recharge. Local subsurface temperature fluctuations

Short Term Energy Storage for Grid Support in Wind Power Applications

DEFF Research Database (Denmark)

Stroe, Daniel Ioan; Stan, Ana-Irina; Diosi, Robert

2012-01-01

The penetration of wind power into the power system has been increasing in the recent years. Therefore, a lot of concerns related to the reliable operation of the power system have been addressed. An attractive solution to minimize the limitations faced by the wind power grid integration, and thus...... to increase the power system stability and the energy quality, is to integrate energy storage devices into wind power plants. This paper gives an overview of the state-of-the-art short-term energy storage devices and presents several applications which can be provided by the energy storage device - wind power...

Short-term variability of Cyg X-1

International Nuclear Information System (INIS)

Oda, M.; Doi, K.; Ogawara, Y.

1976-01-01

The short-term X-ray variability distinguishes Cyg X-1, which is the most likely candidate for a black hole, from other X-ray sources. The present status of our knowledge on this short-term variation, mainly from the UHURU, the MIT and the GSFC observations, is reviewed. The nature of impulsive variations which compose the time variation exceeding the statistical fluctuation is discussed. There are indications that the energy spectrum of large pulses is harder than the average spectrum, or that the large pulses are the characteristics of the hard component of the spectrum if it is composed of two, soft and hard, components. Features of the variations may be partly simulated by the superposition of random shot-noise pulses with a fraction of a second duration. However, the autocorrelation analysis and the dynamic spectrum analysis indicate that the correlation lasts for several seconds and in the variation are buried some regularities which exhibit power concentrations in several frequency bands; 0.2-0.3, 0.4-0.5, 0.8, 1.2-1.5 Hz. There are several possible interpretations of these results in terms of; e.g. (a) a mixture of shot-noise pulses with two or more constant durations, (b) the shape of the basic shot-noise pulse, (c) bunching of the pulses, (d) superposition of wave-packets or temporal oscillations. But we have not yet reached any definite understandings in the nature of the variabilities. The substructure of the fluctuations on a time scale of milliseconds suggested by two investigations is also discussed. (Auth.)

Short-Term Power Plant GHG Emissions Forecasting Model

International Nuclear Information System (INIS)

Vidovic, D.

2016-01-01

In 2010, the share of greenhouse gas (GHG) emissions from power generation in the total emissions at the global level was about 25 percent. From January 1st, 2013 Croatian facilities have been involved in the European Union Emissions Trading System (EU ETS). The share of the ETS sector in total GHG emissions in Croatia in 2012 was about 30 percent, where power plants and heat generation facilities contributed to almost 50 percent. Since 2013 power plants are obliged to purchase all emission allowances. The paper describes the short-term climate forecasting model of greenhouse gas emissions from power plants while covering the daily load diagram of the system. Forecasting is done on an hourly domain typically for one day, it is possible and more days ahead. Forecasting GHG emissions in this way would enable power plant operators to purchase additional or sell surplus allowances on the market at the time. Example that describes the operation of the above mentioned forecasting model is given at the end of the paper.(author).

The Spectrum of Wind Power Fluctuations

Science.gov (United States)

Bandi, Mahesh

2016-11-01

Wind is a variable energy source whose fluctuations threaten electrical grid stability and complicate dynamical load balancing. The power generated by a wind turbine fluctuates due to the variable wind speed that blows past the turbine. Indeed, the spectrum of wind power fluctuations is widely believed to reflect the Kolmogorov spectrum; both vary with frequency f as f - 5 / 3. This variability decreases when aggregate power fluctuations from geographically distributed wind farms are averaged at the grid via a mechanism known as geographic smoothing. Neither the f - 5 / 3 wind power fluctuation spectrum nor the mechanism of geographic smoothing are understood. In this work, we explain the wind power fluctuation spectrum from the turbine through grid scales. The f - 5 / 3 wind power fluctuation spectrum results from the largest length scales of atmospheric turbulence of order 200 km influencing the small scales where individual turbines operate. This long-range influence spatially couples geographically distributed wind farms and synchronizes farm outputs over a range of frequencies and decreases with increasing inter-farm distance. Consequently, aggregate grid-scale power fluctuations remain correlated, and are smoothed until they reach a limiting f - 7 / 3 spectrum. This work was funded by the Collective Interactions Unit, OIST Graduate University, Japan.

Does stress affect the joints? Daily stressors, stress vulnerability, immune and HPA axis activity, and short-term disease and symptom fluctuations in rheumatoid arthritis.

Science.gov (United States)

Evers, Andrea W M; Verhoeven, Elisabeth W M; van Middendorp, Henriët; Sweep, Fred C G J; Kraaimaat, Floris W; Donders, A Rogier T; Eijsbouts, Agnes E; van Laarhoven, Antoinette I M; de Brouwer, Sabine J M; Wirken, Lieke; Radstake, Timothy R D J; van Riel, Piet L C M

2014-09-01

Both stressors and stress vulnerability factors together with immune and hypothalamus-pituitary-adrenal (HPA) axis activity components have been considered to contribute to disease fluctuations of chronic inflammatory diseases, such as rheumatoid arthritis (RA). The aim of the present study was to investigate whether daily stressors and worrying as stress vulnerability factor as well as immune and HPA axis activity markers predict short-term disease activity and symptom fluctuations in patients with RA. In a prospective design, daily stressors, worrying, HPA axis (cortisol) and immune system (interleukin (IL)-1β, IL-6, IL-8, interferon (IFN)-γ, tumour necrosis factor α) markers, clinical and self-reported disease activity (disease activity score in 28 joints, RA disease activity index), and physical symptoms of pain and fatigue were monitored monthly during 6 months in 80 RA patients. Multilevel modelling indicated that daily stressors predicted increased fatigue in the next month and that worrying predicted increased self-reported disease activity, swollen joint count and pain in the next month. In addition, specific cytokines of IL-1β and IFN-γ predicted increased fatigue 1 month later. Overall, relationships remained relatively unchanged after controlling for medication use, disease duration and demographic variables. No evidence was found for immune and HPA axis activity markers as mediators of the stress-disease relationship. Daily stressors and the stress-vulnerability factor worrying predict indicators of the short-term course of RA disease activity and fatigue and pain, while specific cytokines predict short-term fluctuations of fatigue. These stress-related variables and immune markers seem to affect different aspects of disease activity or symptom fluctuations independently in RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Power fluctuation reduction methodology for the grid-connected renewable power systems

Science.gov (United States)

Aula, Fadhil T.; Lee, Samuel C.

2013-04-01

This paper presents a new methodology for eliminating the influence of the power fluctuations of the renewable power systems. The renewable energy, which is to be considered an uncertain and uncontrollable resource, can only provide irregular electrical power to the power grid. This irregularity creates fluctuations of the generated power from the renewable power systems. These fluctuations cause instability to the power system and influence the operation of conventional power plants. Overall, the power system is vulnerable to collapse if necessary actions are not taken to reduce the impact of these fluctuations. This methodology aims at reducing these fluctuations and makes the generated power capability for covering the power consumption. This requires a prediction tool for estimating the generated power in advance to provide the range and the time of occurrence of the fluctuations. Since most of the renewable energies are weather based, as a result a weather forecast technique will be used for predicting the generated power. The reduction of the fluctuation also requires stabilizing facilities to maintain the output power at a desired level. In this study, a wind farm and a photovoltaic array as renewable power systems and a pumped-storage and batteries as stabilizing facilities are used, since they are best suitable for compensating the fluctuations of these types of power suppliers. As an illustrative example, a model of wind and photovoltaic power systems with battery energy and pumped hydro storage facilities for power fluctuation reduction is included, and its power fluctuation reduction is verified through simulation.

Short-term wind power forecasting: probabilistic and space-time aspects

DEFF Research Database (Denmark)

Tastu, Julija

work deals with the proposal and evaluation of new mathematical models and forecasting methods for short-term wind power forecasting, accounting for space-time dynamics based on geographically distributed information. Different forms of power predictions are considered, starting from traditional point...... into the corresponding models are analysed. As a final step, emphasis is placed on generating space-time trajectories: this calls for the prediction of joint multivariate predictive densities describing wind power generation at a number of distributed locations and for a number of successive lead times. In addition......Optimal integration of wind energy into power systems calls for high quality wind power predictions. State-of-the-art forecasting systems typically provide forecasts for every location individually, without taking into account information coming from the neighbouring territories. It is however...

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

From probabilistic forecasts to statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2009-01-01

on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

Optimal shifting of Photovoltaic and load fluctuations from fuel cell and electrolyzer to lead acid battery in a Photovoltaic/hydrogen standalone power system for improved performance and life time

Science.gov (United States)

Tesfahunegn, S. G.; Ulleberg, Ø.; Vie, P. J. S.; Undeland, T. M.

Cost reduction is very critical in the pursuit of realizing more competitive clean and sustainable energy systems. In line with this goal a control method that enables minimization of the cost associated with performance and life time degradation of fuel cell and electrolyzer, and cost of battery replacement in PV/hydrogen standalone power systems is developed. The method uses the advantage of existing peak shaving battery to suppress short-term PV and load fluctuations while reducing impact on the cycle life of the battery itself. This is realized by diverting short-term cyclic charge/discharge events induced by PV/load power fluctuations to the upper band of the battery state of charge regime while operating the fuel cell and electrolyzer systems along stable (smooth) power curves. Comparative studies of the developed method with two other reference cases demonstrate that the proposed method fares better with respect to defined performance indices as fluctuation suppression rate and mean state of charge. Modeling of power electronics and design of controllers used in the study are also briefly discussed in Appendix A.

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)

European Short-term Electricity Market Designs under High Penetration of Wind Power

NARCIS (Netherlands)

Chaves Avila, J.P.

2014-01-01

The EU has ambitious policies for decarbonization of the electricity sector. Due to recent technological developments, wind power already represents a significant share of the generation mix in some European countries. As a result, short-term electricity markets and balancing arrangements must be

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Science.gov (United States)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Developing a Local Neurofuzzy Model for Short-Term Wind Power Forecasting

Directory of Open Access Journals (Sweden)

E. Faghihnia

2014-01-01

Full Text Available Large scale integration of wind generation capacity into power systems introduces operational challenges due to wind power uncertainty and variability. Therefore, accurate wind power forecast is important for reliable and economic operation of the power systems. Complexities and nonlinearities exhibited by wind power time series necessitate use of elaborative and sophisticated approaches for wind power forecasting. In this paper, a local neurofuzzy (LNF approach, trained by the polynomial model tree (POLYMOT learning algorithm, is proposed for short-term wind power forecasting. The LNF approach is constructed based on the contribution of local polynomial models which can efficiently model wind power generation. Data from Sotavento wind farm in Spain was used to validate the proposed LNF approach. Comparison between performance of the proposed approach and several recently published approaches illustrates capability of the LNF model for accurate wind power forecasting.

The footprint of atmospheric turbulence in power grid frequency measurements

Science.gov (United States)

Haehne, H.; Schottler, J.; Waechter, M.; Peinke, J.; Kamps, O.

2018-02-01

Fluctuating wind energy makes a stable grid operation challenging. Due to the direct contact with atmospheric turbulence, intermittent short-term variations in the wind speed are converted to power fluctuations that cause transient imbalances in the grid. We investigate the impact of wind energy feed-in on short-term fluctuations in the frequency of the public power grid, which we have measured in our local distribution grid. By conditioning on wind power production data, provided by the ENTSO-E transparency platform, we demonstrate that wind energy feed-in has a measurable effect on frequency increment statistics for short time scales (renewable generation.

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.

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).

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.

Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

Directory of Open Access Journals (Sweden)

Xuejun Chen

2014-01-01

Full Text Available As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H weighted average smoothing method, ensemble empirical mode decomposition (EEMD algorithm, and nonlinear autoregressive (NAR neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.

Short-Term and Medium-Term Reliability Evaluation for Power Systems With High Penetration of Wind Power

DEFF Research Database (Denmark)

Ding, Yi; Singh, Chanan; Goel, Lalit

2014-01-01

reliability evaluation techniques for power systems are well developed. These techniques are more focused on steady-state (time-independent) reliability evaluation and have been successfully applied in power system planning and expansion. In the operational phase, however, they may be too rough......The expanding share of the fluctuating and less predictable wind power generation can introduce complexities in power system reliability evaluation and management. This entails a need for the system operator to assess the system status more accurately for securing real-time balancing. The existing...... an approximation of the time-varying behavior of power systems with high penetration of wind power. This paper proposes a time-varying reliability assessment technique. Time-varying reliability models for wind farms, conventional generating units, and rapid start-up generating units are developed and represented...

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

OpenAIRE

Wen-Yeau Chang

2013-01-01

High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO) based hybrid forecasting method for short-term wi...

Short-term stability in refractive status despite large fluctuations in glucose levels in diabetes mellitus type 1 and 2.

Directory of Open Access Journals (Sweden)

Byki Huntjens

Full Text Available PURPOSE: This work investigates how short-term changes in blood glucose concentration affect the refractive components of the diabetic eye in patients with long-term Type 1 and Type 2 diabetes. METHODS: Blood glucose concentration, refractive error components (mean spherical equivalent MSE, J0, J45, central corneal thickness (CCT, anterior chamber depth (ACD, crystalline lens thickness (LT, axial length (AL and ocular aberrations were monitored at two-hourly intervals over a 12-hour period in: 20 T1DM patients (mean age ± SD 38±14 years, baseline HbA1c 8.6±1.9%; 21 T2DM patients (mean age ± SD 56±11 years, HbA1c 7.5±1.8%; and in 20 control subjects (mean age ± SD 49±23 years, HbA1c 5.5±0.5%. The refractive and biometric results were compared with the corresponding changes in blood glucose concentration. RESULTS: Blood glucose concentration at different times was found to vary significantly within (p0.05. Minor changes of marginal statistical or optical significance were observed in some biometric parameters. Similarly there were some marginally significant differences between the baseline biometric parameters of well-controlled and poorly-controlled diabetic subjects. CONCLUSION: This work suggests that normal, short-term fluctuations (of up to about 6 mM/l on a timescale of a few hours in the blood glucose levels of diabetics are not usually associated with acute changes in refractive error or ocular wavefront aberrations. It is therefore possible that factors other than refractive error fluctuations are sometimes responsible for the transient visual problems often reported by diabetic patients.

A review on the young history of the wind power short-term prediction

DEFF Research Database (Denmark)

Costa, A.; Crespo, A.; Navarro, J.

2008-01-01

This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly...

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

International Nuclear Information System (INIS)

Touš, Michal; Pavlas, Martin; Putna, Ondřej; Stehlík, Petr; Crha, Lukáš

2015-01-01

In many cases, WtE (waste-to-energy) plants are CHP (combined heat and power) producers. They are often integrated into a central heating system and they also export electricity to the grid. Therefore, they have to plan their operation on a long-term basis (months, years) as well as on a short-term basis (hours, days). Simulation models can effectively support decision making in CHP production planning. In general, CHP production planning on a short-term basis is a challenging task for WtE plants. This article presents a simulation based support. It is demonstrated on an example involving a real WtE plant. Most of the models of relevant WtE sub-systems (boilers, steam turbine) are developed using operational data and applying linear regression and artificial neural network technique. The process randomness given mainly by fluctuating heating value of waste leads to uncertainty in a calculation of CHP production and a stochastic approach is appropriate. The models of the sub-systems are, therefore, extended of a stochastic part and Monte-Carlo simulation is applied. Compared to the current planning strategy in the involved WtE plant, the stochastic simulation based planning provides increased CHP production resulting in better net thermal efficiency and increased revenue. This is demonstrated through a comparison using real operational data. - Highlights: • Introduction of a stochastic model of a CHP production in a waste-to-energy plant. • An application of the model for the next day CHP production planning. • Better net thermal efficiency and therefore increased revenue achieved.

Panorama 2013 - Short term trends in the gas industry

International Nuclear Information System (INIS)

Lecarpentier, Armelle

2012-10-01

The outlook for gas industry development in the short term is clouded by uncertainties (impact of the economic slowdown, competition between energies, price fluctuations, etc.). However, as in 2012, many favorable factors in terms of natural gas supply and demand point to sustained and sustainable growth of this energy. (author)

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Power fluctuations from large wind farms - Final report

Energy Technology Data Exchange (ETDEWEB)

Soerensen, Poul; Pinson, P.; Cutululis, N.A.; Madsen, Henrik; Jensen, Leo Enrico; Hjerrild, J.; Heyman Donovan, M.; Vigueras-ROdriguez, A.

2009-08-15

Experience from power system operation with the first large offshore wind farm in Denmark: Horns Rev shows that the power from the wind farm is fluctuating significantly at certain times, and that this fluctuation is seen directly on the power exchange between Denmark and Germany. This report describes different models for simulation and prediction of wind power fluctuations from large wind farms, and data acquired at the two large offshore wind farms in Denmark are applied to validate the models. Finally, the simulation model is further developed to enable simulations of power fluctuations from several wind farms simultaneously in a larger geographical area, corresponding to a power system control area. (au)

An Analysis of Variable-Speed Wind Turbine Power-Control Methods with Fluctuating Wind Speed

Directory of Open Access Journals (Sweden)

Seung-Il Moon

2013-07-01

Full Text Available Variable-speed wind turbines (VSWTs typically use a maximum power-point tracking (MPPT method to optimize wind-energy acquisition. MPPT can be implemented by regulating the rotor speed or by adjusting the active power. The former, termed speed-control mode (SCM, employs a speed controller to regulate the rotor, while the latter, termed power-control mode (PCM, uses an active power controller to optimize the power. They are fundamentally equivalent; however, since they use a different controller at the outer control loop of the machine-side converter (MSC controller, the time dependence of the control system differs depending on whether SCM or PCM is used. We have compared and analyzed the power quality and the power coefficient when these two different control modes were used in fluctuating wind speeds through computer simulations. The contrast between the two methods was larger when the wind-speed fluctuations were greater. Furthermore, we found that SCM was preferable to PCM in terms of the power coefficient, but PCM was superior in terms of power quality and system stability.

Generation of statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2007-01-01

Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform...... on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind...

Latitudinal Patterns in European Seagrass Carbon Reserves: Influence of Seasonal Fluctuations versus Short-Term Stress and Disturbance Events

Directory of Open Access Journals (Sweden)

Laura M. Soissons

2018-02-01

Full Text Available Seagrass meadows form highly productive and valuable ecosystems in the marine environment. Throughout the year, seagrass meadows are exposed to abiotic and biotic variations linked to (i seasonal fluctuations, (ii short-term stress events such as, e.g., local nutrient enrichment, and (iii small-scale disturbances such as, e.g., biomass removal by grazing. We hypothesized that short-term stress events and small-scale disturbances may affect seagrass chance for survival in temperate latitudes. To test this hypothesis we focused on seagrass carbon reserves in the form of starch stored seasonally in rhizomes, as these have been defined as a good indicator for winter survival. Twelve Zostera noltei meadows were monitored along a latitudinal gradient in Western Europe to firstly assess the seasonal change of their rhizomal starch content. Secondly, we tested the effects of nutrient enrichment and/or biomass removal on the corresponding starch content by using a short-term manipulative field experiment at a single latitude in the Netherlands. At the end of the growing season, we observed a weak but significant linear increase of starch content along the latitudinal gradient from south to north. This agrees with the contention that such reserves are essential for regrowth after winter, which is more severe in the north. In addition, we also observed a weak but significant positive relationship between starch content at the beginning of the growing season and past winter temperatures. This implies a lower regrowth potential after severe winters, due to diminished starch content at the beginning of the growing season. Short-term stress and disturbances may intensify these patterns, because our manipulative experiments show that when nutrient enrichment and biomass loss co-occurred at the end of the growing season, Z. noltei starch content declined. In temperate zones, the capacity of seagrasses to accumulate carbon reserves is expected to determine carbon

Latitudinal Patterns in European Seagrass Carbon Reserves: Influence of Seasonal Fluctuations versus Short-Term Stress and Disturbance Events

Science.gov (United States)

Soissons, Laura M.; Haanstra, Eeke P.; van Katwijk, Marieke M.; Asmus, Ragnhild; Auby, Isabelle; Barillé, Laurent; Brun, Fernando G.; Cardoso, Patricia G.; Desroy, Nicolas; Fournier, Jerome; Ganthy, Florian; Garmendia, Joxe-Mikel; Godet, Laurent; Grilo, Tiago F.; Kadel, Petra; Ondiviela, Barbara; Peralta, Gloria; Puente, Araceli; Recio, Maria; Rigouin, Loic; Valle, Mireia; Herman, Peter M. J.; Bouma, Tjeerd J.

2018-01-01

Seagrass meadows form highly productive and valuable ecosystems in the marine environment. Throughout the year, seagrass meadows are exposed to abiotic and biotic variations linked to (i) seasonal fluctuations, (ii) short-term stress events such as, e.g., local nutrient enrichment, and (iii) small-scale disturbances such as, e.g., biomass removal by grazing. We hypothesized that short-term stress events and small-scale disturbances may affect seagrass chance for survival in temperate latitudes. To test this hypothesis we focused on seagrass carbon reserves in the form of starch stored seasonally in rhizomes, as these have been defined as a good indicator for winter survival. Twelve Zostera noltei meadows were monitored along a latitudinal gradient in Western Europe to firstly assess the seasonal change of their rhizomal starch content. Secondly, we tested the effects of nutrient enrichment and/or biomass removal on the corresponding starch content by using a short-term manipulative field experiment at a single latitude in the Netherlands. At the end of the growing season, we observed a weak but significant linear increase of starch content along the latitudinal gradient from south to north. This agrees with the contention that such reserves are essential for regrowth after winter, which is more severe in the north. In addition, we also observed a weak but significant positive relationship between starch content at the beginning of the growing season and past winter temperatures. This implies a lower regrowth potential after severe winters, due to diminished starch content at the beginning of the growing season. Short-term stress and disturbances may intensify these patterns, because our manipulative experiments show that when nutrient enrichment and biomass loss co-occurred at the end of the growing season, Z. noltei starch content declined. In temperate zones, the capacity of seagrasses to accumulate carbon reserves is expected to determine carbon-based regrowth

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

Energy Technology Data Exchange (ETDEWEB)

Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

2011-01-15

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

Power fluctuation and power loss of wind turbines due to wind shear and tower shadow

Institute of Scientific and Technical Information of China (English)

Binrong WEN; Sha WEI; Kexiang WEI; Wenxian YANG; Zhike PENG; Fulei CHU

2017-01-01

The magnitude and stability of power output are two key indices of wind turbines.This study investigates the effects of wind shear and tower shadow on power output in terms of power fluctuation and power loss to estimate the capacity and quality of the power generated by a wind turbine.First,wind speed models,particularly the wind shear model and the tower shadow model,are described in detail.The widely accepted tower shadow model is modified in view of the cone-shaped towers of modem large-scale wind turbines.Power fluctuation and power loss due to wind shear and tower shadow are analyzed by performing theoretical calculations and case analysis within the framework of a modified version of blade element momentum theory.Results indicate that power fluctuation is mainly caused by tower shadow,whereas power loss is primarily induced by wind shear.Under steady wind conditions,power loss can be divided into wind farm loss and rotor loss.Wind farm loss is constant at 3α(3α-1)R2/(8H2).By contrast,rotor loss is strongly influenced by the wind turbine control strategies and wind speed.That is,when the wind speed is measured in a region where a variable-speed controller works,the rotor loss stabilizes around zero,but when the wind speed is measured in a region where the blade pitch controller works,the rotor loss increases as the wind speed intensifies.The results of this study can serve as a reference for accurate power estimation and strategy development to mitigate the fluctuations in aerodynamic loads and power output due to wind shear and tower shadow.

A tangential CO{sub 2} laser collective scattering system for measuring short-scale turbulent fluctuations in the EAST superconducting tokamak

Energy Technology Data Exchange (ETDEWEB)

Cao, G.M., E-mail: gmcao@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, PO Box 1126, Hefei, Anhui 230031 (China); Li, Y.D. [Institute of Plasma Physics, Chinese Academy of Sciences, PO Box 1126, Hefei, Anhui 230031 (China); Li, Q. [School of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou 510006 (China); Zhang, X.D.; Sun, P.J.; Wu, G.J.; Hu, L.Q. [Institute of Plasma Physics, Chinese Academy of Sciences, PO Box 1126, Hefei, Anhui 230031 (China)

2014-12-15

Highlights: • A tangential CO{sub 2} laser collective scattering system was first installed on EAST. • It can measure the short-scale fluctuations in different regions simultaneously. • It can study the broadband fluctuations, QC fluctuations, MHD phenomenon, etc. - Abstract: A tangential CO{sub 2} laser collective scattering system has been first installed on the Experimental Advanced Superconducting Tokamak (EAST) to measure short-scale turbulent fluctuations in EAST plasmas. The system can measure fluctuations with up to four distinct wavenumbers simultaneously ranging from 10 cm{sup −1} to 26 cm{sup −1}, and correspondingly k{sub ⊥}ρ{sub s}∼1.5−4.3. The system is designed based on the oblique propagation of the probe beam with respect to the magnetic field, and thus the enhanced spatial localization can be achieved by taking full advantage of turbulence anisotropy and magnetic field inhomogeneity. The simultaneous measurements of turbulent fluctuations in different regions can be taken by special optical setup. Initial measurements indicate rich short-scale turbulent dynamics in both core and outer regions of EAST plasmas. The system will be a powerful tool for investigating the features of short-scale turbulent fluctuations in EAST plasmas.

Mitigation of Power System Oscillation Caused by Wind Power Fluctuation

DEFF Research Database (Denmark)

Su, Chi; Hu, Weihao; Chen, Zhe

2013-01-01

oscillation mitigation controllers are proposed and compared. A model of direct-drive-full-convertor-based wind farm connected to the IEEE 10-machine 39-bus system is adopted as the test system. The calculations and simulations are conducted in DIgSILENT PowerFactory 14.0. Results are presented to show......Wind power is increasingly integrated in modern power grids, which brings new challenges to the power system operation. Wind power is fluctuating because of the uncertain nature of wind, whereas wind shear and tower shadow effects also cause periodic fluctuations. These may lead to serious forced...... oscillation when the frequencies of the periodic fluctuations are close to the natural oscillation frequencies of the connected power system. By using modal analysis and time-domain simulations, this study studies the forced oscillation caused by the wind shear and tower shadow effects. Three forced...

Short time ahead wind power production forecast

International Nuclear Information System (INIS)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-01-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)

Short time ahead wind power production forecast

Science.gov (United States)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-09-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

EDM - A model for optimising the short-term power operation of a complex hydroelectric network

International Nuclear Information System (INIS)

Tremblay, M.; Guillaud, C.

1996-01-01

In order to optimize the short-term power operation of a complex hydroelectric network, a new model called EDM was added to PROSPER, a water management analysis system developed by SNC-Lavalin. PROSPER is now divided into three parts: an optimization model (DDDP), a simulation model (ESOLIN), and an economic dispatch model (EDM) for the short-term operation. The operation of the KSEB hydroelectric system (located in southern India) with PROSPER was described. The long-term analysis with monthly time steps is assisted by the DDDP, and the daily analysis with hourly or half-hourly time steps is performed with the EDM model. 3 figs

Analysis of the spontaneous variations in wind power and necessary continuous regulation of hydro-electric and thermal power, related to a future Swedish power system

Energy Technology Data Exchange (ETDEWEB)

Holm, J O; Lindstrom, P O

1982-09-01

Wind power is unlike conventional electric power generation, since the output fluctuates uncontrollably. These fluctuations must be balanced by controlled generation from other power sources. This will create new and interesting demands on the reserves in the power system. The short-term fluctuations have a low simultaneity factor and must be balanced by an automatic frequency control reserve. In Sweden, this consists of automatically controlled hydro-electric power. The report contains calculations of the amount by which the demand on reserves will increase when wind power is introduced.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

2011-04-15

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (author)

An analysis of the performance benefits of short-term energy storage in wind-diesel hybrid power systems

International Nuclear Information System (INIS)

Shirazi, M.; Drouilhet, S.

1996-01-01

A variety of prototype high penetration wind-diesel hybrid power systems have been implemented with different amounts of energy storage. They range from systems with no energy storage to those with many hours worth of energy storage. There has been little consensus among wind-diesel system developers as to the appropriate role and amount of energy storage in such systems. Some researchers advocate providing only enough storage capacity to supply power during the time it takes the diesel genset to start. Others install large battery banks to allow the diesel(s) to operate at full load and/or to time-shift the availability of wind-generated electricity to match the demand. Prior studies indicate that for high penetration wind-diesel systems, short-term energy storage provides the largest operational and economic benefit. This study uses data collected in Deering, Alaska, a small diesel-powered village, and the hybrid systems modeling software Hybrid2 to determine the optimum amount of short-term storage for a particular high penetration wind-diesel system. These findings were then generalized by determining how wind penetration, turbulence intensity, and load variability affect the value of short term energy storage as measured in terms of fuel savings, total diesel run time, and the number of diesel starts

Power-law neuronal fluctuations in a recurrent network model of parametric working memory.

Science.gov (United States)

Miller, Paul; Wang, Xiao-Jing

2006-02-01

In a working memory system, persistent activity maintains information in the absence of external stimulation, therefore the time scale and structure of correlated neural fluctuations reflect the intrinsic microcircuit dynamics rather than direct responses to sensory inputs. Here we show that a parametric working memory model capable of graded persistent activity is characterized by arbitrarily long correlation times, with Fano factors and power spectra of neural activity described by the power laws of a random walk. Collective drifts of the mnemonic firing pattern induce long-term noise correlations between pairs of cells, with the sign (positive or negative) and amplitude proportional to the product of the gradients of their tuning curves. None of the power-law behavior was observed in a variant of the model endowed with discrete bistable neural groups, where noise fluctuations were unable to cause long-term changes in rate. Therefore such behavior can serve as a probe for a quasi-continuous attractor. We propose that the unusual correlated fluctuations have important implications for neural coding in parametric working memory circuits.

The state-of-the-art in short-term prediction of wind power. A literature overview

Energy Technology Data Exchange (ETDEWEB)

Giebel, G.; Brownsword, R.; Kariniotakis, G.

2003-08-01

Based on an appropriate questionnaire (WP1.1) and some other works already in progress, this report details the state-of-the-art in short term prediction of wind power, mostly summarising nearly all existing literature on the topic. (au)

Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

International Nuclear Information System (INIS)

Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

2004-01-01

One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

Evidence for nonuniversal behavior of paraconductivity caused by predominant short-wavelength Gaussian fluctuations in YBa2Cu3O6.9

International Nuclear Information System (INIS)

Gauzzi, A.; Pavuna, D.

1995-01-01

We report on in-plane paraconductivity measurements in thin YBa 2 Cu 3 O 6.9 films. Our analysis of the data shows that the temperature dependence of paraconductivity is affected by lattice disorder and deviates at all temperatures from the universal power laws predicted by both scaling and mean-field theories. This gives evidence for the absence of critical fluctuations and for the failure of the Aslamazov-Larkin universal relation between critical exponent and dimensionality of the spectrum of Gaussian fluctuations. We account quantitatively for the data within the experimental error by introducing a short-wavelength cutoff into this spectrum. This implies that three-dimensional short-wavelength Gaussian fluctuations dominate in YBa 2 Cu 3 O 6.9 and suggests a rapid attenuation of these fluctuations with decreasing wavelength in short-coherence-length systems as compared to the case of the conventional Ginzburg-Landau theory

Very-short-term wind power probabilistic forecasts by sparse vector autoregression

DEFF Research Database (Denmark)

Dowell, Jethro; Pinson, Pierre

2016-01-01

A spatio-temporal method for producing very-shortterm parametric probabilistic wind power forecasts at a large number of locations is presented. Smart grids containing tens, or hundreds, of wind generators require skilled very-short-term forecasts to operate effectively, and spatial information...... is highly desirable. In addition, probabilistic forecasts are widely regarded as necessary for optimal power system management as they quantify the uncertainty associated with point forecasts. Here we work within a parametric framework based on the logit-normal distribution and forecast its parameters....... The location parameter for multiple wind farms is modelled as a vector-valued spatiotemporal process, and the scale parameter is tracked by modified exponential smoothing. A state-of-the-art technique for fitting sparse vector autoregressive models is employed to model the location parameter and demonstrates...

The impact of turbulent renewable energy production on power grid stability and quality

Science.gov (United States)

Schmietendorf, Katrin; Peinke, Joachim; Kamps, Oliver

2017-11-01

Feed-in fluctuations induced by renewables are one of the key challenges to the stability and quality of electrical power grids. In particular short-term fluctuations disturb the system on a time scale, on which load balancing does not operate yet and the system is intrinsically governed by self-organized synchronization. Wind and solar power are known to be strongly non-Gaussian with intermittent increment statistics in these time scales. We investigate the impact of short-term wind fluctuations on the basis of a Kuramoto-like power grid model considering stability in terms of desynchronization and frequency and voltage quality aspects. We present a procedure to generate realistic feed-in fluctuations with temporal correlations, Kolmogorov power spectrum and intermittent increments. By comparison to correlated Gaussian noise of the same spectrum and Gaussian white noise, we found out that while the correlations are essential to capture the likelihood of severe outages, the intermittent nature of wind power has significant consequences on power quality: intermittency is directly transferred into frequency and voltage fluctuations yielding a novel type of fluctuations, which is beyond engineering status of knowledge.

Economic evaluation of short-term wind power forecast in ERCOT. Preliminary results

Energy Technology Data Exchange (ETDEWEB)

Orwig, Kirsten D.; Hodge, Bri-Mathias; Brinkman, Greg; Ela, Erik; Milligan, Michael [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Banunarayanan, Venkat; Nasir, Saleh [ICF International, Fairfax, VA (United States); Freedman, Jeff [AWS Truepower, Albany, NY (United States)

2012-07-01

A number of wind energy integration studies have investigated the monetary value of using day-ahead wind power forecasts for grid operation decisions. Historically, these studies have shown that large cost savings could be gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter term (0- to 6-h ahead) wind power forecasts. In 2010, the Department of Energy and the National Oceanic and Atmospheric Administration partnered to form the Wind Forecasting Improvement Project (WFIP) to fund improvements in short-term wind forecasts and determine the economic value of these improvements to grid operators. In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined and the economic results of a production cost model simulation are analyzed. (orig.)

On the interplay between short and long term memory in the power-law cross-correlations setting

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2015-01-01

Roč. 421, č. 1 (2015), s. 218-222 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : Power-law cross-correlations * Long term memory * Short term memory Subject RIV: AH - Economics Impact factor: 1.785, year: 2015 http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452316.pdf

Ultra-Short-Term Wind-Power Forecasting Based on the Weighted Random Forest Optimized by the Niche Immune Lion Algorithm

Directory of Open Access Journals (Sweden)

Dongxiao Niu

2018-04-01

Full Text Available The continuous increase in energy consumption has made the potential of wind-power generation tremendous. However, the obvious intermittency and randomness of wind speed results in the fluctuation of the output power in a wind farm, seriously affecting the power quality. Therefore, the accurate prediction of wind power in advance can improve the ability of wind-power integration and enhance the reliability of the power system. In this paper, a model of wavelet decomposition (WD and weighted random forest (WRF optimized by the niche immune lion algorithm (NILA-WRF is presented for ultra-short-term wind power prediction. Firstly, the original serials of wind speed and power are decomposed into several sub-serials by WD because the original serials have no obvious day characteristics. Then, the model parameters are set and the model trained with the sub-serials of wind speed and wind power decomposed. Finally, the WD-NILA-WRF model is used to predict the wind power of the relative sub-serials and the result is reconstructed to obtain the final prediction result. The WD-NILA-WRF model combines the advantage of each single model, which uses WD for signal de-noising, and uses the niche immune lion algorithm (NILA to improve the model’s optimization efficiency. In this paper, two empirical analyses are carried out to prove the accuracy of the model, and the experimental results verify the proposed model’s validity and superiority compared with the back propagation neural network (BP neural network, support vector machine (SVM, RF and NILA-RF, indicating that the proposed method is superior in cases influenced by noise and unstable factors, and possesses an excellent generalization ability and robustness.

Short-term economics of virtual power plants

International Nuclear Information System (INIS)

Kok, J.K.

2009-08-01

The Virtual Power Plant (VPP) has gained an increasing interest over the last few years. A VPP is a flexible representation of a portfolio of Distributed Energy Resources (DER: distributed generation, demand response and electricity storage). One of the key activities of a VPP is the delivery of (near-)real-time balancing services. In order to operate such a (near-)real-time coordination activity optimally, the VPP needs to maintain a dynamic merit-order list of all DER participating in the VPP. In order to make optimal decisions based on this list, the merit order needs to be based on the true marginal cost (or marginal benefit in case of demand response) of the individual DER units. The marginal electricity costs of most types of DER are highly dependent on local context and, hence, change over time. From analysis of the short-term bid strategies of various DER units, the existence of a bid strategy spectrum becomes clear. On one end of the spectrum, bidding strategies are based straightforwardly on true marginal cost or benefit. Further along the spectrum, optimal bidding strategies become less dependent on marginal cost levels and more on the price dynamics in the (VPP) market context. These results are relevant for VPP operations both from business and technical perspectives.

Short-term Power Load Forecasting Based on Balanced KNN

Science.gov (United States)

Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei

2018-03-01

To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.

Control voltage and power fluctuations when connecting wind farms

Science.gov (United States)

Berinde, Ioan; Bǎlan, Horia; Oros Pop, Teodora Susana

2015-12-01

Voltage, frequency, active power and reactive power are very important parameters in terms of power quality. These parameters are followed when connecting any power plant, the more the connection of wind farms. Connecting wind farms to the electricity system must not cause interference outside the limits set by regulations. Modern solutions for fast and automatic voltage control and power fluctuations using electronic control systems of reactive power flows. FACTS (Flexible Alternating Current Transmision System) systems, established on the basis of power electronic circuits ensure control of electrical status quantities to achieve the necessary transfer of power to the power grid. FACTS devices can quickly control parameters and sizes of state power lines, such as impedance line voltages and phase angles of the voltages of the two ends of the line. Their use can lead to improvement in power system operation by increasing the transmission capacity of power lines, power flow control lines, improved static and transient stability reserve.

Control voltage and power fluctuations when connecting wind farms

International Nuclear Information System (INIS)

Berinde, Ioan; Bălan, Horia; Oros, Teodora Susana

2015-01-01

Voltage, frequency, active power and reactive power are very important parameters in terms of power quality. These parameters are followed when connecting any power plant, the more the connection of wind farms. Connecting wind farms to the electricity system must not cause interference outside the limits set by regulations. Modern solutions for fast and automatic voltage control and power fluctuations using electronic control systems of reactive power flows. FACTS (Flexible Alternating Current Transmision System) systems, established on the basis of power electronic circuits ensure control of electrical status quantities to achieve the necessary transfer of power to the power grid. FACTS devices can quickly control parameters and sizes of state power lines, such as impedance line voltages and phase angles of the voltages of the two ends of the line. Their use can lead to improvement in power system operation by increasing the transmission capacity of power lines, power flow control lines, improved static and transient stability reserve

Control voltage and power fluctuations when connecting wind farms

Energy Technology Data Exchange (ETDEWEB)

Berinde, Ioan, E-mail: ioan-berinde@yahoo.com; Bălan, Horia, E-mail: hbalan@mail.utcluj.ro; Oros, Teodora Susana, E-mail: teodoraoros-87@yahoo.com [Technical University of Cluj-Napoca, Romania, Faculty of Electrical Engineering, Department of Power Engineering and Management (Romania)

2015-12-23

Voltage, frequency, active power and reactive power are very important parameters in terms of power quality. These parameters are followed when connecting any power plant, the more the connection of wind farms. Connecting wind farms to the electricity system must not cause interference outside the limits set by regulations. Modern solutions for fast and automatic voltage control and power fluctuations using electronic control systems of reactive power flows. FACTS (Flexible Alternating Current Transmision System) systems, established on the basis of power electronic circuits ensure control of electrical status quantities to achieve the necessary transfer of power to the power grid. FACTS devices can quickly control parameters and sizes of state power lines, such as impedance line voltages and phase angles of the voltages of the two ends of the line. Their use can lead to improvement in power system operation by increasing the transmission capacity of power lines, power flow control lines, improved static and transient stability reserve.

Short-term optimal wind power generation capacity in liberalized electricity markets

International Nuclear Information System (INIS)

Olsina, Fernando; Roescher, Mark; Larisson, Carlos; Garces, Francisco

2007-01-01

Mainly because of environmental concerns and fuel price uncertainties, considerable amounts of wind-based generation capacity are being added to some deregulated power systems. The rapid wind development registered in some countries has essentially been driven by strong subsidizing programs. Since wind investments are commonly isolated from market signals, installed wind capacity can be higher than optimal, leading to distortions of the power prices with a consequent loss of social welfare. In this work, the influence of wind generation on power prices in the framework of a liberalized electricity market has been assessed by means of stochastic simulation techniques. The developed methodology allows investigating the maximal wind capacity that would be profitably deployed if wind investments were subject to market conditions only. For this purpose, stochastic variables determining power prices are accurately modeled. A test system resembling the size and characteristics of the German power system has been selected for this study. The expected value of the optimal, short-term wind capacity is evaluated for a considerable number of random realizations of power prices. The impact of dispersing the wind capacity over statistical independent wind sites has also been evaluated. The simulation results reveal that fuel prices, installation and financing costs of wind investments are very influential parameters on the maximal wind capacity that might be accommodated in a market-based manner

Power profiles and short-term visual performance of soft contact lenses.

Science.gov (United States)

Papas, Eric; Dahms, Anne; Carnt, Nicole; Tahhan, Nina; Ehrmann, Klaus

2009-04-01

To investigate the manner in which contemporary soft contact lenses differ in the distribution of optical power within their optic zones and establish if these variations affect the vision of wearers or the prescribing procedure for back vertex power (BVP). By using a Visionix VC 2001 contact lens power analyzer, power profiles were measured across the optic zones of the following contemporary contact lenses ACUVUE 2, ACUVUE ADVANCE, O2OPTIX, NIGHT & DAY and PureVision. Single BVP measures were obtained using a Nikon projection lensometer. Visual performance was assessed in 28 masked subjects who wore each lens type in random order. Measurements taken were high and low contrast visual acuity in normal illumination (250 Cd/m), high contrast acuity in reduced illumination (5 Cd/m), subjective visual quality using a numerical rating scale, and visual satisfaction rating using a Likert scale. Marked differences in the distribution of optical power across the optic zone were evident among the lens types. No significant differences were found for any of the visual performance variables (p > 0.05, analysis of variance with repeated measures and Friedman test). Variations in power profile between contemporary soft lens types exist but do not, in general, result in measurable visual performance differences in the short term, nor do they substantially influence the BVP required for optimal correction.

Energy storage system in medium-sized voltage lines for the integration of decentralized fluctuating energy sources; Energiespeicher im Niederspannungsnetz zur Integration dezentraler, fluktuierender Energiequellen

Energy Technology Data Exchange (ETDEWEB)

Bodach, M.

2006-06-30

The solar radiation fluctuates due to atmospheric and planetary influences. Concerning PV systems, the changes from dark clouds to clear sky result in fast and very deep fluctuations of the time behaviour of the power output fed into the low voltage (LV) network by DC-AC-Converters. On the example of a daily recorded global radiation curve with a very short sampling time (regular interval time 1 s) the paper shows that short-term sags of the solar radiation are possible up to 80% of the previous value as a result of sudden and intensive changes of the density of the clouds. These disturbances of the quality of the generated electric power are directly transformed into the LV grids. If the number of PV systems connected to existing LV networks rises essentially, the fluctuating photovoltaic energy generation will achieve a very high importance and therefore not only the well-known, but also a lot of new problems will occur. They have already been investigated theoretically in different papers and they have also been proven quantitatively by own simulations. Improvements of the energy quality at the point of common coupling will be possible if the grid-coupled PV power plants are supplemented with suitable intelligent storage systems bridging the short-term sags. So the influence of the fluctuating radiation on the generated power can be fundamentally reduced. The developed intelligent short-term storage system smoothes out the generated power of the PV system by means of a storage. It is based on the very high capacity of an electric double layer (UltraCap, produced by EPCOS) and includes a complex electronic control system. The UltraCap has the required storing characteristics and has been adjusted to the system voltage by a highly sophisticated microprocessor controlled DC/DC-converter system. Such an intelligent storage system can also be used for the connection of other decentralised power generation units (e.g. fuel cells, block-unit heating power plant) to the

Short term economic emission power scheduling of hydrothermal energy systems using improved water cycle algorithm

International Nuclear Information System (INIS)

Haroon, S.S.; Malik, T.N.

2017-01-01

Due to the increasing environmental concerns, the demand of clean and green energy and concern of atmospheric pollution is increasing. Hence, the power utilities are forced to limit their emissions within the prescribed limits. Therefore, the minimization of fuel cost as well as exhaust gas emissions is becoming an important and challenging task in the short-term scheduling of hydro-thermal energy systems. This paper proposes a novel algorithm known as WCA-ER (Water Cycle Algorithm with Evaporation Rate) to inspect the short term EEPSHES (Economic Emission Power Scheduling of Hydrothermal Energy Systems). WCA has its ancestries from the natural hydrologic cycle i.e. the raining process forms streams and these streams start flowing towards the rivers which finally flow towards the sea. The worth of WCA-ER has been tested on the standard economic emission power scheduling of hydrothermal energy test system consisting of four hydropower and three thermal plants. The problem has been investigated for the three case studies (i) ECS (Economic Cost Scheduling), (ii) ES (Economic Emission Scheduling) and (iii) ECES (Economic Cost and Emission Scheduling). The results obtained show that WCA-ER is superior to many other methods in the literature in bringing lower fuel cost and emissions. (author)

Implementing a short-term loyalty program : case: Bosch Lawn & Garden and the Ventum short-term loyalty program

OpenAIRE

Logvinova, Veronika

2015-01-01

In 2015, one of the Bosch Home and Garden divisions, Bosch Lawn and Garden, has made a strategic decision to adopt a points-based short-term loyalty program called Ventum LG in the German supermarkets and petrol stations. It was decided that the base of this program will be completed Ventum PT short-term loyalty program which was managed by another division, Bosch Power Tools, and proved to be successful. This thesis aims to evaluate the worthiness of the Ventum LG loyalty program for Bosch L...

Long term persistence in the sea surface temperature fluctuations

OpenAIRE

Monetti, Roberto A.; Havlin, Shlomo; Bunde, Armin

2002-01-01

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific oceans. We apply a method that systematically overcome possible trends in the data. We find that the SST persistence, characterized by the correlation $C(s)$ of temperature fluctuations separated by a time period $s$, displays two different regimes. In the short-time regime which extends up to roughly 10 months, the temperature fluctuations display a...

A review on the young history of the wind power short-term prediction

Energy Technology Data Exchange (ETDEWEB)

Costa, Alexandre; Navarro, Jorge [Wind Energy, Division of Renewable Energies, Department of Energy, CIEMAT, Av. Complutense, 22, Ed. 42, 28044 Madrid (Spain); Crespo, Antonio [Laboratorio de Mecanica de Fluidos, Departmento de Ingenieria Energetica y Fluidomecanica, ETSII, Universidad Politecnica de Madrid, C/Jose Gutierrez Abascal, 2-28006 Madrid (Spain); Lizcano, Gil [Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY (United Kingdom); Madsen, Henrik [Informatics and Mathematical Modelling - IMM, Technical University of Denmark, Richard Petersens Plads, Building 321, Office 019, 2800 Kgs. Lyngby (Denmark); Feitosa, Everaldo [Brazilian Wind Energy Centre - CBEE, Centro de Tecnologia e Geociencias, UFPE-50.740-530 Recife, PE (Brazil)

2008-08-15

This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art on models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect) of each model. On the basis of the review, some topics for future research are pointed out. (author)

Excitation of short-scale fluctuations by parametric decay of helicon waves into ion-sound and Trivelpiece-Gould waves

International Nuclear Information System (INIS)

Lorenz, B; Kraemer, M; Selenin, V L; Aliev, Yu M

2005-01-01

The helicon wave field and the excitation of short-scale electrostatic fluctuations in a helicon-produced plasma are closely related as both the helicon wave damping and the fluctuation level are shown to increase with the launched rf power. Correlation methods using electrostatic probes as well as microwave back-scattering at the upper-hybrid resonance are applied to obtain the dispersion relations of the fluctuations in the low-frequency and high-frequency ranges. The frequency and wavenumber spectra measured for all components of the wave vector allow us to identify the fluctuations as ion-sound and Trivelpiece-Gould waves that originate from parametric decay of the helicon pump wave. The growth rates and thresholds inferred from the evolution of the fluctuations in a wide range of helicon plasma parameters are in good agreement with predictions for the parametric decay instability that takes into account realistic damping rates for the decay waves as well as non-vanishing parallel wavenumber of the helicon pump

Correlation structures in short-term variabilities of stock indices and exchange rates

Science.gov (United States)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

A fast network solution by the decoupled procedure during short-term dynamic processes in power systems

Energy Technology Data Exchange (ETDEWEB)

Popovic, D P; Stefanovic, M D [Nikola Tesla Inst., Belgrade (YU). Power System Dept.

1990-01-01

A simple, fast and reliable decoupled procedure for solving the network problems during short-term dynamic processes in power systems is presented. It is based on the Newton-Raphson method applied to the power balance equations, which include the effects of generator saliency and non-impedance loads, with further modifications resulting from the physical properties of the phenomena under study. The good convergence characteristics of the developed procedure are demonstrated, and a comparison is made with the traditional method based on the current equation and the triangularized admittance matrix, using the example of stability analysis of the Yugoslav power grid. (author).

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

Directory of Open Access Journals (Sweden)

Wen-Yeau Chang

2013-09-01

Full Text Available High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO based hybrid forecasting method for short-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network, and the radial basis function (RBF neural network. The EPSO algorithm is employed to optimize the weight coefficients in the hybrid forecasting method. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a wind energy conversion system (WECS installed on the Taichung coast of Taiwan. Comparisons of forecasting performance are made with the individual forecasting methods. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.

Effect of low dose, short-term creatine supplementation on muscle power output in elite youth soccer players.

Science.gov (United States)

Yáñez-Silva, Aquiles; Buzzachera, Cosme F; Piçarro, Ivan Da C; Januario, Renata S B; Ferreira, Luis H B; McAnulty, Steven R; Utter, Alan C; Souza-Junior, Tacito P

2017-01-01

To determine the effects of a low dose, short-term Creatine monohydrate (Cr) supplementation (0.03 g.kg.d -1 during 14 d) on muscle power output in elite youth soccer players. Using a two-group matched, double blind, placebo-controlled design, nineteen male soccer players (mean age = 17.0 ± 0.5 years) were randomly assigned to either Cr ( N  = 9) or placebo ( N  = 10) group. Before and after supplementation, participants performed a 30s Wingate Anaerobic Test (WAnT) to assess peak power output (PPO), mean power output (MPO), fatigue index (FI), and total work. There were significant increases in both PPO and MPO after the Cr supplementation period ( P  ≤ 0.05) but not the placebo period. There were also significant increases in total work, but not FI, after the Cr supplementation and placebo periods ( P  ≤ 0.05). Notably, there were differences in total work between the Cr and placebo groups after ( P  ≤ 0.05) but not before the 14 d supplementation period. There is substantial evidence to indicate that a low-dose, short-term oral Cr supplementation beneficially affected muscle power output in elite youth soccer players.

Short term scheduling of multiple grid-parallel PEM fuel cells for microgrid applications

Energy Technology Data Exchange (ETDEWEB)

El-Sharkh, M.Y.; Rahman, A.; Alam, M.S. [Dept. of Electrical and Computer Engineering, University of South Alabama, Mobile, AL 36688 (United States)

2010-10-15

This paper presents a short term scheduling scheme for multiple grid-parallel PEM fuel cell power plants (FCPPs) connected to supply electrical and thermal energy to a microgrid community. As in the case of regular power plants, short term scheduling of FCPP is also a cost-based optimization problem that includes the cost of operation, thermal power recovery, and the power trade with the local utility grid. Due to the ability of the microgrid community to trade power with the local grid, the power balance constraint is not applicable, other constraints like the real power operating limits of the FCPP, and minimum up and down time are therefore used. To solve the short term scheduling problem of the FCPPs, a hybrid technique based on evolutionary programming (EP) and hill climbing technique (HC) is used. The EP is used to estimate the optimal schedule and the output power from each FCPP. The HC technique is used to monitor the feasibility of the solution during the search process. The short term scheduling problem is used to estimate the schedule and the electrical and thermal power output of five FCPPs supplying a maximum power of 300 kW. (author)

Application of VSC-HVDC with Shunt Connected SMES for Compensation of Power Fluctuation

Science.gov (United States)

Linn, Zarchi; Kakigano, Hiroaki; Miura, Yushi; Ise, Toshifumi

This paper describes the application of VSC-HVDC (High Voltage DC Transmission using Voltage Source Converter) with shunt connected SMES (Superconducting Magnetic Energy Storage) for compensation of power fluctuation caused by fluctuating power source such as photovoltaics and wind turbines. The objectives of this proposed system is to smooth out fluctuating power in one terminal side of HVDC in order to avoid causing power system instability and frequency deviation by absorbing or providing power according to the system requirement while another terminal side power is fluctuated. The shunt connected SMES charges and discharges the energy to and from the dc side and it compensates required power of fluctuation to obtain constant power flow in one terminal side of VSC-HVDC system. This system configuration has ability for power system stabilization in the case of power fluctuation from natural energy source. PSCAD/EMTDC simulation is used to evaluate the performance of applied system configuration and control method.

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

Improving the principles of short-term electric load forecasting of the Irkutsk region

Directory of Open Access Journals (Sweden)

Kornilov Vladimir

2017-01-01

Full Text Available Forecasting of electric load (EL is an important task for both electric power entities and large consumers of electricity [1]. Large consumers are faced with the need to compose applications for the planned volume of EL, and the deviation of subsequent real consumption from previously announced leads to the appearance of penalties from the wholesale market. In turn, electricity producers are interested in forecasting the demand for electricity for prompt response to its fluctuations and for the purpose of optimal infrastructure development. The most difficult and urgent task is the hourly forecasting of EL, which is extremely important for the successful solution of problems of optimization of generating capacities, minimization of power losses, dispatching control, security assessment of power supply, etc. Ultimately, such forecasts allow optimizing the cash costs for electricity and fuel or water consumption during generation. This paper analyzes the experience of the branch of JSC "SO UPS" Irkutsk Regional Dispatch Office of the procedure for short-term forecasting of the EL of the Irkutsk region.

Short-term electric power demand forecasting based on economic-electricity transmission model

Science.gov (United States)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

Science.gov (United States)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Short-term LNG-markets

International Nuclear Information System (INIS)

Eldegard, Tom; Lund, Arne-Christian; Miltersen, Kristian; Rud, Linda

2005-01-01

The global Liquefied Natural Gas (LNG) industry has experienced substantial growth in the past decades. In the traditional trade patterns of LNG the product has typically been handled within a dedicated chain of plants and vessels fully committed by long term contracts or common ownership, providing risk sharing of large investments in a non-liquid market. Increasing gas prices and substantial cost reductions in all parts of the LNG chain have made LNG projects viable even if only part of the capacity is secured by long-term contracts, opening for more flexible trade of the remainder. Increasing gas demand, especially in power generation, combined with cost reductions in the cost of LNG terminals, open new markets for LNG. For the LNG supplier, the flexibility of shifting volumes between regions represents an additional value. International trade in LNG has been increasing, now accounting for more than one fifth of the world's cross-border gas trade. Despite traditional vertical chain bonds, increased flexibility has contributed in fact to an increasing LNG spot trade, representing 8% of global trade in 2002. The focus of this paper is on the development of global short-term LNG markets, and their role with respect to efficiency and security of supply in European gas markets. Arbitrage opportunities arising from price differences between regional markets (such as North America versus Europe) are important impetuses for flexible short-term trade. However, the short-term LNG trade may suffer from problems related to market access, e.g. limited access to terminals and regulatory issues, as well as rigidities connected to vertical binding within the LNG chain. Important issues related to the role of short-term LNG-trade in the European gas market are: Competition, flexibility in meeting peak demand, security of supply and consequences of differences in pricing policies (oil-linked prices in Europe and spot market prices in North America). (Author)

Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool

International Nuclear Information System (INIS)

Nomikos, Nikos K.; Soldatos, Orestes A.

2010-01-01

In this paper we propose a three-factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the Scandinavian power market. In this model both short and long-run factors are unobservable and are hence estimated as latent variables using the Kalman filter. The proposed model has several advantages. First, it seems to capture in a parsimonious way the most important risks that practitioners face in the market, such as spike risk, short-term risk and long-term risk. Second, it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices, particularly for long-dated forward contracts. Finally, closed-form solutions for forward contracts, derived from the model, are consistent with the fact that the correlation between contracts of different maturities is imperfect. The resulting model is very promising, providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long-dated contracts.

Health Effects of Short-Term Fluctuations in Macroeconomic Conditions: The Case of Hypertension for Older Americans.

Science.gov (United States)

Angrisani, Marco; Lee, Jinkook

2016-11-01

We investigate the health effects of short-term macroeconomic fluctuations as described by changes in unemployment rate, house, and stock market price indexes. The 'Great Recession' provides the opportunity to conduct this analysis as it involved contemporaneous shocks to the labor, housing, and stock markets. Using panel data from the Health and Retirement Study over the period 2004-2010, we relate changes in hypertension status to changes in state-level unemployment rate and house prices and to changes in stock market prices. We consider hypertension, a disease related to stress and of high prevalence among older adults, that has received little attention in the literature linking macroeconomic conditions to individual health. Our analysis exploits self-reports of hypertension diagnosis as well as directly measured blood pressure readings. Using both measures, we find that the likelihood of developing hypertension is negatively related to changes in house prices. Also, decreasing house prices lower the probability of stopping hypertension medication treatment for individuals previously diagnosed with the condition. We do not observe significant associations between hypertension and either changes in unemployment rate or stock market prices. We document heterogeneity in the estimated health effects of the recession by gender, education, asset ownership, and work status. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model

Directory of Open Access Journals (Sweden)

Wenlei Bai

2017-12-01

Full Text Available The deterministic methods generally used to solve DC optimal power flow (OPF do not fully capture the uncertainty information in wind power, and thus their solutions could be suboptimal. However, the stochastic dynamic AC OPF problem can be used to find an optimal solution by fully capturing the uncertainty information of wind power. That uncertainty information of future wind power can be well represented by the short-term future wind power scenarios that are forecasted using the generalized dynamic factor model (GDFM—a novel multivariate statistical wind power forecasting model. Furthermore, the GDFM can accurately represent the spatial and temporal correlations among wind farms through the multivariate stochastic process. Fully capturing the uncertainty information in the spatially and temporally correlated GDFM scenarios can lead to a better AC OPF solution under a high penetration level of wind power. Since the GDFM is a factor analysis based model, the computational time can also be reduced. In order to further reduce the computational time, a modified artificial bee colony (ABC algorithm is used to solve the AC OPF problem based on the GDFM forecasting scenarios. Using the modified ABC algorithm based on the GDFM forecasting scenarios has resulted in better AC OPF’ solutions on an IEEE 118-bus system at every hour for 24 h.

Simple and reliable procedure for the evaluation of short-term dynamic processes in power systems

Energy Technology Data Exchange (ETDEWEB)

Popovic, D P

1986-10-01

An efficient approach is presented to the solution of the short-term dynamics model in power systems. It consists of an adequate algebraic treatment of the original system of nonlinear differential equations, using linearization, decomposition and Cauchy's formula. The simple difference equations obtained in this way are incorporated into a model of the electrical network, which is of a low order compared to the ones usually used. Newton's method is applied to the model formed in this way, which leads to a simple and reliable iterative procedure. The characteristics of the procedure developed are demonstrated on examples of transient stability analysis of real power systems. 12 refs.

Probabilistic forecasting of wind power at the minute time-scale with Markov-switching autoregressive models

DEFF Research Database (Denmark)

Pinson, Pierre; Madsen, Henrik

2008-01-01

Better modelling and forecasting of very short-term power fluctuations at large offshore wind farms may significantly enhance control and management strategies of their power output. The paper introduces a new methodology for modelling and forecasting such very short-term fluctuations. The proposed...... consists in 1-step ahead forecasting exercise on time-series of wind generation with a time resolution of 10 minute. The quality of the introduced forecasting methodology and its interest for better understanding power fluctuations are finally discussed....... methodology is based on a Markov-switching autoregressive model with time-varying coefficients. An advantage of the method is that one can easily derive full predictive densities. The quality of this methodology is demonstrated from the test case of 2 large offshore wind farms in Denmark. The exercise...

Work and power fluctuations in a critical heat engine

Science.gov (United States)

Holubec, Viktor; Ryabov, Artem

2017-09-01

We investigate fluctuations of output work for a class of Stirling heat engines with working fluid composed of interacting units and compare these fluctuations to an average work output. In particular, we focus on engine performance close to a critical point where Carnot's efficiency may be attained at a finite power as reported by M. Campisi and R. Fazio [Nat. Commun. 7, 11895 (2016), 10.1038/ncomms11895]. We show that the variance of work output per cycle scales with the same critical exponent as the heat capacity of the working fluid. As a consequence, the relative work fluctuation diverges unless the output work obeys a rather strict scaling condition, which would be very hard to fulfill in practice. Even under this condition, the fluctuations of work and power do not vanish in the infinite system size limit. Large fluctuations of output work thus constitute inseparable and dominant element in performance of the macroscopic heat engines close to a critical point.

Work and power fluctuations in a critical heat engine.

Science.gov (United States)

Holubec, Viktor; Ryabov, Artem

2017-09-01

We investigate fluctuations of output work for a class of Stirling heat engines with working fluid composed of interacting units and compare these fluctuations to an average work output. In particular, we focus on engine performance close to a critical point where Carnot's efficiency may be attained at a finite power as reported by M. Campisi and R. Fazio [Nat. Commun. 7, 11895 (2016)2041-172310.1038/ncomms11895]. We show that the variance of work output per cycle scales with the same critical exponent as the heat capacity of the working fluid. As a consequence, the relative work fluctuation diverges unless the output work obeys a rather strict scaling condition, which would be very hard to fulfill in practice. Even under this condition, the fluctuations of work and power do not vanish in the infinite system size limit. Large fluctuations of output work thus constitute inseparable and dominant element in performance of the macroscopic heat engines close to a critical point.

Trading wind generation from short-term probabilistic forecasts of wind power

DEFF Research Database (Denmark)

Pinson, Pierre; Chevallier, Christophe; Kariniotakis, Georges

2007-01-01

Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue......, as well as on modeling of the sensitivity a wind power producer may have to regulation costs. The benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi-MW wind farm in the Dutch electricity market over a year....... participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation...

Long-term competitive dynamics of two cryptic rotifer species: diapause and fluctuating conditions.

Directory of Open Access Journals (Sweden)

Carmen Gabaldón

Full Text Available Life-history traits may have an important role in promoting species coexistence. However, the complexity of certain life cycles makes it difficult to draw conclusions about the conditions for coexistence or exclusion based on the study of short-term competitive dynamics. Brachionus plicatilis and B. manjavacasare two cryptic rotifer species co-occurring in many lakes on the Iberian Peninsula. They have a complex life cycle in which cyclical parthenogenesis occurs with diapausing stages being the result of sexual reproduction. B. plicatilis and B. manjavacasare identical in morphology and size, their biotic niches are broadly overlapping, and they have similar competitive abilities. However, the species differ in life-history traits involving sexual reproduction and diapause, and respond differently to salinity and temperature. As in the case of certain other species that are extremely similar in morphology, a fluctuating environment are considered to be important for their coexistence. We studied the long-term competitive dynamics of B. plicatilis and B. manjavacas under different salinity regimes (constant and fluctuating. Moreover, we focused on the dynamics of the diapausing egg bank to explore how the outcome of the entire life cycle of these rotifers can work to mediate stable coexistence. We demonstrated that these species do not coexist under constant-salinity environment, as the outcome of competition is affected by the level of salinity-at low salinity, B. plicatilis excluded B. manjavacas, and the opposite outcome occurred at high salinity. Competitive dynamics under fluctuating salinity showed that the dominance of one species over the other also tended to fluctuate. The duration of co-occurrence of these species was favoured by salinity fluctuation and perhaps by the existence of a diapausing egg bank. Stable coexistence was not found in our system, which suggests that other factors or other salinity fluctuation patterns might act as

Long-term competitive dynamics of two cryptic rotifer species: diapause and fluctuating conditions.

Science.gov (United States)

Gabaldón, Carmen; Carmona, María José; Montero-Pau, Javier; Serra, Manuel

2015-01-01

Life-history traits may have an important role in promoting species coexistence. However, the complexity of certain life cycles makes it difficult to draw conclusions about the conditions for coexistence or exclusion based on the study of short-term competitive dynamics. Brachionus plicatilis and B. manjavacasare two cryptic rotifer species co-occurring in many lakes on the Iberian Peninsula. They have a complex life cycle in which cyclical parthenogenesis occurs with diapausing stages being the result of sexual reproduction. B. plicatilis and B. manjavacasare identical in morphology and size, their biotic niches are broadly overlapping, and they have similar competitive abilities. However, the species differ in life-history traits involving sexual reproduction and diapause, and respond differently to salinity and temperature. As in the case of certain other species that are extremely similar in morphology, a fluctuating environment are considered to be important for their coexistence. We studied the long-term competitive dynamics of B. plicatilis and B. manjavacas under different salinity regimes (constant and fluctuating). Moreover, we focused on the dynamics of the diapausing egg bank to explore how the outcome of the entire life cycle of these rotifers can work to mediate stable coexistence. We demonstrated that these species do not coexist under constant-salinity environment, as the outcome of competition is affected by the level of salinity-at low salinity, B. plicatilis excluded B. manjavacas, and the opposite outcome occurred at high salinity. Competitive dynamics under fluctuating salinity showed that the dominance of one species over the other also tended to fluctuate. The duration of co-occurrence of these species was favoured by salinity fluctuation and perhaps by the existence of a diapausing egg bank. Stable coexistence was not found in our system, which suggests that other factors or other salinity fluctuation patterns might act as stabilizing

A theory of power-law distributions in financial market fluctuations.

Science.gov (United States)

Gabaix, Xavier; Gopikrishnan, Parameswaran; Plerou, Vasiliki; Stanley, H Eugene

2003-05-15

Insights into the dynamics of a complex system are often gained by focusing on large fluctuations. For the financial system, huge databases now exist that facilitate the analysis of large fluctuations and the characterization of their statistical behaviour. Power laws appear to describe histograms of relevant financial fluctuations, such as fluctuations in stock price, trading volume and the number of trades. Surprisingly, the exponents that characterize these power laws are similar for different types and sizes of markets, for different market trends and even for different countries--suggesting that a generic theoretical basis may underlie these phenomena. Here we propose a model, based on a plausible set of assumptions, which provides an explanation for these empirical power laws. Our model is based on the hypothesis that large movements in stock market activity arise from the trades of large participants. Starting from an empirical characterization of the size distribution of those large market participants (mutual funds), we show that the power laws observed in financial data arise when the trading behaviour is performed in an optimal way. Our model additionally explains certain striking empirical regularities that describe the relationship between large fluctuations in prices, trading volume and the number of trades.

Simulation of power fluctuation of wind farms based on frequency domain

DEFF Research Database (Denmark)

Lin, Jin; Sun, Yuanzhang; Li, Guojie

2011-01-01

, however, is incapable of completely explaining the physical mechanism of randomness of power fluctuation. To remedy such a situation, fluctuation modeling based on the frequency domain is proposed. The frequency domain characteristics of stochastic fluctuation on large wind farms are studied using...... the power spectral density of wind speed, the frequency domain model of a wind power generator and the information on weather and geography of the wind farms. The correctness and effectiveness of the model are verified by comparing the measurement data with simulation results of a certain wind farm. © 2011...

Towards uncovering the structure of power fluctuations of wind farms.

Science.gov (United States)

Liu, Huiwen; Jin, Yaqing; Tobin, Nicolas; Chamorro, Leonardo P

2017-12-01

The structure of the turbulence-driven power fluctuations in a wind farm is fundamentally described from basic concepts. A derived tuning-free model, supported with experiments, reveals the underlying spectral content of the power fluctuations of a wind farm. It contains two power-law trends and oscillations in the relatively low- and high-frequency ranges. The former is mostly due to the turbulent interaction between the flow and the turbine properties, whereas the latter is due to the advection between turbine pairs. The spectral wind-farm scale power fluctuations Φ_{P} exhibit a power-law decay proportional to f^{-5/3-2} in the region corresponding to the turbulence inertial subrange and at relatively large scales, Φ_{P}∼f^{-2}. Due to the advection and turbulent diffusion of large-scale structures, a spectral oscillation exists with the product of a sinusoidal behavior and an exponential decay in the frequency domain.

Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

Directory of Open Access Journals (Sweden)

Yimei Wang

2018-04-01

Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

Medium-term fluctuations and the "Great Ratios" of economic growth

DEFF Research Database (Denmark)

Groth, Christian; Madsen, Jakob B.

2016-01-01

Evidence for the OECD countries show that the “great ratios”, such as the unemployment rate, factor shares, Tobin’s q and the investment-capital ratio, fluctuate significantly on medium-term frequencies of 10-40 years duration. To explain these medium-term fluctuations, we establish a macro...

Localized Spectral Analysis of Fluctuating Power Generation from Solar Energy Systems

Directory of Open Access Journals (Sweden)

Johan Nijs

2007-01-01

Full Text Available Fluctuations in solar irradiance are a serious obstacle for the future large-scale application of photovoltaics. Occurring regularly with the passage of clouds, they can cause unexpected power variations and introduce voltage dips to the power distribution system. This paper proposes the treatment of such fluctuating time series as realizations of a stochastic, locally stationary, wavelet process. Its local spectral density can be estimated from empirical data by means of wavelet periodograms. The wavelet approach allows the analysis of the amplitude of fluctuations per characteristic scale, hence, persistence of the fluctuation. Furthermore, conclusions can be drawn on the frequency of occurrence of fluctuations of different scale. This localized spectral analysis was applied to empirical data of two successive years. The approach is especially useful for network planning and load management of power distribution systems containing a high density of photovoltaic generation units.

Comparing the Effectiveness of a Short-Term Vertical Jump vs. Weightlifting Program on Athletic Power Development.

Science.gov (United States)

Teo, Shaun Y M; Newton, Michael J; Newton, Robert U; Dempsey, Alasdair R; Fairchild, Timothy J

2016-10-01

Teo, SYM, Newton, MJ, Newton, RU, Dempsey, AR, and Fairchild, TJ. Comparing the effectiveness of a short-term vertical jump vs. weightlifting program on athletic power development. J Strength Cond Res 30(10): 2741-2748, 2016-Efficient training of neuromuscular power and the translation of this power to sport-specific tasks is a key objective in the preparation of athletes involved in team-based sports. The purpose of this study was to compare changes in center of mass (COM) neuromuscular power and performance of sport-specific tasks after short-term (6-week) training adopting either Olympic-style weightlifting (WL) exercises or vertical jump (VJ) exercises. Twenty-six recreationally active men (18-30 years; height: 178.7 ± 8.3 cm; mass: 78.6 ± 12.2 kg) were randomly allocated to either a WL or VJ training group and performance during the countermovement jump (CMJ), squat jump (SJ), depth jump (DJ), 20-m sprint, and the 5-0-5 agility test-assessed pre and posttraining. Despite the WL group demonstrating larger increases in peak power output during the CMJ (WL group: 10% increase, d = 0.701; VJ group: 5.78% increase, d = 0.328) and SJ (WL group: 12.73% increase, d = 0.854; VJ group: 7.27% increase, d = 0.382), no significant between-group differences were observed in any outcome measure studied. There was a significant main effect of time observed for the 3 VJs (CMJ, SJ, and DJ), 0- to 5-m and 0- to 20-m sprint times, and the 5-0-5 agility test time, which were all shown to improve after the training (all main effects of time p sports, even in athletes with limited preseason training periods.

Short-term forecasting model for aggregated regional hydropower generation

International Nuclear Information System (INIS)

Monteiro, Claudio; Ramirez-Rosado, Ignacio J.; Fernandez-Jimenez, L. Alfredo

2014-01-01

Highlights: • Original short-term forecasting model for the hourly hydropower generation. • The use of NWP forecasts allows horizons of several days. • New variable to represent the capacity level for generating hydroelectric energy. • The proposed model significantly outperforms the persistence model. - Abstract: This paper presents an original short-term forecasting model of the hourly electric power production for aggregated regional hydropower generation. The inputs of the model are previously recorded values of the aggregated hourly production of hydropower plants and hourly water precipitation forecasts using Numerical Weather Prediction tools, as well as other hourly data (load demand and wind generation). This model is composed of three modules: the first one gives the prediction of the “monthly” hourly power production of the hydropower plants; the second module gives the prediction of hourly power deviation values, which are added to that obtained by the first module to achieve the final forecast of the hourly hydropower generation; the third module allows a periodic adjustment of the prediction of the first module to improve its BIAS error. The model has been applied successfully to the real-life case study of the short-term forecasting of the aggregated hydropower generation in Spain and Portugal (Iberian Peninsula Power System), achieving satisfactory results for the next-day forecasts. The model can be valuable for agents involved in electricity markets and useful for power system operations

Temporal structure of aggregate power fluctuations in large-eddy simulations of extended wind-farms

NARCIS (Netherlands)

Stevens, Richard Johannes Antonius Maria; Meneveau, Charles

2014-01-01

Fluctuations represent a major challenge for the incorporation of electric power from large wind-farms into power grids. Wind-farm power output fluctuates strongly in time, over various time scales. Understanding these fluctuations, especially their spatio-temporal characteristics, is particularly

Entropy method combined with extreme learning machine method for the short-term photovoltaic power generation forecasting

International Nuclear Information System (INIS)

Tang, Pingzhou; Chen, Di; Hou, Yushuo

2016-01-01

As the world’s energy problem becomes more severe day by day, photovoltaic power generation has opened a new door for us with no doubt. It will provide an effective solution for this severe energy problem and meet human’s needs for energy if we can apply photovoltaic power generation in real life, Similar to wind power generation, photovoltaic power generation is uncertain. Therefore, the forecast of photovoltaic power generation is very crucial. In this paper, entropy method and extreme learning machine (ELM) method were combined to forecast a short-term photovoltaic power generation. First, entropy method is used to process initial data, train the network through the data after unification, and then forecast electricity generation. Finally, the data results obtained through the entropy method with ELM were compared with that generated through generalized regression neural network (GRNN) and radial basis function neural network (RBF) method. We found that entropy method combining with ELM method possesses higher accuracy and the calculation is faster.

A Novel Short-Term Maintenance Strategy for Power Transmission and Transformation Equipment Based on Risk-Cost-Analysis

Directory of Open Access Journals (Sweden)

Hang Yang

2017-11-01

Full Text Available Current studies on preventive condition-based maintenance of power transmission and transformation equipment mainly focus on mid-term or long-term maintenance, and cannot meet the requirements of short-term especially temporary maintenance. In order to solve the defects of the present preventive maintenance strategies, according to the engineering application and based on risk-cost analysis, a short-term maintenance strategy is proposed in this manuscript. For the equipment working in bad health condition, its active maintenance costs and operation risk costs are evaluated, respectively. Then the latest maintenance time is calculated in accordance with the principle that its operation risk costs are no higher than active maintenance costs. Utilizing the latest maintenance time, the best maintenance time is calculated by setting the maximum relative earnings of postponing maintenance as the target, which provides the operation staffs with comprehensive maintenance-decision support. In the end, different cases on the IEEE 24-bus system are simulated. The effectiveness and advantages of the proposed strategy are demonstrated by the simulation results.

Robust short-term memory without synaptic learning.

Directory of Open Access Journals (Sweden)

Samuel Johnson

Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust short-term memory without synaptic learning.

Science.gov (United States)

Johnson, Samuel; Marro, J; Torres, Joaquín J

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust Short-Term Memory without Synaptic Learning

Science.gov (United States)

Johnson, Samuel; Marro, J.; Torres, Joaquín J.

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

A survey of short-term and long-term stability of tube parameters in a mammography unit

Directory of Open Access Journals (Sweden)

Praskalo Jovica Ž.

2014-01-01

Full Text Available In order to set up a successful mammography screening program in the Republic of Srpska, a Siemens Mammomat 1000 X-ray machine was selected for analysis as the said mammography system is widely used in clinical practice. The variations in tube parameters (specific air kerma, high-voltage accuracy and reproducibility, linearity between exposure and dose exposure time were monitored over a five-year period, from 2008 to 2012. In addition, due to observed daily fluctuations for chosen parameters, a series of measurements were performed three times a day within a single-month period (mainly October 2012. The goal of such an experimental set up is to assess short-term and long-term stability of tube parameters in the given mammography unit and to make a comparison between them. The present paper shows how an early detection of significant parameter fluctuations can help eliminate irregularities and optimize the performance of mammography systems. [Projekat Ministarstva nauke Republike Srbije, br. 171007

Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

Energy Technology Data Exchange (ETDEWEB)

Stewart, Ian B.; Arendt, Dustin L.; Bell, Eric B.; Volkova, Svitlana

2017-05-17

Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. This work addresses several important tasks of visualizing and predicting short term text representation shift, i.e. the change in a word’s contextual semantics. We study the relationship between short-term concept drift and representation shift on a large social media corpus – VKontakte collected during the Russia-Ukraine crisis in 2014 – 2015. We visualize short-term representation shift for example keywords and build predictive models to forecast short-term shifts in meaning from previous meaning as well as from concept drift. We show that short-term representation shift can be accurately predicted up to several weeks in advance and that visualization provides insight into meaning change. Our approach can be used to explore and characterize specific aspects of the streaming corpus during crisis events and potentially improve other downstream classification tasks including real-time event forecasting in social media.

Audit of long-term and short-term liabilities

Directory of Open Access Journals (Sweden)

Korinko M.D.

2017-03-01

Full Text Available The article determines the importance of long-term and short-term liabilities for the management of financial and material resources of an enterprise. It reviews the aim, objects and information generators for realization of audit of short-term and long-term obligations. The organizing and methodical providing of audit of long-term and short-term liabilities of an enterprise are generalized. The authors distinguish the stages of realization of audit of long-term and short-term liabilities, the aim of audit on each of the presented stages, and recommend methodical techniques. It is fixed that it is necessary to conduct the estimation of the systems of internal control and record-keeping of an enterprise by implementation of public accountant procedures for determination of volume and maintenance of selection realization. After estimating the indicated systems, a public accountant determines the methodology for realization of public accountant verification of long-term and short-term liabilities. The analytical procedures that public accountants are expedient to use for realization of audit of short-term and long-term obligations are determined. The authors suggest the classification of the educed defects on the results of the conducted public accountant verification of short-term and long-term obligations.

A New Control Method to Mitigate Power Fluctuations for Grid Integrated PV/Wind Hybrid Power System Using Ultracapacitors

Science.gov (United States)

Jayalakshmi, N. S.; Gaonkar, D. N.

2016-08-01

The output power obtained from solar-wind hybrid system fluctuates with changes in weather conditions. These power fluctuations cause adverse effects on the voltage, frequency and transient stability of the utility grid. In this paper, a control method is presented for power smoothing of grid integrated PV/wind hybrid system using ultracapacitors in a DC coupled structure. The power fluctuations of hybrid system are mitigated and smoothed power is supplied to the utility grid. In this work both photovoltaic (PV) panels and the wind generator are controlled to operate at their maximum power point. The grid side inverter control strategy presented in this paper maintains DC link voltage constant while injecting power to the grid at unity power factor considering different operating conditions. Actual solar irradiation and wind speed data are used in this study to evaluate the performance of the developed system using MATLAB/Simulink software. The simulation results show that output power fluctuations of solar-wind hybrid system can be significantly mitigated using the ultracapacitor based storage system.

FFT transformed quantitative EEG analysis of short term memory load.

Science.gov (United States)

Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

2015-07-01

The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

Propagation of disturbances as voltage fluctuations in transmission networks

Directory of Open Access Journals (Sweden)

Albert Hermina

2016-08-01

Full Text Available Significant changes occurred in the power system in Romania in recent years by reducing the power used in the system, the number of classic power sources in operation as well as by implementing renewable energy sources, have determined short circuit power reduction (node rigidity in the points where disturbing users are connected, that in the absence of adequate measures, result in disturbances above acceptable levels. The paper analyzes two power systems areas in which are connected users that cause voltage fluctuation. Disturbances as voltage fluctuations resulting in these nodes may exceed the acceptable values and can spread in the transmission network affecting power quality over large system areas. The analysis conducted reveals the influence of short circuit power in nodes where these users are connected and highlights the fact that in some cases (e.g. lines out of operation for maintenance, shutdown of classic units in the area the disturbances in the transmission network sent to the users at lower voltages may have values above those allowed. Technical Code of existing power transmission network makes no reference to voltage fluctuations, as a rule, in the electricity transmission network was considered that this phenomenon should not exist.

Short-term high intensity plyometric training program improves strength, power and agility in male soccer players.

Science.gov (United States)

Váczi, Márk; Tollár, József; Meszler, Balázs; Juhász, Ivett; Karsai, István

2013-03-01

The aim of the present study was to investigate the effects of a short-term in-season plyometric training program on power, agility and knee extensor strength. Male soccer players from a third league team were assigned into an experimental and a control group. The experimental group, beside its regular soccer training sessions, performed a periodized plyometric training program for six weeks. The program included two training sessions per week, and maximal intensity unilateral and bilateral plyometric exercises (total of 40 - 100 foot contacts/session) were executed. Controls participated only in the same soccer training routine, and did not perform plyometrics. Depth vertical jump height, agility (Illinois Agility Test, T Agility Test) and maximal voluntary isometric torque in knee extensors using Multicont II dynamometer were evaluated before and after the experiment. In the experimental group small but significant improvements were found in both agility tests, while depth jump height and isometric torque increments were greater. The control group did not improve in any of the measures. Results of the study indicate that plyometric training consisting of high impact unilateral and bilateral exercises induced remarkable improvements in lower extremity power and maximal knee extensor strength, and smaller improvements in soccer-specific agility. Therefore, it is concluded that short-term plyometric training should be incorporated in the in-season preparation of lower level players to improve specific performance in soccer.

Short-Term High Intensity Plyometric Training Program Improves Strength, Power and Agility in Male Soccer Players

Science.gov (United States)

Váczi, Márk; Tollár, József; Meszler, Balázs; Juhász, Ivett; Karsai, István

2013-01-01

The aim of the present study was to investigate the effects of a short-term in-season plyometric training program on power, agility and knee extensor strength. Male soccer players from a third league team were assigned into an experimental and a control group. The experimental group, beside its regular soccer training sessions, performed a periodized plyometric training program for six weeks. The program included two training sessions per week, and maximal intensity unilateral and bilateral plyometric exercises (total of 40 – 100 foot contacts/session) were executed. Controls participated only in the same soccer training routine, and did not perform plyometrics. Depth vertical jump height, agility (Illinois Agility Test, T Agility Test) and maximal voluntary isometric torque in knee extensors using Multicont II dynamometer were evaluated before and after the experiment. In the experimental group small but significant improvements were found in both agility tests, while depth jump height and isometric torque increments were greater. The control group did not improve in any of the measures. Results of the study indicate that plyometric training consisting of high impact unilateral and bilateral exercises induced remarkable improvements in lower extremity power and maximal knee extensor strength, and smaller improvements in soccer-specific agility. Therefore, it is concluded that short-term plyometric training should be incorporated in the in-season preparation of lower level players to improve specific performance in soccer. PMID:23717351

Diagnostics of the boiling state of coolant based on neutron fluctuation at the Paks Nuclear Power Plant

International Nuclear Information System (INIS)

Por, G.; Gloeckler, O.; Izsak, E.; Valko, J.

1985-09-01

A short summary of theory and early experiments on the effect of propagating perturbation on neutron fluctuations in nuclear reactors is given. Boiling noise was examined in the Rheisenberg reactor of 70 MWe. Comparing the results of measurements with those carried out in the Paks nuclear power plant it seems possible that a small subcooled boiling took place during the 2nd fuel cycle. (author)

Super short term forecasting of photovoltaic power generation output in micro grid

Science.gov (United States)

Gong, Cheng; Ma, Longfei; Chi, Zhongjun; Zhang, Baoqun; Jiao, Ran; Yang, Bing; Chen, Jianshu; Zeng, Shuang

2017-01-01

The prediction model combining data mining and support vector machine (SVM) was built. Which provide information of photovoltaic (PV) power generation output for economic operation and optimal control of micro gird, and which reduce influence of power system from PV fluctuation. Because of the characteristic which output of PV rely on radiation intensity, ambient temperature, cloudiness, etc., so data mining was brought in. This technology can deal with large amounts of historical data and eliminate superfluous data, by using fuzzy classifier of daily type and grey related degree. The model of SVM was built, which can dock with information from data mining. Based on measured data from a small PV station, the prediction model was tested. The numerical example shows that the prediction model is fast and accurate.

A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

DEFF Research Database (Denmark)

Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik

2012-01-01

Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes...... fluctuations are characterized by highly volatile dynamics which are difficult to capture and predict. Due to the lack of adequate on-site meteorological observations to relate these dynamics to meteorological phenomena, we propose a general model formulation based on a statistical approach and historical wind...... power measurements only. We introduce an advanced Markov Chain Monte Carlo (MCMC) estimation method to account for the different features observed in an empirical time series of wind power: autocorrelation, heteroscedasticity and regime-switching. The model we propose is an extension of Markov...

Wind model for low frequency power fluctuations in offshore wind farms

DEFF Research Database (Denmark)

Vigueras-Rodríguez, A.; Sørensen, Poul Ejnar; Cutululis, Nicolaos Antonio

2010-01-01

of hours, taking into account the spectral correlation between different wind turbines. The modelling is supported by measurements from two large wind farms, namely Nysted and Horns Rev. Measurements from individual wind turbines and meteorological masts are used. Finally, the models are integrated......This paper investigates the correlation between the frequency components of the wind speed Power Spectral Density. The results extend an already existing power fluctuation model that can simulate power fluctuations of wind power on areas up to several kilometers and for time scales up to a couple...

Short-term fluctuations in vegetation and phytoplankton during the Middle Eocene greenhouse climate: a 640-kyr record from the Messel oil shale (Germany)

Science.gov (United States)

Lenz, Olaf K.; Wilde, Volker; Riegel, Walter

2011-11-01

The Palaeogene was the most recent greenhouse period on Earth. Especially for the Late Palaeocene and Early Eocene, several superimposed short-term hyperthermal events have been described, including extremes such as the Palaeocene-Eocene Thermal Maximum. Major faunal and floral turnovers in the marine and terrestrial realms were recorded in association with these events. High-resolution palynological analysis of the early Middle Eocene maar lake sediments at Messel, near Darmstadt, Germany, provides an insight into the dynamics of a climax vegetation during the Middle Eocene greenhouse climate in a time span without significant climatic excursions. Numerical techniques like detrended correspondence analysis and wavelet analysis have been applied to recognize cyclic fluctuations and long-term trends in the vegetation through a time interval of approximately 640 kyr. Based on the numerical zoning of the pollen diagram, three phases in the development of the vegetation may be distinguished. Throughout these phases, the climax vegetation did not change substantially in qualitative composition, but a trend towards noticeably less humid conditions probably in combination with a drop of the water level in the lake may be recognized. A shift in algal population from the freshwater dinoflagellate cyst Messelodinium thielepfeifferae to a dominance of Botryococcus in the uppermost part of the core is interpreted as a response to changes in acidity and nutrient availability within the lake. Time series analyses of pollen assemblages show that variations in the Milankovitch range of eccentricity, obliquity and precession can be distinguished. In addition, fluctuations in the sub-Milankovitch range are indicated. This demonstrates that floral changes during steady depositional conditions in the Middle Eocene of Messel were controlled by orbital forcing.

A novel economy reflecting short-term load forecasting approach

International Nuclear Information System (INIS)

Lin, Cheng-Ting; Chou, Li-Der

2013-01-01

Highlights: ► We combine MA line of TAIEX and SVR to overcome the load demands over-prediction problems caused by the economic downturn. ► The Taiwan island-wide electricity power system was used as the case study. ► Short- to middle-term MA lines of TAIEX are found to be good economic input variables for load forecasting models. - Abstract: The global economic downturn in 2008 and 2009, which was spurred by the bankruptcy of Lehman Brothers, sharply reduced the demand for electricity load. Conventional load-forecasting approaches were unable to respond to sudden changes in the economy, because these approaches do not consider the effect of economic factors. Therefore, the over-prediction problem occurred. To overcome this problem, this paper proposes a novel, economy-reflecting, short-term load forecasting (STLF) approach based on theories of moving average (MA) line of stock index and machine learning. In this approach, the stock indices decision model is designed to reflect fluctuations in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) series, which is selected as an optimal input variable in support vector regression load forecasting model at an appropriate timing. The Taiwan island-wide hourly electricity load demands from 2008 to 2010 are used as the case study for performance benchmarking. Results show that the proposed approach with a 60-day MA of the TAIEX as economic learning pattern achieves good forecasting performance. It outperforms the conventional approach by 29.16% on average during economic downturn-affected days. Overall, the proposed approach successfully overcomes the over-prediction problems caused by the economic downturn. To the best of our knowledge, this paper is the first attempt to apply MA line theory of stock index on STLF.

The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

Directory of Open Access Journals (Sweden)

Jin-peng Liu

2017-07-01

Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.

Hsp70 expression and metabolite composition in response to short-term thermal changes in Folsomia candida (Collembola)

DEFF Research Database (Denmark)

Waagner, Dorthe; Heckmann, Lars-Henrik; Malmendal, Anders

2010-01-01

In the present study the joint transcriptomic and metabolomic responses in Folsomia candida (Collembola) to temperature changes on a short-term scale were studied. Change in heat tolerance was examined as survival after a 35 degrees C heat shock (2h) in the course of either a fluctuating temperat......In the present study the joint transcriptomic and metabolomic responses in Folsomia candida (Collembola) to temperature changes on a short-term scale were studied. Change in heat tolerance was examined as survival after a 35 degrees C heat shock (2h) in the course of either a fluctuating...... analysed in F. candida using nuclear magnetic resonance spectroscopy ((1)H NMR). A significant metabolomic divergence between pre-treated and control collembolans was evident; partly due to a significantly reduced relative concentration of five free amino acids (arginine, leucine, lysine, phenylalanine...

Non-Gaussian power grid frequency fluctuations characterized by Lévy-stable laws and superstatistics

Science.gov (United States)

Schäfer, Benjamin; Beck, Christian; Aihara, Kazuyuki; Witthaut, Dirk; Timme, Marc

2018-02-01

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading and an increasing share of renewable power feed-in. Here we analyse principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a strong deviation from Gaussianity best described as Lévy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions, as well as a superstatistical approach that systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today's frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids.

A three-stage short-term electric power planning procedure for a generation company in a liberalized market

International Nuclear Information System (INIS)

Nabona, Narcis; Pages, Adela

2007-01-01

In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account the action of the competing generation companies and the market-price formation rules and must be coordinated with long-term planning results. This paper presents a three stage optimization process with a data analysis and parameter calculation, a linearized unit commitment, and a nonlinear generation scheduling refinement. Although the procedure has been developed from the experience with the Spanish power market, with minor adaptations it is also applicable to any generation company participating in a competitive market system. (author)

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

Science.gov (United States)

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

Implementation of short-term prediction

Energy Technology Data Exchange (ETDEWEB)

Landberg, L; Joensen, A; Giebel, G [and others

1999-03-01

This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

Backreaction of Cosmological Fluctuations during Power-Law Inflation

International Nuclear Information System (INIS)

Marozzi, G.

2007-01-01

We study the renormalized energy-momentum tensor of cosmological scalar fluctuations during the slow-rollover regime for power-law inflation and find that it is characterized by a negative energy density at the leading order, with the same time behavior as the background energy. The average expansion rate appears decreased by the backreaction of the effective energy of cosmological fluctuations, but this value is comparable with the energy of the background only if inflation starts at a Planckian energy. We also find that, for this particular model, the first- and second-order inflaton fluctuations are decoupled and satisfy the same equation of motion. To conclude, the fourth-order adiabatic expansion for the inflaton scalar field is evaluated for a general potential V(φ)

An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power

Directory of Open Access Journals (Sweden)

Antonio Bracale

2015-09-01

Full Text Available Currently, among renewable distributed generation systems, wind generators are receiving a great deal of interest due to the great economic, technological, and environmental incentives they involve. However, the uncertainties due to the intermittent nature of wind energy make it difficult to operate electrical power systems optimally and make decisions that satisfy the needs of all the stakeholders of the electricity energy market. Thus, there is increasing interest determining how to forecast wind power production accurately. Most the methods that have been published in the relevant literature provided deterministic forecasts even though great interest has been focused recently on probabilistic forecast methods. In this paper, an advanced probabilistic method is proposed for short-term forecasting of wind power production. A mixture of two Weibull distributions was used as a probability function to model the uncertainties associated with wind speed. Then, a Bayesian inference approach with a particularly-effective, autoregressive, integrated, moving-average model was used to determine the parameters of the mixture Weibull distribution. Numerical applications also are presented to provide evidence of the forecasting performance of the Bayesian-based approach.

The short-term impacts of Earned Income Tax Credit disbursement on health.

Science.gov (United States)

Rehkopf, David H; Strully, Kate W; Dow, William H

2014-12-01

There are conflicting findings regarding long- and short-term effects of income on health. Whereas higher average income is associated with better health, there is evidence that health behaviours worsen in the short-term following income receipt.Prior studies revealing such negative short-term effects of income receipt focus on specific subpopulations and examine a limited set of health outcomes. The United States Earned Income Tax Credit (EITC) is an income supplement tied to work, and is the largest poverty reduction programme in the USA. We utilize the fact that EITC recipients typically receive large cash transfers in the months of February,March and April, in order to examine associated changes in health outcomes that can fluctuate on a monthly basis. We examine associations with 30 outcomes in the categories of diet, food security, health behaviours, cardiovascular biomarkers, metabolic biomarkers and infection and immunity among 6925 individuals from the U.S. National Health and Nutrition Survey. Our research design approximates a natural experiment,since whether individuals were sampled during treatment or non-treatment months is independent of social, demographic and health characteristics that do not vary with time. There are both beneficial and detrimental short-term impacts of income receipt.Although there are detrimental impacts on metabolic factors among women, most other impacts are beneficial, including those for food security, smoking and trying to lose weight. The short-term impacts of EITC income receipt are not universally health promoting, but on balance there are more health benefits than detriments.

A method for short term electricity spot price forecasting

International Nuclear Information System (INIS)

Koreneff, G.; Seppaelae, A.; Lehtonen, M.; Kekkonen, V.; Laitinen, E.; Haekli, J.; Antila, E.

1998-01-01

In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

A method for short term electricity spot price forecasting

Energy Technology Data Exchange (ETDEWEB)

Koreneff, G; Seppaelae, A; Lehtonen, M; Kekkonen, V [VTT Energy, Espoo (Finland); Laitinen, E; Haekli, J [Vaasa Univ. (Finland); Antila, E [ABB Transmit Oy (Finland)

1998-08-01

In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

Increased alpha-band power during the retention of shapes and shape-location associations in visual short-term memory

Directory of Open Access Journals (Sweden)

Jeffrey S. Johnson

2011-06-01

Full Text Available Studies exploring the role of neural oscillations in cognition have revealed sustained increases in alpha-band (~8-14 Hz power during the delay period of delayed-recognition short-term memory tasks. These increases have been proposed to reflect the inhibition, for example, of cortical areas representing task-irrelevant information, or of potentially interfering representations from previous trials. Another possibility, however, is that elevated delay-period alpha-band power reflects the selection and maintenance of information, rather than, or in addition to, the inhibition of task-irrelevant information. In the present study, we explored these possibilities using a delayed-recognition paradigm in which the presence and task-relevance of shape information was systematically manipulated across trial blocks and EEG was used to measure alpha-band power. In the first trial block, participants remembered locations marked by identical black circles. The second block featured the same instructions, but locations were marked by unique shapes. The third block featured the same stimulus presentation as the second, but with pretrial instructions indicating, on a trial-by-trial basis, whether memory for shape or location was required, the other dimension being irrelevant. In the final block, participants remembered the unique pairing of shape and location for each stimulus. Results revealed minimal delay-period alpha-band power in each of the location-memory conditions, whether locations were marked with identical circles or with unique task-irrelevant shapes. In contrast, alpha-band power increases were observed in both the shape-memory condition, in which location was task irrelevant, and in the critical final condition, in which both shape and location were task relevant. These results provide support for the proposal that alpha-band oscillations reflect the retention of shape information and/or shape-location associations in short-term memory.

Pediatric polytrauma : Short-term and long-term outcomes

NARCIS (Netherlands)

vanderSluis, CK; Kingma, J; Eisma, WH; tenDuis, HJ

Objective: To assess the short-term and long-term outcomes of pediatric polytrauma patients and to analyze the extent to which short-term outcomes can predict long-term outcomes. Materials and Methods: Ail pediatric polytrauma patients (Injury Severity Score of greater than or equal to 16, less than

Stability of synchrony against local intermittent fluctuations in tree-like power grids

Science.gov (United States)

Auer, Sabine; Hellmann, Frank; Krause, Marie; Kurths, Jürgen

2017-12-01

90% of all Renewable Energy Power in Germany is installed in tree-like distribution grids. Intermittent power fluctuations from such sources introduce new dynamics into the lower grid layers. At the same time, distributed resources will have to contribute to stabilize the grid against these fluctuations in the future. In this paper, we model a system of distributed resources as oscillators on a tree-like, lossy power grid and its ability to withstand desynchronization from localized intermittent renewable infeed. We find a remarkable interplay of the network structure and the position of the node at which the fluctuations are fed in. An important precondition for our findings is the presence of losses in distribution grids. Then, the most network central node splits the network into branches with different influence on network stability. Troublemakers, i.e., nodes at which fluctuations are especially exciting the grid, tend to be downstream branches with high net power outflow. For low coupling strength, we also find branches of nodes vulnerable to fluctuations anywhere in the network. These network regions can be predicted at high confidence using an eigenvector based network measure taking the turbulent nature of perturbations into account. While we focus here on tree-like networks, the observed effects also appear, albeit less pronounced, for weakly meshed grids. On the other hand, the observed effects disappear for lossless power grids often studied in the complex system literature.

A Simple Hybrid Model for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Suseelatha Annamareddi

2013-01-01

Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power

International Nuclear Information System (INIS)

Zhang, Huifeng; Yue, Dong; Xie, Xiangpeng; Dou, Chunxia; Sun, Feng

2017-01-01

With the integration of wind power and photovoltaic power, optimal operation of hydrothermal power system becomes great challenge due to its non-convex, stochastic and complex-coupled constrained characteristics. This paper extends short-term hydrothermal system optimal model into short-term hydrothermal optimal scheduling of economic emission while considering integrated intermittent energy resources (SHOSEE-IIER). For properly solving SHOSEE-IIER problem, a gradient decent based multi-objective cultural differential evolution (GD-MOCDE) is proposed to improve the optimal efficiency of SHOSEE-IIER combined with three designed knowledge structures, which mainly enhances search ability of differential evolution in the shortest way. With considering those complex-coupled and stochastic constraints, a heuristic constraint-handling measurement is utilized to tackle with them both in coarse and fine tuning way, and probability constraint-handling procedures are taken to properly handle those stochastic constraints combined with their probability density functions. Ultimately, those approaches are implemented on five test systems, which testify the optimization efficiency of proposed GD-MOCDE and constraint-handling efficiency for system load balance, water balance and stochastic constraint-handling measurements, those obtained results reveal that the proposed GD-MOCDE can properly solve the SHOSEE-IIER problem combined with those constraint-handling approaches. - Highlights: • Gradient decent method is proposed to improve mutation operator. • Hydrothermal system is extended to hybrid energy system. • The uncertainty constraint is converted into deterministic constraint. • The results show the viability and efficiency of proposed algorithm.

Paraconductivity of three-dimensional amorphous superconductors: evidence for a short-wavelength cutoff in the fluctuation spectrum

International Nuclear Information System (INIS)

Johnson, W.L.

1977-10-01

Measurements of the temperature dependence and magnetic field dependence of the paraconductivity of a three dimensional amorphous superconductor are presented. The data are analyzed in terms of several current theories and are found to give good agreement for low fields and temperatures near T/sub c/. The paraconductivity falls well below predicted theoretical values in the high temperature and high field limits. This is attributed to the reduced role of high wavevector contributions to the paraconductivity. It is shown that the introduction of a short wavelength cutoff in the theoretical fluctuation spectrum provides a phenomelogical account of the discrepancy between theory and experiment

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

Science.gov (United States)

Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

2016-12-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate

Room Volume Estimation Based on Ambiguity of Short-Term Interaural Phase Differences Using Humanoid Robot Head

Directory of Open Access Journals (Sweden)

Ryuichi Shimoyama

2016-07-01

Full Text Available Humans can recognize approximate room size using only binaural audition. However, sound reverberation is not negligible in most environments. The reverberation causes temporal fluctuations in the short-term interaural phase differences (IPDs of sound pressure. This study proposes a novel method for a binaural humanoid robot head to estimate room volume. The method is based on the statistical properties of the short-term IPDs of sound pressure. The humanoid robot turns its head toward a sound source, recognizes the sound source, and then estimates the ego-centric distance by its stereovision. By interpolating the relations between room volume, average standard deviation, and ego-centric distance experimentally obtained for various rooms in a prepared database, the room volume was estimated by the binaural audition of the robot from the average standard deviation of the short-term IPDs at the estimated distance.

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

2005-01-01

Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

Long-term associative learning predicts verbal short-term memory performance

OpenAIRE

Jones, Gary; Macken, Bill

2017-01-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term...

Long-term associative learning predicts verbal short-term memory performance.

Science.gov (United States)

Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Wind Power Fluctuation Smoothing Controller Based on Risk Assessment of Grid Frequency Deviation in an Isolated System

DEFF Research Database (Denmark)

Lin, Jin; Sun, Yuanzhang; Song, Yonghua

2013-01-01

a smoothing controller to suppress the power fluctuation from doubly-fed induction generator (DFIG)-based wind farm. This controller consists of threemain functionality components: risk assessmentmodel, wind turbine rotor speed optimizer, and rotor speed upper limiter. In order to avoid unnecessary energy...... curve with reduced output so that a trade-off between fluctuation smoothing and energy loss is achieved. Subsequently, the controller limits the maximum rotor speed to shift down the power curve of wind power plant based on the optimal wind turbine rotor speed. Therefore, the power fluctuation......Wind power fluctuation raises the security concern of grid frequency deviation, especially for an isolated power system. Thus, better control methodology needs to be developed to smooth the fluctuation without excessive spillage. Based on an actual industrial power system, this paper proposes...

Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

International Nuclear Information System (INIS)

Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

2016-01-01

Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

Error analysis of short term wind power prediction models

International Nuclear Information System (INIS)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

2011-01-01

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Error analysis of short term wind power prediction models

Energy Technology Data Exchange (ETDEWEB)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

2011-04-15

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Wind power generation and dispatch in competitive power markets

Science.gov (United States)

Abreu, Lisias

Wind energy is currently the fastest growing type of renewable energy. The main motivation is led by more strict emission constraints and higher fuel prices. In addition, recent developments in wind turbine technology and financial incentives have made wind energy technically and economically viable almost anywhere. In restructured power systems, reliable and economical operation of power systems are the two main objectives for the ISO. The ability to control the output of wind turbines is limited and the capacity of a wind farm changes according to wind speeds. Since this type of generation has no production costs, all production is taken by the system. Although, insufficient operational planning of power systems considering wind generation could result in higher system operation costs and off-peak transmission congestions. In addition, a GENCO can participate in short-term power markets in restructured power systems. The goal of a GENCO is to sell energy in such a way that would maximize its profitability. However, due to market price fluctuations and wind forecasting errors, it is essential for the wind GENCO to keep its financial risk at an acceptable level when constituting market bidding strategies. This dissertation discusses assumptions, functions, and methodologies that optimize short-term operations of power systems considering wind energy, and that optimize bidding strategies for wind producers in short-term markets. This dissertation also discusses uncertainties associated with electricity market environment and wind power forecasting that can expose market participants to a significant risk level when managing the tradeoff between profitability and risk.

Short-term load forecasting by a neuro-fuzzy based approach

Energy Technology Data Exchange (ETDEWEB)

Ruey-Hsun Liang; Ching-Chi Cheng [National Yunlin University of Science and Technology (China). Dept. of Electrical Engineering

2002-02-01

An approach based on an artificial neural network (ANN) combined with a fuzzy system is proposed for short-term load forecasting. This approach was developed in order to reach the desired short-term load forecasting in an efficient manner. Over the past few years, ANNs have attained the ability to manage a great deal of system complexity and are now being proposed as powerful computational tools. In order to select the appropriate load as the input for the desired forecasting, the Pearson analysis method is first applied to choose two historical record load patterns that are similar to the forecasted load pattern. These two load patterns and the required weather parameters are then fuzzified and input into a neural network for training or testing the network. The back-propagation (BP) neural network is applied to determine the preliminary forecasted load. In addition, the rule base for the fuzzy inference machine contains important linguistic membership function terms with knowledge in the form of fuzzy IF-THEN rules. This produces the load correction inference from the historical information and past forecasted load errors to obtain an inferred load error. Adding the inferred load error to the preliminary forecasted load, we can obtain the finial forecasted load. The effectiveness of the proposed approach to the short-term load-forecasting problem is demonstrated using practical data from the Taiwan Power Company (TPC). (Author)

Pigeon visual short-term memory directly compared to primates.

Science.gov (United States)

Wright, Anthony A; Elmore, L Caitlin

2016-02-01

Three pigeons were trained to remember arrays of 2-6 colored squares and detect which of two squares had changed color to test their visual short-term memory. Procedures (e.g., stimuli, displays, viewing times, delays) were similar to those used to test monkeys and humans. Following extensive training, pigeons performed slightly better than similarly trained monkeys, but both animal species were considerably less accurate than humans with the same array sizes (2, 4 and 6 items). Pigeons and monkeys showed calculated memory capacities of one item or less, whereas humans showed a memory capacity of 2.5 items. Despite the differences in calculated memory capacities, the pigeons' memory results, like those from monkeys and humans, were all well characterized by an inverse power-law function fit to d' values for the five display sizes. This characterization provides a simple, straightforward summary of the fundamental processing of visual short-term memory (how visual short-term memory declines with memory load) that emphasizes species similarities based upon similar functional relationships. By closely matching pigeon testing parameters to those of monkeys and humans, these similar functional relationships suggest similar underlying processes of visual short-term memory in pigeons, monkeys and humans. Copyright © 2015 Elsevier B.V. All rights reserved.

A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator

International Nuclear Information System (INIS)

Almonacid, F.; Pérez-Higueras, P.J.; Fernández, Eduardo F.; Hontoria, L.

2014-01-01

Highlights: • The output of the majority of renewables energies depends on the variability of the weather conditions. • The short-term forecast is going to be essential for effectively integrating solar energy sources. • A new method based on artificial neural network to predict the power output of a PV generator one hour ahead is proposed. • This new method is based on dynamic artificial neural network to predict global solar irradiance and the air temperature. • The methodology developed can be used to estimate the power output of a PV generator with a satisfactory margin of error. - Abstract: One of the problems of some renewables energies is that the output of these kinds of systems is non-dispatchable depending on variability of weather conditions that cannot be predicted and controlled. From this point of view, the short-term forecast is going to be essential for effectively integrating solar energy sources, being a very useful tool for the reliability and stability of the grid ensuring that an adequate supply is present. In this paper a new methodology for forecasting the output of a PV generator one hour ahead based on dynamic artificial neural network is presented. The results of this study show that the proposed methodology could be used to forecast the power output of PV systems one hour ahead with an acceptable degree of accuracy

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...

Prediction of power fluctuation classes for photovoltaic installations and potential benefits of dynamic reserve allocation

NARCIS (Netherlands)

Nijhuis, M.; Rawn, B.G.; Gibescu, M.

2014-01-01

During partly cloudy conditions, the power delivered by a photovoltaic array can easily fluctuate by three quarters of its rated power in 10 s. Fluctuations from photovoltaics of this size and on this time scale may necessitate adding an additional component to power system secondary and primary

Preparatory Body State before Reacting to an Opponent: Short-Term Joint Torque Fluctuation in Real-Time Competitive Sports.

Science.gov (United States)

Fujii, Keisuke; Yamashita, Daichi; Kimura, Tetsuya; Isaka, Tadao; Kouzaki, Motoki

2015-01-01

, irrespective of the outcome. These results indicate that the preparatory body state as explained by short-term joint torque fluctuations before the defensive step would help explain the performance in competitive sports, and will give insights into understanding human adaptive behavior in unpredicted and uncontrolled environments.

Online Short-term Solar Power Forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2011-01-01

This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

Effect of active warm-up duration on morning short-term maximal ...

African Journals Online (AJOL)

Purpose: To examine the effect of active warm-up duration on short-term maximal performance assessed during Ramadan in the morning. Methods: Twelve healthy active men performed four Wingate tests for measurement of peak power and mean power before and during Ramadan at 09:00 a.m. The tests were performed ...

A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems

Directory of Open Access Journals (Sweden)

Farshid Keynia

2011-03-01

Full Text Available Short-term load forecast (STLF is an important operational function in both regulated power systems and deregulated open electricity markets. However, STLF is not easy to handle due to the nonlinear and random-like behaviors of system loads, weather conditions, and social and economic environment variations. Despite the research work performed in the area, more accurate and robust STLF methods are still needed due to the importance and complexity of STLF. In this paper, a new neural network approach for STLF is proposed. The proposed neural network has a novel learning algorithm based on a new modified harmony search technique. This learning algorithm can widely search the solution space in various directions, and it can also avoid the overfitting problem, trapping in local minima and dead bands. Based on this learning algorithm, the suggested neural network can efficiently extract the input/output mapping function of the forecast process leading to high STLF accuracy. The proposed approach is tested on two practical power systems and the results obtained are compared with the results of several other recently published STLF methods. These comparisons confirm the validity of the developed approach.

Modelling and short-term forecasting of daily peak power demand in Victoria using two-dimensional wavelet based SDP models

International Nuclear Information System (INIS)

Truong, Nguyen-Vu; Wang, Liuping; Wong, Peter K.C.

2008-01-01

Power demand forecasting is of vital importance to the management and planning of power system operations which include generation, transmission, distribution, as well as system's security analysis and economic pricing processes. This paper concerns the modeling and short-term forecast of daily peak power demand in the state of Victoria, Australia. In this study, a two-dimensional wavelet based state dependent parameter (SDP) modelling approach is used to produce a compact mathematical model for this complex nonlinear dynamic system. In this approach, a nonlinear system is expressed by a set of linear regressive input and output terms (state variables) multiplied by the respective state dependent parameters that carry the nonlinearities in the form of 2-D wavelet series expansions. This model is identified based on historical data, descriptively representing the relationship and interaction between various components which affect the peak power demand of a certain day. The identified model has been used to forecast daily peak power demand in the state of Victoria, Australia in the time period from the 9th of August 2007 to the 24th of August 2007. With a MAPE (mean absolute prediction error) of 1.9%, it has clearly implied the effectiveness of the identified model. (author)

Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

Directory of Open Access Journals (Sweden)

Erick López

2018-02-01

Full Text Available Wind power generation has presented an important development around the world. However, its integration into electrical systems presents numerous challenges due to the variable nature of the wind. Therefore, to maintain an economical and reliable electricity supply, it is necessary to accurately predict wind generation. The Wind Power Prediction Tool (WPPT has been proposed to solve this task using the power curve associated with a wind farm. Recurrent Neural Networks (RNNs model complex non-linear relationships without requiring explicit mathematical expressions that relate the variables involved. In particular, two types of RNN, Long Short-Term Memory (LSTM and Echo State Network (ESN, have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed, but using LSTM blocks as units in the hidden layer. The training process of this network has two key stages: (i the hidden layer is trained with a descending gradient method online using one epoch; (ii the output layer is adjusted with a regularized regression. In particular, the case is proposed where Step (i is used as a target for the input signal, in order to extract characteristics automatically as the autoencoder approach; and in the second stage (ii, a quantile regression is used in order to obtain a robust estimate of the expected target. The experimental results show that LSTM+ESN using the autoencoder and quantile regression outperforms the WPPT model in all global metrics used.

Online short-term solar power forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2009-01-01

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen......-minute observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques....... Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours...

Harmonic Injection-Based Power Fluctuation Control of Three-Phase PV Systems under Unbalanced Grid Voltage Conditions

Directory of Open Access Journals (Sweden)

Nian-Cheng Zhou

2015-02-01

Full Text Available Unbalanced voltage will inevitably cause power and DC voltage fluctuations in a three-phase PV system. The deterioration of power quality will do great harm to the PV panels and the loads, so it is necessary to suppress the power fluctuations. This paper further explores the coefficients control strategy of PV converters under unbalanced voltage conditions, aiming to suppress power fluctuations by controlling the injection of some specific orders of current harmonics into the grid. In order to achieve this, the current reference of the PV inverter has been changed by bringing in two control coefficients, and the expression of each order of the current harmonics has been deduced. Based on the standards of PV systems, the regions from which the coefficients can be selected are determined. Then, by tuning these coefficients in the feasible regions, the output parameters (power fluctuation, current THD and odd harmonics can be controlled precisely. The model of this method is built and simulated in PSCAD/EMTDC, and as a result, it is shown that the power fluctuations can be restricted according to different power quality requirements.

The relation between short-term emotion dynamics and psychological well-being: A meta-analysis.

Science.gov (United States)

Houben, Marlies; Van Den Noortgate, Wim; Kuppens, Peter

2015-07-01

Not only how good or bad people feel on average, but also how their feelings fluctuate across time is crucial for psychological health. The last 2 decades have witnessed a surge in research linking various patterns of short-term emotional change to adaptive or maladaptive psychological functioning, often with conflicting results. A meta-analysis was performed to identify consistent relationships between patterns of short-term emotion dynamics-including patterns reflecting emotional variability (measured in terms of within-person standard deviation of emotions across time), emotional instability (measured in terms of the magnitude of consecutive emotional changes), and emotional inertia of emotions over time (measured in terms of autocorrelation)-and relatively stable indicators of psychological well-being or psychopathology. We determined how such relationships are moderated by the type of emotional change, type of psychological well-being or psychopathology involved, valence of the emotion, and methodological factors. A total of 793 effect sizes were identified from 79 articles (N = 11,381) and were subjected to a 3-level meta-analysis. The results confirmed that overall, low psychological well-being co-occurs with more variable (overall ρ̂ = -.178), unstable (overall ρ̂ = -.205), but also more inert (overall ρ̂ = -.151) emotions. These effect sizes were stronger when involving negative compared with positive emotions. Moreover, the results provided evidence for consistency across different types of psychological well-being and psychopathology in their relation with these dynamical patterns, although specificity was also observed. The findings demonstrate that psychological flourishing is characterized by specific patterns of emotional fluctuations across time, and provide insight into what constitutes optimal and suboptimal emotional functioning. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Currency speculation and dollar fluctuations

Directory of Open Access Journals (Sweden)

Stephan Schulmeister

1988-12-01

Full Text Available In this study the reasons behind the wide fluctuations of the dollar exchange rate following the breakdown of the Bretton Woods system, for the most part unexplained by the prevailing exchange rate theories, are explored. To do so, the author investigates the exchange rate between the two most traded currencies, the dollar and the deutschemark, from 1973 to 1988. In the first part, the pattern of the daily exchange rate movements is examined to show that a sequence of upward and downward trends interrupted by non-directional movements is typical of exchange rate dynamics in the short run. Moreover, this pattern is systemically exploited through currency speculation, particularly through the use of “technical analysis”. In the second part, the author focuses on the medium-term, arguing that fluctuations can be explained as the result of interacting disequilibria in the goods and asset markets. Although currency speculation has been systemically profitable for most currencies, it should be considered to be destabilizing since the sequence of price runs caused large and persistent deviations of exchange rates from their equilibrium values (purchasing power parity.

Short-term trends in the gas industry - Panorama 2008

International Nuclear Information System (INIS)

2008-01-01

In a context of high investment costs and rising energy prices, and recurring unseasonably warm temperatures in recent years, the growth of natural gas demand is slowing. On the supply side, and on the demand side too, new trends are emerging, with potentially powerful impact on the short-and long-term development of the industry

Coordinated Control of Wind Turbine and Energy Storage System for Reducing Wind Power Fluctuation

Energy Technology Data Exchange (ETDEWEB)

Muljadi, Eduard [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kim, Chunghun [Hanyang University; Chung, Chung Choo [Hanyang University

2017-11-13

This paper proposes a coordinated control of wind turbine and energy storage system (ESS). Because wind power (WP) is highly dependent on variable wind speed and could induce a severe stability problem to power system especially when the WP has high penetration level. To solve this problem, many power generation corporations or grid operators recently use the ESS. It has very quick response and good performance for reducing the impact of WP fluctuation but has high cost for its installation. Therefore, it is very important to design the control algorithm considering both ESS capacity and grid reliability. Thus, we propose the control algorithm to mitigate the WP fluctuation by using the coordinated control between wind turbine and ESS considering ESS state of charge (SoC) and the WP fluctuation. From deloaded control according to WP fluctuation and ESS SoC management, we can expect the ESS lifespan expansion and improved grid reliability. The effectiveness of the proposed method is validated in MATLAB/Simulink considering power system including both wind turbine generator and conventional generators which react to system frequency deviation.

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

Energy Technology Data Exchange (ETDEWEB)

Sun, Yannan; Hou, Zhangshuan; Meng, Da; Samaan, Nader A.; Makarov, Yuri V.; Huang, Zhenyu

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

Measurement of magnetic fluctuations at small spatial scales in the Tokapole II tokamak

International Nuclear Information System (INIS)

Haines, E.J.

1991-08-01

This thesis is a presentation of the measurements of short-wavelength, high-frequency radial magnetic fluctuations performed on the Tokapole 2 tokamak at the University of Wisconsin-Madison. Theories of electron temperature gradient (η e ) driven turbulence predict the existence of increased magnetic fluctuation power at small spatial scales near the collisionless skin depth c/ω pe and over a wide range of frequencies near and below the electron diamagnetic drift frequency ω* ne . Small magnetic probes of sizes down to 1 m m have been constructed and used to resolve short poloidal and radial wavelength magnetic fluctuations. These probes have been used with larger probes to make comparisons of fluctuation spectra measured in various ranges of wavelength and over the range of frequencies from 10 kHz to 6 MHz in Tokapole 2 plasmas. A calculation of the short-wavelength, high-frequency response of an electrostatically shielded model B r probe has been performed to guide the interpretation of the power comparison measurements. Comparisons of magnetic fluctuation spectra at various positions within the plasma, and for discharges with edge safety factor 1, 2, and 3 are presented. The linear and nonlinear theories and numerical simulations of η e turbulence are reviewed and compared, where possible with the experimental parameters and results

Modeling Long-Term Fluvial Incision : Shall we Care for the Details of Short-Term Fluvial Dynamics?

Science.gov (United States)

Lague, D.; Davy, P.

2008-12-01

Fluvial incision laws used in numerical models of coupled climate, erosion and tectonics systems are mainly based on the family of stream power laws for which the rate of local erosion E is a power function of the topographic slope S and the local mean discharge Q : E = K Qm Sn. The exponents m and n are generally taken as (0.35, 0.7) or (0.5, 1), and K is chosen such that the predicted topographic elevation given the prevailing rates of precipitation and tectonics stay within realistic values. The resulting topographies are reasonably realistic, and the coupled system dynamics behaves somehow as expected : more precipitation induces increased erosion and localization of the deformation. Yet, if we now focus on smaller scale fluvial dynamics (the reach scale), recent advances have suggested that discharge variability, channel width dynamics or sediment flux effects may play a significant role in controlling incision rates. These are not factored in the simple stream power law model. In this work, we study how these short- term details propagate into long-term incision dynamics within the framework of surface/tectonics coupled numerical models. To upscale the short term dynamics to geological timescales, we use a numerical model of a trapezoidal river in which vertical and lateral incision processes are computed from fluid shear stress at a daily timescale, sediment transport and protection effects are factored in, as well as a variable discharge. We show that the stream power law model might still be a valid model but that as soon as realistic effects are included such as a threshold for sediment transport, variable discharge and dynamic width the resulting exponents m and n can be as high as 2 and 4. This high non-linearity has a profound consequence on the sensitivity of fluvial relief to incision rate. We also show that additional complexity does not systematically translates into more non-linear behaviour. For instance, considering only a dynamical width

Propagation of the lower hybrid wave in a density fluctuating scrape-off layer (SOL)

International Nuclear Information System (INIS)

Madi, M; Peysson, Y; Decker, J; Kabalan, K Y

2015-01-01

The perturbation of the lower hybrid wave (LH) power spectrum by fluctuations of the plasma in the vicinity of the antenna is investigated by solving the full wave equation in a slab geometry using COMSOL Multiphysics®. The numerical model whose generality allows to study the effect of various types of fluctuations, including those with short characteristic wavelengths is validated against a coupling code in quiescent regimes. When electron density fluctuations along the toroidal direction are incorporated in the dielectric tensor over a thin perturbed layer in front of the grill, the power spectrum may be strongly modified from the antenna mouth to the plasma separatrix as the LH wave propagates. The diffraction effect by density fluctuations leads to the appearance of multiple satellite lobes with randomly varying positions and the averaged perturbation is found to be maximum for the Fourier components of the fluctuating spectrum in the vicinity of the launched LH wavelength. This highlights that fast toroidal inhomogeneities with short characteristics length scales in front of the grill may change significantly the initial LH power spectrum used in coupled ray-tracing and Fokker–Planck calculations. (paper)

Is WTI crude oil market becoming weakly efficient over time? New evidence from multiscale analysis based on detrended fluctuation analysis

International Nuclear Information System (INIS)

Wang, Yudong; Liu, Li

2010-01-01

This paper extends the work in Tabak and Cajueiro (Are the crude oil markets becoming weakly efficient over time, Energy Economics 29 (2007) 28-36) and Alvarez-Ramirez et al. (Short-term predictability of crude oil markets: a detrended fluctuation analysis approach, Energy Economics 30 (2008) 2645-2656). In this paper, we test for the efficiency of WTI crude oil market through observing the dynamic of local Hurst exponents employing the method of rolling window based on multiscale detrended fluctuation analysis. Empirical results show that short-term, medium-term and long-term behaviors were generally turning into efficient behavior over time. However, in this way, the results also show that the market did not evolve along stable conditions for long times. Multiscale analysis is also implemented based on multifractal detrended fluctuation analysis. We found that the small fluctuations of WTI crude oil market were persistent; however, the large fluctuations had high instability, both in the short- and long-terms. Our discussion is also extended by incorporating arguments from the crude oil market structure for explaining the different correlation dynamics. (author)

Quantum fluctuation theorems and power measurements

International Nuclear Information System (INIS)

Prasanna Venkatesh, B; Watanabe, Gentaro; Talkner, Peter

2015-01-01

Work in the paradigm of the quantum fluctuation theorems of Crooks and Jarzynski is determined by projective measurements of energy at the beginning and end of the force protocol. In analogy to classical systems, we consider an alternative definition of work given by the integral of the supplied power determined by integrating up the results of repeated measurements of the instantaneous power during the force protocol. We observe that such a definition of work, in spite of taking account of the process dependence, has different possible values and statistics from the work determined by the conventional two energy measurement approach (TEMA). In the limit of many projective measurements of power, the system’s dynamics is frozen in the power measurement basis due to the quantum Zeno effect leading to statistics only trivially dependent on the force protocol. In general the Jarzynski relation is not satisfied except for the case when the instantaneous power operator commutes with the total Hamiltonian at all times. We also consider properties of the joint statistics of power-based definition of work and TEMA work in protocols where both values are determined. This allows us to quantify their correlations. Relaxing the projective measurement condition, weak continuous measurements of power are considered within the stochastic master equation formalism. Even in this scenario the power-based work statistics is in general not able to reproduce qualitative features of the TEMA work statistics. (paper)

Management of fluctuations in wind power and CHP comparing two possible Danish strategies

International Nuclear Information System (INIS)

Lund, H.; Clark, W.W.

2002-01-01

Both CHP (combined heat and power production) and wind power are important elements of Danish energy policy. Today, approximately 50% of both the Danish electricity and heat demand are produced in CHP and more than 15% of the electricity demand is produced by wind turbines. Both technologies are essential for the implementation of Danish climate change response objectives, and both technologies are intended for further expansion in the coming decade. Meanwhile, the integration of CHP and wind power is subject to fluctuations in electricity production. Wind turbines depend on the wind, and CHP depends on the heat demand. This article discusses and analyses two different national strategies for solving this problem. One strategy, which is the current official government policy known as the export strategy, proposes to take advantage of the Nordic and European markets for selling and buying electricity. In this case, surplus electricity from wind power and CHP simply will be sold to neighbouring countries. Another strategy, the self-supply strategy, runs the CHP units to meet both demand and the fluctuations in the wind scheduling. In this case, investments in heat storages are necessary and heat pumps have to be added to the CHP units. Based on official Danish energy policy and energy plans, this article quantifies the problem for the year 2015 in terms of the amount of surplus electricity, and investments in heat pumps, etc. needed to solve the problem are calculated. Based on these results between the two different strategies, the conclusion is that the self-supply strategy is recommended over the official export strategy. (author)

The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

Directory of Open Access Journals (Sweden)

Simone Sperati

2015-09-01

Full Text Available A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies (“WIRE” with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasting. The exercise consisted in forecasting the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview and comparison of the principal and the novel approaches that are used today in the field, and to assess the evolution of forecast performance with respect to previous benchmarking exercises. The outcome of this exercise consisted then in proposing new challenges in the renewable power forecasting field and identifying the main areas for improving accuracy in the future.

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G. [CANTECH Associates Limited, Burlington, Ontario (Canada); Nashiem, R.; McQueen, M.; Ma, G. [Bruce Power, Tiverton, Ontario (Canada)

2011-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; Nashiem, R.; McQueen, M.; Ma, G.

2011-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; McQueen, M.; Nashiem, R.; Ma, G.

2011-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G. [CANTECH Associates Ltd., Burlington, ON (Canada); McQueen, M.; Nashiem, R.; Ma, G. [Bruce Power, Tiverton, ON (Canada)

2011-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G., E-mail: alchemy@tnt21.com [CANTECH Associates Ltd., Burlington, Ontario (Canada); Nashiem, R.; McQueen, M.; Ma, G., E-mail: Rod.nashiem@brucepower.com, E-mail: Maureen.mcqueen@brucepower.com, E-mail: guoping.ma@brucepower.com [Bruce Power, Tiverton (Canada)

2010-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; Nashiem, R.; McQueen, M.; Ma, G.

2010-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

What are the differences between long-term, short-term, and working memory?

Science.gov (United States)

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term "working memory") that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1.

Short-term supervised inpatient physiotherapy exercise protocol improves cardiac autonomic function after coronary artery bypass graft surgery--a randomised controlled trial.

Science.gov (United States)

Mendes, Renata Gonçalves; Simões, Rodrigo Polaquini; De Souza Melo Costa, Fernando; Pantoni, Camila Bianca Falasco; Di Thommazo, Luciana; Luzzi, Sérgio; Catai, Aparecida Maria; Arena, Ross; Borghi-Silva, Audrey

2010-01-01

Coronary artery bypass grafting (CABG) is accompanied by severe impairment of cardiac autonomous regulation (CAR). This study aimed to determine whether a short-term physiotherapy exercise protocol post-CABG, during inpatient cardiac rehabilitation (CR), might improve CAR. Seventy-four patients eligible for CABG were recruited and randomised into physiotherapy exercise group (EG) or physiotherapy usual care group (UCG). EG patients underwent a short-term supervised inpatient physiotherapy exercise protocol consisting of an early mobilisation with progressive exercises plus usual care (respiratory exercises). UCG only received respiratory exercises. Forty-seven patients (24 EG and 23 UGC) completed the study. Outcome measures of CAR included linear and non-linear measures of heart rate variability (HRV) assessed before discharge. By hospital discharge, EG presented significantly higher parasympathetic HRV values [rMSSD, high frequency (HF), SD1)], global power (STD RR, SD2), non-linear HRV indexes [detrended fluctuation analysis (DFA)alpha1, DFAalpha2, approximate entropy (ApEn)] and mean RR compared to UCG (pexercise protocol during inpatient CR improves CAR at the time of discharge. Thus, exercise-based inpatient CR might be an effective non-pharmacological tool to improve autonomic cardiac tone in patient's post-CABG.

Electric power from near-term fusion reactors

International Nuclear Information System (INIS)

Longhurst, G.R.; Deis, G.A.; Miller, L.G.

1981-01-01

This paper examines requirements and possbilities of electric power production on near-term fusion reactors using low temperature cycle technology similar to that used in some geothermal power systems. Requirements include the need for a working fluid with suitable thermodynamics properties and which is free of oxygen and hydrogen to facilitate tritium management. Thermal storage will also be required due to the short system thermal time constants on near-time reactors. It is possbile to use the FED shield in a binary power cycle, and results are presented of thermodynamic analyses of this system

Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets

International Nuclear Information System (INIS)

Yamin, H.Y.; Shahidehpour, S.M.; Li, Z.

2004-01-01

This paper proposes a comprehensive model for the adaptive short-term electricity price forecasting using Artificial Neural Networks (ANN) in the restructured power markets. The model consists: price simulation, price forecasting, and performance analysis. The factors impacting the electricity price forecasting, including time factors, load factors, reserve factors, and historical price factor are discussed. We adopted ANN and proposed a new definition for the MAPE using the median to study the relationship between these factors and market price as well as the performance of the electricity price forecasting. The reserve factors are included to enhance the performance of the forecasting process. The proposed model handles the price spikes more efficiently due to considering the median instead of the average. The IEEE 118-bus system and California practical system are used to demonstrate the superiority of the proposed model. (author)

BASEL III: long-term impact on economic performance and fluctuations

OpenAIRE

Paolo Angelini; Laurent Clerc; Vasco Cúrdia; Leonardo Gambacorta; Andrea Gerali; Alberto Locarno; Roberto Motto; Werner Roeger; Skander J. van den Heuvel; Jan Vlcek

2011-01-01

We assess the long-term economic impact of the new regulatory standards (the Basel III reform), answering the following questions: 1) What is the impact of the reform on longterm economic performance? 2) What is the impact of the reform on economic fluctuations? 3) What is the impact of the adoption of countercyclical capital buffers on economic fluctuations? The main results are the following: 1) Each percentage point increase in the capital ratio causes a median 0.09 percent decline in the ...

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

Directory of Open Access Journals (Sweden)

Hongmin Meng

2017-07-01

Full Text Available In wind turbine control, maximum power point tracking (MPPT control is the main control mode for partial-load regimes. Efficiency potentiation of energy conversion and power smoothing are both two important control objectives in partial-load regime. However, on the one hand, low power fluctuation signifies inefficiency of energy conversion. On the other hand, enhancing efficiency may increase output power fluctuation as well. Thus the two objectives are contradictory and difficult to balance. This paper proposes a flexible MPPT control framework to improve the performance of both conversion efficiency and power smoothing, by adaptively compensating the torque reference value. The compensation was determined by a proposed model predictive control (MPC method with dynamic weights in the cost function, which improved control performance. The computational burden of the MPC solver was reduced by transforming the cost function representation. Theoretical analysis proved the good stability and robustness. Simulation results showed that the proposed method not only kept efficiency at a high level, but also reduced power fluctuations as much as possible. Therefore, the proposed method could improve wind farm profits and power grid reliability.

Revisiting short-term price and volatility dynamics in day-ahead electricity markets with rising wind power

International Nuclear Information System (INIS)

Li, Yuanjing

2015-01-01

This paper revisits the short-term price and volatility dynamics in day-ahead electricity markets in consideration of an increasing share of wind power, using an example of the Nord Pool day-ahead market and the Danish wind generation. To do so, a GARCH process is applied, and market coupling and the counterbalance effect of hydropower in the Scandinavian countries are additionally accounted for. As results, we found that wind generation weakly dampens spot prices with an elasticity of 0.008 and also reduces price volatility with an elasticity of 0.02 in the Nordic day-ahead market. The results shed lights on the importance of market coupling and interactions between wind power and hydropower in the Nordic system through cross-border exchanges, which play an essential role in price stabilization. Additionally, an EGARCH specification confirms an asymmetric influence of the price innovations, whereby negative shocks produce larger volatility in the Nordic spot market. While considering heavy tails in error distributions can improve model fits significantly, the EGARCH model outperforms the GARCH model on forecast evaluations. (author)

The Demonstration of Short-Term Consolidation.

Science.gov (United States)

Jolicoeur, Pierre; Dell'Acqua, Roberto

1998-01-01

Results of seven experiments involving 112 college students or staff using a dual-task approach provide evidence that encoding information into short-term memory involves a distinct process termed short-term consolidation (STC). Results suggest that STC has limited capacity and that it requires central processing mechanisms. (SLD)

Power Spectral Analysis of Short-Term Heart Rate Variability in Healthy and Arrhythmia Subjects by the Adaptive Continuous Morlet Wavelet Transform

Directory of Open Access Journals (Sweden)

Ram Sewak SINGH

2017-12-01

Full Text Available Power spectral analysis of short-term heart rate variability (HRV can provide instant valuable information to understand the functioning of autonomic control over the cardiovascular system. In this study, an adaptive continuous Morlet wavelet transform (ACMWT method has been used to describe the time-frequency characteristics of the HRV using band power spectra and the median value of interquartile range. Adaptation of the method was based on the measurement of maximum energy concentration. The ACMWT has been validated on synthetic signals (i.e. stationary, non-stationary as slow varying and fast changing frequency with time modeled as closest to dynamic changes in HRV signals. This method has been also tested in the presence of additive white Gaussian noise (AWGN to show its robustness towards the noise. From the results of testing on synthetic signals, the ACMWT was found to be an enhanced energy concentration estimator for assessment of power spectral of short-term HRV time series compared to adaptive Stockwell transform (AST, adaptive modified Stockwell transform (AMST, standard continuous Morlet wavelet transform (CMWT and Stockwell transform (ST estimators at statistical significance level of 5%. Further, the ACMWT was applied to real HRV data from Fantasia and MIT-BIH databases, grouped as healthy young group (HYG, healthy elderly group (HEG, arrhythmia controlled medication group (ARCMG, and supraventricular tachycardia group (SVTG subjects. The global results demonstrate that spectral indices of low frequency power (LFp and high frequency power (HFp of HRV were decreased in HEG compared to HYG subjects (p<0.0001. While LFp and HFp indices were increased in ARCMG compared to HEG (p<0.00001. The LFp and HFp components of HRV obtained from SVTG were reduced compared to other group subjects (p<0.00001.

Analysis of the fluctuation-induced excess dc conductivity of epitaxial YBa2Cu3O7 films: Influence of a short-wavelength cutoff in the fluctuation spectrum

International Nuclear Information System (INIS)

Hopfengaertner, R.; Hensel, B.; Saemann-Ischenko, G.

1991-01-01

Measurements of the temperature dependence of the in-plane dc conductivity on various high-quality epitaxial YBa 2 Cu 3 O 7 films are presented. The rounding of the resistivity in the transition region has been analyzed in terms of the anisotropic Aslamazov-Larkin (AL), Lawrence-Doniach (LD), and Maki-Thompson theories. In the framework of the time-dependent Ginzburg-Landau (GL) approach we have investigated the influence of a short-wavelength cutoff parameter in the fluctuation spectrum of the AL and LD term. In both theories this physically reasonable cutoff leads to a considerable reduction of the predicted excess dc conductivity at higher temperatures. Moreover, the three-dimensional anisotropic AL term, taking the cutoff into account, predicts nearly the same excess conductivity as the original LD term, although these two approaches describe different systems. A good agreement between experimental data and LD as well as the modified three-dimensional anisotropic AL term was found in the region 1.01T c ≤T≤1.1T c . The zero-temperature GL coherence length ξ c (0) has been estimated to be about 1.5 A

Scaling forecast models for wind turbulence and wind turbine power intermittency

Science.gov (United States)

Duran Medina, Olmo; Schmitt, Francois G.; Calif, Rudy

2017-04-01

The intermittency of the wind turbine power remains an important issue for the massive development of this renewable energy. The energy peaks injected in the electric grid produce difficulties in the energy distribution management. Hence, a correct forecast of the wind power in the short and middle term is needed due to the high unpredictability of the intermittency phenomenon. We consider a statistical approach through the analysis and characterization of stochastic fluctuations. The theoretical framework is the multifractal modelisation of wind velocity fluctuations. Here, we consider three wind turbine data where two possess a direct drive technology. Those turbines are producing energy in real exploitation conditions and allow to test our forecast models of power production at a different time horizons. Two forecast models were developed based on two physical principles observed in the wind and the power time series: the scaling properties on the one hand and the intermittency in the wind power increments on the other. The first tool is related to the intermittency through a multifractal lognormal fit of the power fluctuations. The second tool is based on an analogy of the power scaling properties with a fractional brownian motion. Indeed, an inner long-term memory is found in both time series. Both models show encouraging results since a correct tendency of the signal is respected over different time scales. Those tools are first steps to a search of efficient forecasting approaches for grid adaptation facing the wind energy fluctuations.

Anisotropic power spectrum of refractive-index fluctuation in hypersonic turbulence.

Science.gov (United States)

Li, Jiangting; Yang, Shaofei; Guo, Lixin; Cheng, Mingjian

2016-11-10

An anisotropic power spectrum of the refractive-index fluctuation in hypersonic turbulence was obtained by processing the experimental image of the hypersonic plasma sheath and transforming the generalized anisotropic von Kármán spectrum. The power spectrum suggested here can provide as good a fit to measured spectrum data for hypersonic turbulence as that recorded from the nano-planar laser scattering image. Based on the newfound anisotropic hypersonic turbulence power spectrum, Rytov approximation was employed to establish the wave structure function and the spatial coherence radius model of electromagnetic beam propagation in hypersonic turbulence. Enhancing the anisotropy characteristics of the hypersonic turbulence led to a significant improvement in the propagation performance of electromagnetic beams in hypersonic plasma sheath. The influence of hypersonic turbulence on electromagnetic beams increases with the increase of variance of the refractive-index fluctuation and the decrease of turbulence outer scale and anisotropy parameters. The spatial coherence radius was much smaller than that in atmospheric turbulence. These results are fundamental to understanding electromagnetic wave propagation in hypersonic turbulence.

An Optimized Prediction Intervals Approach for Short Term PV Power Forecasting

Directory of Open Access Journals (Sweden)

Qiang Ni

2017-10-01

Full Text Available High quality photovoltaic (PV power prediction intervals (PIs are essential to power system operation and planning. To improve the reliability and sharpness of PIs, in this paper, a new method is proposed, which involves the model uncertainties and noise uncertainties, and PIs are constructed with a two-step formulation. In the first step, the variance of model uncertainties is obtained by using extreme learning machine to make deterministic forecasts of PV power. In the second stage, innovative PI-based cost function is developed to optimize the parameters of ELM and noise uncertainties are quantization in terms of variance. The performance of the proposed approach is examined by using the PV power and meteorological data measured from 1kW rooftop DC micro-grid system. The validity of the proposed method is verified by comparing the experimental analysis with other benchmarking methods, and the results exhibit a superior performance.

What are the differences between long-term, short-term, and working memory?

OpenAIRE

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rath...

Long-term contracts vs. short-term trade of natural gas - a European perspective

International Nuclear Information System (INIS)

Neuhoff, Karsten; Hirschhausen, Christian von

2005-01-01

This paper analyses the economics of long-term gas contracts under changing institutional conditions, mainly gas sector liberalisation. The paper is motivated by the increasingly tense debate in continental Europe, UK and the US on the security of long-term gas supply. We discuss the main issues regarding long-term contracts, i.e. the changing role of the flexibility clause, the effect of abandoning the destination clause, and the strategic behaviour of producers between long-term sales and spot-sales. The literature suggests consumers and producers benefit from risk hedging through long-term contracts. Furthermore long-term contracts may reduce exercise of market power. Our analysis adds an additional benefit if the long-run demand elasticity is significantly lower than the short-run elasticity, both strategic producers and consumers benefit from lower prices and larger market volume. Some policy implications of the findings are also discussed. (Author)

Short-term memory across eye blinks.

Science.gov (United States)

Irwin, David E

2014-01-01

The effect of eye blinks on short-term memory was examined in two experiments. On each trial, participants viewed an initial display of coloured, oriented lines, then after a retention interval they viewed a test display that was either identical or different by one feature. Participants kept their eyes open throughout the retention interval on some blocks of trials, whereas on others they made a single eye blink. Accuracy was measured as a function of the number of items in the display to determine the capacity of short-term memory on blink and no-blink trials. In separate blocks of trials participants were instructed to remember colour only, orientation only, or both colour and orientation. Eye blinks reduced short-term memory capacity by approximately 0.6-0.8 items for both feature and conjunction stimuli. A third, control, experiment showed that a button press during the retention interval had no effect on short-term memory capacity, indicating that the effect of an eye blink was not due to general motoric dual-task interference. Eye blinks might instead reduce short-term memory capacity by interfering with attention-based rehearsal processes.

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.

Short-term memory and dual task performance

Science.gov (United States)

Regan, J. E.

1982-01-01

Two hypotheses concerning the way in which short-term memory interacts with another task in a dual task situation are considered. It is noted that when two tasks are combined, the activity of controlling and organizing performance on both tasks simultaneously may compete with either task for a resource; this resource may be space in a central mechanism or general processing capacity or it may be some task-specific resource. If a special relationship exists between short-term memory and control, especially if there is an identity relationship between short-term and a central controlling mechanism, then short-term memory performance should show a decrement in a dual task situation. Even if short-term memory does not have any particular identity with a controlling mechanism, but both tasks draw on some common resource or resources, then a tradeoff between the two tasks in allocating resources is possible and could be reflected in performance. The persistent concurrence cost in memory performance in these experiments suggests that short-term memory may have a unique status in the information processing system.

A Study on Electric Power Smoothing System for Lead-Acid Battery of Stand-Alone Natural Energy Power System Using EDLC

Science.gov (United States)

Jia, Yan; Shibata, Ryosuke; Yamamura, Naoki; Ishida, Muneaki

To resolve energy shortage and global warming problem, renewable natural resource and its power system has been gradually generalizing. However, the power fluctuation suppressing in short period and the balance control of consumption and supply in long period are two of main problems that need to be resolved urgently in natural energy power system. In Stand-alone Natural Energy Power System (SNEPS) with power energy storage devices, power fluctuation in short period is one of the main reasons that recharge cycle times increase and lead-acid battery early failure. Hence, to prolong the service life of lead-acid battery and improve power quality through suppressing the power fluctuation, we proposed a method of electric power smoothing for lead-acid battery of SNEPS using bi-directional Buck/Boost converter and Electric Double Layer Capacitor (EDLC) in this paper. According to the test data of existing SNEPS, a power fluctuation condition is selected and as an example to analyze the validity of the proposed method. The analysis of frequency characteristics indicates the power fluctuation is suppressed a desired range in the target frequency region. The experimental results of confirmed the feasibility of the proposed system and the results well satisfy the requirement of system design.

Detrended fluctuation analysis of short datasets: An application to fetal cardiac data

Science.gov (United States)

Govindan, R. B.; Wilson, J. D.; Preißl, H.; Eswaran, H.; Campbell, J. Q.; Lowery, C. L.

2007-02-01

Using detrended fluctuation analysis (DFA) we perform scaling analysis of short datasets of length 500-1500 data points. We quantify the long range correlation (exponent α) by computing the mean value of the local exponents αL (in the asymptotic regime). The local exponents are obtained as the (numerical) derivative of the logarithm of the fluctuation function F(s) with respect to the logarithm of the scale factor s:αL=dlog10F(s)/dlog10s. These local exponents display huge variations and complicate the correct quantification of the underlying correlations. We propose the use of the phase randomized surrogate (PRS), which preserves the long range correlations of the original data, to minimize the variations in the local exponents. Using the numerically generated uncorrelated and long range correlated data, we show that performing DFA on several realizations of PRS and estimating αL from the averaged fluctuation functions (of all realizations) can minimize the variations in αL. The application of this approach to the fetal cardiac data (RR intervals) is discussed and we show that there is a statistically significant correlation between α and the gestation age.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Science.gov (United States)

Merema, Matt R; Speelman, Craig P

2015-01-01

It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males) participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Directory of Open Access Journals (Sweden)

Matt R Merema

Full Text Available It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

Dangerous dream: Nuclear power. With an attached short dictionary of terms in nuclear energy. Der gefaehrliche Traum: Atomkraft. Mit kleinem Lexikon der Atom-Energie

Energy Technology Data Exchange (ETDEWEB)

Paul, R

1986-01-01

After Chernobyl: Necessary basic knowledge and information, data on safety hazards and risks, sketches of all German nuclear power plants and brief accounts of incidents reported so far, consequences of the Chernobyl and Harrisburg accidents for man and the environment, emergency control plans. With an attached short dictionary of terms in nuclear energy.

Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

OpenAIRE

Stewart, Ian; Arendt, Dustin; Bell, Eric; Volkova, Svitlana

2017-01-01

Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. Such dynamics are especially notable during a period of crisis. This work addresses several important tasks of measuring, visualizing and predicting short term text representation shift, i.e. the change in a word's contextual semantics, and contrasting such shift with surface level word dynamics, or concept drift, observed in social media streams. ...

Power injected in dissipative systems and the fluctuation theorem

Science.gov (United States)

Aumaître, S.; Fauve, S.; McNamara, S.; Poggi, P.

We consider three examples of dissipative dynamical systems involving many degrees of freedom, driven far from equilibrium by a constant or time dependent forcing. We study the statistical properties of the injected and dissipated power as well as the fluctuations of the total energy of these systems. The three systems under consideration are: a shell model of turbulence, a gas of hard spheres colliding inelastically and excited by a vibrating piston, and a Burridge-Knopoff spring-block model. Although they involve different types of forcing and dissipation, we show that the statistics of the injected power obey the ``fluctuation theorem" demonstrated in the case of time reversible dissipative systems maintained at constant total energy, or in the case of some stochastic processes. Although this may be only a consequence of the theory of large deviations, this allows a possible definition of ``temperature" for a dissipative system out of equilibrium. We consider how this ``temperature" scales with the energy and the number of degrees of freedom in the different systems under consideration.

Short-Term Solar Collector Power Forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Perers, Bengt

2011-01-01

This paper describes a new approach to online forecasting of power output from solar thermal collectors. The method is suited for online forecasting in many applications and in this paper it is applied to predict hourly values of power from a standard single glazed large area flat plate collector...... enabling tracking of changes in the system and in the surrounding conditions, such as decreasing performance due to wear and dirt, and seasonal changes such as leaves on trees. This furthermore facilitates remote monitoring and check of the system....

Gut microbiome response to short-term dietary interventions in reactive hypoglycemia subjects.

Science.gov (United States)

Quercia, Sara; Turroni, Silvia; Fiori, Jessica; Soverini, Matteo; Rampelli, Simone; Biagi, Elena; Castagnetti, Andrea; Consolandi, Clarissa; Severgnini, Marco; Pianesi, Mario; Fallucca, Francesco; Pozzilli, Paolo; Brigidi, Patrizia; Candela, Marco

2017-11-01

Reactive hypoglycemia is a metabolic disorder that provokes severe hypoglycemic episodes after meals. Over recent years, the gut microbiota has been recognized as potential target for the control of metabolic diseases, and the possibility to correct gut microbiota dysbioses through diet, favouring the recovery of metabolic homeostasis, has been considered. We investigate the impact of 2 short-term (3-day) nutritional interventions, based on the macrobiotic Ma-Pi 2 diet and a control Mediterranean diet, on the structure and functionality of the gut microbiota in 12 patients affected by reactive hypoglycemia. The gut microbiota composition was characterized by next-generation sequencing of the V3 to V4 region of the 16S rRNA gene, and the ecosystem functionality was addressed by measuring the faecal concentration of short-chain fatty acids (SCFAs). In order to measure the short-term physiological gut microbiota fluctuation, the microbiomes of 7 healthy people were characterized before and after 3 days of constant diet. While no convergence of the gut microbiota compositional profiles was observed, a significant increase in SCFA faecal levels was induced only in the Ma-Pi 2 diet group, suggesting the potential of this diet to support a short-term functional convergence of the gut microbiota, regardless of the individual compositional layout. The Ma-Pi 2 diet, with its high fibre load, was effective in increasing the production of SCFAs by the gut microbiota. Because these metabolites are known for their ability to counterbalance the metabolic deregulation in persons with glucose impairment disorders, their increased bioavailability could be of some relevance in reactive hypoglycemia. Copyright © 2017 John Wiley & Sons, Ltd.

A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

Directory of Open Access Journals (Sweden)

Henrik Madsen

2012-03-01

Full Text Available Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes. Such complexity is addressed from three perspectives: (i the modeling of a nonlinear and non-stationary stochastic process; (ii the practical implementation of the model we proposed; (iii the gap between working on synthetic data and real world observations. At time-scales of a few minutes, offshore fluctuations are characterized by highly volatile dynamics which are difficult to capture and predict. Due to the lack of adequate on-site meteorological observations to relate these dynamics to meteorological phenomena, we propose a general model formulation based on a statistical approach and historical wind power measurements only. We introduce an advanced Markov Chain Monte Carlo (MCMC estimation method to account for the different features observed in an empirical time series of wind power: autocorrelation, heteroscedasticity and regime-switching. The model we propose is an extension of Markov-Switching Autoregressive (MSAR models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH errors in each regime to cope with the heteroscedasticity. Then, we analyze the predictive power of our model on a one-step ahead exercise of time series sampled over 10 min intervals. Its performances are compared to state-of-the-art models and highlight the interest of including a GARCH specification for density forecasts.

Effects of Short-Term Jump Squat Training With and Without Chains on Strength and Power in Recreational Lifters

Directory of Open Access Journals (Sweden)

David C. Archer

2016-10-01

Full Text Available Background: The use of chains in resistance training is a way to accommodate the muscular strength curve. Short-term training and jump squats have been shown to increase back squat strength, but not in conjunction with each other or with chains. Jump squats have also been used to increase jump height and power. Objectives: The purpose of this study was to investigate the effects of short-term jump squat training with and without chains on strength and power. Methods: Thirty-one resistance-trained men volunteered to participate (age = 23.87 ± 2.2 years, height=174.87 ± 6.94 cm, mass = 82.74 ± 14.95 kg and were randomly assigned to one of three groups [control (C = 10, no chains (NC =10, or chains (CH = 11]. Participants had their jump height (VJ and back squat strength (BS tested before and after a week of training. The NC and CH groups performed three training sessions consisting of five sets of three reps of jump squats at 30% 1RM with 30s rest between sets. The CH group had 20% of their load added by chains when standing erect. The C group did not train. Results: A 3 (group: CH, NC, C x 2 (time: pre, post mixed factor ANOVA revealed a significant (p = 0.006 interaction for back squat 1RM. Both the CH (pre 142.56 ± 20.40 kg; post 145.66 ± 19.59 kg and NC (pre 150.00 ± 15.23 kg; post 154.77 ± 15.09 kg groups significantly increased while the C (pre 157.27 ± 25.35 kg; post 156.36 ± 24.85 kg group showed no difference. There were no significant interactions (p =0.32 or main effects for VJ (C = pre 50.59 ± 9.39cm; post 51.29 ± 9.68cm; NC = pre 55.29 ± 5.23cm; post 57.39 ± 5.22cm; CH = pre 46.19 ± 5.02; post 47.45 ± 4.62. Conclusions: The CH group was able to increase strength while lifting less overall weight. Coaches may use short-term training with chains to yield a similar increase in back squat strength as without chains. Keywords: variable resistance, back squats, novel, vertical jump

Short-term incentive schemes for hospital managers

Directory of Open Access Journals (Sweden)

Lucas Malambe

2013-10-01

Full Text Available Orientation: Short-term incentives, considered to be an extrinsic motivation, are commonly used to motivate performance. This study explored hospital managers’ perceptions of short term incentives in maximising performance and retention. Research purpose: The study explored the experiences, views and perceptions of private hospital managers in South Africa regarding the use of short-term incentives to maximise performance and retention, as well as the applicability of the findings to public hospitals. Motivation for the study: Whilst there is an established link between performance reward schemes and organisational performance, there is little understanding of the effects of short term incentives on the performance and retention of hospital managers within the South African context. Research design, approach, and method: The study used a qualitative research design: interviews were conducted with a purposive sample of 19 hospital managers, and a thematic content analysis was performed. Main findings: Short-term incentives may not be the primary motivator for hospital managers, but they do play a critical role in sustaining motivation. Participants indicated that these schemes could also be applicable to public hospitals. Practical/managerial implications: Hospital managers are inclined to be more motivated by intrinsic than extrinsic factors. However, hospital managers (as middle managers also seem to be motivated by short-term incentives. A combination of intrinsic and extrinsic motivators should thus be used to maximise performance and retention. Contribution/value-add: Whilst the study sought to explore hospital managers’ perceptions of short-term incentives, it also found that an adequate balance between internal and external motivators is key to implementing an effective short-term incentive scheme.

Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

Science.gov (United States)

Seeley, Karen M.

2004-01-01

This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical…

Why do short term workers have high mortality?

DEFF Research Database (Denmark)

Kolstad, Henrik; Olsen, Jørn

1999-01-01

or violence, the rate ratios for short term employment were 2.30 (95% Cl 1.74-3.06) and 1.86 (95% Cl 1.35-2.56), respectively. An unhealthy lifestyle may also be a determinant of short term employment. While it is possible in principle to adjust for lifestyle factors if proper data are collected, the health......Increased mortality is often reported among workers in short term employment. This may indicate either a health-related selection process or the presence of different lifestyle or social conditions among short term workers. The authors studied these two aspects of short term employment among 16...

Simulation of power fluctuation of wind farms based on frequency domain

DEFF Research Database (Denmark)

Lin, Jin; Sun, Yuanzhang; Li, Guojie

2011-01-01

The wind power fluctuation model built up in the frequency domain is mathematically equivalent with that in the time domain, and has a clearer physical meaning therefore describes the fluctuation more accurately. However, the simulation of this model is required to deal with the time......-frequency transformation related to the power spectrum density (PSD), which is more special and complicated than normal transformations. Meanwhile, the computational complexity also increases significantly, more computation resources are needed. These problems negatively affect the engineering application of the model....... To overcome these disadvantages, the physical meaning of PSD based on fundamental concepts is presented, so that the specialties of this model compared with conventional ones can be understood. Then the time-frequency transformation algorithm is derived, which is fast to be implemented in digital computers...

A fuzzy inference model for short-term load forecasting

International Nuclear Information System (INIS)

Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

2009-01-01

This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes

Relation of the second law of thermodynamics to the power conversion of energy fluctuations

International Nuclear Information System (INIS)

Yater, J.C.

1979-01-01

The relation of the second law of thermodynamics to the power conversion of fluctuation energy is analyzed using the master equation of the model for the conversion circuit. The performance equation for independent particles shows that the power-conversion performance is given by the second law both for classical and quantum-effect diodes. The relation of the second law to power-conversion models based on the theoretical and experimental results for diode performance for interacting particles exhibiting many-body, multiparticle, or other anomalous and excess-current effects is examined. The performance equations are derived from the master equation for models for interacting particles to determine the conditions required by the second law for power conversion. These conditions are given in terms of the distribution throughout the power-conversion circuit for all the parameters that determine the particle and multiparticle barrier-crossing probability such as the effective mass and spectral density functions. Circuits for spectroscopic measurements for power-conversion circuits with interacting particles are noted. Using selected experimental values for the diode nonlinearity factors in these circuits, open circuit voltages are computed that are not predicted by the second law of thermodynamics

Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

DEFF Research Database (Denmark)

López, Erick; Allende, Héctor; Gil, Esteban

2018-01-01

involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed...

Maxwell's Demon at work: Two types of Bose condensate fluctuations in power-law traps.

Science.gov (United States)

Grossmann, S; Holthaus, M

1997-11-10

After discussing the idea underlying the Maxwell's Demon ensemble, we employ this ensemble for calculating fluctuations of ideal Bose gas condensates in traps with power-law single-particle energy spectra. Two essentially different cases have to be distinguished. If the heat capacity is continuous at the condensation point, the fluctuations of the number of condensate particles vanish linearly with temperature, independent of the trap characteristics. In this case, microcanonical and canonical fluctuations are practically indistinguishable. If the heat capacity is discontinuous, the fluctuations vanish algebraically with temperature, with an exponent determined by the trap, and the micro-canonical fluctuations are lower than their canonical counterparts.

Strategy Design of Hybrid Energy Storage System for Smoothing Wind Power Fluctuations

Directory of Open Access Journals (Sweden)

Jingyu Liu

2016-11-01

Full Text Available With the increasing contribution of wind power plants, the reliability and security of modern power systems have become a huge challenge due to the uncertainty and intermittency of wind energy sources. In this paper, a hybrid energy storage system (HESS consisting of battery and supercapacitor is built to smooth the power fluctuations of wind power. A power allocation strategy is proposed to give full play to the respective advantages of the two energy storage components. In the proposed strategy, the low-frequency and high-frequency components of wind power fluctuations are absorbed by battery groups and supercapacitor groups, respectively. By inhibiting the low-frequency components of supercapacitor current, the times of charging-discharging of battery groups can be significantly reduced. A DC/AC converter is applied to achieve the power exchange between the HESS and the grid. Adjustment rules for regulating state-of-charge (SOC of energy storage elements are designed to avoid overcharge and deep discharge considering the safety and the high efficiency of the energy storage elements. Experimental results on the test platform verify the effectiveness of the proposed power allocation strategy in DC/AC converter and battery SOC adjustment rules for regulating SOC levels.

Real-Time Wavelet-Based Coordinated Control of Hybrid Energy Storage Systems for Denoising and Flattening Wind Power Output

Directory of Open Access Journals (Sweden)

Tran Thai Trung

2014-10-01

Full Text Available Since the penetration level of wind energy is continuously increasing, the negative impact caused by the fluctuation of wind power output needs to be carefully managed. This paper proposes a novel real-time coordinated control algorithm based on a wavelet transform to mitigate both short-term and long-term fluctuations by using a hybrid energy storage system (HESS. The short-term fluctuation is eliminated by using an electric double-layer capacitor (EDLC, while the wind-HESS system output is kept constant during each 10-min period by a Ni-MH battery (NB. State-of-charge (SOC control strategies for both EDLC and NB are proposed to maintain the SOC level of storage within safe operating limits. A ramp rate limitation (RRL requirement is also considered in the proposed algorithm. The effectiveness of the proposed algorithm has been tested by using real time simulation. The simulation model of the wind-HESS system is developed in the real-time digital simulator (RTDS/RSCAD environment. The proposed algorithm is also implemented as a user defined model of the RSCAD. The simulation results demonstrate that the HESS with the proposed control algorithm can indeed assist in dealing with the variation of wind power generation. Moreover, the proposed method shows better performance in smoothing out the fluctuation and managing the SOC of battery and EDLC than the simple moving average (SMA based method.

Short-term mechanisms influencing volumetric brain dynamics

Directory of Open Access Journals (Sweden)

Nikki Dieleman

2017-01-01

Full Text Available With the use of magnetic resonance imaging (MRI and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist. When we focus on short-term changes of the brain, changes may be either physiological or pathological. As such determining the cause of volumetric dynamics of the brain is essential. Additionally for an accurate interpretation of longitudinal brain volume measures by means of neurodegeneration, knowledge about the short-term changes is needed. Therefore, in this review, we discuss the possible mechanisms influencing brain volumes on a short-term basis and set-out a framework of MRI techniques to be used for volumetric changes as well as the used analysis tools. 3D T1-weighted images are the images of choice when it comes to MRI of brain volume. These images are excellent to determine brain volume and can be used together with an analysis tool to determine the degree of volume change. Mechanisms that decrease global brain volume are: fluid restriction, evening MRI measurements, corticosteroids, antipsychotics and short-term effects of pathological processes like Alzheimer's disease, hypertension and Diabetes mellitus type II. Mechanisms increasing the brain volume include fluid intake, morning MRI measurements, surgical revascularization and probably medications like anti-inflammatory drugs and anti-hypertensive medication. Exercise was found to have no effect on brain volume on a short-term basis, which may imply that dehydration caused by exercise differs from dehydration by fluid restriction. In the upcoming years, attention should be directed towards studies investigating physiological short-term changes within the light of long-term pathological changes. Ultimately this may lead to a better understanding of the physiological short-term effects of

Short-term stability test for thorium soil candidate a reference material

Energy Technology Data Exchange (ETDEWEB)

Clain, Almir F.; Fonseca, Adelaide M.G.; Dantas, Vanessa V.D.B.; Braganca, Maura J.C.; Souza, Poliana S., E-mail: almir@ird.gov.br, E-mail: adelaide@ird.gov.br, E-mail: vanessa@ird.gov.br, E-mail: maura@ird.gov.br, E-mail: poliana@bolsista.ird.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

2015-07-01

This work describes a methodology to determine the soil short-term stability after the steps of production in laboratory. The short-term stability of the soil is an essential property to be determined in order to producing a reference material. The soil is a candidate of reference material for chemical analysis of thorium with metrological traceability to be used in environmental analysis, equipment calibration, validation methods, and quality control. A material is considered stable in a certain temperature if the property of interest does not change with time, considering the analytical random fluctuations. Due to this, the angular coefficient from the graphic of Th concentration versus elapsed time must be near to zero. The analytical determinations of thorium concentration were performed by Instrumental Neutron activation Analysis. The slopes and their uncertainties were obtained from the regression lines at temperatures of 20 deg C and 60 deg C, with control temperature of -20 deg C. From the obtained data a t-test was applied. In both temperatures the calculated t-value was lower than the critical value, so we can conclude with 95% confidence level that no significant changes happened during the period studied concerning thorium concentration in soil at temperatures of 20 deg C and 60 deg C, showing stability at these temperatures. (author)

Short-term stability test for thorium soil candidate a reference material

International Nuclear Information System (INIS)

Clain, Almir F.; Fonseca, Adelaide M.G.; Dantas, Vanessa V.D.B.; Braganca, Maura J.C.; Souza, Poliana S.

2015-01-01

This work describes a methodology to determine the soil short-term stability after the steps of production in laboratory. The short-term stability of the soil is an essential property to be determined in order to producing a reference material. The soil is a candidate of reference material for chemical analysis of thorium with metrological traceability to be used in environmental analysis, equipment calibration, validation methods, and quality control. A material is considered stable in a certain temperature if the property of interest does not change with time, considering the analytical random fluctuations. Due to this, the angular coefficient from the graphic of Th concentration versus elapsed time must be near to zero. The analytical determinations of thorium concentration were performed by Instrumental Neutron activation Analysis. The slopes and their uncertainties were obtained from the regression lines at temperatures of 20 deg C and 60 deg C, with control temperature of -20 deg C. From the obtained data a t-test was applied. In both temperatures the calculated t-value was lower than the critical value, so we can conclude with 95% confidence level that no significant changes happened during the period studied concerning thorium concentration in soil at temperatures of 20 deg C and 60 deg C, showing stability at these temperatures. (author)

Verbal Short-Term Memory Span in Speech-Disordered Children: Implications for Articulatory Coding in Short-Term Memory.

Science.gov (United States)

Raine, Adrian; And Others

1991-01-01

Children with speech disorders had lower short-term memory capacity and smaller word length effect than control children. Children with speech disorders also had reduced speech-motor activity during rehearsal. Results suggest that speech rate may be a causal determinant of verbal short-term memory capacity. (BC)

A Simplified Short Term Load Forecasting Method Based on Sequential Patterns

DEFF Research Database (Denmark)

Kouzelis, Konstantinos; Bak-Jensen, Birgitte; Mahat, Pukar

2014-01-01

Load forecasting is an essential part of a power system both for planning and daily operation purposes. As far as the latter is concerned, short term load forecasting has been broadly used at the transmission level. However, recent technological advancements and legislation have facilitated the i...... in comparison with an ARIMA model....

Real-time energy resources scheduling considering short-term and very short-term wind forecast

Energy Technology Data Exchange (ETDEWEB)

Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

2012-07-01

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

Short-Term Multiple Forecasting of Electric Energy Loads for Sustainable Demand Planning in Smart Grids for Smart Homes

Directory of Open Access Journals (Sweden)

Adeshina Y. Alani

2017-10-01

Full Text Available Energy consumption in the form of fuel or electricity is ubiquitous globally. Among energy types, electricity is crucial to human life in terms of cooking, warming and cooling of shelters, powering of electronic devices as well as commercial and industrial operations. Users of electronic devices sometimes consume fluctuating amounts of electricity generated from smart-grid infrastructure owned by the government or private investors. However, frequent imbalance is noticed between the demand and supply of electricity, hence effective planning is required to facilitate its distribution among consumers. Such effective planning is stimulated by the need to predict future consumption within a short period. Although several interesting classical techniques have been used for such predictions, they still require improvement for the purpose of reducing significant predictive errors when used for short-term load forecasting. This research develops a near-zero cooperative probabilistic scenario analysis and decision tree (PSA-DT model to address the lacuna of enormous predictive error faced by the state-of-the-art models. The PSA-DT is based on a probabilistic technique in view of the uncertain nature of electricity consumption, complemented by a DT to reinforce the collaboration of the two techniques. Based on detailed experimental analytics on residential, commercial and industrial data loads, the PSA-DT model outperforms the state-of-the-art models in terms of accuracy to a near-zero error rate. This implies that its deployment for electricity demand planning will be of great benefit to various smart-grid operators and homes.

An analog ensemble for short-term probabilistic solar power forecast

International Nuclear Information System (INIS)

Alessandrini, S.; Delle Monache, L.; Sperati, S.; Cervone, G.

2015-01-01

Highlights: • A novel method for solar power probabilistic forecasting is proposed. • The forecast accuracy does not depend on the nominal power. • The impact of climatology on forecast accuracy is evaluated. - Abstract: The energy produced by photovoltaic farms has a variable nature depending on astronomical and meteorological factors. The former are the solar elevation and the solar azimuth, which are easily predictable without any uncertainty. The amount of liquid water met by the solar radiation within the troposphere is the main meteorological factor influencing the solar power production, as a fraction of short wave solar radiation is reflected by the water particles and cannot reach the earth surface. The total cloud cover is a meteorological variable often used to indicate the presence of liquid water in the troposphere and has a limited predictability, which is also reflected on the global horizontal irradiance and, as a consequence, on solar photovoltaic power prediction. This lack of predictability makes the solar energy integration into the grid challenging. A cost-effective utilization of solar energy over a grid strongly depends on the accuracy and reliability of the power forecasts available to the Transmission System Operators (TSOs). Furthermore, several countries have in place legislation requiring solar power producers to pay penalties proportional to the errors of day-ahead energy forecasts, which makes the accuracy of such predictions a determining factor for producers to reduce their economic losses. Probabilistic predictions can provide accurate deterministic forecasts along with a quantification of their uncertainty, as well as a reliable estimate of the probability to overcome a certain production threshold. In this paper we propose the application of an analog ensemble (AnEn) method to generate probabilistic solar power forecasts (SPF). The AnEn is based on an historical set of deterministic numerical weather prediction (NWP) model

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

Directory of Open Access Journals (Sweden)

Haoran Zhao

2018-03-01

Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

Institute of Scientific and Technical Information of China (English)

Xia Hua; Gang Zhang; Jiawei Yang; Zhengyuan Li

2015-01-01

Aiming at the low accuracy problem of power system short⁃term load forecasting by traditional methods, a back⁃propagation artifi⁃cial neural network (BP⁃ANN) based method for short⁃term load forecasting is presented in this paper. The forecast points are re⁃lated to prophase adjacent data as well as the periodical long⁃term historical load data. Then the short⁃term load forecasting model of Shanxi Power Grid (China) based on BP⁃ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP⁃ANN method is simple and with higher precision and practicality.

The Mind and Brain of Short-Term Memory

OpenAIRE

Jonides, John; Lewis, Richard L.; Nee, Derek Evan; Lustig, Cindy A.; Berman, Marc G.; Moore, Katherine Sledge

2008-01-01

The past 10 years have brought near-revolutionary changes in psychological theories about short-term memory, with similarly great advances in the neurosciences. Here, we critically examine the major psychological theories (the “mind”) of short-term memory and how they relate to evidence about underlying brain mechanisms. We focus on three features that must be addressed by any satisfactory theory of short-term memory. First, we examine the evidence for the architecture of short-term memory, w...

Very-long-term and short-term chromatic adaptation: are their influences cumulative?

Science.gov (United States)

Belmore, Suzanne C; Shevell, Steven K

2011-02-09

Very-long-term (VLT) chromatic adaptation results from exposure to an altered chromatic environment for days or weeks. Color shifts from VLT adaptation are observed hours or days after leaving the altered environment. Short-term chromatic adaptation, on the other hand, results from exposure for a few minutes or less, with color shifts measured within seconds or a few minutes after the adapting light is extinguished; recovery to the pre-adapted state is complete in less than an hour. Here, both types of adaptation were combined. All adaptation was to reddish-appearing long-wavelength light. Shifts in unique yellow were measured following adaptation. Previous studies demonstrate shifts in unique yellow due to VLT chromatic adaptation, but shifts from short-term chromatic adaptation to comparable adapting light can be far greater than from VLT adaptation. The question considered here is whether the color shifts from VLT adaptation are cumulative with large shifts from short-term adaptation or, alternatively, does simultaneous short-term adaptation eliminate color shifts caused by VLT adaptation. The results show the color shifts from VLT and short-term adaptation together are cumulative, which indicates that both short-term and very-long-term chromatic adaptation affect color perception during natural viewing. Copyright © 2010 Elsevier Ltd. All rights reserved.

The dependence of the nuclear charge form factor on short range correlations and surface fluctuation effects

International Nuclear Information System (INIS)

Massen, S. E.; Garistov, V. P.; Grypeos, M. E.

1996-01-01

The effects of nuclear surface fluctuations on harmonic oscillator elastic charge form factor of light nuclei are investigated, simultaneously approximating the short-range correlations through a Jastrow correlation factor. Inclusion of the surface fluctuation effects within this description, by truncating the cluster expansion at the two-body part, is found to improve somewhat the fit to the elastic charge form-factor of 16 O and 40 Ca. However, the convergence of the cluster expansion is expected to deteriorate. An additional finding is that surface-fluctuation correlations produce a drastic change in the asymptotic behaviour of the point-proton form-factor, which now falls off quite slowly (i.e. as const.q -4 ) at large values of the momentum transfer q

Short-term load and wind power forecasting using neural network-based prediction intervals.

Science.gov (United States)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Predicting short-term weight loss using four leading health behavior change theories

Directory of Open Access Journals (Sweden)

Barata José T

2007-04-01

Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

FLUCTUATING SELECTION AND THE MAINTENANCE OF INDIVIDUAL AND SEX-SPECIFIC DIET SPECIALIZATION IN FREE-LIVING OYSTERCATCHERS

NARCIS (Netherlands)

van de Pol, Martijn; Brouwer, Lyanne; Ens, B; Oosterbeek, Kees; Tinbergen, Joost M.; Candolin, U.

Fluctuating and disruptive selection are important mechanisms for maintaining intrapopulation trait variation. Nonetheless, few field studies quantify selection pressures over long periods and identify what causes them to fluctuate. Diet specialists in oystercatchers differ in short-term payoffs

Detecting method for crude oil price fluctuation mechanism under different periodic time series

International Nuclear Information System (INIS)

Gao, Xiangyun; Fang, Wei; An, Feng; Wang, Yue

2017-01-01

Highlights: • We proposed the concept of autoregressive modes to indicate the fluctuation patterns. • We constructed transmission networks for studying the fluctuation mechanism. • There are different fluctuation mechanism under different periodic time series. • Only a few types of autoregressive modes control the fluctuations in crude oil price. • There are cluster effects during the fluctuation mechanism of autoregressive modes. - Abstract: Current existing literatures can characterize the long-term fluctuation of crude oil price time series, however, it is difficult to detect the fluctuation mechanism specifically under short term. Because each fluctuation pattern for one short period contained in a long-term crude oil price time series have dynamic characteristics of diversity; in other words, there exhibit various fluctuation patterns in different short periods and transmit to each other, which reflects the reputedly complicate and chaotic oil market. Thus, we proposed an incorporated method to detect the fluctuation mechanism, which is the evolution of the different fluctuation patterns over time from the complex network perspective. We divided crude oil price time series into segments using sliding time windows, and defined autoregressive modes based on regression models to indicate the fluctuation patterns of each segment. Hence, the transmissions between different types of autoregressive modes over time form a transmission network that contains rich dynamic information. We then capture transmission characteristics of autoregressive modes under different periodic time series through the structure features of the transmission networks. The results indicate that there are various autoregressive modes with significantly different statistical characteristics under different periodic time series. However, only a few types of autoregressive modes and transmission patterns play a major role in the fluctuation mechanism of the crude oil price, and these

Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....

Application of data mining methods for power forecast of wind power plants

Energy Technology Data Exchange (ETDEWEB)

Arnoldt, Alexander; Koenig, Stefan; Bretschneider, Peter [Fraunhofer Institute for Optronics, System Technology, and Image Exploitation - Application Centre System Technology (IOSB-AST), Ilmenau (Germany). Energy Systems Group; Mikut, Ralf [Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen (DE). Inst. for Applied Computer Science (IAI)

2010-07-01

Since the last decade power systems underlie a drastic change due to increased exploitation of renewable energy resources (RES) such as wind and photovoltaic power plants. A result of this process is a significant increase of fluctuating generation in low, middle and high voltage grids. Consequently, impacts on short and middle term capacity planning of power plants occur and must be handled to avoid imbalances between generation and demand at any time. Therefore, forecasts of wind and photovoltaic generation play a very important role. Quality improvements potentially ease planning and lead to cost reductions. This work investigated the dependencies of input parameters. The optimal parameter selection was achieved through application of data mining methods. Finally, the wind power prediction was demonstrated with Artificial Neural Networks and Physical Models. (orig.)

Drag and power-loss in rowing due to velocity fluctuations

NARCIS (Netherlands)

Greidanus, A.J.; Delfos, R.; Westerweel, J.; Jansen, A.J.

2016-01-01

The flow motions in the turbulent boundary layer between water and a rowing boat initiate a turbulent skin friction. Reducing this skin friction results in better rowing performances. A Taylor-Couette (TC) facility was used to verify the power losses due to velocity fluctuations P_V′ in

Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems

DEFF Research Database (Denmark)

You, Shi; Liu, Zongyu; Zong, Yi

2015-01-01

A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...

Short term variation of Cyg X-1 in the hard x-ray region

International Nuclear Information System (INIS)

Doi, Kosei

1978-01-01

Cyg X-1 is a peculiar celestial body considered to be a close binary system of a black hole and a blue super-giant star. It is presently known that the time fluctuation of Cyg X-1 is considerably complex, ranging from seconds to days or months. Of these variation, attention has been paid to the short time variation in relation to the black hole theory. Observations of fluctuations in the order of second have been limited to soft X-ray (20 keV or more) so far, because great technical difficulties are involved due to the low intensity of hard X-ray. The present investigation is based on the fluctuations in the order of second in hard X-ray, and was conducted by employing an unprecedented large area X-ray telescope. The text describes on the brief history of the short time fluctuation, explains the experimental plan, X-ray detecting system, flight of a balloon and the analyses and discussions of fluctuation factor by variation function method, and gives the analysis data and conclusion. The observations resulted in the fact that the fluctuations in the order of second were small at 20 to 30 keV, but become large when energy is higher or lower than this value. The most natural explanation available for this result may be that it is essentially spectrum fluctuation, being inverse correlation in higher and lower energies. Physical meaning of such spectrum fluctuation is considered in connection with precipitating disk model around a black hole. (Wakatsuki, Y.)

Short term variation of Cyg X-1 in the hard x-ray region

Energy Technology Data Exchange (ETDEWEB)

Doi, Kosei [Tokyo Univ. (Japan). Inst. of Space and Aeronautical Science

1978-08-01

Cyg X-1 is a peculiar celestial body considered to be a close binary system of a black hole and a blue super-giant star. It is presently known that the time fluctuation of Cyg X-1 is considerably complex, ranging from seconds to days or months. Of these variation, attention has been paid to the short time variation in relation to the black hole theory. Observations of fluctuations in the order of second have been limited to soft X-ray (20 keV or more) so far, because great technical difficulties are involved due to the low intensity of hard X-ray. The present investigation is based on the fluctuations in the order of second in hard X-ray, and was conducted by employing an unprecedented large area X-ray telescope. The text describes on the brief history of the short time fluctuation, explains the experimental plan, X-ray detecting system, flight of a balloon and the analyses and discussions of fluctuation factor by variation function method, and gives the analysis data and conclusion. The observations resulted in the fact that the fluctuations in the order of second were small at 20 to 30 keV, but become large when energy is higher or lower than this value. The most natural explanation available for this result may be that it is essentially spectrum fluctuation, being inverse correlation in higher and lower energies. Physical meaning of such spectrum fluctuation is considered in connection with precipitating disk model around a black hole.

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.

Energy Storage on the Grid and the Short-term Variability of Wind

Science.gov (United States)

Hittinger, Eric Stephen

profitability of wind farms. We find that market scenarios using existing price signals to motivate wind to reduce variability allow wind generators to participate in variability reduction when the market conditions are favorable, and can reduce short-term (30-minute) fluctuations while having little effect on wind farm revenue.

Short term memory in echo state networks

OpenAIRE

Jaeger, H.

2001-01-01

The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

Late Holocene dune mobilizations in the northwestern Negev dunefield, Israel: A response to combined anthropogenic activity and short-term intensified windiness

Science.gov (United States)

Roskin, Joel; Katra, Itzhak; Blumberg, Dan G.

2013-04-01

The study of the effects of past climates on ancient cultures is usually based on geologic records pertaining to rainfall and temperature fluctuations and shifts. This study proposes a paradigm of anthropogenic activity and windiness fluctuations to explain aeolian sedimentation and dune mobilization in the northwestern (NW) Negev Desert dunefield (Israel). The proposed paradigm contributes a different approach to estimating the effect of climate changes on the unprecedented agricultural and urban settlement expansion during the late Roman to Early Islamic period in the northern and central Negev Desert. This study builds upon the late Holocene cluster of luminescence ages of Roskin et al. (Age, origin and climatic controls on vegetated linear dunes in the northwestern Negev Desert (Israel), Quaternary Science Reviews 30 (2011), 1649-1674) coupled with analysis of archaeological finds and historical texts. We suggest that whereas the NW Negev dunefield was generally stable during the Holocene, intermittent dune mobilization during the late Holocene, at ~1.8 ka and mostly 1.4-1.1 ka (~600-900 CE), are linked to periods of human occupation. The idea that the last glacial dune encroachments alone that formed the NW Negev dunefield is connected to cold-event windy climates that may have intensified East Mediterranean cyclonic winter storms, cannot explain the late Holocene dune mobilizations. We conceptually model a connection between late Holocene dune mobilization, widespread anthropogenic occupation and activity, and windiness. We maintain that historic grazing and uprooting shrubs for fuel in the past by nomads and sedentary populations led to decimation of dune stabilizers, biogenic soil crusts and vegetation, causing dune erodibility and low-grade activity. Short-term events of amplified wind power in conjunction with periods of augmented anthropogenic activity that triggered major events of dune mobilization (elongation) and accretion have been preserved in the

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

Science.gov (United States)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Dependability of wind energy generators with short-term energy storage.

Science.gov (United States)

Sørensen, B

1976-11-26

Power fluctuations and power duration curves for wind energy generators, including energy storage facilities of a certain capacity, are compared to those of typical nuclear reactors. A storage system capable of delivering the yearly average power output for about 10 hours already makes the dependability of the wind energy system comparable to that of a typical nuclear plant.

A study of power fluctuations in a flip fuel reactor using the technique of noise analysis

Energy Technology Data Exchange (ETDEWEB)

Randall, J D; Wood, G C; Edwards, M A [Texas A and M University (United States)

1974-07-01

The Nuclear Science Center Reactor at Texas A and M University has experienced minor power fluctuations when operating at or near 1 megawatt. A noise analysis system was developed to investigate these fluctuations assuming that void formation, primarily due to nucleate boiling, was the cause. Experiments were carried out to correlate boiling noise with power level, fission product poisoning, and pool temperature. Results show that void formation in the core is the probable cause of the fluctuations with the onset of boiling occurring at 400 Kw. Data was also obtained that indicated the presence of boiling in a standard TRIGA core. (author)

A comparison of short-term dispersion estimates resulting from various atmospheric stability classification methods

International Nuclear Information System (INIS)

Mitchell, A.E. Jr.

1982-01-01

Four methods of classifying atmospheric stability class are applied at four sites to make short-term (1-h) dispersion estimates from a ground-level source based on a model consistent with U.S. Nuclear Regulatory Commission practice. The classification methods include vertical temperature gradient, standard deviation of horizontal wind direction fluctuations (sigma theta), Pasquill-Turner, and modified sigma theta which accounts for meander. Results indicate that modified sigma theta yields reasonable dispersion estimates compared to those produced using methods of vertical temperature gradient and Pasquill-Turner, and can be considered as a potential economic alternative in establishing onsite monitoring programs. (author)

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

Science.gov (United States)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

Revolutionary interdisciplinary cooperation. Effects of short- term regulation studied in a river environment

Energy Technology Data Exchange (ETDEWEB)

Saimakallio, H.; Virsu, R.

1996-11-01

A three-year study on how short-term regulation affects the river environment provides power plant builders with new capabilities to meet the needs of the riverside population, recreational users and power plants. The study also opens up new perspectives to researchers. Interdisciplinary cooperation between experts on the living environment, vegetation, fish, recreational use and energy has been revolutionary even on the international scale. (orig.)

Output power fluctuations due to different weights of macro particles used in particle-in-cell simulations of Cerenkov devices

International Nuclear Information System (INIS)

Bao, Rong; Li, Yongdong; Liu, Chunliang; Wang, Hongguang

2016-01-01

The output power fluctuations caused by weights of macro particles used in particle-in-cell (PIC) simulations of a backward wave oscillator and a travelling wave tube are statistically analyzed. It is found that the velocities of electrons passed a specific slow-wave structure form a specific electron velocity distribution. The electron velocity distribution obtained in PIC simulation with a relative small weight of macro particles is considered as an initial distribution. By analyzing this initial distribution with a statistical method, the estimations of the output power fluctuations caused by different weights of macro particles are obtained. The statistical method is verified by comparing the estimations with the simulation results. The fluctuations become stronger with increasing weight of macro particles, which can also be determined reversely from estimations of the output power fluctuations. With the weights of macro particles optimized by the statistical method, the output power fluctuations in PIC simulations are relatively small and acceptable.

Neutron density fluctuations in point reactor systems with dichotomic reactivity noise

International Nuclear Information System (INIS)

Sako, Okitsugu

1984-01-01

The exactly solvable stochastic point reactor model systems are analyzed through the stochastic Liouville equation. Three kinds of model systems are treated: (1) linear system without delayed neutrons, (2) linear system with one-group of delayed neutrons, and (3) nonlinear system with direct power feedback. The exact expressions for the fluctuations of neutron density, such as the moments, autocorrelation function and power spectral density, are derived in the case where the colored reactivity noise is described by the dichotomic, or two state, Markov process with arbitrary correlation time and intensity, and the effects of the finite correlation time and intensity of the noise on the neutron density fluctuations are investigated. The influence of presence of delayed neutrons and the effect of nonlinearity of system on the neutron density fluctuations are also elucidated. When the reactivity correlation time is very short, the correlation time has almost no effect on the power spectral density, and the relative fluctuation of neutron density in the stationary state is not affected very much by the presence of delayed neutrons and also by the nonlinearity of system. On the other hand, if the reactivity correlation time is very long, the effect of the reactivity noise on the power spectral density appears at very low frequency, and the presence of delayed neutrons has an effect of reducing the neutron density fluctuations. (author)

Wind Power accuracy and forecast. D3.1. Assumptions on accuracy of wind power to be considered at short and long term horizons

Energy Technology Data Exchange (ETDEWEB)

Morthorst, P.E.; Coulondre, J.M.; Schroeder, S.T.; Meibom, P.

2010-07-15

The main objective of the Optimate project (An Open Platform to Test Integration in new MArkeT designs of massive intermittent Energy sources dispersed in several regional power markets) is to develop a new tool for testing these new market designs with large introduction of variable renewable energy sources. In Optimate a novel network/system/market modelling approach is being developed, generating an open simulation platform able to exhibit the comparative benefits of several market design options. This report constitutes delivery 3.1 on the assumptions on accuracy of wind power to be considered at short and long term horizons. The report handles the issues of state-of-the-art prediction, how predictions for wind power enter into the Optimate model and a simple and a more advanced methodology of how to generate trajectories of prediction errors to be used in Optimate. The main conclusion is that undoubtedly, the advanced approach is to be preferred to the simple one seen from a theoretical viewpoint. However, the advanced approach was developed to the Wilmar-model with the purpose of describing the integration of large-scale wind power in Europe. As the main purpose of the Optimate model is not to test the integration of wind power, but to test new market designs assuming a strong growth in wind power production, a more simplified approach for describing wind power forecasts should be sufficient. Thus a further development of the simple approach is suggested, eventually including correlations between geographical areas. In this report the general methodologies for generating trajectories for wind power forecasts are outlined. However, the methods are not yet implemented. In the next phase of Optimate, the clusters will be defined and the needed data collected. Following this phase actual results will be generated to be used in Optimate. (LN)

Short-Term Memory and Aphasia: From Theory to Treatment.

Science.gov (United States)

Minkina, Irene; Rosenberg, Samantha; Kalinyak-Fliszar, Michelene; Martin, Nadine

2017-02-01

This article reviews existing research on the interactions between verbal short-term memory and language processing impairments in aphasia. Theoretical models of short-term memory are reviewed, starting with a model assuming a separation between short-term memory and language, and progressing to models that view verbal short-term memory as a cognitive requirement of language processing. The review highlights a verbal short-term memory model derived from an interactive activation model of word retrieval. This model holds that verbal short-term memory encompasses the temporary activation of linguistic knowledge (e.g., semantic, lexical, and phonological features) during language production and comprehension tasks. Empirical evidence supporting this model, which views short-term memory in the context of the processes it subserves, is outlined. Studies that use a classic measure of verbal short-term memory (i.e., number of words/digits correctly recalled in immediate serial recall) as well as those that use more intricate measures (e.g., serial position effects in immediate serial recall) are discussed. Treatment research that uses verbal short-term memory tasks in an attempt to improve language processing is then summarized, with a particular focus on word retrieval. A discussion of the limitations of current research and possible future directions concludes the review. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

A Time Series Regime Classification Approach for Short-Term Forecasting; Identificacion de Mecanismos en Series Temporales para la Prediccion a Corto Plazo

Energy Technology Data Exchange (ETDEWEB)

Gallego, C. J.

2010-03-08

Abstract: This technical report is focused on the analysis of stochastic processes that switch between different dynamics (also called regimes or mechanisms) over time. The so-called Switching-regime models consider several underlying functions instead of one. In this case, a classification problem arises as the current regime has to be assessed at each time-step. The identification of the regimes allows the performance of regime-switching models for short-term forecasting purposes. Within this framework, identifying different regimes showed by time-series is the aim of this work. The proposed approach is based on a statistical tool called Gamma-test. One of the main advantages of this methodology is the absence of a mathematical definition for the different underlying functions. Applications with both simulated and real wind power data have been considered. Results on simulated time series show that regimes can be successfully identified under certain hypothesis. Nevertheless, this work highlights that further research has to be done when considering real wind power time-series, which usually show different behaviours (e.g. fluctuations or ramps, followed by low variance periods). A better understanding of these events eventually will improve wind power forecasting. (Author) 15 refs.

A new derivation of Luescher F-term and fluctuations around the giant magnon

International Nuclear Information System (INIS)

Heller, Michal P.; Janik, Romuald A.; Lukowski, Tomasz

2008-01-01

In this paper we give a new derivation of the generalized Luescher F-term formula from a summation over quadratic fluctuations around a given soliton. The result is very general providing that S-matrix is diagonal and is valid for arbitrary dispersion relation. We then apply this formalism to compute the leading finite size corrections to the giant magnon dispersion relation coming from quantum fluctuations.

Observation of voltage fluctuations in a superconducting magnet during MHD power generation

International Nuclear Information System (INIS)

Smith, R.P.; Niemann, R.C.; Kraimer, M.R.; Zinneman, T.E.

1978-01-01

Fluctuating voltage signals on the potential taps of the ANL 5.0 T MHD Superconducting Dipole Magnet have been observed during MHD power generation at the U-25B Facility at the High Temperature Institute (IVTAN) Moscow, USSR. Various other thermodynamic and electrical parameters of the U-25B flow train have been recorded, and statistical analysis concerning correlations between the phenomena with a view of discerning causal interdependence is in progress. Voltage fluctuations observed at the magnet terminals are analyzed with special emphasis on magnet stability

Artificial Neural Network for Short-Term Load Forecasting in Distribution Systems

Directory of Open Access Journals (Sweden)

Luis Hernández

2014-03-01

Full Text Available The new paradigms and latest developments in the Electrical Grid are based on the introduction of distributed intelligence at several stages of its physical layer, giving birth to concepts such as Smart Grids, Virtual Power Plants, microgrids, Smart Buildings and Smart Environments. Distributed Generation (DG is a philosophy in which energy is no longer produced exclusively in huge centralized plants, but also in smaller premises which take advantage of local conditions in order to minimize transmission losses and optimize production and consumption. This represents a new opportunity for renewable energy, because small elements such as solar panels and wind turbines are expected to be scattered along the grid, feeding local installations or selling energy to the grid depending on their local generation/consumption conditions. The introduction of these highly dynamic elements will lead to a substantial change in the curves of demanded energy. The aim of this paper is to apply Short-Term Load Forecasting (STLF in microgrid environments with curves and similar behaviours, using two different data sets: the first one packing electricity consumption information during four years and six months in a microgrid along with calendar data, while the second one will be just four months of the previous parameters along with the solar radiation from the site. For the first set of data different STLF models will be discussed, studying the effect of each variable, in order to identify the best one. That model will be employed with the second set of data, in order to make a comparison with a new model that takes into account the solar radiation, since the photovoltaic installations of the microgrid will cause the power demand to fluctuate depending on the solar radiation.

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Directory of Open Access Journals (Sweden)

Fei Wang

2017-12-01

Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

Social Welfare and the Psychology of Food Sharing: Short-Term Hunger Increases Support for Social Welfare

DEFF Research Database (Denmark)

Petersen, Michael Bang; Aarøe, Lene; Jensen, Niels Holm

2014-01-01

Do politically irrelevant events influence important policy opinions? Previous research on social welfare attitudes has emphasized the role of political factors such as economic self-interest and ideology. Here, we demonstrate that attitudes to social welfare are also influenced by short-term flu......—we consistently find that hungry individuals act in a greedier manner but describe themselves as more cooperative and express greater support for social welfare.......Do politically irrelevant events influence important policy opinions? Previous research on social welfare attitudes has emphasized the role of political factors such as economic self-interest and ideology. Here, we demonstrate that attitudes to social welfare are also influenced by short......-term fluctuations in hunger. Using theories in evolutionary psychology, we predict that hungry individuals will be greedier and take more resources from others while also attempting to induce others to share by signaling cooperative intentions and expressing support for sharing, including evolutionarily novel forms...

Short-term memories with a stochastic perturbation

International Nuclear Information System (INIS)

Pontes, Jose C.A. de; Batista, Antonio M.; Viana, Ricardo L.; Lopes, Sergio R.

2005-01-01

We investigate short-term memories in linear and weakly nonlinear coupled map lattices with a periodic external input. We use locally coupled maps to present numerical results about short-term memory formation adding a stochastic perturbation in the maps and in the external input

Implications of Wide-Area Geographic Diversity for Short- Term Variability of Solar Power

Energy Technology Data Exchange (ETDEWEB)

Mills, Andrew; Wiser, Ryan

2010-08-23

Worldwide interest in the deployment of photovoltaic generation (PV) is rapidly increasing. Operating experience with large PV plants, however, demonstrates that large, rapid changes in the output of PV plants are possible. Early studies of PV grid impacts suggested that short-term variability could be a potential limiting factor in deploying PV. Many of these early studies, however, lacked high-quality data from multiple sites to assess the costs and impacts of increasing PV penetration. As is well known for wind, accounting for the potential for geographic diversity can significantly reduce the magnitude of extreme changes in aggregated PV output, the resources required to accommodate that variability, and the potential costs of managing variability. We use measured 1-min solar insolation for 23 time-synchronized sites in the Southern Great Plains network of the Atmospheric Radiation Measurement program and wind speed data from 10 sites in the same network to characterize the variability of PV with different degrees of geographic diversity and to compare the variability of PV to the variability of similarly sited wind. The relative aggregate variability of PV plants sited in a dense 10 x 10 array with 20 km spacing is six times less than the variability of a single site for variability on time scales less than 15-min. We find in our analysis of wind and PV plants similarly sited in a 5 x 5 grid with 50 km spacing that the variability of PV is only slightly more than the variability of wind on time scales of 5-15 min. Over shorter and longer time scales the level of variability is nearly identical. Finally, we use a simple approximation method to estimate the cost of carrying additional reserves to manage sub-hourly variability. We conclude that the costs of managing the short-term variability of PV are dramatically reduced by geographic diversity and are not substantially different from the costs for managing the short-term variability of similarly sited wind in

Short-term memory

Science.gov (United States)

Toulouse, G.

This is a rather bold attempt to bridge the gap between neuron structure and psychological data. We try to answer the question: Is there a relation between the neuronal connectivity in the human cortex (around 5,000) and the short-term memory capacity (7±2)? Our starting point is the Hopfield model (Hopfield 1982), presented in this volume by D.J. Amit.

Mesoscale wind fluctuations over Danish waters

Energy Technology Data Exchange (ETDEWEB)

Vincent, C.L.

2010-12-15

Mesoscale wind fluctuations affect the large scale integration of wind power because they undermine the day-ahead predictability of wind speed and power production, and because they can result in large fluctuations in power generation that must be balanced using reserve power. Large fluctuations in generated power are a particular problem for offshore wind farms because the typically high concentration of turbines within a limited geographical area means that fluctuations can be correlated across large numbers of turbines. Furthermore, organised mesoscale structures that often form over water, such as convective rolls and cellular convection, have length scales of tens of kilometers, and can cause large wind fluctuations on a time scale of around an hour. This thesis is an exploration of the predictability of mesoscale wind fluctuations using observations from the world's first two large offshore wind farms - Horns Rev I in the North Sea, and Nysted in the Baltic Sea. The thesis begins with a climatological analysis of wind fluctuations on time scales of 1-10 hours at the two sites. A novel method for calculating conditional climatologies of spectral information is proposed, based on binning and averaging the time axis of the Hilbert spectrum. Results reveal clear patterns between wind fluctuations and locally observed meteorological conditions. The analysis is expanded by classifying wind fluctuations on time scales of 1-3 hours according to synoptic patterns, satellite pictures and wind classes. Results indicate that cold air outbreaks and open cellular convection are a significant contributor to mesoscale wind variability at Horns Rev. The predictability of mesoscale wind fluctuations is tested by implementing standard statistical models that relate local wind variability to parameters based on a large scale weather analysis. The models show some skill, but only achieve a 15% improvement on a persistence forecast. The possibility of explicitly modelling

Competitive short-term and long-term memory processes in spatial habituation.

Science.gov (United States)

Sanderson, David J; Bannerman, David M

2011-04-01

Exposure to a spatial location leads to habituation of exploration such that, in a novelty preference test, rodents subsequently prefer exploring a novel location to the familiar location. According to Wagner's (1981) theory of memory, short-term and long-term habituation are caused by separate and sometimes opponent processes. In the present study, this dual-process account of memory was tested. Mice received a series of exposure training trials to a location before receiving a novelty preference test. The novelty preference was greater when tested after a short, rather than a long, interval. In contrast, the novelty preference was weaker when exposure training trials were separated by a short, rather than a long interval. Furthermore, it was found that long-term habituation was determined by the independent effects of the amount of exposure training and the number of exposure training trials when factors such as the intertrial interval and the cumulative intertrial interval were controlled. A final experiment demonstrated that a long-term reduction of exploration could be caused by a negative priming effect due to associations formed during exploration. These results provide evidence against a single-process account of habituation and suggest that spatial habituation is determined by both short-term, recency-based memory and long-term, incrementally strengthened memory.

Retrieval-Induced Inhibition in Short-Term Memory.

Science.gov (United States)

Kang, Min-Suk; Choi, Joongrul

2015-07-01

We used a visual illusion called motion repulsion as a model system for investigating competition between two mental representations. Subjects were asked to remember two random-dot-motion displays presented in sequence and then to report the motion directions for each. Remembered motion directions were shifted away from the actual motion directions, an effect similar to the motion repulsion observed during perception. More important, the item retrieved second showed greater repulsion than the item retrieved first. This suggests that earlier retrieval exerted greater inhibition on the other item being held in short-term memory. This retrieval-induced motion repulsion could be explained neither by reduced cognitive resources for maintaining short-term memory nor by continued inhibition between short-term memory representations. These results indicate that retrieval of memory representations inhibits other representations in short-term memory. We discuss mechanisms of retrieval-induced inhibition and their implications for the structure of memory. © The Author(s) 2015.

Short term hydroelectric power system scheduling with wind turbine generators using the multi-pass iteration particle swarm optimization approach

International Nuclear Information System (INIS)

Lee, T.-Y.

2008-01-01

This paper uses multi-pass iteration particle swarm optimization (MIPSO) to solve short term hydroelectric generation scheduling of a power system with wind turbine generators. MIPSO is a new algorithm for solving nonlinear optimal scheduling problems. A new index called iteration best (IB) is incorporated into particle swarm optimization (PSO) to improve solution quality. The concept of multi-pass dynamic programming is applied to modify PSO further and improve computation efficiency. The feasible operational regions of the hydro units and pumped storage plants over the whole scheduling time range must be determined before applying MIPSO to the problem. Wind turbine power generation then shaves the power system load curves. Next, MIPSO calculates hydroelectric generation scheduling. It begins with a coarse time stage and searching space and refines the time interval between two time stages and the search spacing pass by pass (iteration). With the cooperation of agents called particles, the near optimal solution of the scheduling problem can be effectively reached. The effects of wind speed uncertainty were also considered in this paper. The feasibility of the new algorithm is demonstrated by a numerical example, and MIPSO solution quality and computation efficiency are compared to those of other algorithms

Evaluation of Short Term Memory Span Function In Children

Directory of Open Access Journals (Sweden)

Barış ERGÜL

2016-12-01

Full Text Available Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors affecting operation of short term memory are investigated with regression model. The aim of the research is to examine the factors (age, IQ and reading skills that are expected the have an effect on short-term memory in children through regression analysis. One of the assumptions of regression analysis is to examine which has constant variance and normal distribution of the error term. In this study, because the error term is not normally distributed, robust regression techniques were applied. Also, for each technique; coefficient of determination is determined. According to the findings, the increase in age, IQ and reading skills caused the increase in short term memory in children. After applying robust regression techniques, the Winsorized Least Squares (WLS technique gives the highest coefficient of determination.

A robust control strategy for mitigating renewable energy fluctuations in a real hybrid power system combined with SMES

Science.gov (United States)

Magdy, G.; Shabib, G.; Elbaset, Adel A.; Qudaih, Yaser; Mitani, Yasunori

2018-05-01

Utilizing Renewable Energy Sources (RESs) is attracting great attention as a solution to future energy shortages. However, the irregular nature of RESs and random load deviations cause a large frequency and voltage fluctuations. Therefore, in order to benefit from a maximum capacity of the RESs, a robust mitigation strategy of power fluctuations from RESs must be applied. Hence, this paper proposes a design of Load Frequency Control (LFC) coordinated with Superconducting Magnetic Energy Storage (SMES) technology (i.e., an auxiliary LFC), using an optimal PID controller-based Particle Swarm Optimization (PSO) in the Egyptian Power System (EPS) considering high penetration of Photovoltaics (PV) power generation. Thus, from the perspective of LFC, the robust control strategy is proposed to maintain the nominal system frequency and mitigating the power fluctuations from RESs against all disturbances sources for the EPS with the multi-source environment. The EPS is decomposed into three dynamics subsystems, which are non-reheat, reheat and hydro power plants taking into consideration the system nonlinearity. The results by nonlinear simulation Matlab/Simulink for the EPS combined with SMES system considering PV solar power approves that, the proposed control strategy achieves a robust stability by reducing transient time, minimizing the frequency deviations, maintaining the system frequency, preventing conventional generators from exceeding their power ratings during load disturbances, and mitigating the power fluctuations from the RESs.

Evaluation of Short Term Memory Span Function In Children

OpenAIRE

Barış ERGÜL; Arzu ALTIN YAVUZ; Ebru GÜNDOĞAN AŞIK

2016-01-01

Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors ...

Short-term Memory as a Processing Shift

Science.gov (United States)

Lewis-Smith, Marion Quinn

1975-01-01

The series of experiments described here examined the predictions for free recall from sequential models and the shift formulation, focusing on the roles of short- and long-term memory in the primacy/recency shift and on the effects of expectancies on short- and long-term memory. (Author/RK)

The Effects of Music on High-intensity Short-term Exercise in Well Trained Athletes.

Science.gov (United States)

Jarraya, Mohamed; Chtourou, Hamdi; Aloui, Asma; Hammouda, Omar; Chamari, Karim; Chaouachi, Anis; Souissi, Nizar

2012-12-01

The purpose of this investigation was to assess the effects of listening to music during warm-up on short-term supramaximal performances during the 30-s Wingate test in highly trained athletes. Twelve young male athletes (20.6±1.8 yrs, 177±4.4 cm and 72.3±5.3 kg) underwent two Wingate tests in separate sessions with a recovery period of 48 h in-between, either after a 10 min of warm-up with (MWU) or without (NMWU) music. High tempo music (>120 to 140bpm) was selected for the study. Heart rate (HR) and rate of perceived exertion (RPE) were recorded after the warm-up (for HR = average of warm-up) and immediately after the Wingate test. HR, RPE and the fatigue index during the Wingate test are not affected by the incorporation of music during warm-up. However, power output (P(peak) and P(mean)) was significantly higher after MWU than NMWU (Peffect of music during warm-up on short-term supramaximal performances. As it's a legal method and an additional aid, music may be used during warm-up before performing activities requiring powerful lower limbs' muscles contractions during short-term supramaximal exercises.

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

On the relationship between short- and long-term memory

DEFF Research Database (Denmark)

Sørensen, Thomas Alrik

James (1890) divided memory into separate stores; primary and secondary – or short-term and long-term memory. The interaction between the two stores often assumes that information initially is represented in volatile short-term store before entering and consolidating in the more durable long-term......, accepted). Counter to popular beliefs this suggest that long-term memory precedes short-term memory and not vice versa....... memory system (e.g. Atkinson & Shiffrin, 1968). Short-term memory seems to provide a surprising processing bottleneck where only a very limited amount of information can be represented at any given moment (Miller, 1956; Cowan, 2001). A number of studies have investigated the nature of this processing...

Journal Afrika Statistika ISSN 0852-0305 Short term forecasting of ...

African Journals Online (AJOL)

tion of this research is to propose some procedures to estimate the following ... by Eurostat about six weeks after the end of the reference quarter. .... alized principal components of current values of the variables in the dataset. These factors are designed to remove short-run and variable-specific sources of fluctuation.

Can Weather Radars Help Monitoring and Forecasting Wind Power Fluctuations at Large Offshore Wind Farms?

DEFF Research Database (Denmark)

Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik

2011-01-01

The substantial impact of wind power fluctuations at large offshore wind farms calls for the development of dedicated monitoring and prediction approaches. Based on recent findings, a Local Area Weather Radar (LAWR) was installed at Horns Rev with the aim of improving predictability, controlability...... and potentially maintenance planning. Additional images are available from a Doppler radar covering the same area. The parallel analysis of rain events detection and of regime sequences in wind (and power) fluctuations demonstrates the interest of employing weather radars for a better operation and management...... of offshore wind farms....

Effect of active warm-up duration on morning short-term maximal performance during Ramadan.

Science.gov (United States)

Baklouti, Hana; Chtourou, Hamdi; Aloui, Asma; Chaouachi, Anis; Souissi, Nizar

2015-01-01

To examine the effect of active warm-up duration on short-term maximal performance assessed during Ramadan in the morning. Twelve healthy active men performed four Wingate tests for measurement of peak power and mean power before and during Ramadan at 09:00 a.m. The tests were performed on separate days, after either a 5-min or a 15-min warm-up. The warm-up consisted in pedaling at 50% of the power output obtained at the last stage of a submaximal multistage cycling test. Oral temperature was measured at rest and after warming-up. Furthermore, ratings of perceived exertion were obtained immediately after the Wingate test. Oral temperature was higher after the 15-min warm-up than the 5-min warm-up throughout the study. Moreover, peak power and mean power were higher after the 15-min warm-up than the 5-min warm-up before Ramadan. However, during Ramadan, there was no significant difference between the two warm-up durations. In addition, ratings of perceived exertion were higher after the 15-min warm-up than the 5-min warm-up only during Ramadan. There is no need to prolong the warm-up period before short-term maximal exercise performed during Ramadan in the morning.

Origin of short-period (30-300 s) Doppler frequency fluctuations of lower F region reflections in the equatorial electrojet region

International Nuclear Information System (INIS)

Sastri, J.H.; Ramesh, K.B.; Rao, J.V.S.V.; Somayajulu, V.V.

1991-01-01

Measurements of phase path P of lower F-region reflections at normal incidence at Kodaikanal revealed the ubiquitous presence of 30-300-s quasi-sinusoidal variations in the time rate of change of phase path, P (Doppler frequency shift) during day time. A study is made of the influence of the irregularities in the equatorial electrojet on the P fluctuations using simultaneous observations of F-region phase path at Kodaikanal and of equatorial electrojet with the VHF-backscatter radar at Thumba. It is shown that the spectral content of the Doppler fluctuations (quantified in terms of variance, sigma squared computed from P time series synthesized through FFT exp -1 (FFT) in the chosen period bands, 30-300 s/30-120 s of the FFT of original P times series) bears a significant positive linear relationship to the horizontal phase velocity of electrojet irregularities (3-m scale size) on a hourly basis. This result is in consonance with earlier findings (Sastri et al., 1990) of a significant linear relationship of sigma squared to the electrojet strength (estimated from H-field data) and a practical cessation of the P fluctuations at times of disappearance of Esq on ionograms (partial/complete counterelectrojet). The present work substantiates the interpretation that the short-period Doppler-frequency fluctuations are due to phase-path changes imposed on lower F region reflections by the refractive-index variations associated with the convective motions of plasma density irregularities (type I and II) in the daytime equatorial electrojet. 49 refs

Non-Fourier conduction model with thermal source term of ultra short high power pulsed laser ablation and temperature evolvement before melting

International Nuclear Information System (INIS)

Zhang Duanming; Li, Li; Li Zhihua; Guan Li; Tan Xinyu

2005-01-01

A non-Fourier conduction model with heat source term is presented to study the target temperature evolvement when the target is radiated by high power (the laser intensity is above 10 9 w/cm 2 ) and ultra short (the pulse width is less than 150 ps) pulsed laser. By Laplace transform, the analytical expression of the space- and time-dependence of temperature is derived. Then as an example of aluminum target, the target temperature evolvement is simulated. Compared with the results of Fourier conduction model and non-Fourier model without heat source term, it is found that the effect of non-Fourier conduction is notable and the heat source plays an important role during non-Fourier conduction which makes surface temperature ascending quickly with time. Meanwhile, the corresponding physical mechanism is analyzed theoretically

Short-term memory and long-term memory are still different.

Science.gov (United States)

Norris, Dennis

2017-09-01

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Fast Weight Long Short-Term Memory

OpenAIRE

Keller, T. Anderson; Sridhar, Sharath Nittur; Wang, Xin

2018-01-01

Associative memory using fast weights is a short-term memory mechanism that substantially improves the memory capacity and time scale of recurrent neural networks (RNNs). As recent studies introduced fast weights only to regular RNNs, it is unknown whether fast weight memory is beneficial to gated RNNs. In this work, we report a significant synergy between long short-term memory (LSTM) networks and fast weight associative memories. We show that this combination, in learning associative retrie...

Nonlinear interaction of powerful short electromagnetic pulses with an electron plasma

International Nuclear Information System (INIS)

Rao, N.N.; Yu, M.Y.; Shukla, P.K.

1990-01-01

The nonlinear interaction of powerful short electromagnetic pulses with a plasma consisting of two groups of electrons and immobile ions has been studied. It is shown that the interaction is governed by a nonlinear equation for the electromagnetic wave envelope and a driven nonlinear equation for the low-frequency electron fluctuations. The driver for the latter depends explicitly on the spatio-temporal evolution of the electromagnetic wave flux. It is found that, depending on the cold-to-hot electron density ratio, the localized pulse can propagate with sub- as well as supersonic velocities accompanied by compressional or rarefactional density perturbations. The conditions of existence for the different types of solitary pulses are obtained. The present investigation may be relevant to the study of wave-plasma interaction devices such as inertial fusion confinement as well as to ionospheric modification experiments. (author)

Long-Term Planning in Restructured Power Systems

International Nuclear Information System (INIS)

Botterud, Audun

2003-01-01

This thesis describes the development of three decision support models for long-term investment planning in restructured power systems. The model concepts address the changing conditions for the electric power industry, with the introduction of more competitive markets, higher uncertainty and less centralised planning. Under these circumstances there is an emerging need for new planning models, also for analyses of the power system in a long-term perspective. The thesis focuses particularly on how dynamic and stochastic modelling can contribute to the improvement of decision making in a restructured power industry. We argue that the use of such modelling approaches has become more important after the introduction of competitive power markets, due to the participants' increased exposure to price fluctuations and economic risk. Our models can be applied by individual participants in the power system to evaluate investment projects for new power generation capacity. The models can also serve as a decision support tool on a regulatory level, providing analyses of the long-term performance of the power system under different regulations and market designs. In Chapter 1, we give a brief introduction to the ongoing development towards restructuring and liberalisation of the electrical power system. A discussion of the operation and organisation of restructured power systems is also provided. In Chapter 2, we look more specifically at different modelling approaches for expansion planning in electrical power systems. We also discuss how the contributions in this thesis compare to previous work in the field of decision support models for long-term planning in both regulated and competitive power systems. In Chapter 3, we develop a power market simulation model based on system dynamics. The advantages and limitations of using descriptive system dynamics models for long-term planning purposes in this context are also discussed. Chapter 4 is devoted to a novel optimisation

Electricity generation and microbial community in response to short-term changes in stack connection of self-stacked submersible microbial fuel cell powered by glycerol

DEFF Research Database (Denmark)

Zhao, Nannan; Angelidaki, Irini; Zhang, Yifeng

2017-01-01

community. In this study, a self-stacked submersible microbial fuel cell (SSMFC) powered by glycerol was tested to elucidate this important issue. In series connection, the maximum voltage output reached to 1.15 V, while maximum current density was 5.73 mA in parallel. In both connections, the maximum power......Stack connection (i.e., in series or parallel) of microbial fuel cell (MFC) is an efficient way to boost the power output for practical application. However, there is little information available on short-term changes in stack connection and its effect on the electricity generation and microbial...... density increased with the initial glycerol concentration. However, the glycerol degradation was even faster in parallel connection. When the SSMFC was shifted from series to parallel connection, the reactor reached to a stable power output without any lag phase. Meanwhile, the anodic microbial community...

Improving creativity performance by short-term meditation

Science.gov (United States)

2014-01-01

Background One form of meditation intervention, the integrative body-mind training (IBMT) has been shown to improve attention, reduce stress and change self-reports of mood. In this paper we examine whether short-term IBMT can improve performance related to creativity and determine the role that mood may play in such improvement. Methods Forty Chinese undergraduates were randomly assigned to short-term IBMT group or a relaxation training (RT) control group. Mood and creativity performance were assessed by the Positive and Negative Affect Schedule (PANAS) and Torrance Tests of Creative Thinking (TTCT) questionnaire respectively. Results As predicted, the results indicated that short-term (30 min per day for 7 days) IBMT improved creativity performance on the divergent thinking task, and yielded better emotional regulation than RT. In addition, cross-lagged analysis indicated that both positive and negative affect may influence creativity in IBMT group (not RT group). Conclusions Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation. PMID:24645871

Integration of 18 GW Wind Energy into the Energy Market. Practical Experiences in Germany. Experiences with large-scale integration of wind power into power systems

International Nuclear Information System (INIS)

Krauss, C.; Graeber, B.; Lange, M.; Focken, U.

2006-01-01

This work describes the integration of 18 GW of wind power into the German energy market. The focus lies on reporting practical experiences concerning the use of wind energy in Germany within the framework of the renewable energy act (EEG) and the immediate exchange of wind power between the four German grid control areas. Due to the EEG the demand for monitoring the current energy production of wind farms and for short-term predictions of wind power has significantly increased and opened a broader market for these services. In particular for trading on the intraday market ultra short term predictions in the time frame of 1 to 10 hours require different approaches than usual dayahead predictions because the large numerical meteorological models are not sufficiently optimized for very short time horizons. It is shown that for this range a combination of a statistical and a deterministic model leads to significant improvements and stable results as it unites the characteristics of the current wind power production with the synoptic-scale meteorological situation. The possible concepts of balancing the remaining differences between predicted and actual wind power generation are discussed. As wind power prediction errors and load forecasting errors are uncorrelated, benefits can arise from a combined balancing. Finally practical experiences with wind power fluctuations and large forecast errors are presented.

Long vs. short-term energy storage:sensitivity analysis.

Energy Technology Data Exchange (ETDEWEB)

Schoenung, Susan M. (Longitude 122 West, Inc., Menlo Park, CA); Hassenzahl, William V. (,Advanced Energy Analysis, Piedmont, CA)

2007-07-01

This report extends earlier work to characterize long-duration and short-duration energy storage technologies, primarily on the basis of life-cycle cost, and to investigate sensitivities to various input assumptions. Another technology--asymmetric lead-carbon capacitors--has also been added. Energy storage technologies are examined for three application categories--bulk energy storage, distributed generation, and power quality--with significant variations in discharge time and storage capacity. Sensitivity analyses include cost of electricity and natural gas, and system life, which impacts replacement costs and capital carrying charges. Results are presented in terms of annual cost, $/kW-yr. A major variable affecting system cost is hours of storage available for discharge.

Simulation of Mechanical Processes in Gas Storage Caverns for Short-Term Energy Storage

Science.gov (United States)

Böttcher, Norbert; Nagel, Thomas; Kolditz, Olaf

2015-04-01

In recent years, Germany's energy management has started to be transferred from fossil fuels to renewable and sustainable energy carriers. Renewable energy sources such as solar and wind power are subjected by fluctuations, thus the development and extension of energy storage capacities is a priority in German R&D programs. This work is a part of the ANGUS+ Project, funded by the federal ministry of education and research, which investigates the influence of subsurface energy storage on the underground. The utilization of subsurface salt caverns as a long-term storage reservoir for fossil fuels is a common method, since the construction of caverns in salt rock is inexpensive in comparison to solid rock formations due to solution mining. Another advantage of evaporate as host material is the self-healing behaviour of salt rock, thus the cavity can be assumed to be impermeable. In the framework of short-term energy storage (hours to days), caverns can be used as gas storage reservoirs for natural or artificial fuel gases, such as hydrogen, methane, or compressed air, where the operation pressures inside the caverns will fluctuate more frequently. This work investigates the influence of changing operation pressures at high frequencies on the stability of the host rock of gas storage caverns utilizing numerical models. Therefore, we developed a coupled Thermo-Hydro-Mechanical (THM) model based on the finite element method utilizing the open-source software platform OpenGeoSys. The salt behaviour is described by well-known constitutive material models which are capable of predicting creep, self-healing, and dilatancy processes. Our simulations include the thermodynamic behaviour of gas storage process, temperature development and distribution on the cavern boundary, the deformation of the cavern geometry, and the prediction of the dilatancy zone. Based on the numerical results, optimal operation modes can be found for individual caverns, so the risk of host rock damage

Photovoltaic systems: state of the art and short-medium term perspectives

International Nuclear Information System (INIS)

Brofferio, Sergio C.; Rota, Alberto

2006-01-01

The paper presents and discusses, from a technology and economic point of view, the characteristics, performances, issues and perspectives of the thin films and the solar concentrating photovoltaic systems in the short and medium terms. Both have well based motivations to be an evolutionary step of current wafer based Silicon systems: the former as Building Integrated Photovoltaic and the latter as high density and high power photovoltaic systems [it

The Structure and Content of Long-Term and Short-Term Mate Preferences

Directory of Open Access Journals (Sweden)

Peter K. Jonason

2013-12-01

Full Text Available This study addresses two limitations in the mate preferences literature. First, research all-too-often relies on single-item assessments of mate preferences precluding more advanced statistical techniques like factor analysis. Second, when factor analysis could be done, it exclusively has done for long-term mate preferences, at the exclusion of short-term mate preferences. In this study (N = 401, we subjected 20 items designed to measure short- and long-term mate preferences to both principle components (n = 200 and confirmatory factor analysis (n = 201. In the long-term context, we replicated previous findings that there are three different categories of preferences: physical attractiveness, interpersonal warmth, and social status. In the short-term context, physical attractiveness occupied two parts of the structure, social status dropped out, and interpersonal warmth remained. Across short- and long-term contexts, there were slight changes in what defined the shared dimensions (i.e., physical attractiveness and interpersonal warmth, suggesting prior work that applies the same inventory to each context might be flawed. We also replicated sex differences and similarities in mate preferences and correlates with sociosexuality and mate value. We adopt an evolutionary paradigm to understand our results.

Short-term energy outlook, annual supplement 1994

International Nuclear Information System (INIS)

1994-08-01

The Short-Term Energy Outlook Annual Supplement (Supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts

Short-term energy outlook annual supplement, 1993

Energy Technology Data Exchange (ETDEWEB)

NONE

1993-08-06

The Short-Term Energy Outlook Annual Supplement (supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

The Sources of Life Chances: Does Education, Class Category, Occupation, or Short-Term Earnings Predict 20-Year Long-Term Earnings?

Directory of Open Access Journals (Sweden)

ChangHwan Kim

2018-03-01

Full Text Available In sociological studies of economic stratification and intergenerational mobility, occupation has long been presumed to reflect lifetime earnings better than do short-term earnings. However, few studies have actually tested this critical assumption. In this study, we investigate the cross-sectional determinants of 20-year accumulated earnings using data that match respondents in the Survey of Income and Program Participation to their longitudinal earnings records based on administrative tax information from 1990 to 2009. Fit statistics of regression models are estimated to assess the predictive power of various proxy variables, including occupation, education, and short-term earnings, on cumulative earnings over the 20-year time period. Contrary to the popular assumption in sociology, our results find that cross-sectional earnings have greater predictive power on long-term earnings than occupation-based class classifications, including three-digit detailed occupations for both men and women. The model based on educational attainment, including field of study, has slightly better fit than models based on one-digit occupation or the Erikson, Goldthorpe, and Portocarero class scheme. We discuss the theoretical implications of these findings for the sociology of stratification and intergenerational mobility.

Fluctuations in substitution type alloys and their analyses. Short-range order structures

International Nuclear Information System (INIS)

Iwasaki, Hiroshi; Ohshima, Ken-ichi

2010-01-01

This article is the fifth of the serial lecture, microstructures and fluctuations, in this magazine. The formula of X-ray diffuse scattering intensity was derived for binary alloys by introducing short-range order parameters. Diffuse scattering intensities for a single crystal Cu 3 Au were measured above critical temperature for ordering. The short-range parameters were obtained by a three-dimensional Fourier analysis. The long-range pair interaction between atoms was originated from the indirect screening interaction due to conduction electrons. A detailed study was made on short-range-order diffuse scattering from Cu 3 Au in the disordered state by electron diffraction. Fourfold splitting of the diffuse scattering was observed at 110 in the reciprocal lattice, and this result was attributed to the reflection of the form of the Fermi surface. The X-ray diffuse scattering intensity was measured at room temperature for disordered Cu-Pd alloys for the six composition of Pd. Twofold and fourfold splitting of diffuse scattering due to the short-range order (SRO) were observed at 100, 110 and equivalent positions respectively from alloys with more than 13.0at% Pd. The SRO parameters were determined from all the six alloys. For Cu-Pt alloys, the diffuse scattering originated from the correlation between Cu and Pt layers in direction was observed in addition to the one due to the reflection of the Fermi surface imaging. (author)

TMI-2 Lessons Learned Task Force status report and short-term recommendations

International Nuclear Information System (INIS)

1979-07-01

Review of the Three Mile Island accident by the TMI-2 Lessons Learned Task Force has disclosed a number of actions in the areas of design and analysis and plant operations that the Task Force recommends be required in the short term to provide substantial additional protection which is required for the public health and safety. All nuclear power plants in operation or in various stages of construction or licensing action are affected to varying degrees by the specific recommendations. The Task Force is continuing work in areas of general safety criteria, systems design requirements, nuclear power plant operations, and nuclear power plant licensing

In Search of Decay in Verbal Short-Term Memory

Science.gov (United States)

Berman, Marc G.; Jonides, John; Lewis, Richard L.

2009-01-01

Is forgetting in the short term due to decay with the mere passage of time, interference from other memoranda, or both? Past research on short-term memory has revealed some evidence for decay and a plethora of evidence showing that short-term memory is worsened by interference. However, none of these studies has directly contrasted decay and…

An adaptive short-term prediction scheme for wind energy storage management

International Nuclear Information System (INIS)

Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

2011-01-01

Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

Attention Problems, Phonological Short-Term Memory, and Visuospatial Short-Term Memory: Differential Effects on Near- and Long-Term Scholastic Achievement

Science.gov (United States)

Sarver, Dustin E.; Rapport, Mark D.; Kofler, Michael J.; Scanlan, Sean W.; Raiker, Joseph S.; Altro, Thomas A.; Bolden, Jennifer

2012-01-01

The current study examined individual differences in children's phonological and visuospatial short-term memory as potential mediators of the relationship among attention problems and near- and long-term scholastic achievement. Nested structural equation models revealed that teacher-reported attention problems were associated negatively with…

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

An accident diagnosis algorithm using long short-term memory

Directory of Open Access Journals (Sweden)

Jaemin Yang

2018-05-01

Full Text Available Accident diagnosis is one of the complex tasks for nuclear power plant (NPP operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM, which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents. Keywords: Accident Diagnosis, Long Short-term Memory, Recurrent Neural Network, Softmax

Short-Term Reciprocity in Late Parent-Child Relationships

Science.gov (United States)

Leopold, Thomas; Raab, Marcel

2011-01-01

Long-term concepts of parent-child reciprocity assume that the amount of support given and received is only balanced in a generalized fashion over the life course. We argue that reciprocity in parent-child relationships also operates in the short term. Our analysis of short-term reciprocity focuses on concurrent exchange in its main upward and…

Effect of kinesthetic illusion induced by visual stimulation on muscular output function after short-term immobilization.

Science.gov (United States)

Inada, Toru; Kaneko, Fuminari; Hayami, Tatsuya

2016-04-01

Kinesthetic illusions by visual stimulation (KiNVIS) enhances corticomotor excitability and activates motor association areas. The purpose of this study was to investigate the effect of KiNVIS induction on muscular output function after short-term immobilization. Thirty subjects were assigned to 3 groups: an immobilization group, with the left hand immobilized for 12h (immobilization period); an illusion group, with the left hand immobilized and additionally subjected to KiNVIS of the immobilized part during the immobilization period; and a control group with no manipulation. The maximum voluntary contraction (MVC), fluctuation of force (force fluctuation) during a force modulation task, and twitch force were measured both before (pre-test) and after (post-test) the immobilization period. Data were analyzed by performing two-way (TIME×GROUP) repeated measures ANOVA. The MVC decreased in the immobilization group only (pre-test; 37.8±6.1N, post-test; 32.8±6.9N, p<0.0005) after the immobilization period. The force fluctuation increased only in the immobilization group (pre-test; 2.19±0.54%, post-test; 2.78±0.87%, p=0.007) after the immobilization period. These results demonstrate that induction of KiNVIS prevents negative effect on MVC and force fluctuation after 12h of immobilization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decay uncovered in nonverbal short-term memory.

Science.gov (United States)

Mercer, Tom; McKeown, Denis

2014-02-01

Decay theory posits that memory traces gradually fade away over the passage of time unless they are actively rehearsed. Much recent work exploring verbal short-term memory has challenged this theory, but there does appear to be evidence for trace decay in nonverbal auditory short-term memory. Numerous discrimination studies have reported a performance decline as the interval separating two tones is increased, consistent with a decay process. However, most of this tone comparison research can be explained in other ways, without reference to decay, and these alternative accounts were tested in the present study. In Experiment 1, signals were employed toward the end of extended retention intervals to ensure that listeners were alert to the presence and frequency content of the memoranda. In Experiment 2, a mask stimulus was employed in an attempt to distinguish between a highly detailed sensory trace and a longer-lasting short-term memory, and the distinctiveness of the stimuli was varied. Despite these precautions, slow-acting trace decay was observed. It therefore appears that the mere passage of time can lead to forgetting in some forms of short-term memory.

Short-term energy outlook annual supplement, 1993

International Nuclear Information System (INIS)

1993-01-01

The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the third quarter of 1993 through the fourth quarter of 1994. Values for the second quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding

Short-term variability of Cyg X-1 and the accretion disk temperature fluctuation

International Nuclear Information System (INIS)

Doi, K.

1980-01-01

Recent theoretical models which have been proposed to explain the observed time-averaged spectrum of Cyg X-1 assume that the hard x-rays are emitted by inverse-Compton mechanism from an optically thin, hot accretion disk around a black hole. Results are reported here of balloon observations (20-68 keV) and compared with previous rocket observations (1.5-25 keV). Using the results an analysis is made of the variability of the source intensity in the hard x-ray range which suggests that the variation is essentially spectral indicating that it originated from temperature fluctuation in an accretive disk. Such a model, which explains the stochastic nature of the variability, its characteristic time scale and spectral features at the same time in the context of the conventional accretion disk model for Cyg X-1, is examined. (U.K.)

Parent-Offspring Conflict over Short-Term Mating Strategies

Directory of Open Access Journals (Sweden)

Spyroulla Georgiou

2011-12-01

Full Text Available Individuals engage in short-term mating strategies that enable them to obtain fitness benefits from casual relationships. These benefits, however, count for less and cost more to their parents. On this basis three hypotheses are tested. First, parents and offspring are likely to disagree over short-term mating strategies, with the former considering these as less acceptable than the latter. Second, parents are more likely to disapprove of the short-term mating strategies of their daughters than of their sons. Finally, mothers and fathers are expected to agree on how much they disagree over the short-term mating strategies of their children. Evidence from a sample of 148 Greek-Cypriot families (140 mothers, 105 fathers, 119 daughters, 77 sons provides support for the first two hypotheses and partial support for the third hypothesis. The implications of these findings for understanding family dynamics are further discussed.

Short-term trends in the gas industry - Panorama 2008; Tendances a court terme de l'industrie gaziere - Panorama 2008

Energy Technology Data Exchange (ETDEWEB)

NONE

2008-07-01

In a context of high investment costs and rising energy prices, and recurring unseasonably warm temperatures in recent years, the growth of natural gas demand is slowing. On the supply side, and on the demand side too, new trends are emerging, with potentially powerful impact on the short-and long-term development of the industry.

Determination of circulation and short period fluctuation in Ilha Grande Bay (RJ, Brazil

Directory of Open Access Journals (Sweden)

Yoshimine Ikeda

1980-06-01

Full Text Available A mesosoale study was made of the Ilha Grande area. The local circulation described through -progressive vector diagrams showed a clochwise bottom circulation determined in June 1976, while in the upper 10 m the direction of the flow entering the Ilha Grande Bay was towards the center in the west and towards the Marambaia sandbank in the east side of the Bay. Short periods and amplitude fluctuations were evaluted using power spectral analysis, Fourier and Maximum Entropy Method, which showed that in the upper 10 m predominant periods decrease from 1.1h (A = 6.3cm sec-1 (position = 3C to 1.0h (A = 7.4 cm sec-1 (position = 2D and increase to 5.8h (A = 6.8 cm., sec-1 (position = ID, while at the bottom layer the predominant period increases from 0.4 h (A = 5.0 cm sec-1 (position = 3G to 6.4h (A = 7.0 cm sec-1 (position = 2G and to 4.4h (A = 7.9 cm sec-1 (position = 1G . From the original data it has been possible to determine an "intense pulsation" between 30-70 cm sec-1 in the upper 10 m with about 1.0h period and 10-20 min duration in all the stations.

Circadian modulation of short-term memory in Drosophila.

Science.gov (United States)

Lyons, Lisa C; Roman, Gregg

2009-01-01

Endogenous biological clocks are widespread regulators of behavior and physiology, allowing for a more efficient allocation of efforts and resources over the course of a day. The extent that different processes are regulated by circadian oscillators, however, is not fully understood. We investigated the role of the circadian clock on short-term associative memory formation using a negatively reinforced olfactory-learning paradigm in Drosophila melanogaster. We found that memory formation was regulated in a circadian manner. The peak performance in short-term memory (STM) occurred during the early subjective night with a twofold performance amplitude after a single pairing of conditioned and unconditioned stimuli. This rhythm in memory is eliminated in both timeless and period mutants and is absent during constant light conditions. Circadian gating of sensory perception does not appear to underlie the rhythm in short-term memory as evidenced by the nonrhythmic shock avoidance and olfactory avoidance behaviors. Moreover, central brain oscillators appear to be responsible for the modulation as cryptochrome mutants, in which the antennal circadian oscillators are nonfunctional, demonstrate robust circadian rhythms in short-term memory. Together these data suggest that central, rather than peripheral, circadian oscillators modulate the formation of short-term associative memory and not the perception of the stimuli.

Critical neural networks with short- and long-term plasticity

Science.gov (United States)

Michiels van Kessenich, L.; Luković, M.; de Arcangelis, L.; Herrmann, H. J.

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1 /f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

The Role of Short-term Consolidation in Memory Persistence

OpenAIRE

Timothy J. Ricker

2015-01-01

Short-term memory, often described as working memory, is one of the most fundamental information processing systems of the human brain. Short-term memory function is necessary for language, spatial navigation, problem solving, and many other daily activities. Given its importance to cognitive function, understanding the architecture of short-term memory is of crucial importance to understanding human behavior. Recent work from several laboratories investigating the entry of information into s...

The interaction of short-term and long-term memory in phonetic category formation

Science.gov (United States)

Harnsberger, James D.

2002-05-01

This study examined the role that short-term memory capacity plays in the relationship between novel stimuli (e.g., non-native speech sounds, native nonsense words) and phonetic categories in long-term memory. Thirty native speakers of American English were administered five tests: categorial AXB discrimination using nasal consonants from Malayalam; categorial identification, also using Malayalam nasals, which measured the influence of phonetic categories in long-term memory; digit span; nonword span, a short-term memory measure mediated by phonetic categories in long-term memory; and paired-associate word learning (word-word and word-nonword pairs). The results showed that almost all measures were significantly correlated with one another. The strongest predictor for the discrimination and word-nonword learning results was nonword (r=+0.62) and digit span (r=+0.51), respectively. When the identification test results were partialed out, only nonword span significantly correlated with discrimination. The results show a strong influence of short-term memory capacity on the encoding of phonetic detail within phonetic categories and suggest that long-term memory representations regulate the capacity of short-term memory to preserve information for subsequent encoding. The results of this study will also be discussed with regards to resolving the tension between episodic and abstract models of phonetic category structure.

Prospective testing of Coulomb short-term earthquake forecasts

Science.gov (United States)

Jackson, D. D.; Kagan, Y. Y.; Schorlemmer, D.; Zechar, J. D.; Wang, Q.; Wong, K.

2009-12-01

Earthquake induced Coulomb stresses, whether static or dynamic, suddenly change the probability of future earthquakes. Models to estimate stress and the resulting seismicity changes could help to illuminate earthquake physics and guide appropriate precautionary response. But do these models have improved forecasting power compared to empirical statistical models? The best answer lies in prospective testing in which a fully specified model, with no subsequent parameter adjustments, is evaluated against future earthquakes. The Center of Study of Earthquake Predictability (CSEP) facilitates such prospective testing of earthquake forecasts, including several short term forecasts. Formulating Coulomb stress models for formal testing involves several practical problems, mostly shared with other short-term models. First, earthquake probabilities must be calculated after each “perpetrator” earthquake but before the triggered earthquakes, or “victims”. The time interval between a perpetrator and its victims may be very short, as characterized by the Omori law for aftershocks. CSEP evaluates short term models daily, and allows daily updates of the models. However, lots can happen in a day. An alternative is to test and update models on the occurrence of each earthquake over a certain magnitude. To make such updates rapidly enough and to qualify as prospective, earthquake focal mechanisms, slip distributions, stress patterns, and earthquake probabilities would have to be made by computer without human intervention. This scheme would be more appropriate for evaluating scientific ideas, but it may be less useful for practical applications than daily updates. Second, triggered earthquakes are imperfectly recorded following larger events because their seismic waves are buried in the coda of the earlier event. To solve this problem, testing methods need to allow for “censoring” of early aftershock data, and a quantitative model for detection threshold as a function of

Semantic and phonological contributions to short-term repetition and long-term cued sentence recall.

Science.gov (United States)

Meltzer, Jed A; Rose, Nathan S; Deschamps, Tiffany; Leigh, Rosie C; Panamsky, Lilia; Silberberg, Alexandra; Madani, Noushin; Links, Kira A

2016-02-01

The function of verbal short-term memory is supported not only by the phonological loop, but also by semantic resources that may operate on both short and long time scales. Elucidation of the neural underpinnings of these mechanisms requires effective behavioral manipulations that can selectively engage them. We developed a novel cued sentence recall paradigm to assess the effects of two factors on sentence recall accuracy at short-term and long-term stages. Participants initially repeated auditory sentences immediately following a 14-s retention period. After this task was complete, long-term memory for each sentence was probed by a two-word recall cue. The sentences were either concrete (high imageability) or abstract (low imageability), and the initial 14-s retention period was filled with either an undemanding finger-tapping task or a more engaging articulatory suppression task (Exp. 1, counting backward by threes; Exp. 2, repeating a four-syllable nonword). Recall was always better for the concrete sentences. Articulatory suppression reduced accuracy in short-term recall, especially for abstract sentences, but the sentences initially recalled following articulatory suppression were retained better at the subsequent cued-recall test, suggesting that the engagement of semantic mechanisms for short-term retention promoted encoding of the sentence meaning into long-term memory. These results provide a basis for using sentence imageability and subsequent memory performance as probes of semantic engagement in short-term memory for sentences.

Short-term and long-term sick-leave in Sweden

DEFF Research Database (Denmark)

Blank, N; Diderichsen, Finn

1995-01-01

The primary aim of the study was to analyse similarities and differences between repeated spells of short-term sick-leave (more than 3 spells of less than 7 days' duration in a 12-month period) and long-term absence through sickness (at least 1 spell of more than 59 days' duration in a 12-month p...

Magnetic fluctuations associated with density fluctuations in the tokamak edge

International Nuclear Information System (INIS)

Kim, Y.J.; Gentle, K.W.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.

1989-01-01

Electrostatic density and potential fluctuations occurring with high amplitude near the edge of a tokamak are correlated with components of the fluctuating magnetic field measured outside the limiter radius. It has been established that this turbulence is associated with fluctuations in current as well as density and potential. The correlation extends for substantial toroidal distances, but only if the probes are displaced approximately along field lines, consistent with the short coherence lengths poloidally but long coherence lengths parallel to the field which are characteristic for this turbulence. Furthermore, the correlation can be found only with density fluctuations measured inside the limiter radius; density fluctuations behind the limiter have no detectable magnetic concomitant for the toroidally spaced probes used here. (author). Letter-to-the-editor. 12 refs, 3 figs

Short-Term Power Load Point Prediction Based on the Sharp Degree and Chaotic RBF Neural Network

Directory of Open Access Journals (Sweden)

Dongxiao Niu

2015-01-01

Full Text Available In order to realize the predicting and positioning of short-term load inflection point, this paper made reference to related research in the field of computer image recognition. It got a load sharp degree sequence by the transformation of the original load sequence based on the algorithm of sharp degree. Then this paper designed a forecasting model based on the chaos theory and RBF neural network. It predicted the load sharp degree sequence based on the forecasting model to realize the positioning of short-term load inflection point. Finally, in the empirical example analysis, this paper predicted the daily load point of a region using the actual load data of the certain region to verify the effectiveness and applicability of this method. Prediction results showed that most of the test sample load points could be accurately predicted.

Short-term Consumer Benefits of Dynamic Pricing

OpenAIRE

Dupont, Benjamin; De Jonghe, Cedric; Kessels, Kris; Belmans, Ronnie

2011-01-01

Consumer benefits of dynamic pricing depend on a variety of factors. Consumer characteristics and climatic circumstances widely differ, which forces a regional comparison. This paper presents a general overview of demand response programs and focuses on the short-term benefits of dynamic pricing for an average Flemish residential consumer. It reaches a methodology to develop a cost reflective dynamic pricing program and to estimate short-term bill savings. Participating in a dynamic pricing p...

Very short-term probabilistic forecasting of wind power with generalized logit-Normal distributions

DEFF Research Database (Denmark)

Pinson, Pierre

2012-01-01

and probability masses at the bounds. Both auto-regressive and conditional parametric auto-regressive models are considered for the dynamics of their location and scale parameters. Estimation is performed in a recursive least squares framework with exponential forgetting. The superiority of this proposal over......Very-short-term probabilistic forecasts, which are essential for an optimal management of wind generation, ought to account for the non-linear and double-bounded nature of that stochastic process. They take here the form of discrete–continuous mixtures of generalized logit–normal distributions...

Short-term hydro-thermal scheduling using particle swarm optimization method

International Nuclear Information System (INIS)

Yu, Binghui; Yuan, Xiaohui; Wang, Jinwen

2007-01-01

The approaches based on different particle swarm optimization (PSO) techniques are applied to solve the short-term hydro-thermal scheduling problem. In the proposed methods, many constraints of the hydro-thermal system, such as power balance, water balance, reservoir volume limits and the operation limits of hydro and thermal plants, are considered. The feasibility of the proposed algorithm is demonstrated through an example system, and the results are compared with the results of a genetic algorithm and evolutionary programming approaches. The experimental results show that all the PSO algorithms have the ability to achieve nearly global solutions, but a local version of PSO with inertia weight appears to be the best amongst all the PSOs in terms of high quality solution

Critical fluctuations in cortical models near instability

Directory of Open Access Journals (Sweden)

Matthew J. Aburn

2012-08-01

Full Text Available Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human EEG, however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where nonlinearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power-law scaling and bistable switching have been suggested as generic indicators of the approach to bifurcation in nonlinear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen-Rit model of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations.

Features in the primordial power spectrum of double D-term inflation

International Nuclear Information System (INIS)

Lesgourgues, Julien

2000-01-01

Recently, there has been some interest for building supersymmetric models of double inflation. These models, realistic from a particle physics point of view, predict a broken-scale-invariant power spectrum of primordial cosmological perturbations, that may explain eventual nontrivial features in the present matter power spectrum. In previous works, the primordial spectrum was calculated using analytic slow-roll approximations. However, these models involve a fast second-order phase transition during inflation, with a stage of spinodal instability, and an interruption of slow-roll. For our previous model of double D-term inflation, we simulate numerically the evolution of quantum fluctuations, taking into account the spinodal modes, and we show that the semiclassical approximation can be employed even during the transition, due to the presence of a second inflaton field. The primordial power spectrum possesses a rich structure, and possibly, a non-Gaussian spike on observable scales

Musical and Verbal Memory in Alzheimer's Disease: A Study of Long-Term and Short-Term Memory

Science.gov (United States)

Menard, Marie-Claude; Belleville, Sylvie

2009-01-01

Musical memory was tested in Alzheimer patients and in healthy older adults using long-term and short-term memory tasks. Long-term memory (LTM) was tested with a recognition procedure using unfamiliar melodies. Short-term memory (STM) was evaluated with same/different judgment tasks on short series of notes. Musical memory was compared to verbal…

A least squares approach for efficient and reliable short-term versus long-term optimization

DEFF Research Database (Denmark)

Christiansen, Lasse Hjuler; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

The uncertainties related to long-term forecasts of oil prices impose significant financial risk on ventures of oil production. To minimize risk, oil companies are inclined to maximize profit over short-term horizons ranging from months to a few years. In contrast, conventional production...... optimization maximizes long-term profits over horizons that span more than a decade. To address this challenge, the oil literature has introduced short-term versus long-term optimization. Ideally, this problem is solved by a posteriori multi-objective optimization methods that generate an approximation...... the balance between the objectives, leaving an unfulfilled potential to increase profits. To promote efficient and reliable short-term versus long-term optimization, this paper introduces a natural way to characterize desirable Pareto points and proposes a novel least squares (LS) method. Unlike hierarchical...

The economic benefit of short-term forecasting for wind energy in the UK electricity market

International Nuclear Information System (INIS)

Barthelmie, R.J.; Murray, F.; Pryor, S.C.

2008-01-01

In the UK market, the total price of renewable electricity is made up of the Renewables Obligation Certificate and the price achieved for the electricity. Accurate forecasting improves the price if electricity is traded via the power exchange. In order to understand the size of wind farm for which short-term forecasting becomes economically viable, we develop a model for wind energy. Simulations were carried out for 2003 electricity prices for different forecast accuracies and strategies. The results indicate that it is possible to increase the price obtained by around pound 5/MWh which is about 14% of the electricity price in 2003 and about 6% of the total price. We show that the economic benefit of using short-term forecasting is also dependant on the accuracy and cost of purchasing the forecast. As the amount of wind energy requiring integration into the grid increases, short-term forecasting becomes more important to both wind farm owners and the transmission/distribution operators. (author)

Do Short-Term Managerial Objectives Lead to Under- or Over-Investment in Long-Term Projects

OpenAIRE

Lucian Arye Bebchuk; Lars A. Stole

1994-01-01

This paper studies managerial decisions about investment in long-run projects in the presence of imperfect information (the market knows less about such investments than the firm's managers) and short-term managerial objectives (the managers are concerned about the short-term stock price as well as the long-term stock price). Prior work has suggested that imperfect information and short-term managerial objectives induce managers to underinvest in long-run projects. We show that either underin...

Impact of economic fluctuations on suicide mortality in Canada (1926-2008): Testing the Durkheim, Ginsberg, and Henry and Short theories.

Science.gov (United States)

Thibodeau, Lise; Lachaud, James

2016-01-01

Three theories have been proposed to explain the relationship between suicide and economic fluctuations, including the Durkheim (nonlinear), Ginsberg (procyclical), and Henry and Short (countercyclical) theories. This study tested the effect of economic fluctuations, measured by unemployment rate, on suicide rates in Canada from 1926 to 2008. Autoregressive integrated moving average time-series models were used. The results showed a significant relationship between suicide and economic fluctuation; this association was positive during the contraction period (1926-1950) and negative in the period of economic expansion (1951-1973). Males and females showed differential effects in the period of moderate unemployment (1974-2008). In addition, the suicide rate of mid-adults (45-64) was most impacted by economic fluctuations. Our study tends to support Durkheim's theory and suggests the need for public health responses in times of economic contraction and expansion.

Sleep Quality, Short-Term and Long-Term CPAP Adherence

Science.gov (United States)

Somiah, Manya; Taxin, Zachary; Keating, Joseph; Mooney, Anne M.; Norman, Robert G.; Rapoport, David M.; Ayappa, Indu

2012-01-01

Study Objectives: Adherence to CPAP therapy is low in patients with obstructive sleep apnea/hypopnea syndrome (OSAHS). The purpose of the present study was to evaluate the utility of measures of sleep architecture and sleep continuity on the CPAP titration study as predictors of both short- and long-term CPAP adherence. Methods: 93 patients with OSAHS (RDI 42.8 ± 34.3/h) underwent in-laboratory diagnostic polysomnography, CPAP titration, and follow-up polysomnography (NPSG) on CPAP. Adherence to CPAP was objectively monitored. Short-term (ST) CPAP adherence was averaged over 14 days immediately following the titration study. Long-term (LT) CPAP adherence was obtained in 56/93 patients after approximately 2 months of CPAP use. Patients were grouped into CPAP adherence groups for ST ( 4 h) and LT adherence ( 4 h). Sleep architecture, sleep disordered breathing (SDB) indices, and daytime outcome variables from the diagnostic and titration NPSGs were compared between CPAP adherence groups. Results: There was a significant relationship between ST and LT CPAP adherence (r = 0.81, p CPAP adherence groups had significantly lower %N2 and greater %REM on the titration NPSG. A model combining change in sleep efficiency and change in sleep continuity between the diagnostic and titration NPSGs predicted 17% of the variance in LT adherence (p = 0.006). Conclusions: These findings demonstrate that characteristics of sleep architecture, even on the titration NPSG, may predict some of the variance in CPAP adherence. Better sleep quality on the titration night was related to better CPAP adherence, suggesting that interventions to improve sleep on/prior to the CPAP titration study might be used as a therapeutic intervention to improve CPAP adherence. Citation: Somiah M; Taxin Z; Keating J; Mooney AM; Norman RG; Rapoport DM; Ayappa I. Sleep quality, short-term and long-term CPAP adherence. J Clin Sleep Med 2012;8(5):489-500. PMID:23066359

Assessing the associative deficit of older adults in long-term and short-term/working memory.

Science.gov (United States)

Chen, Tina; Naveh-Benjamin, Moshe

2012-09-01

Older adults exhibit a deficit in associative long-term memory relative to younger adults. However, the literature is inconclusive regarding whether this deficit is attenuated in short-term/working memory. To elucidate the issue, three experiments assessed younger and older adults' item and interitem associative memory and the effects of several variables that might potentially contribute to the inconsistent pattern of results in previous studies. In Experiment 1, participants were tested on item and associative recognition memory with both long-term and short-term retention intervals in a single, continuous recognition paradigm. There was an associative deficit for older adults in the short-term and long-term intervals. Using only short-term intervals, Experiment 2 utilized mixed and blocked test designs to examine the effect of test event salience. Blocking the test did not attenuate the age-related associative deficit seen in the mixed test blocks. Finally, an age-related associative deficit was found in Experiment 3, under both sequential and simultaneous presentation conditions. Even while accounting for some methodological issues, the associative deficit of older adults is evident in short-term/working memory.

Power considerations for the application of detrended fluctuation analysis in gait variability studies.

Directory of Open Access Journals (Sweden)

Nikita A Kuznetsov

Full Text Available The assessment of gait variability using stochastic signal processing techniques such as detrended fluctuation analysis (DFA has been shown to be a sensitive tool for evaluation of gait alterations due to aging and neuromuscular disease. However, previous studies have suggested that the application of DFA requires relatively long recordings (600 strides, which is difficult when working with clinical populations or older adults. In this paper we propose a model for predicting DFA variance in experimental data and conduct a Monte Carlo simulation to estimate the sample size and number of trials required to detect a change in DFA scaling exponent. We illustrate the model in a simulation to detect a difference of 0.1 (medium effect between two groups of subjects when using short gait time series (100 to 200 strides in the context of between- and within-subject designs. We assumed that the variance of DFA scaling exponent arises due to individual differences, time series length, and experimental error. Results showed that sample sizes required to achieve acceptable power of 80% are practically feasible, especially when using within-subject designs. For example, to detect a group difference in the DFA scaling exponent of 0.1, it would require either 25 subjects and 2 trials per subject or 12 subjects and 4 trials per subject using a within-subject design. We then compared plausibility of such power predictions to the empirically observed power from a study that required subjects to synchronize with a persistent fractal metronome. The results showed that the model adequately predicted the empirical pattern of results. Our power simulations could be used in conjunction with previous design guidelines in the literature when planning new gait variability experiments.

Tunneling probe of fluctuating superconductivity in disordered thin films

Science.gov (United States)

Dentelski, David; Frydman, Aviad; Shimshoni, Efrat; Dalla Torre, Emanuele G.

2018-03-01

Disordered thin films close to the superconductor-insulator phase transition (SIT) hold the key to understanding quantum phase transition in strongly correlated materials. The SIT is governed by superconducting quantum fluctuations, which can be revealed, for example, by tunneling measurements. These experiments detect a spectral gap, accompanied by suppressed coherence peaks, on both sides of the transition. Here we describe the insulating side in terms of a fluctuating superconducting field with finite-range correlations. We perform a controlled diagrammatic resummation and derive analytic expressions for the tunneling differential conductance. We find that short-range superconducting fluctuations suppress the coherence peaks even in the presence of long-range correlations. Our approach offers a quantitative description of existing measurements on disordered thin films and accounts for tunneling spectra with suppressed coherence peaks.

The pedagogy of Short-Term Study-Abroad Programs

Directory of Open Access Journals (Sweden)

Jude Gonsalvez

2013-10-01

Full Text Available This paper focuses on establishing guidelines on the pedagogy of short term study abroad programs. This study follows 33 students who participated in a short-term study-abroad program to India with the researcher from 2006 through 2011. The study relies heavily on the student reflections and expressions as they experienced them. It is qualitative in nature. Focus groups were the main method of data collection, where participants were invited to reflect, express, and share their experiences with one another. This provided an opportunity for the participants to come together, relive their experiences, and help provide information as to how and what type of an influence this short-term study-abroad program provided.

Quantum fluctuations of the Coulomb potential as a source of flicker noise: the influence of external electric field

International Nuclear Information System (INIS)

Kazakov, Kirill A

2006-01-01

Fluctuations of the electromagnetic field produced by quantized matter in an external electric field are investigated. A general expression for the power spectrum of fluctuations is derived within the long-range expansion. It is found that in the whole measured frequency band, the power spectrum of fluctuations exhibits an inverse frequency dependence. A general argument is given showing that for all practically relevant values of the electric field, the power spectrum of induced fluctuations is proportional to the field strength squared. As an illustration, the power spectrum is calculated explicitly using a kinetic model with a relaxation-type collision term. Finally, it is shown that the magnitude of fluctuations produced by a sample generally has a Gaussian distribution around its mean value, and its dependence on the sample geometry is determined. In particular, it is demonstrated that for geometrically similar samples the power spectrum is inversely proportional to the sample volume. Application of the results obtained to the problem of flicker noise is discussed

International Short-Term Countermeasures Survey - 2012 Update

International Nuclear Information System (INIS)

Ingham, Grant

2013-01-01

Nuclear emergency planning, preparedness, response, and management, in general, are essential elements of any country's nuclear power programme. Part of nuclear emergency planning and preparedness is the implementation of national emergency plans, including detailed procedures for the implementation of short-term countermeasures, before during, and after the release of radioactive substances. The timely and appropriate implementation of short-term countermeasures, such as sheltering, evacuation, and iodine prophylaxis, can, in case of a nuclear emergency with a release of radioactive material, considerably reduce the doses to the public in the vicinity of the nuclear installation. Although international guidelines exist, national procedures and practices may differ due to different national habits, cultural specificity, and societal needs. Different national procedures and practices may, however, in the case of a radioactive release affecting two neighbouring countries, lead to different decisions in the implementation of countermeasures. In order to better understand existing approaches and to facilitate the comparison of national practices, the NEA decided to launch a questionnaire on current practices regarding short-term countermeasures, updating a similar survey performed in 1994 and 2003, as countries' practices have since evolved and been modified. In 2012, it was decided to reevaluate the country approaches in light of the early lessons learnt from the Fukushima Daiichi NPP accident. The information collected may be used to understand the basis for decisions in various countries, and, if deemed appropriate, as a basis for international harmonisation. This may also assist member countries to explain to the public affected by an emergency why the decisions in neighbouring countries may vary. This report summarises the information given by member countries and includes nine sections to explore the different aspects, covering the following topics: member

Genetic deletion of melanin-concentrating hormone neurons impairs hippocampal short-term synaptic plasticity and hippocampal-dependent forms of short-term memory.

Science.gov (United States)

Le Barillier, Léa; Léger, Lucienne; Luppi, Pierre-Hervé; Fort, Patrice; Malleret, Gaël; Salin, Paul-Antoine

2015-11-01

The cognitive role of melanin-concentrating hormone (MCH) neurons, a neuronal population located in the mammalian postero-lateral hypothalamus sending projections to all cortical areas, remains poorly understood. Mainly activated during paradoxical sleep (PS), MCH neurons have been implicated in sleep regulation. The genetic deletion of the only known MCH receptor in rodent leads to an impairment of hippocampal dependent forms of memory and to an alteration of hippocampal long-term synaptic plasticity. By using MCH/ataxin3 mice, a genetic model characterized by a selective deletion of MCH neurons in the adult, we investigated the role of MCH neurons in hippocampal synaptic plasticity and hippocampal-dependent forms of memory. MCH/ataxin3 mice exhibited a deficit in the early part of both long-term potentiation and depression in the CA1 area of the hippocampus. Post-tetanic potentiation (PTP) was diminished while synaptic depression induced by repetitive stimulation was enhanced suggesting an alteration of pre-synaptic forms of short-term plasticity in these mice. Behaviorally, MCH/ataxin3 mice spent more time and showed a higher level of hesitation as compared to their controls in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task. Deletion of MCH neurons could thus alter spatial short-term memory by impairing short-term plasticity in the hippocampus. Altogether, these findings could provide a cellular mechanism by which PS may facilitate memory encoding. Via MCH neuron activation, PS could prepare the day's learning by increasing and modulating short-term synaptic plasticity in the hippocampus. © 2015 Wiley Periodicals, Inc.

Relationship between short and long term radon measurements

International Nuclear Information System (INIS)

Martinez, T.; Ramirez, D.; Navarrete, M.; Cabrera, L.; Ramirez, A.; Gonzalez, P.

2000-01-01

In this work the radon group of the Faculty of Chemistry at the National University of Mexico presents the results obtained in the establishment of a relation between the short and long term radon measures made with passive electret detectors E-PERM type LLT and HST. The measures were carried out inside single family dwellings (open house condition) located in the southeast of Mexico City (in Xochimilco) during the four seasons of the year 1997. A correlation was established between the short term measures (five days) and those of a long term for every season as well as an annual average, with an equation that relates them. The objective and advantage of this correlation are that with a short term measure it is possible to predict the annual mean radon concentration, that represents a saving of human and economic resources. (author)

Impact of short-term severe accident management actions in a long-term perspective. Final Report

International Nuclear Information System (INIS)

2000-03-01

The present systems for severe accident management are focused on mitigating the consequences of special severe accident phenomena and to reach a safe plant state. However, in the development of strategies and procedures for severe accident management, it is also important to consider the long-term perspective of accident management and especially to secure the safe state of the plant. The main reason for this is that certain short-term actions have an impact on the long-term scenario. Both positive and negative effects from short-term actions on the accident management in the long-term perspective have been included in this paper. Short-term actions are accident management measures taken within about 24 hours after the initiating event. The purpose of short-term actions is to reach a stable status of the plant. The main goal in the long-term perspective is to maintain the reactor in a stable state and prevent uncontrolled releases of activity. The purpose of this short Technical Note, deliberately limited in scope, is to draw attention to potential long-term problems, important to utilities and regulatory authorities, arising from the way a severe accident would be managed during the first hours. Its objective is to encourage discussions on the safest - and maybe also most economical - way to manage a severe accident in the long term by not making the situation worse through inappropriate short-term actions, and on the identification of short-term actions likely to make long-term management easier and safer. The Note is intended as a contribution to the knowledge base put at the disposal of Member countries through international collaboration. The scope of the work has been limited to a literature search. Useful further activities have been identified. However, there is no proposal, at this stage, for more detailed work to be undertaken under the auspices of the CSNI. Plant-specific applications would need to be developed by utilities

Ordered short-term memory differs in signers and speakers: Implications for models of short-term memory

OpenAIRE

Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

2008-01-01

Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers (Boutla, Supalla, Newport, & Bavelier, 2004). Here, we test the hypothesis that this population difference reflects differences in the way speakers and signers maintain temporal order information in short-te...

Short-term and long-term deflection of reinforced hollow core ...

African Journals Online (AJOL)

This paper presents a study on different methods of analysis that are currently used by design codes to predict the short-term and long-term deflection of reinforced concrete slab systems and compares the predicted deflections with measured deflections. The experimental work to measure deflections involved the testing of ...

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

A multifractal detrended fluctuation analysis of financial market efficiency: Comparison using Dow Jones sector ETF indices

Science.gov (United States)

Tiwari, Aviral Kumar; Albulescu, Claudiu Tiberiu; Yoon, Seong-Min

2017-10-01

This study challenges the efficient market hypothesis, relying on the Dow Jones sector Exchange-Traded Fund (ETF) indices. For this purpose, we use the generalized Hurst exponent and multifractal detrended fluctuation analysis (MF-DFA) methods, using daily data over the timespan from 2000 to 2015. We compare the sector ETF indices in terms of market efficiency between short- and long-run horizons, small and large fluctuations, and before and after the global financial crisis (GFC). Our findings can be summarized as follows. First, there is clear evidence that the sector ETF markets are multifractal in nature. We also find a crossover in the multifractality of sector ETF market dynamics. Second, the utilities and consumer goods sector ETF markets are more efficient compared with the financial and telecommunications sector ETF markets, in terms of price prediction. Third, there are noteworthy discrepancies in terms of market efficiency, between the short- and long-term horizons. Fourth, the ETF market efficiency is considerably diminished after the global financial crisis.

Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

International Nuclear Information System (INIS)

Trapero, Juan R.; Kourentzes, Nikolaos; Martin, A.

2015-01-01

Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1–24 h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 h ahead. - Highlights: • Solar irradiation forecasts at short-term are required to operate solar power plants. • This paper assesses the Dynamic Harmonic Regression to forecast solar irradiation. • Models are evaluated using hourly GHI and DNI data collected in Spain. • The results show that forecasting accuracy is improved by using the model proposed

Short-term memory binding deficits in Alzheimer's disease

OpenAIRE

Parra, Mario; Abrahams, S.; Fabi, K.; Logie, R.; Luzzi, S.; Della Sala, Sergio

2009-01-01

Alzheimer's disease impairs long term memories for related events (e.g. faces with names) more than for single events (e.g. list of faces or names). Whether or not this associative or ‘binding’ deficit is also found in short-term memory has not yet been explored. In two experiments we investigated binding deficits in verbal short-term memory in Alzheimer's disease. Experiment 1 : 23 patients with Alzheimer's disease and 23 age and education matched healthy elderly were recruited. Participants...

A New Strategy for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Yi Yang

2013-01-01

Full Text Available Electricity is a special energy which is hard to store, so the electricity demand forecasting remains an important problem. Accurate short-term load forecasting (STLF plays a vital role in power systems because it is the essential part of power system planning and operation, and it is also fundamental in many applications. Considering that an individual forecasting model usually cannot work very well for STLF, a hybrid model based on the seasonal ARIMA model and BP neural network is presented in this paper to improve the forecasting accuracy. Firstly the seasonal ARIMA model is adopted to forecast the electric load demand day ahead; then, by using the residual load demand series obtained in this forecasting process as the original series, the follow-up residual series is forecasted by BP neural network; finally, by summing up the forecasted residual series and the forecasted load demand series got by seasonal ARIMA model, the final load demand forecasting series is obtained. Case studies show that the new strategy is quite useful to improve the accuracy of STLF.

Relationship between short-term sexual strategies and sexual jealousy.

Science.gov (United States)

Mathes, Eugene W

2005-02-01

In a classic study, Buss, Larson, Westen, and Semmelroth reported that men were more distressed by the thought of a partner's sexual infidelity (sexual jealousy) and women were more distressed by the thought of a partner's emotional infidelity (emotional jealousy). Initially, Buss and his associates explained these results by suggesting that men are concerned about uncertainty of paternity, that is, the possibility of raising another man's child while believing the child is their own. However, later they explained the results in terms of men's preference for short-term sexual strategies. The purpose of this research was to test the explanation of short-term sexual strategies. Men and women subjects were instructed to imagine themselves in a relationship which was either short-term (primarily sexual) or long-term (involving commitment) and then respond to Buss's jealousy items. It was hypothesized that, when both men and women imagined a short-term relationship, they would be more threatened by a partner's sexual infidelity, and, when they imagined a long-term relationship, they would be more threatened by a partner's emotional infidelity. Support was found for this hypothesis.

Impact of long-term and short-term therapies on seminal parameters

Directory of Open Access Journals (Sweden)

Jlenia Elia

2013-04-01

Full Text Available Aim: The aim of this work was: i to evaluate the prevalence of male partners of subfertile couples being treated with long/short term therapies for non andrological diseases; ii to study their seminal profile for the possible effects of their treatments on spermatogenesis and/or epididymal maturation. Methods: The study group was made up of 723 subjects, aged between 25 and 47 years. Semen analysis was performed according to World Health Organization (WHO guidelines (1999. The Superimposed Image Analysis System (SIAS, which is based on the computerized superimposition of spermatozoa images, was used to assess sperm motility parameters. Results: The prevalence of subjects taking pharmacological treatments was 22.7% (164/723. The prevalence was 3.7% (27/723 for the Short-Term Group and 18.9% (137/723 for the Long-Term Group. The subjects of each group were also subdivided into subgroups according to the treatments being received. Regarding the seminal profile, we did not observe a significant difference between the Long-Term, Short-Term or the Control Group. However, regarding the subgroups, we found a significant decrease in sperm number and progressive motility percentage in the subjects receiving treatment with antihypertensive drugs compared with the other subgroups and the Control Group. Conclusions: In the management of infertile couples, the potential negative impact on seminal parameters of any drugs being taken as Long-Term Therapy should be considered. The pathogenic mechanism needs to be clarified.

Ambiguity Aversion, Asset Prices, and the Welfare Costs of Aggregate Fluctuations

DEFF Research Database (Denmark)

Alonso, Irasema; Prado, Mauricio

2015-01-01

with a representative agent facing consumption fluctuations calibrated to match U.S. data from 1889 to 2008. Our experiment is to restrict preference parameters in order to as well as possible match some asset-price facts—the average returns on equity and a short-term risk-free bond—and then compute the welfare...

Model documentation report: Short-Term Hydroelectric Generation Model

International Nuclear Information System (INIS)

1993-08-01

The purpose of this report is to define the objectives of the Short- Term Hydroelectric Generation Model (STHGM), describe its basic approach, and to provide details on the model structure. This report is intended as a reference document for model analysts, users, and the general public. Documentation of the model is in accordance with the Energy Information Administration's (AYE) legal obligation to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). The STHGM performs a short-term (18 to 27- month) forecast of hydroelectric generation in the United States using an autoregressive integrated moving average (UREMIA) time series model with precipitation as an explanatory variable. The model results are used as input for the short-term Energy Outlook

Comment on “Short-term combined economic emission scheduling of hydrothermal power systems with cascaded reservoirs using differential evolution” by K.K. Mandal and N. Chakaborty [Energy Convers. Manage. 50 (2009) 97–104

International Nuclear Information System (INIS)

Ahmadi, Abdollah; Nezhad, Ali Esmaeel

2015-01-01

This paper discusses the short-term combined economic emission scheduling of hydrothermal power systems with cascaded reservoirs [Energy Convers Manage. 50 (2009) 97–104], while differential evolution algorithm has been employed to solve the optimization problem. However, this problem is subjected to several constraints like the generation limitations of generating units. The solutions reported in the original paper do not satisfy the constraint on the initial and final reservoir storage volumes of hydro units as well as the constraint on the generated power by such units, which should be positive at any time of the scheduling period. Thus, this paper intends to prove this issue and solve the problem using Normal Boundary Intersection (NBI) method, in order to propose the correct solutions satisfying all the constraints of the short-term hydrothermal scheduling problem

Time-dependent perpendicular fluctuations in the driven lattice Lorentz gas

Science.gov (United States)

Leitmann, Sebastian; Schwab, Thomas; Franosch, Thomas

2018-02-01

We present results for the fluctuations of the displacement of a tracer particle on a planar lattice pulled by a step force in the presence of impenetrable, immobile obstacles. The fluctuations perpendicular to the applied force are evaluated exactly in first order of the obstacle density for arbitrarily strong pulling and all times. The complex time-dependent behavior is analyzed in terms of the diffusion coefficient, local exponent, and the non-Skellam parameter, which quantifies deviations from the dynamics on the lattice in the absence of obstacles. The non-Skellam parameter along the force is analyzed in terms of an asymptotic model and reveals a power-law growth for intermediate times.

Long-term power generation expansion planning with short-term demand response: Model, algorithms, implementation, and electricity policies

Science.gov (United States)

Lohmann, Timo

Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the

Multiscale probability distribution of pressure fluctuations in fluidized beds

International Nuclear Information System (INIS)

Ghasemi, Fatemeh; Sahimi, Muhammad; Reza Rahimi Tabar, M; Peinke, Joachim

2012-01-01

Analysis of flow in fluidized beds, a common chemical reactor, is of much current interest due to its fundamental as well as industrial importance. Experimental data for the successive increments of the pressure fluctuations time series in a fluidized bed are analyzed by computing a multiscale probability density function (PDF) of the increments. The results demonstrate the evolution of the shape of the PDF from the short to long time scales. The deformation of the PDF across time scales may be modeled by the log-normal cascade model. The results are also in contrast to the previously proposed PDFs for the pressure fluctuations that include a Gaussian distribution and a PDF with a power-law tail. To understand better the properties of the pressure fluctuations, we also construct the shuffled and surrogate time series for the data and analyze them with the same method. It turns out that long-range correlations play an important role in the structure of the time series that represent the pressure fluctuation. (paper)

Short-term flow induced crystallization in isotactic polypropylene : how short is short?

NARCIS (Netherlands)

Ma, Z.; Balzano, L.; Portale, G.; Peters, G.W.M.

2013-01-01

The so-called "short-term flow" protocol is widely applied in experimental flow-induced crystallization studies on polymers in order to separate the nucleation and subsequent growth processes [Liedauer et al. Int. Polym. Proc. 1993, 8, 236–244]. The basis of this protocol is the assumption that

Comparison of Short Term with Long Term Catheterization after Anterior Colporrhaphy Surgery

Directory of Open Access Journals (Sweden)

F. Movahed

2010-07-01

Full Text Available Introduction & Objective: This belief that overfilling the bladder after anterior colporrhaphy might have a negative influence on surgical outcome, causes routine catheterization after operation. This study was done to compare short term (24h with long term (72h catheterization after anterior colporrhaphy.Materials & Methods: This randomized clinical trial was carried out at Kosar Hospital , Qazvin (Iran in 2005-2006. One hundred cases candidating for anterior colporrhaphy , were divided in two equal groups . In the first group foley catheter was removed 24 hours and in the second group 72 hours after the operation. Before removing catheter, urine sample was obtained for culture . After removal and urination, residual volume was determinded. If the volume exceeded 200 ml or retention occured, the catheter would be fixed for more 72 hours. Need for recatheterization, urinary retention, positive urine culture,and hospital stay were surveyed. The data was analyzed using T and Fisher tests.Results: Residual volume exceeding 200 ml and the need for recatheterization occurred in one case (2% in the short term group but in the long term group none of the subjects needed recatheterization (P=1. Retention was not seen. In the both groups, one case (2% had positive urine culture with no statistically significant difference (P=1. Mean hospital stay was short in the first group (P=0.00.Conclusion: Short term catheterization after anterior colporrhaphy does not cause urinary retention and decreases hospital stay.

Short-term versus long-term market opportunities and financial constraints

International Nuclear Information System (INIS)

Ferrari, Angelo

1999-01-01

This presentation discusses gas developments in Europe, the European Gas Directive, short term vs. long term, and Snam's new challenges. The European gas market is characterized by (1) The role of gas in meeting the demand for energy, which varies greatly from one country to another, (2) A growing market, (3) Decreasing role of domestic production, and (4) Increasing imports. Within the European Union, the Gas Directive aims to transform single national markets into one integrated European market by introducing third party access to the network for eligible clients as a means of increasing the competition between operators. The Gas Directive would appear to modify the form of the market rather than its size, and in particular the sharing of responsibility and risk among operators. The market in the future will offer operators the possibility to exploit opportunities deriving mainly from demands for increased flexibility. Opportunities linked to entrepreneurial initiatives require long-term investments characteristic of the gas business. Risks and opportunities must be balanced evenly between different operators. If everyone takes on their own risks and responsibilities, this means a wider distribution of the risks of long-term vs. short-term, currently borne by the gas companies that are integrated, into a market that tends to favour the short-term. A gradual liberalization process should allow incumbent operators to gradually diversify their activities in new gas market areas or enter new business activities. They could move beyond their local and European boundaries in pursuit of an international dimension. The market will have to make the transition from the national to the European dimension: as an example, Snam covers 90% of the Italian market, but its share of an integrated European market will be about 15%

Short-Term Group Treatment for Adult Children of Alcoholics.

Science.gov (United States)

Cooper, Alvin; McCormack, WIlliam A.

1992-01-01

Adult children of alcoholics (n=24) were tested on measures of loneliness, anxiety, hostility, depression, and interpersonal dependency before and after participation in short-term group therapy. Highly significant test score changes supported effectiveness of individual therapy in short-term groups. (Author/NB)

Power spectral density of velocity fluctuations estimated from phase Doppler data

OpenAIRE

Jicha Miroslav; Lizal Frantisek; Jedelsky Jan

2012-01-01

Laser Doppler Anemometry (LDA) and its modifications such as PhaseDoppler Particle Anemometry (P/DPA) is point-wise method for optical nonintrusive measurement of particle velocity with high data rate. Conversion of the LDA velocity data from temporal to frequency domain – calculation of power spectral density (PSD) of velocity fluctuations, is a non trivial task due to nonequidistant data sampling in time. We briefly discuss possibilities for the PSD estimation and specify limitations caused...

Frequency-specific insight into short-term memory capacity

OpenAIRE

Feurra, Matteo; Galli, Giulia; Pavone, Enea Francesco; Rossi, Alessandro; Rossi, Simone

2016-01-01

We provided novel evidence of a frequency-specific effect by transcranial alternating current stimulation (tACS) of the left posterior parietal cortex on short-term memory, during a digit span task. the effect was prominent with stimulation at beta frequency for young and not for middle-aged adults and correlated with age. Our findings highlighted a short-term memory capacity improvement by tACS application.

Reconciling long-term cultural diversity and short-term collective social behavior.

Science.gov (United States)

Valori, Luca; Picciolo, Francesco; Allansdottir, Agnes; Garlaschelli, Diego

2012-01-24

An outstanding open problem is whether collective social phenomena occurring over short timescales can systematically reduce cultural heterogeneity in the long run, and whether offline and online human interactions contribute differently to the process. Theoretical models suggest that short-term collective behavior and long-term cultural diversity are mutually excluding, since they require very different levels of social influence. The latter jointly depends on two factors: the topology of the underlying social network and the overlap between individuals in multidimensional cultural space. However, while the empirical properties of social networks are intensively studied, little is known about the large-scale organization of real societies in cultural space, so that random input specifications are necessarily used in models. Here we use a large dataset to perform a high-dimensional analysis of the scientific beliefs of thousands of Europeans. We find that interopinion correlations determine a nontrivial ultrametric hierarchy of individuals in cultural space. When empirical data are used as inputs in models, ultrametricity has strong and counterintuitive effects. On short timescales, it facilitates a symmetry-breaking phase transition triggering coordinated social behavior. On long timescales, it suppresses cultural convergence by restricting it within disjoint groups. Moreover, ultrametricity implies that these results are surprisingly robust to modifications of the dynamical rules considered. Thus the empirical distribution of individuals in cultural space appears to systematically optimize the coexistence of short-term collective behavior and long-term cultural diversity, which can be realized simultaneously for the same moderate level of mutual influence in a diverse range of online and offline settings.

Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

DEFF Research Database (Denmark)

Dahl, Christian M.; Croonenbroeck, Carsten

2014-01-01

We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium......-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...... accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology....

Qualitative and, as far as possible, quantitative assessment of the short-term and long-term effect of a nuclear phase-out

International Nuclear Information System (INIS)

Jaenicke, M.; Mez, L.; Spelthahn, S.; Springmann, F.; Theissen, A.; Ullrich, O.; Leuchtner, J.; Seifried, D.

1986-08-01

This survey starts from a series of scenarios or comments on the question of West Germany, leaving the field of nuclear power. These were submitted after the accident at Chernobyl and have gained particular importance in this context. The possibilities of leaving in the short, medium and long term were examined. In a further section, the connection between operation of powerstations and the resulting environmental effects is treated. Economic aspects of leaving the field of nuclear power are examined and the possibilities and potentials of rational energy use (potential saving of electricity, potential of combined heat and power plants and potential from regenerative sources of energy) are estimated. (orig./UA) [de

Short-Term Robustness of Production Management Systems : New Methodology

NARCIS (Netherlands)

Kleijnen, J.P.C.; Gaury, E.G.A.

2000-01-01

This paper investigates the short-term robustness of production planning and control systems. This robustness is defined here as the systems ability to maintain short-term service probabilities (i.e., the probability that the fill rate remains within a prespecified range), in a variety of

Differences in health status between long-term and short-term benzodiazepine users.

NARCIS (Netherlands)

Zandstra, S.M.; Furer, J.W.; Lisdonk, E.H. van de; Bor, J.H.J.; Zitman, F.G.; Weel, C. van

2002-01-01

BACKGROUND: Despite generally accepted advice to keep treatment short, benzodiazepines are often prescibed for more than six months. Prevention of long-term benzodiazepine use could be facilitated by the utilisation of risk indicators for long-term use. However, the characteristics of long-term

The roles of long-term phonotactic and lexical prosodic knowledge in phonological short-term memory.

Science.gov (United States)

Tanida, Yuki; Ueno, Taiji; Lambon Ralph, Matthew A; Saito, Satoru

2015-04-01

Many previous studies have explored and confirmed the influence of long-term phonological representations on phonological short-term memory. In most investigations, phonological effects have been explored with respect to phonotactic constraints or frequency. If interaction between long-term memory and phonological short-term memory is a generalized principle, then other phonological characteristics-that is, suprasegmental aspects of phonology-should also exert similar effects on phonological short-term memory. We explored this hypothesis through three immediate serial-recall experiments that manipulated Japanese nonwords with respect to lexical prosody (pitch-accent type, reflecting suprasegmental characteristics) as well as phonotactic frequency (reflecting segmental characteristics). The results showed that phonotactic frequency affected the retention not only of the phonemic sequences, but also of pitch-accent patterns, when participants were instructed to recall both the phoneme sequence and accent pattern of nonwords. In addition, accent pattern typicality influenced the retention of the accent pattern: Typical accent patterns were recalled more accurately than atypical ones. These results indicate that both long-term phonotactic and lexical prosodic knowledge contribute to phonological short-term memory performance.

Visual Short-Term Memory Complexity

DEFF Research Database (Denmark)

Sørensen, Thomas Alrik

Several recent studies have explored the nature and limits of visual short-term memory (VSTM) (e.g. Luck & Vogel, 1997). A general VSTM capacity limit of about 3 to 4 letters has been found, thus confirming results from earlier studies (e.g. Cattell, 1885; Sperling, 1960). However, Alvarez...

Brain oscillatory substrates of visual short-term memory capacity.

Science.gov (United States)

Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

SHORT-TERM MEMORY IS INDEPENDENT OF BRAIN PROTEIN SYNTHESIS

Energy Technology Data Exchange (ETDEWEB)

Davis, Hasker P.; Rosenzweig, Mark R.; Jones, Oliver W.

1980-09-01

Male Swiss albino CD-1 mice given a single injection of a cerebral protein synthesis inhibitor, anisomycin (ANI) (1 mg/animal), 20 min prior to single trial passive avoidance training demonstrated impaired retention at tests given 3 hr, 6 hr, 1 day, and 7 days after training. Retention was not significantly different from saline controls when tests were given 0.5 or 1.5 hr after training. Prolonging inhibition of brain protein synthesis by giving either 1 or 2 additional injections of ANI 2 or 2 and 4 hr after training did not prolong short-term retention performance. The temporal development of impaired retention in ANI treated mice could not be accounted for by drug dosage, duration of protein synthesis inhibition, or nonspecific sickness at test. In contrast to the suggestion that protein synthesis inhibition prolongs short-term memory (Quinton, 1978), the results of this experiment indicate that short-term memory is not prolonged by antibiotic drugs that inhibit cerebral protein synthesis. All evidence seems consistent with the hypothesis that short-term memory is protein synthesis independent and that the establishment of long-term memory depends upon protein synthesis during or shortly after training. Evidence for a role of protein synthesis in memory maintenance is discussed.

Impaired short-term memory for pitch in congenital amusia.

Science.gov (United States)

Tillmann, Barbara; Lévêque, Yohana; Fornoni, Lesly; Albouy, Philippe; Caclin, Anne

2016-06-01

Congenital amusia is a neuro-developmental disorder of music perception and production. The hypothesis is that the musical deficits arise from altered pitch processing, with impairments in pitch discrimination (i.e., pitch change detection, pitch direction discrimination and identification) and short-term memory. The present review article focuses on the deficit of short-term memory for pitch. Overall, the data discussed here suggest impairments at each level of processing in short-term memory tasks; starting with the encoding of the pitch information and the creation of the adequate memory trace, the retention of the pitch traces over time as well as the recollection and comparison of the stored information with newly incoming information. These impairments have been related to altered brain responses in a distributed fronto-temporal network, associated with decreased connectivity between these structures, as well as in abnormalities in the connectivity between the two auditory cortices. In contrast, amusic participants׳ short-term memory abilities for verbal material are preserved. These findings show that short-term memory deficits in congenital amusia are specific to pitch, suggesting a pitch-memory system that is, at least partly, separated from verbal memory. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

The uranium industry: long-term planning for short-term competition

International Nuclear Information System (INIS)

Vottero, X.; Georges Capus, G.

2001-01-01

Long term planning for short term competition Today, uranium producers face new challenges in terms of both production (new regulatory, environmental and social constraints) and market conditions (new sources of uranium supply, very low prices and tough competition). In such a context, long-term planning is not just a prerequisite to survive in the nuclear fuel cycle industry. In fact, it also contributes to sustaining nuclear electricity generation facing fierce competition from other energy sources in increasingly deregulated markets. Firstly, the risk of investing in new mining projects in western countries is growing because, on the one hand, of very erratic market conditions and, on the other hand, of increasingly lengthy, complex and unpredictable regulatory conditions. Secondly, the supply of other sources of uranium (uranium derived from nuclear weapons, uranium produced in CIS countries, ...) involve other risks, mainly related to politics and commercial restrictions. Consequently, competitive uranium supply requires not only technical competence but also financial strength and good marketing capabilities in order to anticipate long-term market trends, in terms of both demand and supply. It also requires taking into account new parameters such as politics, environment, regulations, etc. Today, a supplier dedicated to the sustainable production of nuclear electricity must manage a broad range of long-term risks inherent to the procurement of uranium. Taking into account all these parameters in a context of short-term, fast-changing market is a great challenge for the future generation. World Uranium Civilian Supply and Demand. (authors)

Insensitivity of visual short-term memory to irrelevant visual information.

Science.gov (United States)

Andrade, Jackie; Kemps, Eva; Werniers, Yves; May, Jon; Szmalec, Arnaud

2002-07-01

Several authors have hypothesized that visuo-spatial working memory is functionally analogous to verbal working memory. Irrelevant background speech impairs verbal short-term memory. We investigated whether irrelevant visual information has an analogous effect on visual short-term memory, using a dynamic visual noise (DVN) technique known to disrupt visual imagery (Quinn & McConnell, 1996b). Experiment I replicated the effect of DVN on pegword imagery. Experiments 2 and 3 showed no effect of DVN on recall of static matrix patterns, despite a significant effect of a concurrent spatial tapping task. Experiment 4 showed no effect of DVN on encoding or maintenance of arrays of matrix patterns, despite testing memory by a recognition procedure to encourage visual rather than spatial processing. Serial position curves showed a one-item recency effect typical of visual short-term memory. Experiment 5 showed no effect of DVN on short-term recognition of Chinese characters, despite effects of visual similarity and a concurrent colour memory task that confirmed visual processing of the characters. We conclude that irrelevant visual noise does not impair visual short-term memory. Visual working memory may not be functionally analogous to verbal working memory, and different cognitive processes may underlie visual short-term memory and visual imagery.

Polymer electrolyte membrane water electrolysis: Restraining degradation in the presence of fluctuating power

Science.gov (United States)

Rakousky, Christoph; Reimer, Uwe; Wippermann, Klaus; Kuhri, Susanne; Carmo, Marcelo; Lueke, Wiebke; Stolten, Detlef

2017-02-01

Polymer electrolyte membrane (PEM) water electrolysis generates 'green' hydrogen when conducted with electricity from renewable - but fluctuating - sources like wind or solar photovoltaic. Unfortunately, the long-term stability of the electrolyzer performance is still not fully understood under these input power profiles. In this study, we contrast the degradation behavior of our PEM water electrolysis single cells that occurs under operation with constant and intermittent power and derive preferable operating states. For this purpose, five different current density profiles are used, of which two were constant and three dynamic. Cells operated at 1 A cm-2 show no degradation. However, degradation was observed for the remaining four profiles, all of which underwent periods of high current density (2 A cm-2). Hereby, constant operation at 2 A cm-2 led to the highest degradation rate (194 μV h-1). Degradation can be greatly reduced when the cells are operated with an intermittent profile. Current density switching has a positive effect on durability, as it causes reversible parts of degradation to recover and results in a substantially reduced degradation per mole of hydrogen produced. Two general degradation phenomena were identified, a decreased anode exchange current density and an increased contact resistance at the titanium porous transport layer (Ti-PTL).

Remembering over the short-term: the case against the standard model.

Science.gov (United States)

Nairne, James S

2002-01-01

Psychologists often assume that short-term storage is synonymous with activation, a mnemonic property that keeps information in an immediately accessible form. Permanent knowledge is activated, as a result of on-line cognitive processing, and an activity trace is established "in" short-term (or working) memory. Activation is assumed to decay spontaneously with the passage of time, so a refreshing process-rehearsal-is needed to maintain availability. Most of the phenomena of immediate retention, such as capacity limitations and word length effects, are assumed to arise from trade-offs between rehearsal and decay. This "standard model" of how we remember over the short-term still enjoys considerable popularity, although recent research questions most of its main assumptions. In this chapter I review the recent research and identify the empirical and conceptual problems that plague traditional conceptions of short-term memory. Increasingly, researchers are recognizing that short-term retention is cue driven, much like long-term memory, and that neither rehearsal nor decay is likely to explain the particulars of short-term forgetting.

Gummed-up memory: chewing gum impairs short-term recall.

Science.gov (United States)

Kozlov, Michail D; Hughes, Robert W; Jones, Dylan M

2012-01-01

Several studies have suggested that short-term memory is generally improved by chewing gum. However, we report the first studies to show that chewing gum impairs short-term memory for both item order and item identity. Experiment 1 showed that chewing gum reduces serial recall of letter lists. Experiment 2 indicated that chewing does not simply disrupt vocal-articulatory planning required for order retention: Chewing equally impairs a matched task that required retention of list item identity. Experiment 3 demonstrated that manual tapping produces a similar pattern of impairment to that of chewing gum. These results clearly qualify the assertion that chewing gum improves short-term memory. They also pose a problem for short-term memory theories asserting that forgetting is based on domain-specific interference given that chewing does not interfere with verbal memory any more than tapping. It is suggested that tapping and chewing reduce the general capacity to process sequences.

A Short Term Analogue Memory

DEFF Research Database (Denmark)

Shah, Peter Jivan

1992-01-01

A short term analogue memory is described. It is based on a well-known sample-hold topology in which leakage currents have been minimized partly by circuit design and partly by layout techniques. Measurements on a test chip implemented in a standard 2.4 micron analogue CMOS process show a droop...

Retention interval affects visual short-term memory encoding.

Science.gov (United States)

Bankó, Eva M; Vidnyánszky, Zoltán

2010-03-01

Humans can efficiently store fine-detailed facial emotional information in visual short-term memory for several seconds. However, an unresolved question is whether the same neural mechanisms underlie high-fidelity short-term memory for emotional expressions at different retention intervals. Here we show that retention interval affects the neural processes of short-term memory encoding using a delayed facial emotion discrimination task. The early sensory P100 component of the event-related potentials (ERP) was larger in the 1-s interstimulus interval (ISI) condition than in the 6-s ISI condition, whereas the face-specific N170 component was larger in the longer ISI condition. Furthermore, the memory-related late P3b component of the ERP responses was also modulated by retention interval: it was reduced in the 1-s ISI as compared with the 6-s condition. The present findings cannot be explained based on differences in sensory processing demands or overall task difficulty because there was no difference in the stimulus information and subjects' performance between the two different ISI conditions. These results reveal that encoding processes underlying high-precision short-term memory for facial emotional expressions are modulated depending on whether information has to be stored for one or for several seconds.

Rapid deterioration of pain sensory-discriminative information in short-term memory.

Science.gov (United States)

Rainville, Pierre; Doucet, Jean-Charles; Fortin, Marie-Chantale; Duncan, Gary H

2004-08-01

The assessment of pain and analgesic efficacy sometimes relies on the retrospective evaluation of pain felt in the immediate, recent or distant past, yet we have a very limited understanding of the processes involved in the encoding, maintenance and intentional retrieval of pain. We examine the properties of the short-term memory of thermal and pain sensation intensity with a delayed-discrimination task using pairs of heat pain, warm and cool stimulation in healthy volunteers. Performance decreased as a function of the inter-stimulus interval (ISI), indicating a robust deterioration of sensory information over the test period of 4-14 s. As expected, performance also decreased with smaller temperature differences (Delta-T) and shorter stimulus durations (6-2 s). The relation between performance and Delta-T was adequately described by a power function, the exponent of which increased linearly with longer ISI. Importantly, performance declined steadily with increasing ISI (from 6 to 14 s)--but only for pairs of heat pain stimuli that were relatively difficult to discriminate (Delta-T short-term memory for pain and temperature sensation intensity relies on a transient analog representation that is quickly degraded and transformed into a more resistant but less precise categorical format. This implies that retrospective pain ratings obtained even after very short delays may be rather inaccurate but relatively reliable.

Comparison of Sugammadex and Neostigmine in Short Term Surgery

Directory of Open Access Journals (Sweden)

Fatih Koc

2014-03-01

Full Text Available Aim: This study compared the efficacy and cost effectivines of sugammadex and neostigmine for reversal of neuromuscular blockade induced by rocuronium for short term elective surgery. Material and Method: After written informed consent, 33 patients aged 18%u201365, ASA I-III, who were undergoing short term surgery (

Short term fluctuations and succession trends in tropical floodplain vegetation measured by correspondence analysis

Directory of Open Access Journals (Sweden)

Anderson Medeiros dos Santos

2008-08-01

Full Text Available The aim of this work was to study the aquatic macrophytes community development to distinguish the fluctuations from succession trends at different temporal and spatial scales in the Upper Paraná River floodplain. The samples were collected quarterly from May 2000 to March 2002 in seven lakes with different degrees of connectivity from the main river channel and analyzed by between-class correspondence analysis. It was difficult to establish any pattern of community development at local scale but at a higher level of organization, disconnected lakes were characterized by fluctuation of the floristic composition. Connected lakes showed a straight trajectory, indicating that succession was occurring at these sites. Probably the income of propagules and diaspores from the river into connected lakes was the driving force of the observed change in community composition.Trabalhos sobre sucessão ecológica foram realizados principalmente com ecologia vegetal de plantas terrestres, onde a maioria das teorias foram concebidas. Poucos estudos abordam a vegetação de áreas alagáveis especialmente no Brasil. Este trabalho investigou o desenvolvimento da comunidade de macrófitas aquáticas tentando distinguir flutuações populacionais de tendências sucessionais em diferentes escalas temporal e espacial na planície de inundação do Alto Rio Paraná. As amostras foram coletadas a cada três meses, de maio de 2000 a março de 2002, em 7 lagoas com diferentes graus de conectividade com a calha principal dos rios, e analisadas pela análise de correspondência (CA entre-classes. Foi difícil estabelecer qualquer padrão de desenvolvimento da comunidade sob uma escala local, mas em uma escala mais ampla, as lagoas desconectadas foram caracterizadas pela flutuação da composição florística. As lagoas conectadas apresentaram uma trajetória retilínea no diagrama da CA, indicando que a sucessão estava ocorrendo nestes locais. Provavelmente, o aporte

Short-term memory for scenes with affective content

OpenAIRE

Maljkovic, Vera; Martini, Paolo

2005-01-01

The emotional content of visual images can be parameterized along two dimensions: valence (pleasantness) and arousal (intensity of emotion). In this study we ask how these distinct emotional dimensions affect the short-term memory of human observers viewing a rapid stream of images and trying to remember their content. We show that valence and arousal modulate short-term memory as independent factors. Arousal influences dramatically the average speed of data accumulation in memory: Higher aro...

LANGUAGE REPETITION AND SHORT-TERM MEMORY: AN INTEGRATIVE FRAMEWORK

Directory of Open Access Journals (Sweden)

Steve eMajerus

2013-07-01

Full Text Available Short-term maintenance of verbal information is a core factor of language repetition, especially when reproducing multiple or unfamiliar stimuli. Many models of language processing locate the verbal short-term maintenance function in the left posterior superior temporo-parietal area and its connections with the inferior frontal gyrus. However, research in the field of short-term memory has implicated bilateral fronto-parietal networks, involved in attention and serial order processing, as being critical for the maintenance and reproduction of verbal sequences. We present here an integrative framework aimed at bridging research in the language processing and short-term memory fields. This framework considers verbal short-term maintenance as an emergent function resulting from synchronized and integrated activation in dorsal and ventral language processing networks as well as fronto-parietal attention and serial order processing networks. To-be-maintained item representations are temporarily activated in the dorsal and ventral language processing networks, novel phoneme and word serial order information is proposed to be maintained via a right fronto-parietal serial order processing network, and activation in these different networks is proposed to be coordinated and maintained via a left fronto-parietal attention processing network. This framework provides new perspectives for our understanding of information maintenance at the nonword-, word- and sentence-level as well as of verbal maintenance deficits in case of brain injury.

Language repetition and short-term memory: an integrative framework.

Science.gov (United States)

Majerus, Steve

2013-01-01

Short-term maintenance of verbal information is a core factor of language repetition, especially when reproducing multiple or unfamiliar stimuli. Many models of language processing locate the verbal short-term maintenance function in the left posterior superior temporo-parietal area and its connections with the inferior frontal gyrus. However, research in the field of short-term memory has implicated bilateral fronto-parietal networks, involved in attention and serial order processing, as being critical for the maintenance and reproduction of verbal sequences. We present here an integrative framework aimed at bridging research in the language processing and short-term memory fields. This framework considers verbal short-term maintenance as an emergent function resulting from synchronized and integrated activation in dorsal and ventral language processing networks as well as fronto-parietal attention and serial order processing networks. To-be-maintained item representations are temporarily activated in the dorsal and ventral language processing networks, novel phoneme and word serial order information is proposed to be maintained via a right fronto-parietal serial order processing network, and activation in these different networks is proposed to be coordinated and maintained via a left fronto-parietal attention processing network. This framework provides new perspectives for our understanding of information maintenance at the non-word-, word- and sentence-level as well as of verbal maintenance deficits in case of brain injury.

Short-horizon regulation for long-term investors

NARCIS (Netherlands)

Shi, Z.; Werker, B.J.M.

2012-01-01

We study the effects of imposing repeated short-horizon regulatory constraints on long-term investors. We show that Value-at-Risk and Expected Shortfall constraints, when imposed dynamically, lead to similar optimal portfolios and wealth distributions. We also show that, in utility terms, the costs

Verbal short-term memory and vocabulary learning in polyglots.

Science.gov (United States)

Papagno, C; Vallar, G

1995-02-01

Polyglot and non-polyglot Italian subjects were given tests assessing verbal (phonological) and visuo-spatial short-term and long-term memory, general intelligence, and vocabulary knowledge in their native language. Polyglots had a superior level of performance in verbal short-term memory tasks (auditory digit span and nonword repetition) and in a paired-associate learning test, which assessed the subjects' ability to acquire new (Russian) words. By contrast, the two groups had comparable performance levels in tasks assessing general intelligence, visuo-spatial short-term memory and learning, and paired-associate learning of Italian words. These findings, which are in line with neuropsychological and developmental evidence, as well as with data from normal subjects, suggest a close relationship between the capacity of phonological memory and the acquisition of foreign languages.

The stimulation of hematosis on short-term and prolong irradiation

International Nuclear Information System (INIS)

Tukhtaev, T.M.

1978-01-01

This book studies the stimulation of hematosis on short-term and prolong irradiation, pathogenetic mechanisms of lesion and reconstruction of hematosis at critical radiation sickness, action hematosis stimulators in short-term irradiation conditions

Rapid effects of estrogens on short-term memory: Possible mechanisms.

Science.gov (United States)

Paletta, Pietro; Sheppard, Paul A S; Matta, Richard; Ervin, Kelsy S J; Choleris, Elena

2018-06-01

Estrogens affect learning and memory through rapid and delayed mechanisms. Here we review studies on rapid effects on short-term memory. Estradiol rapidly improves social and object recognition memory, spatial memory, and social learning when administered systemically. The dorsal hippocampus mediates estrogen rapid facilitation of object, social and spatial short-term memory. The medial amygdala mediates rapid facilitation of social recognition. The three estrogen receptors, α (ERα), β (ERβ) and the G-protein coupled estrogen receptor (GPER) appear to play different roles depending on the task and brain region. Both ERα and GPER agonists rapidly facilitate short-term social and object recognition and spatial memory when administered systemically or into the dorsal hippocampus and facilitate social recognition in the medial amygdala. Conversely, only GPER can facilitate social learning after systemic treatment and an ERβ agonist only rapidly improved short-term spatial memory when given systemically or into the hippocampus, but also facilitates social recognition in the medial amygdala. Investigations into the mechanisms behind estrogens' rapid effects on short term memory showed an involvement of the extracellular signal-regulated kinase (ERK) and the phosphoinositide 3-kinase (PI3K) kinase pathways. Recent evidence also showed that estrogens interact with the neuropeptide oxytocin in rapidly facilitating social recognition. Estrogens can increase the production and/or release of oxytocin and other neurotransmitters, such as dopamine and acetylcholine. Therefore, it is possible that estrogens' rapid effects on short-term memory may occur through the regulation of various neurotransmitters, although more research is need on these interactions as well as the mechanisms of estrogens' actions on short-term memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Analysis of losses within SMES system for compensating output fluctuation of wind power farm

Energy Technology Data Exchange (ETDEWEB)

Park, S. I.; Kim, J. H.; Le, T. D.; Lee, D. H.; Kim, H. M. [Jeju National University, Jeju (Korea, Republic of); Yoon, Y. S. [Dept. of Electrical Engineering, Shin Ansan University, Ansan (Korea, Republic of); Yoon, K. Y. [Dept. of lectrical and Electronic Engineering, Yonsei University, Seoul (Korea, Republic of)

2014-12-15

Output fluctuation which is generated in wind power farm can hinder stability of total power system. The electric energy storage (EES) reduces unstable output, and superconducting magnetic energy storage (SMES) of various EESs has the proper performance for output compensation of wind power farm since it charges and discharges large scale power quickly with high efficiency. However, because of the change of current within SMES, the electromagnetic losses occur in the process of output compensation. In this paper, the thermal effect of the losses that occur in SMES system while compensating in wind power farm is analyzed. The output analysis of wind power farm is processed by numerical analysis, and the losses of SMES system is analyzed by 3D finite element analysis (FEA) simulation tool.

Analysis of losses within SMES system for compensating output fluctuation of wind power farm

International Nuclear Information System (INIS)

Park, S. I.; Kim, J. H.; Le, T. D.; Lee, D. H.; Kim, H. M.; Yoon, Y. S.; Yoon, K. Y.

2014-01-01

Output fluctuation which is generated in wind power farm can hinder stability of total power system. The electric energy storage (EES) reduces unstable output, and superconducting magnetic energy storage (SMES) of various EESs has the proper performance for output compensation of wind power farm since it charges and discharges large scale power quickly with high efficiency. However, because of the change of current within SMES, the electromagnetic losses occur in the process of output compensation. In this paper, the thermal effect of the losses that occur in SMES system while compensating in wind power farm is analyzed. The output analysis of wind power farm is processed by numerical analysis, and the losses of SMES system is analyzed by 3D finite element analysis (FEA) simulation tool.

Short-Term Reproducibility of Twenty-Four-Hour Intraocular Pressure Curves in Untreated Patients with Primary Open-Angle Glaucoma and Ocular Hypertension.

Directory of Open Access Journals (Sweden)

Shuo Xu

Full Text Available To assess the short-term day-to-day reproducibility of 24-hour intraocular pressure (IOP curves in various respects in untreated primary open-angle glaucoma (POAG and ocular hypertension (OHT patients.47 subjects with POAG and 34 subjects with OHT underwent IOP measurements every 2 hours in both eyes for consecutive 48 hours by a non-contact tonometer (NCT. IOP values at each time point were recorded. Mean IOP, peak IOP, time difference of peak IOP between two days and IOP fluctuation were also calculated. Intraclass correlation coefficients (ICCs and Bland-Altman plots were used to evaluate reproducibility.ICCs of the entire IOP values for a complete 24-hour curve were 0.577 and 0.561 in POAG and OHT patients, respectively. ICCs of IOP values at different time points ranged from 0.384 (10am to 0.686 (4am in POAG patients and from 0.347 (6am to 0.760 (4am in OHT patients. ICCs of mean IOP, peak IOP and IOP fluctuation were respectively 0.832, 0.704, 0.367 in POAG patients and 0.867, 0.816 0.633 in OHT patients. Only 37.23% and 35.29% of the peak IOP time points appeared within the time difference of 2 hours in POAG and OHT patients, respectively, while 53.19% and 48.53% appeared within 4 hours in POAG and OHT patients, respectively.A 24-hour IOP curve in a single day is not highly reproducible in short-term and has limited use for evaluating individual IOP condition. Mean IOP and peak IOP for a 24-hour IOP curve are useful parameters in clinical follow-up, while IOP value at a certain time point, IOP fluctuation and peak IOP time point should be interpreted with caution.

Spectral indices of cardiovascular adaptations to short-term simulated microgravity exposure

Science.gov (United States)

Patwardhan, A. R.; Evans, J. M.; Berk, M.; Grande, K. J.; Charles, J. B.; Knapp, C. F.

1995-01-01

We investigated the effects of exposure to microgravity on the baseline autonomic balance in cardiovascular regulation using spectral analysis of cardiovascular variables measured during supine rest. Heart rate, arterial pressure, radial flow, thoracic fluid impedance and central venous pressure were recorded from nine volunteers before and after simulated microgravity, produced by 20 hours of 6 degrees head down bedrest plus furosemide. Spectral powers increased after simulated microgravity in the low frequency region (centered at about 0.03 Hz) in arterial pressure, heart rate and radial flow, and decreased in the respiratory frequency region (centered at about 0.25 Hz) in heart rate. Reduced heart rate power in the respiratory frequency region indicates reduced parasympathetic influence on the heart. A concurrent increase in the low frequency power in arterial pressure, heart rate, and radial flow indicates increased sympathetic influence. These results suggest that the baseline autonomic balance in cardiovascular regulation is shifted towards increased sympathetic and decreased parasympathetic influence after exposure to short-term simulated microgravity.

An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

Energy Technology Data Exchange (ETDEWEB)

Lu, Songfeng; Sun, Chengfu; Lu, Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-03-15

This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms. (author)

An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

Energy Technology Data Exchange (ETDEWEB)

Lu Songfeng [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Sun Chengfu, E-mail: ajason_369@sina.co [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-03-15

This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms.

An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

International Nuclear Information System (INIS)

Lu Songfeng; Sun Chengfu; Lu Zhengding

2010-01-01

This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms.

PDF models and synthetic model for the wind speed fluctuations based on the resolution of Langevin equation

International Nuclear Information System (INIS)

Calif, Rudy

2012-01-01

Highlights: ► Probability Density Functions are proposed to fit the wind speed fluctuations distributions for three representative classes. ► Stochastic simulations are performed using a Langevin equation for each class. ► The properties of simulated and measured wind speed sequences are close. -- Abstract: Wind energy production is very sensitive to turbulent wind speed. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output, in particular when wind power variations on very short time scales, range at few seconds to 1 h, are considered. In small grid as they exist on islands (Guadeloupean Archipelago: French West Indies) such fluctuations can cause instabilities in case of intermediate power shortages. The developed analysis in reveals three main classes of time series for the wind speed fluctuations. In this work, Probability Density Functions (PDFs) are proposed to fit the wind speed fluctuations distributions in each class. After, to simulate wind speed fluctuations sequences, we use a stochastic differential equation, the Langevin equation considering Gaussian turbulence PDF (class I), Gram–Charlier PDF (class II) and a mixture of gaussian PDF (class III). The statistical and dynamical properties of simulated wind sequences are close to those of measured wind sequences, for each class.

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

2005-07-01

Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

Short-Term Energy Outlook: Quarterly projections. Fourth quarter 1993

Energy Technology Data Exchange (ETDEWEB)

1993-11-05

The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the fourth quarter of 1993 through the fourth quarter of 1994. Values for the third quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications.

Short-term and long-term earthquake occurrence models for Italy: ETES, ERS and LTST

Directory of Open Access Journals (Sweden)

Maura Murru

2010-11-01

Full Text Available This study describes three earthquake occurrence models as applied to the whole Italian territory, to assess the occurrence probabilities of future (M ≥5.0 earthquakes: two as short-term (24 hour models, and one as long-term (5 and 10 years. The first model for short-term forecasts is a purely stochastic epidemic type earthquake sequence (ETES model. The second short-term model is an epidemic rate-state (ERS forecast based on a model that is physically constrained by the application to the earthquake clustering of the Dieterich rate-state constitutive law. The third forecast is based on a long-term stress transfer (LTST model that considers the perturbations of earthquake probability for interacting faults by static Coulomb stress changes. These models have been submitted to the Collaboratory for the Study of Earthquake Predictability (CSEP for forecast testing for Italy (ETH-Zurich, and they were locked down to test their validity on real data in a future setting starting from August 1, 2009.

Category Specific Knowledge Modulate Capacity Limitations of Visual Short-Term Memory

DEFF Research Database (Denmark)

Dall, Jonas Olsen; Watanabe, Katsumi; Sørensen, Thomas Alrik

2016-01-01