WorldWideScience

Sample records for maximal predictive power

  1. Power maximization of a point absorber wave energy converter using improved model predictive control

    Science.gov (United States)

    Milani, Farideh; Moghaddam, Reihaneh Kardehi

    2017-08-01

    This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

  2. Maximal locality and predictive power in higher-dimensional, compactified field theories

    International Nuclear Information System (INIS)

    Kubo, Jisuke; Nunami, Masanori

    2004-01-01

    To realize maximal locality in a trivial field theory, we maximize the ultraviolet cutoff of the theory by fine tuning the infrared values of the parameters. This optimization procedure is applied to the scalar theory in D + 1 dimensional (D ≥ 4) with one extra dimension compactified on a circle of radius R. The optimized, infrared values of the parameters are then compared with the corresponding ones of the uncompactified theory in D dimensions, which is assumed to be the low-energy effective theory. We find that these values approximately agree with each other as long as R -1 > approx sM is satisfied, where s ≅ 10, 50, 50, 100 for D = 4,5,6,7, and M is a typical scale of the D-dimensional theory. This result supports the previously made claim that the maximization of the ultraviolet cutoff in a nonrenormalizable field theory can give the theory more predictive power. (author)

  3. Scheduling of Domestic Water Heater Power Demand for Maximizing PV Self-Consumption Using Model Predictive Control

    DEFF Research Database (Denmark)

    Sossan, Fabrizio; Kosek, Anna Magdalena; Martinenas, Sergejus

    2013-01-01

    This paper presents a model predictive control (MPC) strategy for maximizing photo-voltaic (PV) selfconsumption in a household context exploiting the flexible demand of an electric water heater. The predictive controller uses a water heater model and forecast of the hot Water consumption in order...... to predict the future temperature of the water and it manages its state (on and off) according to the forecasted PV production, which are computed starting from forecast of the solar irradiance. Simulations for the proof of concept and for validating the proposed control strategy are proposed. Results...... of the control approach are compared with a traditional thermostatic controller using historical measurements of a 10 kW PV installation. Economic results based on the Italian self consumption tariffs are also reported. The model of the water heater complex is a mixed grey and white box and its parameters have...

  4. Adjoint-based model predictive control of wind farms : Beyond the quasi steady-state power maximization

    NARCIS (Netherlands)

    Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here

  5. Developing maximal neuromuscular power: Part 1--biological basis of maximal power production.

    Science.gov (United States)

    Cormie, Prue; McGuigan, Michael R; Newton, Robert U

    2011-01-01

    This series of reviews focuses on the most important neuromuscular function in many sport performances, the ability to generate maximal muscular power. Part 1 focuses on the factors that affect maximal power production, while part 2, which will follow in a forthcoming edition of Sports Medicine, explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability of the neuromuscular system to generate maximal power is affected by a range of interrelated factors. Maximal muscular power is defined and limited by the force-velocity relationship and affected by the length-tension relationship. The ability to generate maximal power is influenced by the type of muscle action involved and, in particular, the time available to develop force, storage and utilization of elastic energy, interactions of contractile and elastic elements, potentiation of contractile and elastic filaments as well as stretch reflexes. Furthermore, maximal power production is influenced by morphological factors including fibre type contribution to whole muscle area, muscle architectural features and tendon properties as well as neural factors including motor unit recruitment, firing frequency, synchronization and inter-muscular coordination. In addition, acute changes in the muscle environment (i.e. alterations resulting from fatigue, changes in hormone milieu and muscle temperature) impact the ability to generate maximal power. Resistance training has been shown to impact each of these neuromuscular factors in quite specific ways. Therefore, an understanding of the biological basis of maximal power production is essential for developing training programmes that effectively enhance maximal power production in the human.

  6. Developing maximal neuromuscular power: part 2 - training considerations for improving maximal power production.

    Science.gov (United States)

    Cormie, Prue; McGuigan, Michael R; Newton, Robert U

    2011-02-01

    This series of reviews focuses on the most important neuromuscular function in many sport performances: the ability to generate maximal muscular power. Part 1, published in an earlier issue of Sports Medicine, focused on the factors that affect maximal power production while part 2 explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability to generate maximal power during complex motor skills is of paramount importance to successful athletic performance across many sports. A crucial issue faced by scientists and coaches is the development of effective and efficient training programmes that improve maximal power production in dynamic, multi-joint movements. Such training is referred to as 'power training' for the purposes of this review. Although further research is required in order to gain a deeper understanding of the optimal training techniques for maximizing power in complex, sports-specific movements and the precise mechanisms underlying adaptation, several key conclusions can be drawn from this review. First, a fundamental relationship exists between strength and power, which dictates that an individual cannot possess a high level of power without first being relatively strong. Thus, enhancing and maintaining maximal strength is essential when considering the long-term development of power. Second, consideration of movement pattern, load and velocity specificity is essential when designing power training programmes. Ballistic, plyometric and weightlifting exercises can be used effectively as primary exercises within a power training programme that enhances maximal power. The loads applied to these exercises will depend on the specific requirements of each particular sport and the type of movement being trained. The use of ballistic exercises with loads ranging from 0% to 50% of one-repetition maximum (1RM) and

  7. Maximizing electrical power supply using FACTS devices

    OpenAIRE

    Lehmann, Karsten; Bent, Russell; Pan, Feng

    2015-01-01

    Modern society critically depends on the services electric power provides. Power systems rely on a network of power lines and transformers to deliver power from sources of power (generators) to the consumers (loads). However, when power lines fail (for example, through lightning or natural disasters) or when the system is heavily used, the network is often unable to fulfill all of the demand for power. While systems are vulnerable to these failures, increasingly, sophisticated control devices...

  8. Power Converters Maximize Outputs Of Solar Cell Strings

    Science.gov (United States)

    Frederick, Martin E.; Jermakian, Joel B.

    1993-01-01

    Microprocessor-controlled dc-to-dc power converters devised to maximize power transferred from solar photovoltaic strings to storage batteries and other electrical loads. Converters help in utilizing large solar photovoltaic arrays most effectively with respect to cost, size, and weight. Main points of invention are: single controller used to control and optimize any number of "dumb" tracker units and strings independently; power maximized out of converters; and controller in system is microprocessor.

  9. LOAD THAT MAXIMIZES POWER OUTPUT IN COUNTERMOVEMENT JUMP

    Directory of Open Access Journals (Sweden)

    Pedro Jimenez-Reyes

    2016-02-01

    Full Text Available ABSTRACT Introduction: One of the main problems faced by strength and conditioning coaches is the issue of how to objectively quantify and monitor the actual training load undertaken by athletes in order to maximize performance. It is well known that performance of explosive sports activities is largely determined by mechanical power. Objective: This study analysed the height at which maximal power output is generated and the corresponding load with which is achieved in a group of male-trained track and field athletes in the test of countermovement jump (CMJ with extra loads (CMJEL. Methods: Fifty national level male athletes in sprinting and jumping performed a CMJ test with increasing loads up to a height of 16 cm. The relative load that maximized the mechanical power output (Pmax was determined using a force platform and lineal encoder synchronization and estimating the power by peak power, average power and flight time in CMJ. Results: The load at which the power output no longer existed was at a height of 19.9 ± 2.35, referring to a 99.1 ± 1% of the maximum power output. The load that maximizes power output in all cases has been the load with which an athlete jump a height of approximately 20 cm. Conclusion: These results highlight the importance of considering the height achieved in CMJ with extra load instead of power because maximum power is always attained with the same height. We advise for the preferential use of the height achieved in CMJEL test, since it seems to be a valid indicative of an individual's actual neuromuscular potential providing a valid information for coaches and trainers when assessing the performance status of our athletes and to quantify and monitor training loads, measuring only the height of the jump in the exercise of CMJEL.

  10. Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

    Science.gov (United States)

    DeChant, C. M.; Moradkhani, H.

    2014-12-01

    Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

  11. Prediction of maximal heart rate: comparison using a novel and ...

    African Journals Online (AJOL)

    Prediction of maximal heart rate: comparison using a novel and conventional equation. LR Keytel, E Mukwevho, MA Will, M Lambert. Abstract. No Abstract. African Journal for Physical, Health Education, Recreation and Dance Vol. 11(3) 2005: 269-277. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL ...

  12. Submaximal exercise capacity and maximal power output in polio subjects

    NARCIS (Netherlands)

    Nollet, F.; Beelen, A.; Sargeant, A. J.; de Visser, M.; Lankhorst, G. J.; de Jong, B. A.

    2001-01-01

    OBJECTIVES: To compare the submaximal exercise capacity of polio subjects with postpoliomyelitis syndrome (PPS) and without (non-PPS) with that of healthy control subjects, to investigate the relationship of this capacity with maximal short-term power and quadriceps strength, and to evaluate

  13. Discussion on: "Profit Maximization of a Power Plant"

    DEFF Research Database (Denmark)

    Boomsma (fhv. Kristoffersen), Trine Krogh; Fleten, Stein-Erik

    2012-01-01

    Kragelund et al. provides an interesting contribution to operations scheduling in liberalized electricity markets. They address the problem of profit maximization for a power plant participating in the electricity market. In particular, given that the plant has already been dispatched in a day...

  14. Maximal network reliability for a stochastic power transmission network

    International Nuclear Information System (INIS)

    Lin, Yi-Kuei; Yeh, Cheng-Ta

    2011-01-01

    Many studies regarded a power transmission network as a binary-state network and constructed it with several arcs and vertices to evaluate network reliability. In practice, the power transmission network should be stochastic because each arc (transmission line) combined with several physical lines is multistate. Network reliability is the probability that the network can transmit d units of electric power from a power plant (source) to a high voltage substation at a specific area (sink). This study focuses on searching for the optimal transmission line assignment to the power transmission network such that network reliability is maximized. A genetic algorithm based method integrating the minimal paths and the Recursive Sum of Disjoint Products is developed to solve this assignment problem. A real power transmission network is adopted to demonstrate the computational efficiency of the proposed method while comparing with the random solution generation approach.

  15. Quantum coherence generating power, maximally abelian subalgebras, and Grassmannian geometry

    Science.gov (United States)

    Zanardi, Paolo; Campos Venuti, Lorenzo

    2018-01-01

    We establish a direct connection between the power of a unitary map in d-dimensions (d algebra). This set can be seen as a topologically non-trivial subset of the Grassmannian over linear operators. The natural distance over the Grassmannian induces a metric structure on Md, which quantifies the lack of commutativity between the pairs of subalgebras. Given a maximally abelian subalgebra, one can define, on physical grounds, an associated measure of quantum coherence. We show that the average quantum coherence generated by a unitary map acting on a uniform ensemble of quantum states in the algebra (the so-called coherence generating power of the map) is proportional to the distance between a pair of maximally abelian subalgebras in Md connected by the unitary transformation itself. By embedding the Grassmannian into a projective space, one can pull-back the standard Fubini-Study metric on Md and define in this way novel geometrical measures of quantum coherence generating power. We also briefly discuss the associated differential metric structures.

  16. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  17. Maximizing gain in high-throughput screening using conformal prediction.

    Science.gov (United States)

    Svensson, Fredrik; Afzal, Avid M; Norinder, Ulf; Bender, Andreas

    2018-02-21

    Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening. Using this setup we were able to show that by evaluating the predictions on the training data, very accurate predictions on what settings will produce the highest gain on the test data can be made. We evaluate the approach on 12 bioactivity datasets from PubChem training the models using 20% of the data. Depending on the settings of the gain-cost function, the settings generating the maximum gain were accurately identified in 8-10 out of the 12 datasets. Broadly, our approach can predict what strategy generates the highest gain based on the results of the cost-gain evaluation: to screen the compounds predicted to be active, to screen all the remaining data, or not to screen any additional compounds. When the algorithm indicates that the predicted active compounds should be screened, our approach also indicates what confidence level to apply in order to maximize gain. Hence, our approach facilitates decision-making and allocation of the resources where they deliver the most value by indicating in advance the likely outcome of a screening campaign.

  18. A study of the optimum draft of multiple resonance power buoys for maximizing electric power production

    Directory of Open Access Journals (Sweden)

    Hyuck-Min Kweon

    2014-12-01

    Full Text Available To maximize electric power production using wave energy extractions from resonance power buoys, the maximum motion displacement spectra of the buoys can primarily be obtained under a given wave condition. In this study, wave spectra observed in shoaling water were formulated. Target resonance frequencies were established from the arithmetic means of modal frequency bands and the peak frequencies. The motion characteristics of the circular cylindrical power buoys with corresponding drafts were then calculated using numerical models without considering PTO damping force. Results showed that the heave motions of the power buoys in shoaling waters with insufficient drafts produced greater amplification effects than those in deep seas with sufficient drafts.

  19. Output power maximization of low-power wind energy conversion systems revisited: Possible control solutions

    Energy Technology Data Exchange (ETDEWEB)

    Vlad, Ciprian; Munteanu, Iulian; Bratcu, Antoneta Iuliana; Ceanga, Emil [' ' Dunarea de Jos' ' University of Galati, 47, Domneasca, 800008-Galati (Romania)

    2010-02-15

    This paper discusses the problem of output power maximization for low-power wind energy conversion systems operated in partial load. These systems are generally based on multi-polar permanent-magnet synchronous generators, who exhibit significant efficiency variations over the operating range. Unlike the high-power systems, whose mechanical-to-electrical conversion efficiency is high and practically does not modify the global optimum, the low-power systems global conversion efficiency is affected by the generator behavior and the electrical power optimization is no longer equivalent with the mechanical power optimization. The system efficiency has been analyzed by using both the maxima locus of the mechanical power versus the rotational speed characteristics, and the maxima locus of the electrical power delivered versus the rotational speed characteristics. The experimental investigation has been carried out by using a torque-controlled generator taken from a real-world wind turbine coupled to a physically simulated wind turbine rotor. The experimental results indeed show that the steady-state performance of the conversion system is strongly determined by the generator behavior. Some control solutions aiming at maximizing the energy efficiency are envisaged and thoroughly compared through experimental results. (author)

  20. Output power maximization of low-power wind energy conversion systems revisited: Possible control solutions

    International Nuclear Information System (INIS)

    Vlad, Ciprian; Munteanu, Iulian; Bratcu, Antoneta Iuliana; Ceanga, Emil

    2010-01-01

    This paper discusses the problem of output power maximization for low-power wind energy conversion systems operated in partial load. These systems are generally based on multi-polar permanent-magnet synchronous generators, who exhibit significant efficiency variations over the operating range. Unlike the high-power systems, whose mechanical-to-electrical conversion efficiency is high and practically does not modify the global optimum, the low-power systems global conversion efficiency is affected by the generator behavior and the electrical power optimization is no longer equivalent with the mechanical power optimization. The system efficiency has been analyzed by using both the maxima locus of the mechanical power versus the rotational speed characteristics, and the maxima locus of the electrical power delivered versus the rotational speed characteristics. The experimental investigation has been carried out by using a torque-controlled generator taken from a real-world wind turbine coupled to a physically simulated wind turbine rotor. The experimental results indeed show that the steady-state performance of the conversion system is strongly determined by the generator behavior. Some control solutions aiming at maximizing the energy efficiency are envisaged and thoroughly compared through experimental results.

  1. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

    Directory of Open Access Journals (Sweden)

    Abut F

    2015-08-01

    Full Text Available Fatih Abut, Mehmet Fatih AkayDepartment of Computer Engineering, Çukurova University, Adana, TurkeyAbstract: Maximal oxygen uptake (VO2max indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance

  2. Prediction of maximal lactate steady state in runners with an incremental test on the field.

    Science.gov (United States)

    Leti, Thomas; Mendelson, Monique; Laplaud, David; Flore, Patrice

    2012-01-01

    During a maximal incremental ergocycle test, the power output associated with Respiratory Exchange Ratio equal to 1.00 (RER = 1.00) predicts maximal lactate steady state (MLSS). We hypothesised that these results are transferable for runners on the field. Fourteen runners performed a maximal progressive test, to assess the speed associated with RER = 1.00, and several 30 minutes constant velocity tests to determine the speed at MLSS. We observed that the speeds at RER = 1.00, at the second ventilatory threshold (VT2) and at MLSS did not differ (15.7 ± 1.1 km · h⁻¹, 16.2 ± 1.4 km · h⁻¹, 15.5 ± 1.1 km · h⁻¹ respectively). The speed associated with RER = 1.00 was better correlated with that at MLSS (r = 0.79; p = 0.0008) than that at VT2 (r = 0.73; p = 0.002). Neither the concentration of blood lactate nor the heart rate differed between the speed at RER = 1.00 and that at MLSS from the 10th and the 30th minute of the constant velocity test. Bland and Altman analysis showed a fair agreement between the speed at MLSS and that at RER (0.2 ± 1.4 km · h⁻¹). This study demonstrated that the speed associated with RER = 1.00 determined during maximal progressive track running allows a fair estimation of the speed associated with MLSS, markedly decreasing the burden of numerous invasive tests required to assess it.

  3. Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks

    National Research Council Canada - National Science Library

    Sun, Fangting; Shayman, Mark

    2006-01-01

    ...: adaptive power control. They focus on the sensor networks that consist of a sink and a set of homogeneous wireless sensor nodes, which are randomly deployed according to a uniform distribution...

  4. Designing a solar powered Stirling heat engine based on multiple criteria: Maximized thermal efficiency and power

    International Nuclear Information System (INIS)

    Ahmadi, Mohammad Hossein; Sayyaadi, Hoseyn; Dehghani, Saeed; Hosseinzade, Hadi

    2013-01-01

    Highlights: • Thermodynamic model of a solar-dish Stirling engine was presented. • Thermal efficiency and output power of the engine were simultaneously maximized. • A final optimal solution was selected using several decision-making methods. • An optimal solution with least deviation from the ideal design was obtained. • Optimal solutions showed high sensitivity against variation of system parameters. - Abstract: A solar-powered high temperature differential Stirling engine was considered for optimization using multiple criteria. A thermal model was developed so that the output power and thermal efficiency of the solar Stirling system with finite rate of heat transfer, regenerative heat loss, conductive thermal bridging loss, finite regeneration process time and imperfect performance of the dish collector could be obtained. The output power and overall thermal efficiency were considered for simultaneous maximization. Multi-objective evolutionary algorithms (MOEAs) based on the NSGA-II algorithm were employed while the solar absorber temperature and the highest and lowest temperatures of the working fluid were considered the decision variables. The Pareto optimal frontier was obtained and a final optimal solution was also selected using various decision-making methods including the fuzzy Bellman–Zadeh, LINMAP and TOPSIS. It was found that multi-objective optimization could yield results with a relatively low deviation from the ideal solution in comparison to the conventional single objective approach. Furthermore, it was shown that, if the weight of thermal efficiency as one of the objective functions is considered to be greater than weight of the power objective, lower absorber temperature and low temperature ratio should be considered in the design of the Stirling engine

  5. Size matters: Installed maximal unit size predicts market life cycles of electricity generation technologies and systems

    International Nuclear Information System (INIS)

    Li, N.

    2008-01-01

    The electricity generation technologies and systems are complex and change in very dynamic fashions, with a multitude of energy sources and prime movers. Since an important concept in generator design is the 'economies of scale', we discover that the installed maximal unit size (capacity) of the generators is a key 'envelope-pushing' characteristic with logistical behaviors. The logistical wavelet analysis of the max unit sizes for different fuels and prime movers, and the cumulative capacities, reveals universal quantitative features in the aggregate evolution of the power industry. We extract the transition times of the max sizes (spanning 10-90% of the saturation limits) for different technologies and systems, and discover that the max size saturation in the 90-99% range precedes the saturation of cumulative capacities of the corresponding systems in the US. While these universal laws are still empirical, they give us a simple yet elegant framework to examine the evolution of the power industry and markets in predictive, not just descriptive, terms. Such laws give us a quantitative tool to spot trends and predict future development, invaluable in planning and resource allocation based on intrinsic technology and system market life cycles

  6. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

    Science.gov (United States)

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.

  7. Wind Farm Active Power Dispatch for Output Power Maximizing Based on a Wind Turbine Control Strategy for Load Minimizing

    DEFF Research Database (Denmark)

    Zhang, Baohua; Hu, Weihao; Hou, Peng

    2015-01-01

    Inclusion of the wake effect in the wind farm control design (WF) can increase the total captured power by wind turbines (WTs), which is usually implemented by derating upwind WTs. However, derating the WT without a proper control strategy will increase the structural loads, caused by operation...... in stall mode. Therefore, the WT control strategy for derating operation should be considered in the attempt at maximizing the total captured power while reducing structural loads. Moreover, electrical power loss on the transmission system inside a WF is also not negligible for maximizing the total output...... power of the WF. In this paper, an optimal active power dispatch strategy based on a WT derating strategy and considering the transmission loss is proposed for maximizing the total output power. The active power reference of each WT is chosen as the optimization variable. A partial swarm optimizing...

  8. Accounting for complementarity to maximize monitoring power for species management.

    Science.gov (United States)

    Tulloch, Ayesha I T; Chadès, Iadine; Possingham, Hugh P

    2013-10-01

    To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. © 2013 Society for Conservation Biology.

  9. Cooperative wind turbine control for maximizing wind farm power using sequential convex programming

    International Nuclear Information System (INIS)

    Park, Jinkyoo; Law, Kincho H.

    2015-01-01

    Highlights: • The continuous wake model describes well the wake profile behind a wind turbine. • The wind farm power function describes well the power production of a wind farm. • Cooperative control increases the wind farm power efficiency by 7.3% in average. • SCP can be employed to efficiently optimize the control actions of wind turbines. - Abstract: This paper describes the use of a cooperative wind farm control approach to improve the power production of a wind farm. The power production by a downstream wind turbine can decrease significantly due to reduced wind speed caused by the upstream wind turbines, thereby lowering the overall wind farm power production efficiency. In spite of the interactions among the wind turbines, the conventional (greedy) wind turbine control strategy tries to maximize the power of each individual wind turbine by controlling its yaw angle, its blade pitch angle and its generator torque. To maximize the overall wind farm power production while taking the wake interference into account, this study employs a cooperative control strategy. We first derive the wind farm power as a differentiable function of the control actions for the wind turbines in a wind farm. The wind farm power function is then maximized using sequential convex programming (SCP) to determine the optimum coordinated control actions for the wind turbines. Using an example wind farm site and available wind data, we show how the cooperative control strategy improves the power production of the wind farm

  10. Effects of ethnicity on the relationship between vertical jump and maximal power on a cycle ergometer

    Directory of Open Access Journals (Sweden)

    Rouis Majdi

    2016-06-01

    Full Text Available The aim of this study was to verify the impact of ethnicity on the maximal power-vertical jump relationship. Thirty-one healthy males, sixteen Caucasian (age: 26.3 ± 3.5 years; body height: 179.1 ± 5.5 cm; body mass: 78.1 ± 9.8 kg and fifteen Afro-Caribbean (age: 24.4 ±2.6 years; body height: 178.9 ± 5.5 cm; body mass: 77.1 ± 10.3 kg completed three sessions during which vertical jump height and maximal power of lower limbs were measured. The results showed that the values of vertical jump height and maximal power were higher for Afro-Caribbean participants (62.92 ± 6.7 cm and 14.70 ± 1.75 W∙kg-1 than for Caucasian ones (52.92 ± 4.4 cm and 12.75 ± 1.36 W∙kg-1. Moreover, very high reliability indices were obtained on vertical jump (e.g. 0.95 < ICC < 0.98 and maximal power performance (e.g. 0.75 < ICC < 0.97. However, multiple linear regression analysis showed that, for a given value of maximal power, the Afro-Caribbean participants jumped 8 cm higher than the Caucasians. Together, these results confirmed that ethnicity impacted the maximal power-vertical jump relationship over three sessions. In the current context of cultural diversity, the use of vertical jump performance as a predictor of muscular power should be considered with caution when dealing with populations of different ethnic origins.

  11. Maximal power output during incremental exercise by resistance and endurance trained athletes.

    Science.gov (United States)

    Sakthivelavan, D S; Sumathilatha, S

    2010-01-01

    This study was aimed at comparing the maximal power output by resistance trained and endurance trained athletes during incremental exercise. Thirty male athletes who received resistance training (Group I) and thirty male athletes of similar age group who received endurance training (Group II) for a period of more than 1 year were chosen for the study. Physical parameters were measured and exercise stress testing was done on a cycle ergometer with a portable gas analyzing system. The maximal progressive incremental cycle ergometer power output at peak exercise and carbon dioxide production at VO2max were measured. Highly significant (P biofeedback and perk up the athlete's performance.

  12. Coordinated Power Dispatch of a PMSG based Wind Farm for Output Power Maximizing Considering the Wake Effect and Losses

    DEFF Research Database (Denmark)

    Zhang, Baohua; Hu, Weihao; Hou, Peng

    2016-01-01

    The energy loss in a wind farm (WF) caused by wake interaction between wind turbines (WTs) is quite high, which can be reduced by proper active power dispatch. The electrical loss inside a WF by improper active power and reactive power dispatch is also considerable. In this paper, a coordinated...... active power and reactive power dispatch strategy is proposed for a Permanent magnet synchronous generator (PMSG) based WF, in order to maximize the total output power by reducing the wake effect and losses inside the devices of the WF, including the copper loss and iron loss of PMSGs, losses inside...

  13. Maximizing Output Power of a Solar Panel via Combination of Sun Tracking and Maximum Power Point Tracking by Fuzzy Controllers

    Directory of Open Access Journals (Sweden)

    Mohsen Taherbaneh

    2010-01-01

    Full Text Available In applications with low-energy conversion efficiency, maximizing the output power improves the efficiency. The maximum output power of a solar panel depends on the environmental conditions and load profile. In this paper, a method based on simultaneous use of two fuzzy controllers is developed in order to maximize the generated output power of a solar panel in a photovoltaic system: fuzzy-based sun tracking and maximum power point tracking. The sun tracking is performed by changing the solar panel orientation in horizontal and vertical directions by two DC motors properly designed. A DC-DC converter is employed to track the solar panel maximum power point. In addition, the proposed system has the capability of the extraction of solar panel I-V curves. Experimental results present that the proposed fuzzy techniques result in increasing of power delivery from the solar panel, causing a reduction in size, weight, and cost of solar panels in photovoltaic systems.

  14. Using Maximal Isometric Force to Determine the Optimal Load for Measuring Dynamic Muscle Power

    Science.gov (United States)

    Spiering, Barry A.; Lee, Stuart M. C.; Mulavara, Ajitkumar P.; Bentley, Jason R.; Nash, Roxanne E.; Sinka, Joseph; Bloomberg, Jacob J.

    2009-01-01

    Maximal power output occurs when subjects perform ballistic exercises using loads of 30-50% of one-repetition maximum (1-RM). However, performing 1-RM testing prior to power measurement requires considerable time, especially when testing involves multiple exercises. Maximal isometric force (MIF), which requires substantially less time to measure than 1-RM, might be an acceptable alternative for determining the optimal load for power testing. PURPOSE: To determine the optimal load based on MIF for maximizing dynamic power output during leg press and bench press exercises. METHODS: Twenty healthy volunteers (12 men and 8 women; mean +/- SD age: 31+/-6 y; body mass: 72 +/- 15 kg) performed isometric leg press and bench press movements, during which MIF was measured using force plates. Subsequently, subjects performed ballistic leg press and bench press exercises using loads corresponding to 20%, 30%, 40%, 50%, and 60% of MIF presented in randomized order. Maximal instantaneous power was calculated during the ballistic exercise tests using force plates and position transducers. Repeated-measures ANOVA and Fisher LSD post hoc tests were used to determine the load(s) that elicited maximal power output. RESULTS: For the leg press power test, six subjects were unable to be tested at 20% and 30% MIF because these loads were less than the lightest possible load (i.e., the weight of the unloaded leg press sled assembly [31.4 kg]). For the bench press power test, five subjects were unable to be tested at 20% MIF because these loads were less than the weight of the unloaded aluminum bar (i.e., 11.4 kg). Therefore, these loads were excluded from analysis. A trend (p = 0.07) for a main effect of load existed for the leg press exercise, indicating that the 40% MIF load tended to elicit greater power output than the 60% MIF load (effect size = 0.38). A significant (p . 0.05) main effect of load existed for the bench press exercise; post hoc analysis indicated that the effect of

  15. Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

    Science.gov (United States)

    Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

    2016-01-01

    Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

  16. The Measurement of Maximal (Anaerobic Power Output on a Cycle Ergometer: A Critical Review

    Directory of Open Access Journals (Sweden)

    Tarak Driss

    2013-01-01

    Full Text Available The interests and limits of the different methods and protocols of maximal (anaerobic power ( assessment are reviewed: single all-out tests versus force-velocity tests, isokinetic ergometers versus friction-loaded ergometers, measure of during the acceleration phase or at peak velocity. The effects of training, athletic practice, diet and pharmacological substances upon the production of maximal mechanical power are not discussed in this review mainly focused on the technical (ergometer, crank length, toe clips, methodological (protocols and biological factors (muscle volume, muscle fiber type, age, gender, growth, temperature, chronobiology and fatigue limiting in cycling. Although the validity of the Wingate test is questionable, a large part of the review is dedicated to this test which is currently the all-out cycling test the most often used. The biomechanical characteristics specific of maximal and high speed cycling, the bioenergetics of the all-out cycling exercises and the influence of biochemical factors (acidosis and alkalosis, phosphate ions… are recalled at the beginning of the paper. The basic knowledge concerning the consequences of the force-velocity relationship upon power output, the biomechanics of sub-maximal cycling exercises and the study on the force-velocity relationship in cycling by Dickinson in 1928 are presented in Appendices.

  17. Evaluation of the maximized power of a regenerative endoreversible Stirling cycle using the thermodynamic analysis

    International Nuclear Information System (INIS)

    Ahmadi, Mohammad H.; Mohammadi, Amir H.; Dehghani, Saeed

    2013-01-01

    Highlights: • The optimal power of an endoreversible Stirling cycle is investigated. • In the endoreversible cycle, external heat transfer processes are considered irreversible. • Optimal temperature of the heat source leading to a maximum power for the cycle is detained. • Effect of design parameters on the power and its corresponding thermal efficiency is studied. - Abstract: In this communication, the optimal power of an endoreversible Stirling cycle with perfect regeneration is investigated. In the endoreversible cycle, external heat transfer processes are irreversible. Optimal temperature of the heat source leading to a maximum power for the cycle is detained. Moreover, effect of design parameters of the Stirling engine on the maximized power of the engine and its corresponding thermal efficiency is studied

  18. Power Maximization Control of Variable Speed Wind Generation System Using Permanent Magnet Synchronous Generator

    Science.gov (United States)

    Morimoto, Shigeo; Nakamura, Tomohiko; Takeda, Yoji

    This paper proposes the sensorless output power maximization control of the wind generation system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed system. The generator torque is suitably controlled according to the generator speed and thus the power from a wind turbine settles down on the maximum power point by the proposed MPPT control method, where the information of wind velocity is not required. Moreover, the maximum available generated power is obtained by the optimum current vector control. The current vector of PMSG is optimally controlled according to the generator speed and the required torque in order to minimize the losses of PMSG considering the voltage and current constraints. The proposed wind power generation system can be achieved without mechanical sensors such as a wind velocity detector and a position sensor. Several experimental results show the effectiveness of the proposed control method.

  19. Lithium-thionyl chloride battery design concepts for maximized power applications

    Science.gov (United States)

    Kane, P.; Marincic, N.

    The need for primary batteries configured to deliver maximized power has been asserted by many different procuring activities. Battery Engineering Inc. has developed some specific design concepts and mastered some specialized techniques utilized in the production of this type of power source. The batteries have been successfully bench tested during the course of virtually all of these programs, with ultimate success coming in the form of two successful test launches under the USAF Plasma Effects Decoy Program. This paper briefly discusses some of these design concepts and the rationale behind them.

  20. Comparison of Critical Power and W' Derived From 2 or 3 Maximal Tests.

    Science.gov (United States)

    Simpson, Len Parker; Kordi, Mehdi

    2017-07-01

    Typically, accessing the asymptote (critical power; CP) and curvature constant (W') parameters of the hyperbolic power-duration relationship requires multiple constant-power exhaustive-exercise trials spread over several visits. However, more recently single-visit protocols and personal power meters have been used. This study investigated the practicality of using a 2-trial, single-visit protocol in providing reliable CP and W' estimates. Eight trained cyclists underwent 3- and 12-min maximal-exercise trials in a single session to derive (2-trial) CP and W' estimates. On a separate occasion a 5-min trial was performed, providing a 3rd trial to calculate (3-trial) CP and W'. There were no differences in CP (283 ± 66 vs 282 ± 65 W) or W' (18.72 ± 6.21 vs 18.27 ± 6.29 kJ) obtained from either the 2-trial or 3-trial method, respectively. After 2 familiarization sessions (completing a 3- and a 12-min trial on both occasions), both CP and W' remained reliable over additional separate measurements. The current study demonstrates that after 2 familiarization sessions, reliable CP and W' parameters can be obtained from trained cyclists using only 2 maximal-exercise trials. These results offer practitioners a practical, time-efficient solution for incorporating power-duration testing into applied athlete support.

  1. Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

    Science.gov (United States)

    Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

    2017-08-18

    Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

  2. Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

    Science.gov (United States)

    Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

    2017-01-01

    Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

  3. Subwavelength elastic joints connecting torsional waveguides to maximize the power transmission coefficient

    Science.gov (United States)

    Lee, Joong Seok; Lee, Il Kyu; Seung, Hong Min; Lee, Jun Kyu; Kim, Yoon Young

    2017-03-01

    Joints with slowly varying tapered shapes, such as linear or exponential profiles, are known to transmit incident wave power efficiently between two waveguides with dissimilar impedances. This statement is valid only when the considered joint length is longer than the wavelengths of the incident waves. When the joint length is shorter than the wavelengths, however, appropriate shapes of such subwavelength joints for efficient power transmission have not been explored much. In this work, considering one-dimensional torsional wave motion in a cylindrical elastic waveguide system, optimal shapes or radial profiles of a subwavelength joint maximizing the power transmission coefficient are designed by a gradient-based optimization formulation. The joint is divided into a number of thin disk elements using the transfer matrix approach and optimal radii of the disks are determined by iterative shape optimization processes for several single or bands of wavenumbers. Due to the subwavelength constraint, the optimized joint profiles were found to be considerably different from the slowly varying tapered shapes. Specifically, for bands of wavenumbers, peculiar gourd-like shapes were obtained as optimal shapes to maximize the power transmission coefficient. Numerical results from the proposed optimization formulation were also experimentally realized to verify the validity of the present designs.

  4. Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

    DEFF Research Database (Denmark)

    Faria, Pedro; Vale, Zita; Morais, Hugo

    2013-01-01

    based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used...... that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual...... in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system....

  5. Calculation of the optimum fuel distribution which maximizes the power output of a reactor

    International Nuclear Information System (INIS)

    Santos, W.N. dos.

    1979-01-01

    Using optimal control techniques, the optimum fuel distribution - which maximizes the power output of a thermal reactor - is obtained. The nuclear reactor is described by a diffusion theory model with four energy groups and by assuming plane geometry. Since the analytical solution is impracticable, by using a perturbation method, a FORTRAN program was written, in order to obtain the numerical solution. Numerical results, for a thermal reactor light water moderated, non reflected, are shown. The fissile fuel material considered is Uranium-235. (Author) [pt

  6. Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

    Directory of Open Access Journals (Sweden)

    Da Xie

    2016-06-01

    Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

  7. Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller

    Directory of Open Access Journals (Sweden)

    Suresh Chintalapudi Venkata

    2015-09-01

    Full Text Available In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC. This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.

  8. Optimized Power Dispatch in Wind Farms for Power Maximizing Considering Fatigue Loads

    DEFF Research Database (Denmark)

    Zhang, Baohua; N. Soltani, Mohsen; Hu, Weihao

    2018-01-01

    Wake effects in a wind farm (WF) include the wind velocity deficit and added turbulence. The wind velocity deficit may bring significant loss of the wind power and the added turbulence may cause extra fatigue load on the wind turbines (WTs). Inclusion of the wake effects in the wind farm control...... at a series of turbulence intensity, mean wind speed and active power reference to form a lookup table, which is used for the WF control. The proposed strategy is compared with WT MPPT control strategy and WF MPPT control strategy. The simulation results show the effectiveness of the proposed strategy....

  9. Ingestion of High Molecular Weight Carbohydrate Enhances Subsequent Repeated Maximal Power: A Randomized Controlled Trial.

    Directory of Open Access Journals (Sweden)

    Jonathan M Oliver

    Full Text Available Athletes in sports demanding repeat maximal work outputs frequently train concurrently utilizing sequential bouts of intense endurance and resistance training sessions. On a daily basis, maximal work within subsequent bouts may be limited by muscle glycogen availability. Recently, the ingestion of a unique high molecular weight (HMW carbohydrate was found to increase glycogen re-synthesis rate and enhance work output during subsequent endurance exercise, relative to low molecular weight (LMW carbohydrate ingestion. The effect of the HMW carbohydrate, however, on the performance of intense resistance exercise following prolonged-intense endurance training is unknown. Sixteen resistance trained men (23±3 years; 176.7±9.8 cm; 88.2±8.6 kg participated in a double-blind, placebo-controlled, randomized 3-way crossover design comprising a muscle-glycogen depleting cycling exercise followed by ingestion of placebo (PLA, or 1.2 g•kg•bw-1 of LMW or HMW carbohydrate solution (10% with blood sampling for 2-h post-ingestion. Thereafter, participants performed 5 sets of 10 maximal explosive repetitions of back squat (75% of 1RM. Compared to PLA, ingestion of HMW (4.9%, 90%CI 3.8%, 5.9% and LMW (1.9%, 90%CI 0.8%, 3.0% carbohydrate solutions substantially increased power output during resistance exercise, with the 3.1% (90% CI 4.3, 2.0% almost certain additional gain in power after HMW-LMW ingestion attributed to higher movement velocity after force kinematic analysis (HMW-LMW 2.5%, 90%CI 1.4, 3.7%. Both carbohydrate solutions increased post-exercise plasma glucose, glucoregulatory and gut hormones compared to PLA, but differences between carbohydrates were unclear; thus, the underlying mechanism remains to be elucidated. Ingestion of a HMW carbohydrate following prolonged intense endurance exercise provides superior benefits to movement velocity and power output during subsequent repeated maximal explosive resistance exercise. This study was registered

  10. On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting

    DEFF Research Database (Denmark)

    Khalid, Muhammad; Aguilera, Ricardo P.; Savkin, Andrey V.

    2017-01-01

    This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting...... Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity...... of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes...

  11. Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

    International Nuclear Information System (INIS)

    Fujimoto, Kazufumi; Nagai, Hideo; Runggaldier, Wolfgang J.

    2013-01-01

    We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).

  12. Isometric parameters in the monitoring of maximal strength, power, and hypertrophic resistance-training.

    Science.gov (United States)

    Peltonen, Heikki; Walker, Simon; Lähitie, Anuliisa; Häkkinen, Keijo; Avela, Janne

    2018-02-01

    This study monitored strength-training adaptations via isometric parameters throughout 2 × 10 weeks of hypertrophic (HYP I-II) or 10 weeks maximum strength (MS) followed by 10 weeks power (P) training with untrained controls. Trainees performed bilateral isometric leg press tests analyzed for peak force (maximal voluntary contraction (MVC)) and rate of force development (RFD) every 3.5 weeks. These parameters were compared with dynamic performance, voluntary and electrically induced isometric contractions, muscle activity, and cross-sectional area (CSA) in the laboratory before and after 10 and 20 weeks. RFD increased similarly during the first 7 weeks (HYP I, 44% ± 53%; MS, 48% ± 55%, P strength/power training, while MVC cannot distinguish between strength or muscle mass changes. Monitoring RFD provided important information regarding plateaus in RFD improvement, which were observed in dynamic explosive performances after HYP II compared with P.

  13. Maximizing power output from continuous-wave single-frequency fiber amplifiers.

    Science.gov (United States)

    Ward, Benjamin G

    2015-02-15

    This Letter reports on a method of maximizing the power output from highly saturated cladding-pumped continuous-wave single-frequency fiber amplifiers simultaneously, taking into account the stimulated Brillouin scattering and transverse modal instability thresholds. This results in a design figure of merit depending on the fundamental mode overlap with the doping profile, the peak Brillouin gain coefficient, and the peak mode coupling gain coefficient. This figure of merit is then numerically analyzed for three candidate fiber designs including standard, segmented acoustically tailored, and micro-segmented acoustically tailored photonic-crystal fibers. It is found that each of the latter two fibers should enable a 50% higher output power than standard photonic crystal fiber.

  14. Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

    Energy Technology Data Exchange (ETDEWEB)

    Fujimoto, Kazufumi, E-mail: m_fuji@kvj.biglobe.ne.jp [Bank of Tokyo-Mitsubishi UFJ, Ltd., Corporate Risk Management Division (Japan); Nagai, Hideo, E-mail: nagai@sigmath.es.osaka-u.ac.jp [Osaka University, Division of Mathematical Science for Social Systems, Graduate School of Engineering Science (Japan); Runggaldier, Wolfgang J., E-mail: runggal@math.unipd.it [Universita di Padova, Dipartimento di Matematica Pura ed Applicata (Italy)

    2013-02-15

    We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).

  15. Predicting High-Power Performance in Professional Cyclists.

    Science.gov (United States)

    Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

    2017-03-01

    To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

  16. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

    Science.gov (United States)

    Lorenz, Aaron J

    2013-03-01

    Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

  17. Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

    Directory of Open Access Journals (Sweden)

    Roland Stöggl, Erich Müller, Thomas Stöggl

    2017-09-01

    Full Text Available The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs performed roller skiing tests consisting of both shorter (50 m and longer durations (575 m. Test results were correlated with on snow XC skiing performance (PXC based on 3 skating and 3 classical distance competitions (3 to 6 km. The main findings of the current study were: 1 Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2 Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating and PXC were found; 3 Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4 When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent.

  18. Maximal aerobic and anaerobic power generation in large crocodiles versus mammals: implications for dinosaur gigantothermy.

    Science.gov (United States)

    Seymour, Roger S

    2013-01-01

    Inertial homeothermy, the maintenance of a relatively constant body temperature that occurs simply because of large size, is often applied to large dinosaurs. Moreover, biophysical modelling and actual measurements show that large crocodiles can behaviourally achieve body temperatures above 30°C. Therefore it is possible that some dinosaurs could achieve high and stable body temperatures without the high energy cost of typical endotherms. However it is not known whether an ectothermic dinosaur could produce the equivalent amount of muscular power as an endothermic one. To address this question, this study analyses maximal power output from measured aerobic and anaerobic metabolism in burst exercising estuarine crocodiles, Crocodylusporosus, weighing up to 200 kg. These results are compared with similar data from endothermic mammals. A 1 kg crocodile at 30°C produces about 16 watts from aerobic and anaerobic energy sources during the first 10% of exhaustive activity, which is 57% of that expected for a similarly sized mammal. A 200 kg crocodile produces about 400 watts, or only 14% of that for a mammal. Phosphocreatine is a minor energy source, used only in the first seconds of exercise and of similar concentrations in reptiles and mammals. Ectothermic crocodiles lack not only the absolute power for exercise, but also the endurance, that are evident in endothermic mammals. Despite the ability to achieve high and fairly constant body temperatures, therefore, large, ectothermic, crocodile-like dinosaurs would have been competitively inferior to endothermic, mammal-like dinosaurs with high aerobic power. Endothermy in dinosaurs is likely to explain their dominance over mammals in terrestrial ecosystems throughout the Mesozoic.

  19. Maximal aerobic and anaerobic power generation in large crocodiles versus mammals: implications for dinosaur gigantothermy.

    Directory of Open Access Journals (Sweden)

    Roger S Seymour

    Full Text Available Inertial homeothermy, the maintenance of a relatively constant body temperature that occurs simply because of large size, is often applied to large dinosaurs. Moreover, biophysical modelling and actual measurements show that large crocodiles can behaviourally achieve body temperatures above 30°C. Therefore it is possible that some dinosaurs could achieve high and stable body temperatures without the high energy cost of typical endotherms. However it is not known whether an ectothermic dinosaur could produce the equivalent amount of muscular power as an endothermic one. To address this question, this study analyses maximal power output from measured aerobic and anaerobic metabolism in burst exercising estuarine crocodiles, Crocodylusporosus, weighing up to 200 kg. These results are compared with similar data from endothermic mammals. A 1 kg crocodile at 30°C produces about 16 watts from aerobic and anaerobic energy sources during the first 10% of exhaustive activity, which is 57% of that expected for a similarly sized mammal. A 200 kg crocodile produces about 400 watts, or only 14% of that for a mammal. Phosphocreatine is a minor energy source, used only in the first seconds of exercise and of similar concentrations in reptiles and mammals. Ectothermic crocodiles lack not only the absolute power for exercise, but also the endurance, that are evident in endothermic mammals. Despite the ability to achieve high and fairly constant body temperatures, therefore, large, ectothermic, crocodile-like dinosaurs would have been competitively inferior to endothermic, mammal-like dinosaurs with high aerobic power. Endothermy in dinosaurs is likely to explain their dominance over mammals in terrestrial ecosystems throughout the Mesozoic.

  20. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  1. Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition.

    Science.gov (United States)

    Smith, Michael M; Sommer, Allan J; Starkoff, Brooke E; Devor, Steven T

    2013-11-01

    The purpose of this study was to examine the effects of a crossfit-based high-intensity power training (HIPT) program on aerobic fitness and body composition. Healthy subjects of both genders (23 men, 20 women) spanning all levels of aerobic fitness and body composition completed 10 weeks of HIPT consisting of lifts such as the squat, deadlift, clean, snatch, and overhead press performed as quickly as possible. Additionally, this crossfit-based HIPT program included skill work for the improvement of traditional Olympic lifts and selected gymnastic exercises. Body fat percentage was estimated using whole-body plethysmography, and maximal aerobic capacity (VO2max) was measured by analyzing expired gasses during a Bruce protocol maximal graded treadmill test. These variables were measured again after 10 weeks of training and compared for significant changes using a paired t-test. Results showed significant (p < 0.05) improvements of VO2max in men (43.10 ± 1.40 to 48.96 ± 1.42 ml · kg · min) and women (35.98 ± 1.60 to 40.22 ± 1.62 ml · kg · min) and decreased body fat percentage in men (22.2 ± 1.3 to 18.0 ± 1.3) and women (26.6 ± 2.0 to 23.2 ± 2.0). These improvements were significant across all levels of initial fitness. Significant correlations between absolute oxygen consumption and oxygen consumption relative to body weight was found in both men (r = 0.83, p < 0.001) and women (r = 0.94, p < 0.001), indicating that HIPT improved VO2max scaled to body weight independent of changes to body composition. Our data show that HIPT significantly improves VO2max and body composition in subjects of both genders across all levels of fitness.

  2. Power maximization method for land-transportable fully passive lead–bismuth cooled small modular reactor systems

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jaehyun, E-mail: chojh@kaeri.re.kr [Korea Atomic Energy Research Institute, 1405 Daedeok-daero, Yuseong-gu, Daejeon 305-353 (Korea, Republic of); Shin, Yong-Hoon; Hwang, Il Soon [Seoul National University, Sillim-dong, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

    2015-08-15

    Highlights: • The power maximization method for LBE natural circulation cooled SMRs was developed. • The two powers in view of neutronics and thermal-hydraulics were considered. • The limitations for designing of LBE natural circulation cooled SMRs were summarized. • The necessary conditions for safety shutdown in accidents were developed. • The maximized power in the case study is 206 MW thermal. - Abstract: Although current pressurized water reactors (PWRs) have significantly contributed to global energy supply, PWR technology has not been considered a trustworthy energy solution owing to its problems of spent nuclear fuels (SNFs), nuclear safety, and nuclear economy. In order to overcome these problems, a lead–bismuth eutectic (LBE) fully passive cooling small modular reactor (SMR) system is suggested. This technology can not only provide the solution for the problems of SNFs through the transmutation feature of the LBE coolant, but also strengthen safety and economy through the concept of natural circulation cooling SMRs. It is necessary to maximize the advantages, namely safety and economy, of this type of nuclear power plants for broader applications in the future. Accordingly, the objective of this study is to maximize the reactor core power while satisfying the limitations of shipping size, materials endurance, and criticality of a long-burning core as well as safety under beyond design basis events. To achieve these objectives, the design limitations of natural circulating LBE-cooling SMRs are derived. Then, the power maximization method is developed based on obtaining the design limitations. The results of this study are expected to contribute to the effectiveness of the reactor design stage by providing insights to designers, as well as by formulating methods for the power maximization of other types of SMRs.

  3. Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

    Energy Technology Data Exchange (ETDEWEB)

    Morita, Takeshi [Department of Physics, Shizuoka University,836 Ohya, Suruga-ku, Shizuoka 422-8529 (Japan); Department of Physics and Astronomy, University of Kentucky,Lexington, KY 40506 (United States); Shiba, Shotaro [Maskawa Institute for Science and Culture, Kyoto Sangyo University,Kamigamo-Motoyama, Kita-ku, Kyoto 603-8555 (Japan); Wiseman, Toby [Theoretical Physics Group, Blackett Laboratory, Imperial College,Exhibition Road, London SW7 2AZ (United Kingdom); Withers, Benjamin [Mathematical Sciences and STAG Research Centre, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom)

    2015-07-09

    Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic quantities for these strongly coupled phases, but also certain transcendental factors with a geometric origin, and allows one to deduce transitions between the phases. We emphasise it also gives predictions for the behaviour of other observables in these phases.

  4. Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

    International Nuclear Information System (INIS)

    Morita, Takeshi; Shiba, Shotaro; Wiseman, Toby; Withers, Benjamin

    2015-01-01

    Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic quantities for these strongly coupled phases, but also certain transcendental factors with a geometric origin, and allows one to deduce transitions between the phases. We emphasise it also gives predictions for the behaviour of other observables in these phases.

  5. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  6. Test-retest reliability of maximal leg muscle power and functional performance measures in patients with severe osteoarthritis (OA)

    DEFF Research Database (Denmark)

    Villadsen, Allan; Roos, Ewa M.; Overgaard, Søren

    Abstract : Purpose To evaluate the reliability of single-joint and multi-joint maximal leg muscle power and functional performance measures in patients with severe OA. Background Muscle power, taking both strength and velocity into account, is a more functional measure of lower extremity muscle...... and scheduled for unilateral total hip (n=9) or knee (n=11) replacement. Patients underwent a test battery on two occasions separated by approximately one week (range 7 to 11 days). Muscle power was measured using: 1. A linear encoder, unilateral lower limb isolated single-joint dynamic movement, e.g. knee...... flexion 2. A leg extension press, unilateral multi-joint knee and hip extension Functional performance was measured using: 1. 20 m walk usual pace 2. 20 m walk maximal pace 3. 5 times chair stands 4. Maximal number of knee bends/30sec Pain was measured on a VAS prior to and after conducting the entire...

  7. Laboratory- and Field-Based Assessment of Maximal Aerobic Power of Elite Stand-Up Paddle-Board Athletes.

    Science.gov (United States)

    Schram, Ben; Hing, Wayne; Climstein, Mike

    2016-01-01

    Stand-up paddle boarding (SUP) is a rapidly growing sport and recreational activity for which only anecdotal evidence exists on its proposed health, fitness, and injury-rehabilitation benefits. 10 internationally and nationally ranked elite SUP athletes. Participants were assessed for their maximal aerobic power on an ergometer in a laboratory and compared with other water-based athletes. Field-based assessments were subsequently performed using a portable gas-analysis system, and a correlation between the 2 measures was performed. Maximal aerobic power (relative) was significantly higher (P = .037) when measured in the field with a portable gas-analysis system (45.48 ± 6.96 mL · kg(-1) · min(-1)) than with laboratory-based metabolic-cart measurements (43.20 ± 6.67 mL · kg(-1) · min(-1)). There was a strong, positive correlation (r = .907) between laboratory and field maximal aerobic power results. Significantly higher (P = .000) measures of SUP paddling speed were found in the field than with the laboratory ergometer (+42.39%). There were no significant differences in maximal heart rate between the laboratory and field settings (P = .576). The results demonstrate the maximal aerobic power representative of internationally and nationally ranked SUP athletes and show that SUP athletes can be assessed for maximal aerobic power in the laboratory with high correlation to field-based measures. The field-based portable gas-analysis unit has a tendency to consistently measure higher oxygen consumption. Elite SUP athletes display aerobic power outputs similar to those of other upper-limb-dominant elite water-based athletes (surfing, dragon-boat racing, and canoeing).

  8. A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses

    International Nuclear Information System (INIS)

    Aman, M.M.; Jasmon, G.B.; Bakar, A.H.A.; Mokhlis, H.

    2013-01-01

    Highlights: • A new algorithm is proposed for optimum DG placement and sizing.• I 2 R losses minimization and voltage stability maximization is considered in fitness function.• Bus voltage stability and line stability is considered in voltage stability maximization.• Multi-objective PSO is used to solve the problem.• Proposed method is compared with analytical and grid search algorithm. - Abstract: Distributed Generation (DG) placement on the basis of minimization of losses and maximization of system voltage stability are two different approaches, discussed in research. In the new proposed algorithm, a multi-objective approach is used to combine the both approaches together. Minimization of power losses and maximization of voltage stability due to finding weakest voltage bus as well as due to weakest link in the system are considered in the fitness function. Particle Swarm Optimization (PSO) algorithm is used in this paper to solve the multi-objective problem. This paper will also compare the propose method with existing DG placement methods. From results, the proposed method is found more advantageous than the previous work in terms of voltage profile improvement, maximization of system loadability, reduction in power system losses and maximization of bus and line voltage stability. The results are validated on 12-bus, 30-bus, 33-bus and 69-bus radial distribution networks and also discussed in detailed

  9. Maximal heart rate in soccer players: Measured versus age-predicted

    Directory of Open Access Journals (Sweden)

    Pantelis T Nikolaidis

    2015-02-01

    Full Text Available Background: Although maximal heart rate (HR max is widely used to assess exercise intensity in sport training, and particularly in soccer, there are limited data with regards to the use of age-based prediction equations of HR max in soccer players. The aim of this study was to compare the measured-HR max with two prediction equations (Fox-HR max = 220 – age and Tanaka-HR max = 208 – 0.7 × age in soccer players. Methods: Adolescent (n = 162, 15.8 ± 1.5 years and adult players (n = 158, 23.4 ± 4.6 years, all members of competitive clubs, voluntarily performed a graded exercise field test (Conconi protocol to assess HR max . Results: The measured-HR max (197.6 ± 9.4 bpm in total, 200.2 ± 7.9 bpm in adolescent players, and 195.0 ± 10.0 bpm in adult players was explained by the formula HR max = 212.3 – 0.75 × age (r = −0.41, standard error of the estimate = 8.6. In the total sample, Fox-HR max overestimated measured-HR max [mean difference (95% confidence intervals = 2.8 bpm (1.6; 3.9], while Tanaka-HR max underestimated HR max [–3.3 bpm (–4.5; –2.2]. In adolescents, Fox-HR max overestimated measured-HR max [4.0 bpm (2.5; 5.5] and Tanaka-HR max underestimated HR max [– 3.2 bpm (–4.7; –1.8]. In adults, Tanaka-HR max underestimated HR max [–5.0 bpm (–5.3; –4.7], while there was not any difference between Fox-HR max and measured-HR max [1.6 bpm (–3.4; 0.2]. Conclusions: The results of this study failed to validate two widely used prediction equations in a large sample of soccer players, indicating the need for a sport-specific equation. On the other hand, the new equation that we presented should be investigated further by future studies before being adopted by coaches and fitness trainers.

  10. Composable and Predictable Power Management

    NARCIS (Netherlands)

    Nelson, A.T.

    2014-01-01

    The functionality of embedded systems is ever growing. The computational power of embedded systems is growing to match this demand, with embedded multiprocessor systems becoming more common. The limitations of embedded systems are not always related to chip size but are commonly due to energy and/or

  11. Severity scoring in the critically ill: part 2: maximizing value from outcome prediction scoring systems.

    Science.gov (United States)

    Breslow, Michael J; Badawi, Omar

    2012-02-01

    Part 2 of this review of ICU scoring systems examines how scoring system data should be used to assess ICU performance. There often are two different consumers of these data: lCU clinicians and quality leaders who seek to identify opportunities to improve quality of care and operational efficiency, and regulators, payors, and consumers who want to compare performance across facilities. The former need to know how to garner maximal insight into their care practices; this includes understanding how length of stay (LOS) relates to quality, analyzing the behavior of different subpopulations, and following trends over time. Segregating patients into low-, medium-, and high-risk populations is especially helpful, because care issues and outcomes may differ across this severity continuum. Also, LOS behaves paradoxically in high-risk patients (survivors often have longer LOS than nonsurvivors); failure to examine this subgroup separately can penalize ICUs with superior outcomes. Consumers of benchmarking data often focus on a single score, the standardized mortality ratio (SMR). However, simple SMRs are disproportionately affected by outcomes in high-risk patients, and differences in population composition, even when performance is otherwise identical, can result in different SMRs. Future benchmarking must incorporate strategies to adjust for differences in population composition and report performance separately for low-, medium- and high-acuity patients. Moreover, because many ICUs lack the resources to care for high-acuity patients (predicted mortality >50%), decisions about where patients should receive care must consider both ICU performance scores and their capacity to care for different types of patients.

  12. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  13. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  14. Maximizing the use of research reactors in training power reactor operating staff with special reference to US experience

    International Nuclear Information System (INIS)

    Cox, J.A.

    1976-01-01

    Research reactors have been used in training nuclear power plant personnel for many years. Using the experience in the United States of America a programme is proposed that will maximize the training conducted at a research reactor and lessen the time that the staff must spend training elsewhere. The programme is adaptable to future training of replacement staff and for staff retraining. (author)

  15. Maximal loads acting on legs of powered roof support unit in longwalls with bumping hazards

    Institute of Scientific and Technical Information of China (English)

    StanislawSzweda

    2001-01-01

    In the article the results of measurements of the resultant force in the legs of a powered roof support unit, caused by a dynamic interaction bf the rock mass, are discussed. The measurements have been taken in the Iongwalls mined with a roof fall, characterized by the highest degree of bumping hazard. It has been stated that the maximal force in the legs Fro, recorded during a dynamic interaction of the rock mass, is proportional to the initial static force in the legs Fst.p Therefore a need for a careful selection of the initial load of the powered roof support, according to the local mining and geological conditions, results from such a statement. Setting the legs with the supporting load exceeding the indispensable value for keeping the direct roof solids in balance, deteriorating the operational parameters of a Iongwall system also has a disadvantageous influence on the value of the force in the legs and the rate of its increase, caused by a dynamic interaction of the rock mass. A correct selection of the initial load causes a decrease in the intensity of a dynamic interaction of the rock mass on powered roof supports, which also has an advanta igeous influence on their life, Simultaneously with the measurements of the resultant force in the legs, the vertical acceleration of the canopy was also recorded. It has enabled to prove that the external dynamic forces may act on the unit both from the roof as well as from the floor. The changes of the force in the legs caused by dynamic phenomena intrinsically created in the roof and changes of the force in the legs caused by blasting explosives in the roof of the working, have been analyzed separately. It has been stated that an increase in the loads of legs, caused by intrinsic phenomena is significantly higher than a force increase in the legs caused by blasting. It means that powered roof supports, to be operated in the workings, where the bumping hazard occurs, will also transmit the loads acting on a unit

  16. Maximal planar networks with large clustering coefficient and power-law degree distribution

    International Nuclear Information System (INIS)

    Zhou Tao; Yan Gang; Wang Binghong

    2005-01-01

    In this article, we propose a simple rule that generates scale-free networks with very large clustering coefficient and very small average distance. These networks are called random Apollonian networks (RANs) as they can be considered as a variation of Apollonian networks. We obtain the analytic results of power-law exponent γ=3 and clustering coefficient C=(46/3)-36 ln (3/2)≅0.74, which agree with the simulation results very well. We prove that the increasing tendency of average distance of RANs is a little slower than the logarithm of the number of nodes in RANs. Since most real-life networks are both scale-free and small-world networks, RANs may perform well in mimicking the reality. The RANs possess hierarchical structure as C(k)∼k -1 that are in accord with the observations of many real-life networks. In addition, we prove that RANs are maximal planar networks, which are of particular practicability for layout of printed circuits and so on. The percolation and epidemic spreading process are also studied and the comparisons between RANs and Barabasi-Albert (BA) as well as Newman-Watts (NW) networks are shown. We find that, when the network order N (the total number of nodes) is relatively small (as N∼10 4 ), the performance of RANs under intentional attack is not sensitive to N, while that of BA networks is much affected by N. And the diseases spread slower in RANs than BA networks in the early stage of the suseptible-infected process, indicating that the large clustering coefficient may slow the spreading velocity, especially in the outbreaks

  17. Attenuated Increase in Maximal Force of Rat Medial Gastrocnemius Muscle after Concurrent Peak Power and Endurance Training

    Directory of Open Access Journals (Sweden)

    Regula Furrer

    2013-01-01

    Full Text Available Improvement of muscle peak power and oxidative capacity are generally presumed to be mutually exclusive. However, this may not be valid by using fibre type-specific recruitment. Since rat medial gastrocnemius muscle (GM is composed of high and low oxidative compartments which are recruited task specifically, we hypothesised that the adaptive responses to peak power training were unaffected by additional endurance training. Thirty rats were subjected to either no training (control, peak power training (PT, or both peak power and endurance training (PET, which was performed on a treadmill 5 days per week for 6 weeks. Maximal running velocity increased 13.5% throughout the training and was similar in both training groups. Only after PT, GM maximal force was 10% higher than that of the control group. In the low oxidative compartment, mRNA levels of myostatin and MuRF-1 were higher after PT as compared to those of control and PET groups, respectively. Phospho-S6 ribosomal protein levels remained unchanged, suggesting that the elevated myostatin levels after PT did not inhibit mTOR signalling. In conclusion, even by using task-specific recruitment of the compartmentalized rat GM, additional endurance training interfered with the adaptive response of peak power training and attenuated the increase in maximal force after power training.

  18. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

  19. 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...

  20. Simulators predict power plant operation

    Energy Technology Data Exchange (ETDEWEB)

    Peltier, R.

    2002-07-01

    Mix the complexity of a new construction or major retrofit project with today's 'do more with less', a pinch of 'personnel inexperience,' and a dash of 'unintended consequences', and you have got a recipe for insomnia. Advanced simulation tools, however, can help you wring out your design train your operators before the first wire is terminated and just may be get a good night's rest. The article describes several examples of uses of simulation tools. Esscor recently completed a simulation project for a major US utility exploring the potential for furnace/duct implosion that could result from adding higher volumetric flow induced-draft fans and selective catalytic reduction to a 650-MW coal-fired plant. CAF Electronics Inc. provided a full-scope simulator for Alstom's KA24-1 combined-cycle power plant in Paris, France. Computational fluid dynamics (CFD) tools are being used by the Gas Technology Institute to simulate the performance of the next generation of pulverized coal combustors. 5 figs.

  1. Maximal loads acting on legs of powered roof support unit in longwalls with bumping hazards

    Institute of Scientific and Technical Information of China (English)

    Stanislaw Szweda

    2001-01-01

    In the article the results of measurements of the resultant force in th e legs of a powered roof support unit, caused by a dynamic interaction of the ro ck mass, are discussed. The measurements have been taken in the longwalls mined with a roof fall, characterized by the highest degree of bumping hazard. It has been stated that the maximal force in the legs Fm, recorded during a dynam ic interaction of the rock mass, is proportional to the initial static force in the legs Fst,p. Th erefore a need for a careful selection of the initial load of the powered roof s upport, according to the local mining and geological conditions, results from su ch a statement. Setting the legs with the supporting load exceeding the indispen sable value for keeping the direct roof solids in balance, deteriorating the ope rational parameters of a longwall system also has a disadvantageous influence on the value of the force in the legs and the rate of its increase, caused by a dy namic interaction of the rock mass. A correct selection of the initial load caus es a decrease in the intensity of a dynamic interaction of the rock mass on powe red roof supports, which also has an advantageous influence on their life.   Simultaneously with the measurements of the resultant force in the legs, the vertical acceleration of the canopy was also recorded. It has enabled to prove that the exte rnal dynamic forces may act on the unit both from the roof as well as from the f loor. The changes of the force in the legs caused by dynamic phenomena intrinsic ally created in the roof and changes of the force in the legs caused by blasting explosives in the roof of the working, have been analyzed separately. It has been stated that an increase in the loads of legs, caused by intrinsi c phenomena is significantly higher than a force increase in the legs caused by blasting. It means that powered roof supports, to be operated in the workings, w here the bumping hazard occurs, will also transmit the loads

  2. Two-loop controller for maximizing performance of a grid-connected photovoltaic - fuel cell hybrid power plant

    Science.gov (United States)

    Ro, Kyoungsoo

    The study started with the requirement that a photovoltaic (PV) power source should be integrated with other supplementary power sources whether it operates in a stand-alone or grid-connected mode. First, fuel cells for a backup of varying PV power were compared in detail with batteries and were found to have more operational benefits. Next, maximizing performance of a grid-connected PV-fuel cell hybrid system by use of a two-loop controller was discussed. One loop is a neural network controller for maximum power point tracking, which extracts maximum available solar power from PV arrays under varying conditions of insolation, temperature, and system load. A real/reactive power controller (RRPC) is the other loop. The RRPC meets the system's requirement for real and reactive powers by controlling incoming fuel to fuel cell stacks as well as switching control signals to a power conditioning subsystem. The RRPC is able to achieve more versatile control of real/reactive powers than the conventional power sources since the hybrid power plant does not contain any rotating mass. Results of time-domain simulations prove not only effectiveness of the proposed computer models of the two-loop controller, but also their applicability for use in transient stability analysis of the hybrid power plant. Finally, environmental evaluation of the proposed hybrid plant was made in terms of plant's land requirement and lifetime COsb2 emissions, and then compared with that of the conventional fossil-fuel power generating forms.

  3. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans

    DEFF Research Database (Denmark)

    Timmons, James A; Knudsen, Steen; Rankinen, Tuomo

    2010-01-01

    A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial s...

  4. Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization

    Science.gov (United States)

    Qiu, Sihang; Chen, Bin; Wang, Rongxiao; Zhu, Zhengqiu; Wang, Yuan; Qiu, Xiaogang

    2018-04-01

    Hazardous gas leak accident has posed a potential threat to human beings. Predicting atmospheric dispersion and estimating its source become increasingly important in emergency management. Current dispersion prediction and source estimation models cannot satisfy the requirement of emergency management because they are not equipped with high efficiency and accuracy at the same time. In this paper, we develop a fast and accurate dispersion prediction and source estimation method based on artificial neural network (ANN), particle swarm optimization (PSO) and expectation maximization (EM). The novel method uses a large amount of pre-determined scenarios to train the ANN for dispersion prediction, so that the ANN can predict concentration distribution accurately and efficiently. PSO and EM are applied for estimating the source parameters, which can effectively accelerate the process of convergence. The method is verified by the Indianapolis field study with a SF6 release source. The results demonstrate the effectiveness of the method.

  5. Improved techniques for predicting spacecraft power

    International Nuclear Information System (INIS)

    Chmielewski, A.B.

    1987-01-01

    Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance

  6. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-03

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  7. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar; Tom, Nathan

    2017-09-01

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  8. Maximization of revenues for power sales from a solid waste resources recovery facility

    Energy Technology Data Exchange (ETDEWEB)

    1991-12-01

    The report discusses the actual implementation of the best alternative in selling electrical power generated by an existing waste-to-energy facility, the Metro-Dade County Resources Recovery Plant. After the plant processes and extracts various products out of the municipal solid waste, it burns it to produce electrical power. The price for buying power to satisfy the internal needs of our Resources Recovery Facility (RRF) is substantially higher than the power price for selling electricity to any other entity. Therefore, without any further analysis, it was decided to first satisfy those internal needs and then export the excess power. Various alternatives were thoroughly explored as to what to do with the excess power. Selling power to the power utilities or utilizing the power in other facilities were the primary options.

  9. Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.

    Science.gov (United States)

    Guo, Jiin-Huarng; Luh, Wei-Ming

    2009-05-01

    When planning a study, sample size determination is one of the most important tasks facing the researcher. The size will depend on the purpose of the study, the cost limitations, and the nature of the data. By specifying the standard deviation ratio and/or the sample size ratio, the present study considers the problem of heterogeneous variances and non-normality for Yuen's two-group test and develops sample size formulas to minimize the total cost or maximize the power of the test. For a given power, the sample size allocation ratio can be manipulated so that the proposed formulas can minimize the total cost, the total sample size, or the sum of total sample size and total cost. On the other hand, for a given total cost, the optimum sample size allocation ratio can maximize the statistical power of the test. After the sample size is determined, the present simulation applies Yuen's test to the sample generated, and then the procedure is validated in terms of Type I errors and power. Simulation results show that the proposed formulas can control Type I errors and achieve the desired power under the various conditions specified. Finally, the implications for determining sample sizes in experimental studies and future research are discussed.

  10. ATP and phosphocreatine utilization in single human muscle fibres during the development of maximal power output at elevated muscle temperatures.

    Science.gov (United States)

    Gray, Stuart R; Söderlund, Karin; Ferguson, Richard A

    2008-05-01

    In this study, we examined the effect of muscle temperature (Tm) on adenosine triphosphate (ATP) and phosphocreatine utilization in single muscle fibres during the development of maximal power output in humans. Six male participants performed a 6-s maximal sprint on a friction-braked cycle ergometer under both normal (Tm = 34.3 degrees C, s = 0.6) and elevated (T(m) = 37.3 degrees C, s = 0.2) muscle temperature conditions. During the elevated condition, muscle temperature of the legs was raised, passively, by hot water immersion followed by wrapping in electrically heated blankets. Muscle biopsies were taken from the vastus lateralis before and immediately after exercise. Freeze-dried single fibres were dissected, characterized according to myosin heavy chain composition, and analysed for ATP and phosphocreatine content. Single fibres were classified as: type I, IIA, IIAX25 (1 - 25% IIX isoform), IIAX50 (26 - 50% IIX), IIAX75 (51 - 75% IIX), or IIAX100 (76 - 100% IIX). Maximal power output and pedal rate were both greater (P < 0.05) during the elevated condition by 258 W (s = 110) and 22 rev . min(-1) (s = 6), respectively. In both conditions, phosphocreatine content decreased significantly in all fibre types, with a greater decrease during the elevated condition in type IIA fibres (P < 0.01). Adenosine triphosphate content was also reduced to a greater (P < 0.01) extent in type IIA fibres during the elevated condition. The results of the present study indicate that after passive elevation of muscle temperature, there was a greater decrease in ATP and phosphocreatine content in type IIA fibres than in the normal trial, which contributed to the higher maximal power output.

  11. Design and implementation of a low-cost maximization power conversion system for brushless DC generator

    OpenAIRE

    Abolfazl Halvaei Niasar; AmirHossein Sabbaghean

    2017-01-01

    This paper presents a simple and low-cost method to capture maximum power throughput of permanent magnet brushless DC (BLDC) generator. Conventional methods of rectification are based on passive converters, and because the current waveform cannot be controlled as ideal waveform, a highly distorted current is drawn from brushless generator. It leads to lower power factor and reduces the efficiency and power per ampere capability. So, in this study an active six-witch power converter is employe...

  12. Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons.

    Directory of Open Access Journals (Sweden)

    Yasuhiro Tsubo

    Full Text Available The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI, which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.

  13. The wind power prediction research based on mind evolutionary algorithm

    Science.gov (United States)

    Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

    2018-04-01

    When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

  14. Low levels of maximal aerobic power impair the profile of mood state in individuals with temporal lobe epilepsy

    Directory of Open Access Journals (Sweden)

    Rodrigo Luiz Vancini

    2015-01-01

    Full Text Available Objective To investigate the correlation between cardiorespiratory fitness and mood state in individuals with temporal lobe epilepsy (TLE. Method Individuals with TLE (n = 20 and healthy control subjects (C, n = 20 were evaluated. Self-rating questionnaires were used to assess mood (POMS and habitual physical activity (BAECKE. Cardiorespiratory fitness was evaluated by a maximal incremental test. Results People with TLE presented lower cardiorespiratory fitness; higher levels of mood disorders; and lower levels of vigor when compared to control health subjects. A significant negative correlation was observed between the levels of tension-anxiety and maximal aerobic power. Conclusion Low levels of cardiorespiratory fitness may modify the health status of individuals with TLE and it may be considered a risk factor for the development of mood disorders.

  15. Optimization of E-DCH channel power ratios to maximize link level efficiency

    DEFF Research Database (Denmark)

    Zarco, Carlos Ruben Delgado; Malone, Jaime Tito; Wigard, Jeroen

    2006-01-01

    For the WCDMA/HSUPA concept, a key to ensuring high spectral efficiency is to correctly adjust the transmission power ratios among the data and control channels. This paper provides optimal values for the power ratio between the Enhanced-Dedicated Physical Data Channel (E-DPDCH) and the Dedicated...... rate (typical values ranging from 8.1 to 9.9 dB) and the RSN target (maintaining or decreasing their value as the target increases). These results show that it is more link efficient to increase the DPCCH transmission power with the bit rate (and the E-DPDCH's by applying the power ratio) than...... to maintain a constant DPCCH transmission power and just increase the EDPDCH to DPCCH power ratio....

  16. Uncertainties in predicting solar panel power output

    Science.gov (United States)

    Anspaugh, B.

    1974-01-01

    The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.

  17. Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

    Science.gov (United States)

    Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

    2018-02-01

    Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

  18. Maximizing direct current power delivery from bistable vibration energy harvesting beams subjected to realistic base excitations

    Science.gov (United States)

    Dai, Quanqi; Harne, Ryan L.

    2017-04-01

    Effective development of vibration energy harvesters is required to convert ambient kinetic energy into useful electrical energy as power supply for sensors, for example in structural health monitoring applications. Energy harvesting structures exhibiting bistable nonlinearities have previously been shown to generate large alternating current (AC) power when excited so as to undergo snap-through responses between stable equilibria. Yet, most microelectronics in sensors require rectified voltages and hence direct current (DC) power. While researchers have studied DC power generation from bistable energy harvesters subjected to harmonic excitations, there remain important questions as to the promise of such harvester platforms when the excitations are more realistic and include both harmonic and random components. To close this knowledge gap, this research computationally and experimentally studies the DC power delivery from bistable energy harvesters subjected to such realistic excitation combinations as those found in practice. Based on the results, it is found that the ability for bistable energy harvesters to generate peak DC power is significantly reduced by introducing sufficient amount of stochastic excitations into an otherwise harmonic input. On the other hand, the elimination of a low amplitude, coexistent response regime by way of the additive noise promotes power delivery if the device was not originally excited to snap-through. The outcomes of this research indicate the necessity for comprehensive studies about the sensitivities of DC power generation from bistable energy harvester to practical excitation scenarios prior to their optimal deployment in applications.

  19. Estimated maximal and current brain volume predict cognitive ability in old age

    Science.gov (United States)

    Royle, Natalie A.; Booth, Tom; Valdés Hernández, Maria C.; Penke, Lars; Murray, Catherine; Gow, Alan J.; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.

    2013-01-01

    Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. PMID:23850342

  20. Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

    Science.gov (United States)

    Nath, Abhigyan; Subbiah, Karthikeyan

    2015-12-01

    Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance

  1. Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

    Energy Technology Data Exchange (ETDEWEB)

    Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

    2009-07-01

    In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

  2. Design and implementation of a low-cost maximization power conversion system for brushless DC generator

    Directory of Open Access Journals (Sweden)

    Abolfazl Halvaei Niasar

    2017-12-01

    Full Text Available This paper presents a simple and low-cost method to capture maximum power throughput of permanent magnet brushless DC (BLDC generator. Conventional methods of rectification are based on passive converters, and because the current waveform cannot be controlled as ideal waveform, a highly distorted current is drawn from brushless generator. It leads to lower power factor and reduces the efficiency and power per ampere capability. So, in this study an active six-witch power converter is employed and based on the phase back-EMF voltage, an optimum current waveform is generated. The phase currents are controlled inphase to phase voltages and their magnitudes are adjusted to regulate the DC-link voltage. Proposed control theory is verified by simulations for BLDC generator and permanent magnet synchronous generator (PMSG. Moreover, some experimental results are given to demonstrate the theoretical and simulation results.

  3. Proceedings of the Canadian Institute's BC power conference : maximizing opportunities in the evolving electricity sector

    International Nuclear Information System (INIS)

    2004-01-01

    This conference provided a forum for reviewing recent events and activities in British Columbia's electric power industry. Issues regarding energy supply, reliability, power generation, power distribution and power transmission were discussed along with the opportunities and challenges of developing renewable energy sources. Participants at the conference gained insight into strategies for determining the usefulness of an energy plan; assessing the prospects for new generation capacity; examining future whole sale markets; analyzing congestion problems; identifying import and export opportunities; planning for rate design and exploring the future supply on Vancouver Island. The possibilities for meeting the growing demand for electricity through an integrated electrical transmission system throughout the west coast, British Columbia, the Pacific Northwest and Alberta were examined along with financing structures and strategies of renewable energy projects. The role of regulators and their influence on electricity prices were also discussed. Resource planning guidelines were examined as well as other topics such as demand side management, energy conservation, the role of liquefied natural gas in power generation, and land use challenges for power generation. The conference featured 21 presentations, of which 7 have been catalogued separately for inclusion in this database. tabs, figs

  4. Assessment of cardiovascular reflexes is of limited value in predicting maximal +Gz-tolerance

    NARCIS (Netherlands)

    van Lieshout, E. J.; van Lieshout, J. J.; Krol, J.; Simons, M.; Karemaker, J. M.

    1992-01-01

    The importance of +Gz-induced loss of consciousness as a major cause of inflight incapacitation emphasizes the need for predicting +Gz-tolerance and investigating its possible determinants. The cardiovascular changes from +Gz-stress are initially counteracted reflexly by the cardiovascular autonomic

  5. Maximizing the science return of interplanetary missions using nuclear electric power

    International Nuclear Information System (INIS)

    Zubrin, R.M.

    1995-01-01

    The multi-kilowatt power sources on the spaecraft also enables active sensing, including radar, which could be used to do topographic and subsurface studies of clouded bodies such as Titan, ground pentrating sounding of Pluto, the major planet's moons, and planetoids, and topside sounding of the electrically conductive atmospheres of Jupiter, Saturn, Uranus and Neptune to produce profiles of fluid density, conductivity, and horizontal and vertical velocity as a function of depth and global location. Radio science investigations of planetary atmospheres and ring systems would be greatly enhanced by increased transmitter power. The scientific benefits of utilizing such techniques are discussed, and a comparison is made with the quantity and quality of science that a low-powered spacecraft employing RTGs could return. It is concluded that the non-propulsive benefits of nuclear power for spacecraft exploring the outer solar system are enormous, and taken together with the well documented mission enhancements enabled by electric propulsion fully justify the expanditures needed to bring a space qualified nuclear electric power source into being. copyright 1995 American Institute of Physics

  6. Maximizing the transferred power to electric arc furnace for having maximum production

    International Nuclear Information System (INIS)

    Samet, Haidar; Ghanbari, Teymoor; Ghaisari, Jafar

    2014-01-01

    In order to increase production of an EAF (electric arc furnace) by reduction of melting time, one can increase transferred power to the EAF. In other words a certain value of energy can be transferred to the EAF in less time. The transferred power to the EAF reduces when series reactors are utilized in order to have stable arc with desired characteristics. To compensate the reduced transferred power, the secondary voltage of the EAF transformer should be increased by tap changing of the transformer. On the other hand, after any tap changing of the EAF transformer, improved arc stability is degraded. Therefore, the series reactor and EAF transformer tap changing should be simultaneously determined to achieve arc with desired characteristics. In this research, three approaches are proposed to calculate the EAF system parameters, by which the optimal set-points of the different series reactor and EAF transformer taps are determined. The electric characteristics relevant to the EAF for the all transformer and series reactor taps with and without SVC (static VAr compensator) are plotted and based on these graphs the optimal set-points are tabulated. Finally, an economic evaluation is also presented for the methods. - Highlights: • The main goal is to transfer the maximum power to electric arc furnace. • Optimal transformer and series reactor taps are determined. • Arc stability and transferred power to EAF determine the optimal performance. • An economic assessment is done and the number of increased meltings is calculated

  7. Power maximization of a spheric reflected reactor with optimized fuel distribution

    International Nuclear Information System (INIS)

    Reade, Joamar Rodrigues Vincent

    1979-01-01

    The maximum power of a spheric reflected reactor was determined using the theory of optimal control. The control variable employed was the fuel distribution, in accordance to constraints on the power density and on the concentration fuel. It was considered a thermal reactor with a fixed radius. The reactor was fuelled with U-235 and moderated with light water. The nuclear reactor was described by a diffusion theory model. The analytical solution was obtained for both two and four groups of energy and a FORTRAN program was developed to obtain the numerical results. (author)

  8. Feature Selection and ANN Solar Power Prediction

    Directory of Open Access Journals (Sweden)

    Daniel O’Leary

    2017-01-01

    Full Text Available A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers. These new participants in the energy market, prosumers, require new artificial neural network (ANN performance tuning techniques to create accurate ANN forecasts. Input masking, an ANN tuning technique developed for acoustic signal classification and image edge detection, is applied to prosumer solar data to improve prosumer forecast accuracy over traditional macrogrid ANN performance tuning techniques. ANN inputs tailor time-of-day masking based on error clustering in the time domain. Results show an improvement in prediction to target correlation, the R2 value, lowering inaccuracy of sample predictions by 14.4%, with corresponding drops in mean average error of 5.37% and root mean squared error of 6.83%.

  9. Maximal compression of the redshift-space galaxy power spectrum and bispectrum

    Science.gov (United States)

    Gualdi, Davide; Manera, Marc; Joachimi, Benjamin; Lahav, Ofer

    2018-05-01

    We explore two methods of compressing the redshift-space galaxy power spectrum and bispectrum with respect to a chosen set of cosmological parameters. Both methods involve reducing the dimension of the original data vector (e.g. 1000 elements) to the number of cosmological parameters considered (e.g. seven ) using the Karhunen-Loève algorithm. In the first case, we run MCMC sampling on the compressed data vector in order to recover the 1D and 2D posterior distributions. The second option, approximately 2000 times faster, works by orthogonalizing the parameter space through diagonalization of the Fisher information matrix before the compression, obtaining the posterior distributions without the need of MCMC sampling. Using these methods for future spectroscopic redshift surveys like DESI, Euclid, and PFS would drastically reduce the number of simulations needed to compute accurate covariance matrices with minimal loss of constraining power. We consider a redshift bin of a DESI-like experiment. Using the power spectrum combined with the bispectrum as a data vector, both compression methods on average recover the 68 {per cent} credible regions to within 0.7 {per cent} and 2 {per cent} of those resulting from standard MCMC sampling, respectively. These confidence intervals are also smaller than the ones obtained using only the power spectrum by 81 per cent, 80 per cent, and 82 per cent respectively, for the bias parameter b1, the growth rate f, and the scalar amplitude parameter As.

  10. Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

    Science.gov (United States)

    Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

    2017-09-01

    Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

  11. Abusive alcohol consumption among adolescents: a predictive model for maximizing early detection and responses.

    Science.gov (United States)

    de Freitas Ferreira, M; de Moraes, C L; Braga, J U; Reichenheim, M E; da Veiga, G V

    2018-03-17

    To present a predictive model of alcohol abuse among adolescents based on prevalence projections in various population subgroups. Cross-sectional study. The sample consisted of 785 adolescents enrolled in the second year of high school in Rio de Janeiro, Brazil. Alcohol consumption was assessed using the Alcohol Use Disorder Identification Test. Socio-economic, demographic, family, individuals, and school-related variables were examined as potential predictors. The logit model was used to estimate the prevalence projections. Model fitting was examined in relation to the observed data set, and in a subset, that was generated from 200 subsamples of individuals via a bootstrap process using general fit estimators, discrimination, and calibration measures. About 25.5% of the adolescents were classified as positive for alcohol abuse. Being male, being 17-19 years old, not living with mothers, presenting symptoms suggestive of binge eating, having used a strategy of weight reduction in the last 3 months, and, especially, being a victim of family violence were important predictors of abusive consumption of alcohol. While the model's prevalence projection in the absence of these features was 8%, it reaches 68% in the presence of all predictors. Knowledge of predictive characteristics of alcohol abuse is essential for screening, early detection of positive cases, and establishing interventions to reduce consumption among adolescents. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  12. Maximization of ICRF power by SOL density tailoring with local gas injection

    Czech Academy of Sciences Publication Activity Database

    Jacquet, P.; Goniche, M.; Bobkov, V.; Lerche, E.; Pinsker, R.I.; Pitts, R.A.; Zhang, W.; Colas, L.; Hosea, J.; Moriyama, S.; Wang, S.-J.; Wukitch, S.; Zhang, X.; Bilato, R.; Bufferand, H.; Guimarais, L.; Faugel, H.; Hanson, G.R.; Kocan, M.; Monakhov, I.; Noterdaeme, J.-M.; Petržílka, Václav; Shaw, A.; Stepanov, I.; Sips, A.C.C.; Van Eester, D.; Wauters, T.

    2016-01-01

    Roč. 56, č. 4 (2016), s. 046001 ISSN 0029-5515 EU Projects: European Commission(XE) 633053 - EUROfusion Institutional support: RVO:61389021 Keywords : ICRF power * antenna loading * gas injection * SOL density Subject RIV: BL - Plasma and Gas Discharge Physics OBOR OECD: Fluids and plasma physics (including surface physics) Impact factor: 3.307, year: 2016 http://iopscience.iop.org/article/10.1088/0029-5515/56/4/046001

  13. Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

    Energy Technology Data Exchange (ETDEWEB)

    Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

    2017-09-01

    The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.

  14. Utilizing Maximum Power Point Trackers in Parallel to Maximize the Power Output of a Solar (Photovoltaic) Array

    Science.gov (United States)

    2012-12-01

    completing the academic workload at NPS. Taking care of two toddlers all day, every day, is not an easy task. You make xxviii it seem effortless and...for the development of numerous thin-cell applications that meet the military’s requirements for ruggedness and power output. For example, the...2012, September 5). PV microinverters and power optimizers set for significant growth [PV Magazine Online]. Available: http://www.pv- magazine.com

  15. Optimizing Half Squat Postactivation Potential Load in Squat Jump Training for Eliciting Relative Maximal Power in Ski Jumpers.

    Science.gov (United States)

    Gołaś, Artur; Wilk, Michal; Stastny, Petr; Maszczyk, Adam; Pajerska, Katarzyna; Zając, Adam

    2017-11-01

    Gołaś, A, Wilk, M, Stastny, P, Maszczyk, A, Pajerska, K, and Zając, A. Optimizing half squat postactivation potential load in squat jump training for eliciting relative maximal power in ski jumpers. J Strength Cond Res 31(11): 3010-3017, 2017-Training load manipulation in a single workout session can increase or decrease training effectiveness in terms of athletes' strength or power gains. In ski jumping, the complex training that elicits maximal power gains may take advantage of the postactivation potentiation (PAP) mechanism. The aim of this research was to evaluate the changes in rate of force development (RFD), rate of power development (RPD), and jump height during a complex training session consisted of the barbell half squat (Sq) as a conditioning exercise with loads ranged between 60 and 100% of 1 repetition maximum (1RM), followed by a body weight squat jump (SqJ) as a performance task. The study was conducted with 16 elite athletes from the Polish National Ski Jumping Team, age 23 ± 8 years, body mass 56 ± 9 kg, and height 172 ± 12 cm. Complex training session started with the Sq at 60% of 1RM as the conditioning exercise, followed by 3 minutes of rest and the SqJ. The conditioning barbell half Sq was performed with 70, 80, 90, and 100% of 1RM with 5 minutes of rest. The differences in RFD occurred between an SqJ following the application of 80% of 1RM and all other SqJs (p = 0.01), and in RPD between SqJ without conditioning, SqJ after 60% of 1RM and 80% of 1RM (p = 0.02). On average, the most effective load in inducing PAP during ski jumpers' SqJ training is 80% of 1RM. The intensity of the conditioning exercise that elicits the greatest PAP effect should be individualized (60-100% 1RM), as it is dependent on the level of maximal strength.

  16. Least cost addition of power from hydroelectrical developments: Maximizing existing assets

    Energy Technology Data Exchange (ETDEWEB)

    Felix, Lafontant; Briand, Marie-Helene; Veilleux, Rheaume

    2010-09-15

    Hydroelectric developments built in the early 1900's are nearing their useful lifespan and require significant rehabilitation in order to meet modern safety and performance criteria. Also, global increasing energy costs represent a strong incentive for operators to find low-cost, environment-friendly solutions while increasing energy generation at existing facilities. Projects promoting innovative ways of recycling existing developments are great examples of sustainable development and represent win-win solutions for population and hydropower industry alike. The proposed presentation describes successful projects consisting in the rehabilitation or addition of power to existing hydroelectric. These recycling projects are very attractive from both economic and environmental.

  17. Balanced and optimal bianisotropic particles: maximizing power extracted from electromagnetic fields

    International Nuclear Information System (INIS)

    Ra'di, Younes; Tretyakov, Sergei A

    2013-01-01

    Here we introduce the concept of ‘optimal particles’ for strong interactions with electromagnetic fields. We assume that a particle occupies a given electrically small volume in space and study the required optimal relations between the particle polarizabilities. In these optimal particles, the inclusion shape and material are chosen so that the particles extract the maximum possible power from given incident fields. It appears that for different excitation scenarios the optimal particles are bianisotropic chiral, omega, moving and Tellegen particles. The optimal dimensions of resonant canonical chiral and omega particles are found analytically. Such optimal particles have extreme properties in scattering (e.g., zero backscattering or invisibility). Planar arrays of optimal particles possess extreme properties in reflection and transmission (e.g. total absorption or magnetic-wall response), and volumetric composites of optimal particles realize, for example, such extreme materials as the chiral nihility medium. (paper)

  18. Trend analysis of the power law process using Expectation-Maximization algorithm for data censored by inspection intervals

    International Nuclear Information System (INIS)

    Taghipour, Sharareh; Banjevic, Dragan

    2011-01-01

    Trend analysis is a common statistical method used to investigate the operation and changes of a repairable system over time. This method takes historical failure data of a system or a group of similar systems and determines whether the recurrent failures exhibit an increasing or decreasing trend. Most trend analysis methods proposed in the literature assume that the failure times are known, so the failure data is statistically complete; however, in many situations, such as hidden failures, failure times are subject to censoring. In this paper we assume that the failure process of a group of similar independent repairable units follows a non-homogenous Poisson process with a power law intensity function. Moreover, the failure data are subject to left, interval and right censoring. The paper proposes using the likelihood ratio test to check for trends in the failure data. It uses the Expectation-Maximization (EM) algorithm to find the parameters, which maximize the data likelihood in the case of null and alternative hypotheses. A recursive procedure is used to solve the main technical problem of calculating the expected values in the Expectation step. The proposed method is applied to a hospital's maintenance data for trend analysis of the components of a general infusion pump.

  19. Power maximization of an asynchronous wind turbine with a variable speed feeding a centrifugal pump

    International Nuclear Information System (INIS)

    Ouchbel, T.; Zouggar, S.; Elhafyani, M.L.; Seddik, M.; Oukili, M.; Aziz, A.; Kadda, F.Z.

    2014-01-01

    Highlights: • The pumping system studied contain a WT, a SEIG, an IM and a CP. • The system must ensure the water pumping in optimum conditions despite the wind speed. • A steady state study and a practical testing are performed to resolve the control law. • A MPPT is proposed on the basis of static converter SVC. - Abstract: This article focuses on the study of a pumping system compound of a wind turbine, a self-excited induction generator (SEIG), an induction motor (IM), and a centrifugal pump (CP), which aims to ensure the water pumping in optimum conditions regardless the wind speed. As a first step, a study in the steady and dynamic state to determine the control law is examined. As a second step, and so as to achieve a maximum energy flow we have proposed a Maximum Power Point Tracking (MPPT) algorithm based on a static converter SVC. As a final step, experimental and simulation results are discussed to show the reliability of the system proposed

  20. A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm

    Directory of Open Access Journals (Sweden)

    Mahdi M. M. El-Arini

    2013-01-01

    Full Text Available In recent years, the solar energy has become one of the most important alternative sources of electric energy, so it is important to operate photovoltaic (PV panel at the optimal point to obtain the possible maximum efficiency. This paper presents a new optimization approach to maximize the electrical power of a PV panel. The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. First the dummy variables that have effect on the output power are classified into two categories: dependent and independent. The proposed approach is a multistage one as the genetic algorithm, GA, is used to obtain the best initial population at optimal solution and this initial population is fed to Lagrange multiplier algorithm (LM, then a comparison between the two algorithms, GA and LM, is performed. The proposed technique is applied to solar radiation measured at Helwan city at latitude 29.87°, Egypt. The results showed that the proposed technique is applicable.

  1. Modus operandi for maximizing energy efficiency and increasing permeate flux of community scale solar powered reverse osmosis systems

    International Nuclear Information System (INIS)

    Vyas, Harsh; Suthar, Krunal; Chauhan, Mehul; Jani, Ruchita; Bapat, Pratap; Patel, Pankaj; Markam, Bhupendra; Maiti, Subarna

    2015-01-01

    Highlights: • Experimental data on energy efficient photovoltaic powered reverse osmosis system. • Synergetic management of electrical, thermal and hydraulic energies. • Use of reflectors, heat exchanger and turgo turbine. - Abstract: Photovoltaic powered reverse osmosis systems can only be made cost effective if they are made highly energy efficient. In this work we describe a protocol to maximize energy efficiency and increase permeate flux in a fully integrated installation of such a system. The improved system consisted of (i) photovoltaic array fitted with suitably positioned and aligned North–South V-trough reflectors to enhance power output from the array; (ii) direct contact heat exchanger fitted on the rear of the photovoltaic modules for active cooling of the same while safeguarding the terminals from short-circuit and corrosion; (iii) use of reverse osmosis feed water as heat exchange medium while taking due care to limit the temperature rise of feed water; (iv) enhancing permeate flux through the rise in feed water temperature; (v) turgo-turbine for conversion of hydraulic energy in reverse osmosis reject water into mechanical energy to provide part of the energy to replace booster pump utilized in the reverse osmosis unit. The V-trough reflectors onto the photovoltaic modules with thermal energy recovery system brought about an increase in power output of 40% and the synergistic effect of (i)–(iv) gave rise to total permeate volume boost of 59%. Integration of (v) resulted in 56% and 26% saving of electrical power when the reverse osmosis plant was operated by battery bank and direct photovoltaic array respectively

  2. Safety prediction technique for nuclear power plants

    International Nuclear Information System (INIS)

    Henry, C.D. III; Anderson, R.T.

    1985-01-01

    This paper presents a safety prediction technique (SPT) developed by Reliability Technology Associates (RTA) for nuclear power plants. It is based on a technique applied by RTA to assess the flight safety of US Air Force aircraft. The purpose of SPT is to provide a computerized technique for objective measurement of the effect on nuclear plant safety of component failure or procedural, software, or human error. A quantification is determined, called criticality, which is proportional to the probability that a given component or procedural-human action will cause the plant to operate in a hazardous mode. A hazardous mode is characterized by the fact that there has been a failure/error and the plant, its operating crew, and the public are exposed to danger. Whether the event results in an accident, an incident, or merely the exposure to danger is dependent on the skill and reaction of the operating crew as well as external influences. There are three major uses of SPT: (a) to predict unsafe situations so that corrective action can be taken before accidents occur, (b) to quantify the impact of equipment malfunction or procedural, software, or human error on safety and thereby establish priorities for proposed modifications, and (c) to provide a means of evaluating proposed changes for their impact on safety prior to implementation and to provide a method of tracking implemented changes

  3. Low power predictable memory and processing architectures

    OpenAIRE

    Chen, Jiaoyan

    2013-01-01

    Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support mo...

  4. Power load prediction based on GM (1,1)

    Science.gov (United States)

    Wu, Di

    2017-05-01

    Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

  5. Age-Predicted Maximal Heart Rate in Recreational Marathon Runners: A Cross-Sectional Study on Fox's and Tanaka's Equations

    Science.gov (United States)

    Nikolaidis, Pantelis T.; Rosemann, Thomas; Knechtle, Beat

    2018-01-01

    Age-based prediction equations of maximal heart rate (HRmax), such as the popular formulas Fox's 220-age, or Tanaka's 208-0.7 × age, have been widely used in various populations. Surprisingly, so far these equations have not been validated in marathon runners, despite the importance of the role of HRmax for training purposes in endurance running. The aim of the present study was to examine the validity of Fox and Tanaka equations in a large sample of women and men recreational marathon runners. Participants (n = 180, age 43.2 ± 8.5 years, VO2max 46.8 mL/min/kg, finishers in at least one marathon during the last year) performed a graded exercise test on a treadmill, where HRmax was measured. Measured HRmax correlated largely with age in the total sample (r = −0.50, p marathon runners. In addition, exercise physiologists and sport scientists should consider the observed differences among various assessment methods when performing exercise testing or prescribing training program relying on HR. PMID:29599724

  6. Age-Predicted Maximal Heart Rate in Recreational Marathon Runners: A Cross-Sectional Study on Fox's and Tanaka's Equations.

    Science.gov (United States)

    Nikolaidis, Pantelis T; Rosemann, Thomas; Knechtle, Beat

    2018-01-01

    Age-based prediction equations of maximal heart rate (HR max ), such as the popular formulas Fox's 220-age, or Tanaka's 208-0.7 × age, have been widely used in various populations. Surprisingly, so far these equations have not been validated in marathon runners, despite the importance of the role of HR max for training purposes in endurance running. The aim of the present study was to examine the validity of Fox and Tanaka equations in a large sample of women and men recreational marathon runners. Participants ( n = 180, age 43.2 ± 8.5 years, VO 2max 46.8 mL/min/kg, finishers in at least one marathon during the last year) performed a graded exercise test on a treadmill, where HR max was measured. Measured HR max correlated largely with age in the total sample ( r = -0.50, p marathon runners. In addition, exercise physiologists and sport scientists should consider the observed differences among various assessment methods when performing exercise testing or prescribing training program relying on HR.

  7. Mechanisms underlying enhancements in muscle force and power output during maximal cycle ergometer exercise induced by chronic β2-adrenergic stimulation in men

    DEFF Research Database (Denmark)

    Hostrup, Morten; Kalsen, Anders; Onslev, Johan

    2015-01-01

    The study was a randomized placebo-controlled trial investigating mechanisms by which chronic β2-adrenergic stimulation enhances muscle force and power output during maximal cycle ergometer exercise in young men. Eighteen trained men were assigned to an experimental group (oral terbutaline 5 mg∙30...... of muscle proteins involved in growth, ion handling, lactate production and clearance increased (P≤0.05) with the intervention in TER compared to PLA, with no change in oxidative enzymes. Our observations suggest that muscle hypertrophy is the primary mechanism underlying enhancements in muscle force...... and peak power during maximal cycling induced by chronic β2-adrenergic stimulation in humans....

  8. Sludge pipe flow pressure drop prediction using composite power ...

    African Journals Online (AJOL)

    Sludge pipe flow pressure drop prediction using composite power-law friction ... Water SA. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue ... When predicting pressure gradients for the flow of sludges in pipes, the ...

  9. The influence of single whole body cryostimulation treatment on the dynamics and the level of maximal anaerobic power.

    Science.gov (United States)

    Klimek, Andrzej T; Lubkowska, Anna; Szyguła, Zbigniew; Frączek, Barbara; Chudecka, Monika

    2011-06-01

    The objective of this work was to determine the dynamics of maximal anaerobic power (MAP) of the lower limbs, following a single whole body cryostimulation treatment (WBC), in relation to the temperature of thigh muscles. The subjects included 15 men and 15 women with an average age (± SD) of 21.6 ± 1.2 years. To evaluate the level of anaerobic power, the Wingate test was applied. The subjects were submitted to 6 WBC treatments at -130°C once a day. After each session they performed a single Wingate test in the 15, 30, 45, 60, 75 and 90th min after leaving the cryogenic chamber. The order of the test was randomized. All Wingate tests were preceded by an evaluation of thigh surface temperature with the use of a thermovisual camera. The average thigh surface temperature (T(av)) in both men and women dropped significantly after the whole body cryostimulation treatment, and next increased gradually. In women T(av) remained decreased for 75 min, whereas in men it did not return to the basal level until 90th min. A statistically insignificant decrease in MAP was observed in women after WBC. On the contrary, a non-significant increase in MAP was observed in men. The course of changes in MAP following the treatment was similar in both sexes to the changes in thigh surface temperature, with the exception of the period between 15th and 30th min. The shorter time to obtain MAP was observed in women till 90th min and in men till 45 min after WBC compared to the initial level. A single whole body cryostimulation may have a minor influence on short-term physical performance of supramaximal intensity, but it leads to improvement of velocity during the start as evidenced by shorter time required to obtain MAP.

  10. Feature Selection and ANN Solar Power Prediction

    OpenAIRE

    O’Leary, Daniel; Kubby, Joel

    2017-01-01

    A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers). These new participants in the energy market, prosumers, require new artificial neural...

  11. Power Admission Control with Predictive Thermal Management in Smart Buildings

    DEFF Research Database (Denmark)

    Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

    2015-01-01

    This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...

  12. Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women.

    Science.gov (United States)

    Wright, Glenn A; Pustina, Andrew A; Mikat, Richard P; Kernozek, Thomas W

    2012-03-01

    The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PP(est)) for each load and for each prediction equation were compared with criterion PP values from a force plate (PP(FP)). The PP(est) values had high test-retest reliability and were strongly correlated to PP(FP) in both men and women at all relative loads. However, only the Harman equation accurately predicted PP(FP) at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

  13. Development and design of photovoltaic power prediction system

    Science.gov (United States)

    Wang, Zhijia; Zhou, Hai; Cheng, Xu

    2018-02-01

    In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

  14. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  15. Effect of formoterol, a long-acting β2-adrenergic agonist, on muscle strength and power output, metabolism and fatigue during maximal sprinting in men

    DEFF Research Database (Denmark)

    Kalsen, Anders; Hostrup, Morten; Backer, Vibeke

    2016-01-01

    The aim was to investigate the effect of the long-acting β2-adrenergic agonist formoterol on muscle strength and power output, muscle metabolism and phosphorylation of CaMKII Thr(287) and FXYD1 during maximal sprinting. In a double-blind crossover study, thirteen males (VO2max: 45.0±0.2 (mean±SE) m......L min(-1) kg(-1)) performed a 30-s cycle ergometer sprint after inhalation of either 54 µg formoterol (FOR) or placebo (PLA). Before and after the sprint, muscle biopsies were collected from vastus lateralis and maximal voluntary contraction (MVC) and contractile properties of quadriceps were measured...

  16. Age-Predicted Maximal Heart Rate in Recreational Marathon Runners: A Cross-Sectional Study on Fox's and Tanaka's Equations

    Directory of Open Access Journals (Sweden)

    Pantelis T. Nikolaidis

    2018-03-01

    Full Text Available Age-based prediction equations of maximal heart rate (HRmax, such as the popular formulas Fox's 220-age, or Tanaka's 208-0.7 × age, have been widely used in various populations. Surprisingly, so far these equations have not been validated in marathon runners, despite the importance of the role of HRmax for training purposes in endurance running. The aim of the present study was to examine the validity of Fox and Tanaka equations in a large sample of women and men recreational marathon runners. Participants (n = 180, age 43.2 ± 8.5 years, VO2max 46.8 mL/min/kg, finishers in at least one marathon during the last year performed a graded exercise test on a treadmill, where HRmax was measured. Measured HRmax correlated largely with age in the total sample (r = −0.50, p < 0.001, women (r = −0.60, p < 0.001 and men (r = −0.53, p < 0.001. In women, a large main effect of method on HRmax (p = 0.001, η2 = 0.294 was shown with measured HRmax lower than Fox-HRmax (−4.8 bpm; −8.4, −1.3 and Tanaka-HRmax (−4.9 bpm; −8.1, −1.8. In men, a moderate effect of assessment method on HRmax was found (p = 0.001, η2 = 0.066 with measured HRmax higher than Fox-HRmax (+2.8; 1.0, 4.6, Tanaka-HRmax higher than Fox-HRmax (+1.2; 0.7, 1.7. Based on these findings, it was concluded that Fox and Tanaka' formulas overestimated HRmax by ~5 bpm in women, whereas Fox underestimated HRmax in men by ~3 bpm. Thus, we recommend the further use of Tanaka's formula in men marathon runners. In addition, exercise physiologists and sport scientists should consider the observed differences among various assessment methods when performing exercise testing or prescribing training program relying on HR.

  17. Entropy maximization

    Indian Academy of Sciences (India)

    Abstract. It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf f that satisfy. ∫ fhi dμ = λi for i = 1, 2,...,...k the maximizer of entropy is an f0 that is pro- portional to exp(. ∑ ci hi ) for some choice of ci . An extension of this to a continuum of.

  18. Entropy Maximization

    Indian Academy of Sciences (India)

    It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf that satisfy ∫ f h i d = i for i = 1 , 2 , … , … k the maximizer of entropy is an f 0 that is proportional to exp ⁡ ( ∑ c i h i ) for some choice of c i . An extension of this to a continuum of ...

  19. Automatic determination of pressurized water reactor core loading patterns which maximize end-of-cycle reactivity within power peaking and burnup constraints

    International Nuclear Information System (INIS)

    Hobson, G.H.

    1985-01-01

    An automated procedure for determining the optimal core loading pattern for a pressurized water reactor which maximizes end-of-cycle k/sub eff/ while satisfying constraints on power peaking and discharge burnup has been developed. The optimization algorithm combines a two energy group, two-dimensional coarse-mesh finite difference diffusion theory neutronics model to simulate core conditions, a perturbation theory approach to determine reactivity, flux, power and burnup changes as a function of assembly shuffling, and Monte Carlo integer programming to select the optimal loading pattern solution. The core examined was a typical Cycle 2 reload with no burnable poisons. Results indicate that the core loading pattern that maximizes end-of-cycle k/sub eff/ results in a 5.4% decrease in fuel cycle costs compared with the core loading pattern that minimizes the maximum relative radial power peak

  20. Forced vital capacity and not central chemoreflex predicts maximal hyperoxic breath-hold duration in elite apneists.

    Science.gov (United States)

    Bain, Anthony R; Barak, Otto F; Hoiland, Ryan L; Drvis, Ivan; Bailey, Damian M; Dujic, Zeljko; Mijacika, Tanja; Santoro, Antoinette; DeMasi, Daniel K; MacLeod, David B; Ainslie, Philip N

    2017-08-01

    The determining mechanisms of a maximal hyperoxic apnea duration in elite apneists have remained unexplored. We tested the hypothesis that maximal hyperoxic apnea duration in elite apneists is related to forced vital capacity (FVC) but not the central chemoreflex (for CO 2 ). Eleven elite apneists performed a maximal dry static-apnea with prior hyperoxic (100% oxygen) pre-breathing, and a central chemoreflex test via a hyperoxic re-breathing technique (hyperoxic-hypercapnic ventilatory response: HCVR); expressed as the increase in ventilation (pneumotachometry) per increase in arterial CO 2 tension (PaCO 2 ; radial artery). FVC was assessed using standard spirometry. Maximal apnea duration ranged from 807 to 1262s (mean=1034s). Average HCVR was 2.0±1.2Lmin -1 mmHg -1 PaCO 2 . The hyperoxic apnea duration was related to the FVC (r 2 =0.45, p0.05). These findings were interpreted to suggest that during a hyperoxic apnea, a larger initial lung volume prolongs the time before reaching intolerable discomfort associated with pending lung squeeze, while CO 2 sensitivity has little impact. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Comparison of the sensitivities of the Buehler test and the guinea pig maximization test for predictive testing of contact allergy

    DEFF Research Database (Denmark)

    Frankild, S; Vølund, A; Wahlberg, J E

    2001-01-01

    International test guidelines, such as the Organisation for Economic Cooperation and Development (OECD) guideline #406, recommend 2 guinea pig methods for testing of the contact allergenic potential of chemicals: the Guinea Pig Maximization Test (GPMT) and the Buehler test. Previous comparisons...

  2. Magnetic storm effects in electric power systems and prediction needs

    Science.gov (United States)

    Albertson, V. D.; Kappenman, J. G.

    1979-01-01

    Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

  3. Automatic determination of pressurized water reactor core loading patterns that maximize beginning-of-cycle reactivity within power-peaking and burnup constraints

    International Nuclear Information System (INIS)

    Hobson, G.H.; Turinsky, P.J.

    1986-01-01

    Computational capability has been developed to automatically determine a good estimate of the core loading pattern, which minimizes fuel cycle costs for a pressurized water reactor (PWR). Equating fuel cycle cost minimization with core reactivity maximization, the objective is to determine the loading pattern that maximizes core reactivity while satisfying power peaking, discharge burnup, and other constraints. The method utilizes a two-dimensional, coarse-mesh, finite difference scheme to evaluate core reactivity and fluxes for an initial reference loading pattern. First-order perturbation theory is applied to determine the effects of assembly shuffling on reactivity, power distribution, end-of-cycle burnup. Monte Carlo integer programming is then used to determine a near-optimal loading pattern within a range of loading patterns near the reference pattern. The process then repeats with the new loading pattern as the reference loading pattern and terminates when no better loading pattern can be determined. The process was applied with both reactivity maximization and radial power-peaking minimization as objectives. Results on a typical large PWR indicate that the cost of obtaining an 8% improvement in radial power-peaking margin is ≅2% in fuel cycle costs, for the reload core loaded without burnable poisons that was studied

  4. Skeletal muscle ATP turnover and muscle fiber conduction velocity are elevated at higher muscle temperatures during maximal power output development in humans.

    Science.gov (United States)

    Gray, Stuart R; De Vito, Giuseppe; Nimmo, Myra A; Farina, Dario; Ferguson, Richard A

    2006-02-01

    The effect of temperature on skeletal muscle ATP turnover and muscle fiber conduction velocity (MFCV) was studied during maximal power output development in humans. Eight male subjects performed a 6-s maximal sprint on a mechanically braked cycle ergometer under conditions of normal (N) and elevated muscle temperature (ET). Muscle temperature was passively elevated through the combination of hot water immersion and electric blankets. Anaerobic ATP turnover was calculated from analysis of muscle biopsies obtained before and immediately after exercise. MFCV was measured during exercise using surface electromyography. Preexercise muscle temperature was 34.2 degrees C (SD 0.6) in N and 37.5 degrees C (SD 0.6) in ET. During ET, the rate of ATP turnover for phosphocreatine utilization [temperature coefficient (Q10) = 3.8], glycolysis (Q10 = 1.7), and total anaerobic ATP turnover [Q10 = 2.7; 10.8 (SD 1.9) vs. 14.6 mmol x kg(-1) (dry mass) x s(-1) (SD 2.3)] were greater than during N (P < 0.05). MFCV was also greater in ET than in N [3.79 (SD 0.47) to 5.55 m/s (SD 0.72)]. Maximal power output (Q10 = 2.2) and pedal rate (Q10 = 1.6) were greater in ET compared with N (P < 0.05). The Q10 of maximal and mean power were correlated (P < 0.05; R = 0.82 and 0.85, respectively) with the percentage of myosin heavy chain type IIA. The greater power output obtained with passive heating was achieved through an elevated rate of anaerobic ATP turnover and MFCV, possibly due to a greater effect of temperature on power production of fibers, with a predominance of myosin heavy chain IIA at the contraction frequencies reached.

  5. Maximizers versus satisficers

    Directory of Open Access Journals (Sweden)

    Andrew M. Parker

    2007-12-01

    Full Text Available Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007. Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002, we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Contrary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures of other decision-making styles, decision-making competence, and demographic variables.

  6. Power Load Prediction Based on Fractal Theory

    OpenAIRE

    Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song

    2015-01-01

    The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...

  7. VT Predicted Mean Wind Power - 50 meter height

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

  8. Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

    Energy Technology Data Exchange (ETDEWEB)

    Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng; Pota, Hemanshu; Gadh, Rajit

    2016-05-02

    This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.

  9. WPPT, a tool for on-line wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

    2004-07-01

    This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

  10. Prediction of Wind Energy Resources (PoWER) Users Guide

    Science.gov (United States)

    2016-01-01

    ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...manufacturer’s or trade names does not constitute an official endorsement or approval of the use thereof. Destroy this report when it is no longer needed. Do...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER

  11. Evaluation of peak power prediction equations in male basketball players.

    Science.gov (United States)

    Duncan, Michael J; Lyons, Mark; Nevill, Alan M

    2008-07-01

    This study compared peak power estimated using 4 commonly used regression equations with actual peak power derived from force platform data in a group of adolescent basketball players. Twenty-five elite junior male basketball players (age, 16.5 +/- 0.5 years; mass, 74.2 +/- 11.8 kg; height, 181.8 +/- 8.1 cm) volunteered to participate in the study. Actual peak power was determined using a countermovement vertical jump on a force platform. Estimated peak power was determined using countermovement jump height and body mass. All 4 prediction equations were significantly related to actual peak power (all p jump prediction equations, 12% for the Canavan and Vescovi equation, and 6% for the Sayers countermovement jump equation. In all cases peak power was underestimated.

  12. Wind Power Plant Prediction by Using Neural Networks: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.

    2012-08-01

    This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.

  13. Hybrid robust predictive optimization method of power system dispatch

    Science.gov (United States)

    Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

    2011-08-02

    A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

  14. Skill forecasting from ensemble predictions of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

    2009-01-01

    Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

  15. Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

    Science.gov (United States)

    Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

    2007-08-01

    Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

  16. Operational results from a physical power prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L [Risoe National Lab., Meteorology and Wind Energy Dept., Roskilde (Denmark)

    1999-03-01

    This paper will describe a prediction system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual implementation of the system will be described and the robustness demonstrated. (au) 11 refs.

  17. Local Geomagnetic Indices and the Prediction of Auroral Power

    Science.gov (United States)

    Newell, P. T.; Gjerloev, J. W.

    2014-12-01

    As the number of magnetometer stations and data processing power increases, just how auroral power relates to geomagnetic observations becomes a quantitatively more tractable question. This paper compares Polar UVI auroral power observations during 1997 with a variety of geomagnetic indices. Local time (LT) versions of the SuperMAG auroral electojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East-West component, BE, is investigated. We also consider whether using any of the local indices is actually better at predicting local auroral power than a single global index. Each index is separated into 24 LT indices based on a sliding 3-h MLT window. The ability to predict - or better reconstruct - auroral power varies greatly with LT, peaking at 1900 MLT, where about 75% of the variance (r2) can be predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT - 0400 MLT, roughly the region in which substorms occur. Auroral power is poorly predicted from auroral electrojet indices from 0500 MLT - 1500 MLT, with the minima at 1000-1300 MLT. In the region of high predictability, the local variable which works best is BE, in contrast to long-standing expectations. However using global SME is better than any local variable. Auroral power is best predicted by combining global SME with a local index: BE from 1500-0200 MLT, and either SMU or SML from 0300-1400 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500-0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.

  18. Integrated Solid Oxide Fuel Cell Power System Characteristics Prediction

    Directory of Open Access Journals (Sweden)

    Marian GAICEANU

    2009-07-01

    Full Text Available The main objective of this paper is to deduce the specific characteristics of the CHP 100kWe Solid Oxide Fuel Cell (SOFC Power System from the steady state experimental data. From the experimental data, the authors have been developed and validated the steady state mathematical model. From the control room the steady state experimental data of the SOFC power conditioning are available and using the developed steady state mathematical model, the authors have been obtained the characteristic curves of the system performed by Siemens-Westinghouse Power Corporation. As a methodology the backward and forward power flow analysis has been employed. The backward power flow makes possible to obtain the SOFC power system operating point at different load levels, resulting as the load characteristic. By knowing the fuel cell output characteristic, the forward power flow analysis is used to predict the power system efficiency in different operating points, to choose the adequate control decision in order to obtain the high efficiency operation of the SOFC power system at different load levels. The CHP 100kWe power system is located at Gas Turbine Technologies Company (a Siemens Subsidiary, TurboCare brand in Turin, Italy. The work was carried out through the Energia da Ossidi Solidi (EOS Project. The SOFC stack delivers constant power permanently in order to supply the electric and thermal power both to the TurboCare Company and to the national grid.

  19. Prediction of lacking control power in power plants using statistical models

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Mataji, B.; Stoustrup, Jakob

    2007-01-01

    Prediction of the performance of plants like power plants is of interest, since the plant operator can use these predictions to optimize the plant production. In this paper the focus is addressed on a special case where a combination of high coal moisture content and a high load limits the possible...... plant load, meaning that the requested plant load cannot be met. The available models are in this case uncertain. Instead statistical methods are used to predict upper and lower uncertainty bounds on the prediction. Two different methods are used. The first relies on statistics of recent prediction...... errors; the second uses operating point depending statistics of prediction errors. Using these methods on the previous mentioned case, it can be concluded that the second method can be used to predict the power plant performance, while the first method has problems predicting the uncertain performance...

  20. 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...

  1. Testing the predictive power of nuclear mass models

    International Nuclear Information System (INIS)

    Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

    2008-01-01

    A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

  2. Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

    Science.gov (United States)

    Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

    2017-05-01

    The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

  3. Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

    Directory of Open Access Journals (Sweden)

    Akça Firat

    2014-07-01

    Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

  4. Influence of the Sampling Rate and Noise Characteristics on Prediction of the Maximal Safe Laser Exposure in Human Skin Using Pulsed Photothermal Radiometry

    Science.gov (United States)

    Vidovič, L.; Milanič, M.; Majaron, B.

    2013-09-01

    Pulsed photothermal radiometry (PPTR) allows for noninvasive determination of the laser-induced temperature depth profile in strongly scattering samples, including human skin. In a recent experimental study, we have demonstrated that such information can be used to derive rather accurate predictions of the maximal safe radiant exposure on an individual patient basis. This has important implications for efficacy and safety of several laser applications in dermatology and aesthetic surgery, which are often compromised by risk of adverse side effects (e.g., scarring, and dyspigmentation) resulting from nonselective absorption of strong laser light in epidermal melanin. In this study, the differences between the individual maximal safe radiant exposure values as predicted from PPTR temperature depth profiling performed using a commercial mid-IR thermal camera (as used to acquire the original patient data) and our customized PPTR setup are analyzed. To this end, the latter has been used to acquire 17 PPTR records from three healthy volunteers, using 1 ms laser irradiation at 532 nm and a signal sampling rate of 20 000 . The laser-induced temperature profiles are reconstructed first from the intact PPTR signals, and then by binning the data to imitate the lower sampling rate of the IR camera (1000 fps). Using either the initial temperature profile in a dedicated numerical model of heat transfer or protein denaturation dynamics, the predicted levels of epidermal thermal damage and the corresponding are compared. A similar analysis is performed also with regard to the differences between noise characteristics of the two PPTR setups.

  5. Phasic dopamine as a prediction error of intrinsic and extrinsic reinforcements driving both action acquisition and reward maximization: a simulated robotic study.

    Science.gov (United States)

    Mirolli, Marco; Santucci, Vieri G; Baldassarre, Gianluca

    2013-03-01

    An important issue of recent neuroscientific research is to understand the functional role of the phasic release of dopamine in the striatum, and in particular its relation to reinforcement learning. The literature is split between two alternative hypotheses: one considers phasic dopamine as a reward prediction error similar to the computational TD-error, whose function is to guide an animal to maximize future rewards; the other holds that phasic dopamine is a sensory prediction error signal that lets the animal discover and acquire novel actions. In this paper we propose an original hypothesis that integrates these two contrasting positions: according to our view phasic dopamine represents a TD-like reinforcement prediction error learning signal determined by both unexpected changes in the environment (temporary, intrinsic reinforcements) and biological rewards (permanent, extrinsic reinforcements). Accordingly, dopamine plays the functional role of driving both the discovery and acquisition of novel actions and the maximization of future rewards. To validate our hypothesis we perform a series of experiments with a simulated robotic system that has to learn different skills in order to get rewards. We compare different versions of the system in which we vary the composition of the learning signal. The results show that only the system reinforced by both extrinsic and intrinsic reinforcements is able to reach high performance in sufficiently complex conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Predicting Harmonic Distortion of Multiple Converters in a Power System

    Directory of Open Access Journals (Sweden)

    P. M. Ivry

    2017-01-01

    Full Text Available Various uncertainties arise in the operation and management of power systems containing Renewable Energy Sources (RES that affect the systems power quality. These uncertainties may arise due to system parameter changes or design parameter choice. In this work, the impact of uncertainties on the prediction of harmonics in a power system containing multiple Voltage Source Converters (VSCs is investigated. The study focuses on the prediction of harmonic distortion level in multiple VSCs when some system or design parameters are only known within certain constraints. The Univariate Dimension Reduction (UDR method was utilized in this study as an efficient predictive tool for the level of harmonic distortion of the VSCs measured at the Point of Common Coupling (PCC to the grid. Two case studies were considered and the UDR technique was also experimentally validated. The obtained results were compared with that of the Monte Carlo Simulation (MCS results.

  7. On the universality of power laws for tokamak plasma predictions

    Science.gov (United States)

    Garcia, J.; Cambon, D.; Contributors, JET

    2018-02-01

    Significant deviations from well established power laws for the thermal energy confinement time, obtained from extensive databases analysis as the IPB98(y,2), have been recently reported in dedicated power scans. In order to illuminate the adequacy, validity and universality of power laws as tools for predicting plasma performance, a simplified analysis has been carried out in the framework of a minimal modeling for heat transport which is, however, able to account for the interplay between turbulence and collinear effects with the input power known to play a role in experiments with significant deviations from such power laws. Whereas at low powers, the usual scaling laws are recovered with little influence of other plasma parameters, resulting in a robust power low exponent, at high power it is shown how the exponents obtained are extremely sensitive to the heating deposition, the q-profile or even the sampling or the number of points considered due to highly non-linear behavior of the heat transport. In particular circumstances, even a minimum of the thermal energy confinement time with the input power can be obtained, which means that the approach of the energy confinement time as a power law might be intrinsically invalid. Therefore plasma predictions with a power law approximation with a constant exponent obtained from a regression of a broad range of powers and other plasma parameters which can non-linearly affect and suppress heat transport, can lead to misleading results suggesting that this approach should be taken cautiously and its results continuously compared with modeling which can properly capture the underline physics, as gyrokinetic simulations.

  8. Estimation of peak oxygen uptake from maximal power output among 9-10 year-old children in Lhasa, Tibet

    DEFF Research Database (Denmark)

    Bianba, B; Berntsen, S; Andersen, Lars Bo

    2010-01-01

    with the equations from the present study. None of the three could accurately predict the direct measured V.O2peak, and predictions differed in an unsystematic manner, including over- or underestimation and no differentiation between genders. CONCLUSION: Peak oxygen uptake could be estimated from Wmax and sex...

  9. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  10. Using machine learning to predict wind turbine power output

    International Nuclear Information System (INIS)

    Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P

    2013-01-01

    Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site. (letter)

  11. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  12. Prediction of power-ramp defects in CANDU fuel

    International Nuclear Information System (INIS)

    Gillespie, P.; Wadsworth, S.; Daniels, T.

    2010-01-01

    Power ramps result in fuel pellet expansion and can lead to fuel sheath failures by fission product induced stress corrosion cracking (SCC). Historically, empirical models fit to experimental test data were used to predict the onset of power-ramp failures in CANDU fuel. In 1988, a power-ramped fuel defect event at PNGS-1 led to the refinement of these empirical models. This defect event has recently been re-analyzed and the empirical model updated. The empirical model is supported by a physically based model which can be used to extrapolate to fuel conditions (density, burnup) outside of the 1988 data set. (author)

  13. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2013-01-01

    The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination....... The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates...

  14. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  15. Predictive Smart Grid Control with Exact Aggregated Power Constraints

    DEFF Research Database (Denmark)

    Trangbæk, K; Petersen, Mette Højgaard; Bendtsen, Jan Dimon

    2012-01-01

    of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The load variations on the grid arise on one hand from varying......This chapter deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high-level MPC controller, a second level of so-called aggregators,which reduces the computational and communication related load on the high-level control, and a lower level...... consumption, and on the other hand from natural variations in power production from e.g. wind turbines. The consumers represent energy-consuming units such as heat pumps, car batteries etc. These units obviously have limits on how much power and energy they can consume at any given time, which impose...

  16. When Power Shapes Interpersonal Behavior: Low Relationship Power Predicts Men’s Aggressive Responses to Low Situational Power

    Science.gov (United States)

    Overall, Nickola C.; Hammond, Matthew D.; McNulty, James K.; Finkel, Eli J.

    2016-01-01

    When does power in intimate relationships shape important interpersonal behaviors, such as psychological aggression? Five studies tested whether possessing low relationship power was associated with aggressive responses, but (1) only within power-relevant relationship interactions when situational power was low, and (2) only by men because masculinity (but not femininity) involves the possession and demonstration of power. In Studies 1 and 2, men lower in relationship power exhibited greater aggressive communication during couples’ observed conflict discussions, but only when they experienced low situational power because they were unable to influence their partner. In Study 3, men lower in relationship power reported greater daily aggressive responses toward their partner, but only on days when they experienced low situational power because they were either (a) unable to influence their partner or (b) dependent on their partner for support. In Study 4, men who possessed lower relationship power exhibited greater aggressive responses during couples’ support-relevant discussions, but only when they had low situational power because they needed high levels of support. Study 5 provided evidence for the theoretical mechanism underlying men’s aggressive responses to low relationship power. Men who possessed lower relationship power felt less manly on days they faced low situational power because their partner was unwilling to change to resolve relationship problems, which in turn predicted greater aggressive responses to their partner. These results demonstrate that fully understanding when and why power is associated with interpersonal behavior requires differentiating between relationship and situational power. PMID:27442766

  17. Model output statistics applied to wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

    1999-03-01

    Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

  18. Skill forecasting from different wind power ensemble prediction methods

    International Nuclear Information System (INIS)

    Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

    2007-01-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

  19. Electrical predictive maintenance at Trillo I Nuclear Power Plant

    International Nuclear Information System (INIS)

    Vicente, L. R.; Fernandez de la Mata, R.; Cano Gonzalez, J. C.

    1998-01-01

    An electrical predictive maintenance plan is currently being put into effect at Trillo I Nuclear Power Plant which is initially being applied to three types of equipment: motors, transformers and motor-driven valves. This paper describes the different phases considered in the implementation of the Predictive Maintenance Plan: study of existing techniques for such equipment (tangoδ, spectral analysis of stator current, chromatographic analysis of gases, spectral analysis of the axial stray magnetic flux, etc), study of the special characteristics of the electrical equipment at Trillo NPP, analysis of applicable techniques (characteristic parameters, alert-alarm values, experience with such techniques, etc), analysis of machine history records, study of the optimum preventive-predictive case, study of applicable frequencies and definition of the computerised predictive maintenance management tool. With the exception of the computerised predictive maintenance management applications which are presently being implemented, all the activities described above have been carried out on the three types of equipment mentioned. (Author)

  20. Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

    2013-01-01

    A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...

  1. Prediction of future dispute concerning nuclear power generation

    International Nuclear Information System (INIS)

    1981-04-01

    This investigation is the third research on the public acceptance of nuclear power generation by the National Congress on Social Economics. In this study, how the energy dispute including that concerning nuclear power generation will develop in 1980s and 1990s, how the form of dispute and the point of controversy will change, were predicted. Though the maintenance of the concord of groups strongly regulates the behavior of people, recently they have become to exercise individual rights frequently. The transition to the society of dispute is the natural result of the modernization of society and the increase of richness. The proper prediction of social problems and the planning and execution of proper countermeasures are very important. The background, objective, basic viewpoint, range and procedure of this investigation, the change of social dispute, the history of the dispute concerning nuclear power generation, the basic viewpoint in the prediction of the dispute concerning nuclear power generation, the social situation in 1980s, the prediction and avoidance of the dispute in view of social and energy situations, and the fundamental strategy for seeking a clue to the solution in 1980s and 1990s are described. The establishment of neutral mediation organs and the flexible technologies of nuclear reactors are necessary. (Kako, I.)

  2. Model predictive control for Z-source power converter

    DEFF Research Database (Denmark)

    Mo, W.; Loh, P.C.; Blaabjerg, Frede

    2011-01-01

    This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...

  3. Changes in Maximal Strength, Velocity, and Power After 8 Weeks of Training With Pneumatic or Free Weight Resistance.

    Science.gov (United States)

    Frost, David M; Bronson, Stefanie; Cronin, John B; Newton, Robert U

    2016-04-01

    Because free weight (FW) and pneumatic (PN) resistance are characterized by different inertial properties, training with either resistance could afford unique strength, velocity, and power adaptations. Eighteen resistance-trained men completed baseline tests to determine their FW and PN bench press 1 repetition maximum (1RM). During the FW session, 4 explosive repetitions were performed at loads of 15, 30, 45, 60, 75, and 90% 1RM to assess force, velocity, and power. Participants were then assigned to a FW or PN training group, which involved three 90-minute sessions per week for 8 weeks. Both intervention groups completed identical periodized programs with the exception of the resistance used to perform all bench press movements. Free weight participants significantly increased their FW and PN 1RM (10.4 and 9.4%), and maximum (any load) force (9.8%), velocity (11.6%), and power (22.5%). Pneumatic-trained participants also exhibited increases in FW and PN 1RM (11.6 and 17.5%), and maximum force (8.4%), velocity (13.6%), and power (33.4%). Both interventions improved peak barbell velocity at loads of 15 and 30% 1RM; however, only the PN-trained individuals displayed improvements in peak force and power at these same loads. Training with PN resistance may offer advantages if attempting to improve power at lighter relative loads by affording an opportunity to consistently achieve higher accelerations and velocities (F = ma), in comparison with FW. Exploiting the inertial properties of the resistance, whether mass, elastic or PN, could afford an opportunity to develop mixed-method training strategies and/or elicit unique neuromuscular adaptations to suit the specific needs of athletes from sports characterized by varying demands.

  4. Predictive power of the grace score in population with diabetes.

    Science.gov (United States)

    Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

    2017-12-01

    Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  5. Predictive Maintenance: One key to improved power plant availability

    International Nuclear Information System (INIS)

    Mobley; Allen, J.W.

    1986-01-01

    Recent developments in microprocessor technology has provided the ability to routinely monitor the actual mechanical condition of all rotating and reciprocating machinery and process variables (i.e. pressure, temperature, flow, etc.) of other process equipment within an operating electric power generating plant. This direct correlation between frequency domain vibration and actual mechanical condition of machinery and trending process variables of non-rotating equipment can provide the ''key'' to improving the availability and reliability, thermal efficiency and provide the baseline information necessary for developing a realistic plan for extending the useful life of power plants. The premise of utilizing microprocessor-based Predictive Maintenance to improve power plant operation has been proven by a number of utilities. This paper provides a comprehensive discussion of the TEC approach to Predictive Maintenance and examples of successful programs

  6. Maximal aerobic power in cycle ergometry in middle-aged men and women, active in sports, in relation to age and physical activity.

    Science.gov (United States)

    Bovens, A M; van Baak, M A; Vrencken, J G; Wijnen, J A; Saris, W H; Verstappen, F T

    1993-02-01

    Reliable standards of maximal power output in middle-aged and physically active men and women are desirable in sports-medical practice. For this purpose maximal cycle ergometer tests were evaluated in 2038 men and 898 women over 40 years of age (46.8 +/- 6.1 years (mean +/- SD) and 47.5 +/- 6.6 years), who volunteered in a sports-medical check-up and all of whom were active in sports for at least three months in the year preceding the screening (4.3 +/- 3.1 hours/week respectively 3.6 +/- 2.5 hours/week). The range of maximal values for power output (Wmax), heart rate (HRmax), systolic blood pressure (SBPmax) and peak plasma lactate concentrations (PPLa) during progressive cycle ergometer testing are presented for males and females who were divided into groups with a 5-years age difference. Wmax varied with sex (male = 1, female = 0), age (year) and height (cm); Wmax = 65.3 x (sex) + 2.0 x (height) -1.9 x (age) - 67.9 (See = 38.2; r = 0.76). The weighing of different factors that influence performance was also studied by multiple regression analysis to provide improved precision in standards used to interpret exercise tests. In both men and women about half of the variation of Wmax could be explained by the independent variables age, body mass, body fat, smoking habits, vital capacity, heart rate, and physical activity parameters. It is concluded that active involvement in endurance sports and/or the use of the bicycle for transport, contributed substantially to cardiovascular fitness in healthy, middle-aged men and women.

  7. Attenuated increase in maximal force of rat medial gastrocnemius muscle after concurrent peak power and endurance training

    NARCIS (Netherlands)

    Furrer, R.; Jaspers, R.T.; Baggerman, H.L.; Bravenboer, N.; Lips, P.; de Haan, A.

    2013-01-01

    Improvement of muscle peak power and oxidative capacity are generally presumed to be mutually exclusive. However, this may not be valid by using fibre type-specific recruitment. Since rat medial gastrocnemius muscle (GM) is composed of high and low oxidative compartments which are recruited task

  8. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  9. Effect of accuracy of wind power prediction on power system operator

    Science.gov (United States)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-01-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  10. Maximizing Power Output in Homogeneous Charge Compression Ignition (HCCI) Engines and Enabling Effective Control of Combustion Timing

    Science.gov (United States)

    Saxena, Samveg

    Homogeneous Charge Compression Ignition (HCCI) engines are one of the most promising engine technologies for the future of energy conversion from clean, efficient combustion. HCCI engines allow high efficiency and lower CO2 emission through the use of high compression ratios and the removal of intake throttle valves (like Diesel), and allow very low levels of urban pollutants like nitric oxide and soot (like Otto). These engines, however, are not without their challenges, such as low power density compared with other engine technologies, and a difficulty in controlling combustion timing. This dissertation first addresses the power output limits. The particular strategies for enabling high power output investigated in this dissertation focus on avoiding five critical limits that either damage an engine, drastically reduce efficiency, or drastically increase emissions: (1) ringing limits, (2) peak in-cylinder pressure limits, (3) misfire limits, (4) low intake temperature limits, and (5) excessive emissions limits. The research shows that the key factors that enable high power output, sufficient for passenger vehicles, while simultaneously avoiding the five limits defined above are the use of: (1) high intake air pressures allowing improved power output, (2) highly delayed combustion timing to avoid ringing limits, and (3) using the highest possible equivalence ratio before encountering ringing limits. These results are revealed by conducting extensive experiments spanning a wide range of operating conditions on a multi-cylinder HCCI engine. Second, this dissertation discusses strategies for effectively sensing combustion characteristics on a HCCI engine. For effective feedback control of HCCI combustion timing, a sensor is required to quantify when combustion occurs. Many laboratory engines use in-cylinder pressure sensors but these sensors are currently prohibitively expensive for wide-scale commercialization. Instead, ion sensors made from inexpensive sparkplugs

  11. Using meteorological forecasts in on-line predictions of wind power

    DEFF Research Database (Denmark)

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

    1999-01-01

    This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...

  12. Influence of directionality and maximal power output on speech understanding with bone anchored hearing implants in single sided deafness

    OpenAIRE

    Krempaska, Silvia; Koval, Juraj; Schmid, Christoph; Pfiffner, Flurin; Kurz, Anja; Kompis, Martin

    2014-01-01

    Bone-anchored hearing implants (BAHI) are routinely used to alleviate the effects of the acoustic head shadow in single-sided sensorineural deafness (SSD). In this study, the influence of the directional microphone setting and the maximum power output of the BAHI sound processor on speech understanding in noise in a laboratory setting were investigated. Eight adult BAHI users with SSD participated in this pilot study. Speech understanding in noise was measured using a new Slovak speech-in-noi...

  13. Empirical Information Metrics for Prediction Power and Experiment Planning

    Directory of Open Access Journals (Sweden)

    Christopher Lee

    2011-01-01

    Full Text Available In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target, independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning.    

  14. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  15. Analysis of the maximal possible grid relief from PV-peak-power impacts by using storage systems for increased self-consumption

    International Nuclear Information System (INIS)

    Moshövel, Janina; Kairies, Kai-Philipp; Magnor, Dirk; Leuthold, Matthias; Bost, Mark; Gährs, Swantje; Szczechowicz, Eva; Cramer, Moritz; Sauer, Dirk Uwe

    2015-01-01

    Highlights: • Presentation of a MATLAB battery storage model. • Development of a controlled persistence forecast management strategy. • Perfect forecast in comparison to an easy feasible persistence forecast. • More grid relief with forecast than with strategies to maximize self-consumption. - Abstract: For future energy supply systems the effects and benefits of battery storage systems in households with photovoltaic (PV) generators and the effects on distribution and transmission grids need to be identified and analyzed. The development of grid relieving management strategies for the storage system in due consideration of self-consumption is a necessary step forward in order to analyze the potential of private home battery storage systems to reduce stress on the power supply system. A MATLAB-based model of a lithium-ion storage system has been developed. The model is applicable for a wide range of PV generator sizes, different battery storage systems and diverse management strategies. In order to identify the potential of grid relieving forecast strategies, without discharging the storage into the grid, a management strategy based on persistence forecasts of solar radiation and household load demand has been implemented and analyzed. To minimize forecast uncertainties a proportional plus integral controller has been developed. The persistence forecast management strategy is applicable in real-life PV-battery-systems and due to the simple forecast it is easy to equip existing systems with such a management system with only low effort. As a result it will be shown that a storage system management based on forecasts has a significantly higher potential to relieve the grid than a system that only maximizes self-consumption as it is usually used nowadays. Besides, such a management strategy is able to unload the grid more than a static power reduction to 70% of the nominal power rating according to the current German Renewable Energy Sources Act (EEG). At the

  16. Applying model predictive control to power system frequency control

    OpenAIRE

    Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

    2013-01-01

    16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

  17. Pre-stimulus thalamic theta power predicts human memory formation.

    Science.gov (United States)

    Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

    2016-09-01

    Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  19. 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)

  20. 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)

  1. Predicting Output Power for Nearshore Wave Energy Harvesting

    Directory of Open Access Journals (Sweden)

    Henock Mamo Deberneh

    2018-04-01

    Full Text Available Energy harvested from a Wave Energy Converter (WEC varies greatly with the location of its installation. Determining an optimal location that can result in maximum output power is therefore critical. In this paper, we present a novel approach to predicting the output power of a nearshore WEC by characterizing ocean waves using floating buoys. We monitored the movement of the buoys using an Arduino-based data collection module, including a gyro-accelerometer sensor and a wireless transceiver. The collected data were utilized to train and test prediction models. The models were developed using machine learning algorithms: SVM, RF and ANN. The results of the experiments showed that measurements from the data collection module can yield a reliable predictor of output power. Furthermore, we found that the predictors work better when the regressors are combined with a classifier. The accuracy of the proposed prediction model suggests that it could be extremely useful in both locating optimal placement for wave energy harvesting plants and designing the shape of the buoys used by them.

  2. Prediction of Chiller Power Consumption: An Entropy Generation Approach

    KAUST Repository

    Saththasivam, Jayaprakash

    2016-06-21

    Irreversibilities in each component of vapor compression chillers contribute to additional power consumption in chillers. In this study, chiller power consumption was predicted by computing the Carnot reversible work and entropy generated in every component of the chiller. Thermodynamic properties namely enthalpy and entropy of the entire refrigerant cycle were obtained by measuring the pressure and temperature at the inlet and outlet of each primary component of a 15kW R22 water cooled scroll chiller. Entropy generation of each component was then calculated using the First and Second Laws of Thermodynamics. Good correlation was found between the measured and computed chiller power consumption. This irreversibility analysis can be also effectively used as a performance monitoring tool in vapor compression chillers as higher entropy generation is anticipated during faulty operations.

  3. Predicting the emissive power of hydrocarbon pool fires

    International Nuclear Information System (INIS)

    Munoz, Miguel; Planas, Eulalia; Ferrero, Fabio; Casal, Joaquim

    2007-01-01

    The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6 m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E lum , E soot and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction

  4. COSMIC EMULATION: FAST PREDICTIONS FOR THE GALAXY POWER SPECTRUM

    Energy Technology Data Exchange (ETDEWEB)

    Kwan, Juliana; Heitmann, Katrin; Habib, Salman; Frontiere, Nicholas; Pope, Adrian [High Energy Physics Division, Argonne National Laboratory, Lemont, IL 60439 (United States); Padmanabhan, Nikhil [Department of Physics, Yale University, 260 Whitney Ave., New Haven, CT 06520 (United States); Lawrence, Earl [Statistical Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Finkel, Hal [Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, IL 60439 (United States)

    2015-09-01

    The halo occupation distribution (HOD) approach has proven to be an effective method for modeling galaxy clustering and bias. In this approach, galaxies of a given type are probabilistically assigned to individual halos in N-body simulations. In this paper, we present a fast emulator for predicting the fully nonlinear galaxy–galaxy auto and galaxy–dark matter cross power spectrum and correlation function over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large ΛCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ∼1% in the auto correlations and ∼2% in the cross correlations from z = 1 to z = 0, over the considered parameter range. We use the emulator to investigate the accuracy of various analytic prescriptions for the galaxy power spectrum, parametric dependencies in the HOD model, and the behavior of galaxy bias as a function of HOD parameters. Additionally, we obtain fully nonlinear predictions for tangential shear correlations induced by galaxy–galaxy lensing from our galaxy–dark matter cross power spectrum emulator. All emulation products are publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.

  5. Proceedings of the Canadian Institute's Power On conference : the latest strategies to maximize opportunities in Ontario's electricity sector

    International Nuclear Information System (INIS)

    2004-01-01

    This conference provided a forum for reviewing strategies for Ontario's electricity sector with particular reference to electricity sector reform strategies and coal phase-out commitments. A supply adequacy outlook in terms of projected demand growth and generation mix and capacity was presented by the Independent Market Operator (IMO) along with issues concerning rising energy costs in various jurisdictions. Consumer adaptation to new pricing structures was discussed as well as generation investment needs to the year 2020. Government policies and commitments in the electricity sector were reviewed, as well as issues related to emissions and the impacts of air pollution. Renewable energy portfolios were also discussed along with issues concerning infrastructure adequacy. Imports of power and the expansion of transmission capabilities between Ontario and surrounding jurisdictions were reviewed and various opportunities from Manitoba were explored. Other topics of discussion included issues concerning pricing mechanisms; cost recovery; the development of effective buying strategies; and electricity purchasing for large energy consumers. The conference featured 23 presentations, of which 8 have been catalogued separately for inclusion in this database. tabs., figs

  6. Synapse:neural network for predict power consumption: users guide

    Energy Technology Data Exchange (ETDEWEB)

    Muller, C; Mangeas, M; Perrot, N

    1994-08-01

    SYNAPSE is forecasting tool designed to predict power consumption in metropolitan France on the half hour time scale. Some characteristics distinguish this forecasting model from those which already exist. In particular, it is composed of numerous neural networks. The idea for using many neural networks arises from past tests. These tests showed us that a single neural network is not able to solve the problem correctly. From this result, we decided to perform unsupervised classification of the 24 consumption curves. From this classification, six classes appeared, linked with the weekdays: Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, Sundays, holidays and bridge days. For each class and for each half hour, two multilayer perceptrons are built. The two of them forecast the power for one particular half hour, and for a day including one of the determined class. The input of these two network are different: the first one (short time forecasting) includes the powers for the most recent half hour and relative power of the previous day; the second (medium time forecasting) includes only the relative power of the previous day. A process connects the results of every networks and allows one to forecast more than one half-hour in advance. In this process, short time forecasting networks and medium time forecasting networks are used differently. The first kind of neural networks gives good results on the scale of one day. The second one gives good forecasts for the next predicted powers. In this note, the organization of the SYNAPSE program is detailed, and the user`s menu is described. This first version of synapse works and should allow the APC group to evaluate its utility. (authors). 6 refs., 2 appends.

  7. Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

    Science.gov (United States)

    Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

    2004-09-01

    Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

  8. Social group utility maximization

    CERN Document Server

    Gong, Xiaowen; Yang, Lei; Zhang, Junshan

    2014-01-01

    This SpringerBrief explains how to leverage mobile users' social relationships to improve the interactions of mobile devices in mobile networks. It develops a social group utility maximization (SGUM) framework that captures diverse social ties of mobile users and diverse physical coupling of mobile devices. Key topics include random access control, power control, spectrum access, and location privacy.This brief also investigates SGUM-based power control game and random access control game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the critical SGUM-b

  9. The effects of elevated levels of sodium bicarbonate (NaHCO₃) on the acute power output and time to fatigue of maximally stimulated mouse soleus and EDL muscles.

    Science.gov (United States)

    Higgins, M F; Tallis, J; Price, M J; James, R S

    2013-05-01

    This study examined the effects of elevated buffer capacity [~32 mM HCO₃(-)] through administration of sodium bicarbonate (NaHCO₃) on maximally stimulated isolated mouse soleus (SOL) and extensor digitorum longus (EDL) muscles undergoing cyclical length changes at 37 °C. The elevated buffering capacity was of an equivalent level to that achieved in humans with acute oral supplementation. We evaluated the acute effects of elevated [HCO₃(-)] on (1) maximal acute power output (PO) and (2) time to fatigue to 60 % of maximum control PO (TLIM60), the level of decline in muscle PO observed in humans undertaking similar exercise, using the work loop technique. Acute PO was on average 7.0 ± 4.8 % greater for NaHCO₃-treated EDL muscles (P < 0.001; ES = 2.0) and 3.6 ± 1.8 % greater for NaHCO₃-treated SOL muscles (P < 0.001; ES = 2.3) compared to CON. Increases in PO were likely due to greater force production throughout shortening. The acute effects of NaHCO₃ on EDL were significantly greater (P < 0.001; ES = 0.9) than on SOL. Treatment of EDL (P = 0.22; ES = 0.6) and SOL (P = 0.19; ES = 0.9) with NaHCO₃ did not alter the pattern of fatigue. Although significant differences were not observed in whole group data, the fatigability of muscle performance was variable, suggesting that there might be inter-individual differences in response to NaHCO₃ supplementation. These results present the best indication to date that NaHCO₃ has direct peripheral effects on mammalian skeletal muscle resulting in increased acute power output.

  10. Predicting Power Outages Using Multi-Model Ensemble Forecasts

    Science.gov (United States)

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

    2017-12-01

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

  11. Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

    Science.gov (United States)

    Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

    2017-10-12

    This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

  12. On the impact of NWP model resolution and power source disaggregation on photovoltaic power prediction

    Czech Academy of Sciences Publication Activity Database

    Eben, Kryštof; Juruš, Pavel; Resler, Jaroslav; Pelikán, Emil; Krč, Pavel

    2011-01-01

    Roč. 8, - (2011), EMS2011-667-4 [EMS Annual Meeting /11./ and European Conference on Applications of Meteorology /10./. 12.09.2011-16.09.2011, Berlin] Institutional research plan: CEZ:AV0Z10300504 Keywords : photovoltaic power prediction * NWP * numerical model parameterization Subject RIV: DG - Athmosphere Sciences, Meteorology

  13. The Effects of a Maximal Power Training Cycle on the Strength, Maximum Power, Vertical Jump Height and Acceleration of High-Level 400-Meter Hurdlers

    Science.gov (United States)

    Balsalobre-Fernández, Carlos; Tejero-González, Carlos Mª; del Campo-Vecino, Juan; Alonso-Curiel, Dionisio

    2013-01-01

    The aim of this study was to determine the effects of a power training cycle on maximum strength, maximum power, vertical jump height and acceleration in seven high-level 400-meter hurdlers subjected to a specific training program twice a week for 10 weeks. Each training session consisted of five sets of eight jump-squats with the load at which each athlete produced his maximum power. The repetition maximum in the half squat position (RM), maximum power in the jump-squat (W), a squat jump (SJ), countermovement jump (CSJ), and a 30-meter sprint from a standing position were measured before and after the training program using an accelerometer, an infra-red platform and photo-cells. The results indicated the following statistically significant improvements: a 7.9% increase in RM (Z=−2.03, p=0.021, δc=0.39), a 2.3% improvement in SJ (Z=−1.69, p=0.045, δc=0.29), a 1.43% decrease in the 30-meter sprint (Z=−1.70, p=0.044, δc=0.12), and, where maximum power was produced, a change in the RM percentage from 56 to 62% (Z=−1.75, p=0.039, δc=0.54). As such, it can be concluded that strength training with a maximum power load is an effective means of increasing strength and acceleration in high-level hurdlers. PMID:23717361

  14. Model Predictive Voltage Control of Wind Power Plants

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei

    2018-01-01

    the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

  15. Power flow prediction in vibrating systems via model reduction

    Science.gov (United States)

    Li, Xianhui

    This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

  16. A mathematical look at a physical power prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations, and to give guidelines as to where the simplifications can be made and where they can not. This paper shows that there is a linear dependence between the geostrophic wind and the wind at the surface, but also that great care must be taken in the selection of the models since physical dependencies play a very important role, e.g. through the dependence of the turning of the wind on the wind speed.

  17. A mathematical look at a physical power prediction model

    DEFF Research Database (Denmark)

    Landberg, L.

    1998-01-01

    This article takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations and to give guidelines as to where simplifications can be made and where they cannot....... The article shows that there is a linear dependence between the geostrophic wind and the local wind at the surface, but also that great care must be taken in the selection of the simple mathematical models, since physical dependences play a very important role, e.g. through the dependence of the turning...

  18. Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

    DEFF Research Database (Denmark)

    Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller

    2018-01-01

    Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how...... the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how...

  19. Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

    Directory of Open Access Journals (Sweden)

    Anders Hedegaard Hansen

    2018-03-01

    Full Text Available Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how the inclusion of a loss model may increase the energy output. Based on the presented results it is concluded that power extraction algorithms based on model predictive control principles are both feasible and favorable for use in a discrete fluid power power take-off system for point absorber wave energy converters.

  20. Epileptic seizure prediction based on a bivariate spectral power methodology.

    Science.gov (United States)

    Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

    2012-01-01

    The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

  1. Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

    Science.gov (United States)

    Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

    2009-12-01

    Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

  2. Bayesian calibration of power plant models for accurate performance prediction

    International Nuclear Information System (INIS)

    Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

    2014-01-01

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  3. Characterizing and predicting the robustness of power-law networks

    International Nuclear Information System (INIS)

    LaRocca, Sarah; Guikema, Seth D.

    2015-01-01

    Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2000 randomly-generated power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing networks such as the Internet and cellular metabolic pathways, and efficiently degrading networks such as terrorist cells. - Highlights: • Examine relationship between network topology and robustness to failures. • Relationship is statistically significant for scale-free networks. • Use statistical models to estimate robustness to failures for real-world networks

  4. Method for Prediction of the Power Output from Photovoltaic Power Plant under Actual Operating Conditions

    Science.gov (United States)

    Obukhov, S. G.; Plotnikov, I. A.; Surzhikova, O. A.; Savkin, K. D.

    2017-04-01

    Solar photovoltaic technology is one of the most rapidly growing renewable sources of electricity that has practical application in various fields of human activity due to its high availability, huge potential and environmental compatibility. The original simulation model of the photovoltaic power plant has been developed to simulate and investigate the plant operating modes under actual operating conditions. The proposed model considers the impact of the external climatic factors on the solar panel energy characteristics that improves accuracy in the power output prediction. The data obtained through the photovoltaic power plant operation simulation enable a well-reasoned choice of the required capacity for storage devices and determination of the rational algorithms to control the energy complex.

  5. Maximal power training induced different improvement in throwing velocity and muscle strength according to playing positions in elite male handball players.

    Science.gov (United States)

    Cherif, M; Chtourou, H; Souissi, N; Aouidet, A; Chamari, K

    2016-12-01

    This study was designed to assess the effect of strength and power training on throwing velocity and muscle strength in handball players according to their playing positions. Twenty-two male handball players were assigned to either an experimental group (n=11) or a control group (n=11) (age: 22.1 ± 3.0 years). They were asked to complete (i) the ball throwing velocity test and (ii) the one-repetition maximum (1-RM) tests for the half-back squat, the pull-over, the bench press, the developed neck, and the print exercises before and after 12 weeks of maximal power training. The training was designed to improve strength and power with an intensity of 85-95% of the 1RM. In addition to their usual routine handball training sessions, participants performed two sessions per week. During each session, they performed 3-5 sets of 3-8 repetitions with 3 min of rest in between. Then, they performed specific shots (i.e., 12 to 40). Ball-throwing velocity (p<0.001) was higher after the training period in rear line players (RL). The training programme resulted in an improvement of 1RM bench press (p<0.001), 1RM developed neck (p<0.001) and 1RM print (p<0.001) in both front line (FL) and RL. The control group showed a significant improvement only in ball-throwing velocity (p<0.01) and 1RM bench press (p<0.01) in RL. A significantly greater improvement was found in ball-throwing velocity (p<0.001), 1RM bench press (p<0.001), and 1RM half-back squat exercises in players of the central axis (CA) compared to the lateral axis (LA) (p<0.01). The power training programme induced significantly greater increases in ball-throwing velocity and muscle strength in FL than RL and in CA than LA axis players.

  6. Improvement of Repeated-Sprint Ability and Horizontal-Jumping Performance in Elite Young Basketball Players With Low-Volume Repeated-Maximal-Power Training.

    Science.gov (United States)

    Gonzalo-Skok, Oliver; Tous-Fajardo, Julio; Arjol-Serrano, José Luis; Suarez-Arrones, Luis; Casajús, José Antonio; Mendez-Villanueva, Alberto

    2016-05-01

    To examine the effects of a low-volume repeated-power-ability (RPA) training program on repeated-sprint and change-of- direction (COD) ability and functional jumping performance. Twenty-two male elite young basketball players (age 16.2 ± 1.2 y, height 190.0 ± 10.0 cm, body mass 82.9 ± 10.1 kg) were randomly assigned either to an RPA-training group (n = 11) or a control group (n = 11). RPA training consisted of leg-press exercise, twice a week for 6 wk, of 1 or 2 blocks of 5 sets × 5 repetitions with 20 s of passive recovery between sets and 3 min between blocks with the load that maximized power output. Before and after training, performance was assessed by a repeated-sprint-ability (RSA) test, a repeated-COD-ability test, a hop for distance, and a drop jump followed by tests of a double unilateral hop with the right and left legs. Within-group and between-groups differences showed substantial improvements in slowest (RSAs) and mean time (RSAm) on RSA; best, slowest and mean time on repeated-COD ability; and unilateral right and left hop in the RPA group in comparison with control. While best time on RSA showed no improvement in any group, there was a large relationship (r = .68, 90% CI .43;.84) between the relative decrement in RSAm and RSAs, suggesting better sprint maintenance with RPA training. The relative improvements in best and mean repeated-COD ability were very largely correlated (r = .89, 90% CI .77;.94). Six weeks of lowvolume (4-14 min/wk) RPA training improved several physical-fitness tests in basketball players.

  7. Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

    Science.gov (United States)

    Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S

    2017-02-01

    Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in

  8. Monte Carlo simulation techniques for predicting annual power production

    International Nuclear Information System (INIS)

    Cross, J.P.; Bulandr, P.J.

    1991-01-01

    As the owner and operator of a number of small to mid-sized hydroelectric sites, STS HydroPower has been faced with the need to accurately predict anticipated hydroelectric revenues over a period of years. The typical approach to this problem has been to look at each site from a mathematical deterministic perspective and evaluate the annual production from historic streamflows. Average annual production is simply taken to be the area under the flow duration curve defined by the operating and design characteristics of the selected turbines. Minimum annual production is taken to be a historic dry year scenario and maximum production is viewed as power generated under the most ideal of conditions. Such an approach creates two problems. First, in viewing the characteristics of a single site, it does not take into account the probability of such an event occurring. Second, in viewing all sites in a single organization's portfolio together, it does not reflect the varying flow conditions at the different sites. This paper attempts to address the first of these two concerns, that being the creation of a simulation model utilizing the Monte Carlo method at a single site. The result of the analysis is a picture of the production at the site that is both a better representation of anticipated conditions and defined probabilistically

  9. Maximizing and customer loyalty: Are maximizers less loyal?

    Directory of Open Access Journals (Sweden)

    Linda Lai

    2011-06-01

    Full Text Available Despite their efforts to choose the best of all available solutions, maximizers seem to be more inclined than satisficers to regret their choices and to experience post-decisional dissonance. Maximizers may therefore be expected to change their decisions more frequently and hence exhibit lower customer loyalty to providers of products and services compared to satisficers. Findings from the study reported here (N = 1978 support this prediction. Maximizers reported significantly higher intentions to switch to another service provider (television provider than satisficers. Maximizers' intentions to switch appear to be intensified and mediated by higher proneness to regret, increased desire to discuss relevant choices with others, higher levels of perceived knowledge of alternatives, and higher ego involvement in the end product, compared to satisficers. Opportunities for future research are suggested.

  10. Profit maximization mitigates competition

    DEFF Research Database (Denmark)

    Dierker, Egbert; Grodal, Birgit

    1996-01-01

    We consider oligopolistic markets in which the notion of shareholders' utility is well-defined and compare the Bertrand-Nash equilibria in case of utility maximization with those under the usual profit maximization hypothesis. Our main result states that profit maximization leads to less price...... competition than utility maximization. Since profit maximization tends to raise prices, it may be regarded as beneficial for the owners as a whole. Moreover, if profit maximization is a good proxy for utility maximization, then there is no need for a general equilibrium analysis that takes the distribution...... of profits among consumers fully into account and partial equilibrium analysis suffices...

  11. Prediction and optimization of process variables to maximize the Young's modulus of plasma sprayed alumina coatings on AZ31B magnesium alloy

    Directory of Open Access Journals (Sweden)

    D. Thirumalaikumarasamy

    2017-03-01

    Full Text Available Like other manufacturing techniques, plasma spraying has also a non-linear behavior because of the contribution of many coating variables. This characteristic results in finding optimal factor combination difficult. Subsequently, the issue can be solved through effective and strategic statistical procedures integrated with systematic experimental data. Plasma spray parameters such as power, stand-off distance and powder feed rate have significant influence on coating characteristics like Young's modulus. This paper presents the use of statistical techniques in specifically response surface methodology (RSM, analysis of variance, and regression analysis to develop empirical relationship to predict Young's modulus of plasma-sprayed alumina coatings. The developed empirical relationships can be effectively used to predict Young's modulus of plasma-sprayed alumina coatings at 95% confidence level. Response graphs and contour plots were constructed to identify the optimum plasma spray parameters to attain maximum Young's modulus in alumina coatings. A linear regression relationship was established between porosity and Young's modulus of the alumina coatings.

  12. Geometrical prediction of maximum power point for photovoltaics

    International Nuclear Information System (INIS)

    Kumar, Gaurav; Panchal, Ashish K.

    2014-01-01

    Highlights: • Direct MPP finding by parallelogram constructed from geometry of I–V curve of cell. • Exact values of V and P at MPP obtained by Lagrangian interpolation exploration. • Extensive use of Lagrangian interpolation for implementation of proposed method. • Method programming on C platform with minimum computational burden. - Abstract: It is important to drive solar photovoltaic (PV) system to its utmost capacity using maximum power point (MPP) tracking algorithms. This paper presents a direct MPP prediction method for a PV system considering the geometry of the I–V characteristic of a solar cell and a module. In the first step, known as parallelogram exploration (PGE), the MPP is determined from a parallelogram constructed using the open circuit (OC) and the short circuit (SC) points of the I–V characteristic and Lagrangian interpolation. In the second step, accurate values of voltage and power at the MPP, defined as V mp and P mp respectively, are decided by the Lagrangian interpolation formula, known as the Lagrangian interpolation exploration (LIE). Specifically, this method works with a few (V, I) data points instead most of the MPP algorithms work with (P, V) data points. The performance of the method is examined by several PV technologies including silicon, copper indium gallium selenide (CIGS), copper zinc tin sulphide selenide (CZTSSe), organic, dye sensitized solar cell (DSSC) and organic tandem cells’ data previously reported in literatures. The effectiveness of the method is tested experimentally for a few silicon cells’ I–V characteristics considering variation in the light intensity and the temperature. At last, the method is also employed for a 10 W silicon module tested in the field. To testify the preciseness of the method, an absolute value of the derivative of power (P) with respect to voltage (V) defined as (dP/dV) is evaluated and plotted against V. The method estimates the MPP parameters with high accuracy for any

  13. Training for vigilance: using predictive power to evaluate feedback effectiveness.

    Science.gov (United States)

    Szalma, James L; Hancock, Peter A; Warm, Joel S; Dember, William N; Parsons, Kelley S

    2006-01-01

    We examined the effects of knowledge of results (KR) on vigilance accuracy and report the first use of positive and negative predictive power (PPP and NPP) to assess vigilance training effectiveness. Training individuals to detect infrequent signals among a plethora of nonsignals is critical to success in many failure-intolerant monitoring technologies. KR has been widely used for vigilance training, but the effect of the schedule of KR presentation on accuracy has been neglected. Previous research on training for vigilance has used signal detection metrics or hits and false alarms. In this study diagnosticity measures were applied to augment traditional analytic methods. We examined the effects of continuous KR and a partial-KR regimen versus a no-KR control on decision diagnosticity. Signal detection theory (SDT) analysis indicated that KR induced conservatism in responding but did not enhance sensitivity. However, KR in both forms equally enhanced PPP while selectively impairing NPP. There is a trade-off in the effectiveness of KR in reducing false alarms and misses. Together, SDT and PPP/NPP measures provide a more complete portrait of performance effects. PPP and NPP together provide another assessment technique for vigilance performance, and as additional diagnostic tools, these measures are potentially useful to the human factors community.

  14. Replicability and 40-Year Predictive Power of Childhood ARC Types

    Science.gov (United States)

    Chapman, Benjamin P.; Goldberg, Lewis R.

    2011-01-01

    We examined three questions surrounding the Undercontrolled, Overcontrolled, and Resilient--or Asendorpf-Robins-Caspi (ARC)--personality types originally identified by Block (1971). In analyses of the teacher personality assessments of over 2,000 children in 1st through 6th grade in 1959-1967, and follow-up data on general and cardiovascular health outcomes in over 1,100 adults recontacted 40 years later, we found: (1) Bootstrapped internal replication clustering suggested that Big Five scores were best characterized by a tripartite cluster structure corresponding to the ARC types; (2) this cluster structure was fuzzy, rather than discrete, indicating that ARC constructs are best represented as gradients of similarity to three prototype Big Five profiles; and (3) ARC types and degrees of ARC prototypicality showed associations with multiple health outcomes 40 years later. ARC constructs were more parsimonious, but neither better nor more consistent predictors than the dimensional Big Five traits. Forty-year incident cases of heart disease could be correctly identified with 68% accuracy by personality information alone, a figure approaching the 12-year accuracy of a leading medical cardiovascular risk model. Findings support the theoretical validity of ARC constructs, their treatment as continua of prototypicality rather than discrete categories, and the need for further understanding the robust predictive power of childhood personality traits for mid-life health. PMID:21744975

  15. Analysis of variability and predictability challenges of wind and solar power

    NARCIS (Netherlands)

    Haan, de J.E.S.; Virag, A.; Kling, W.L.

    2013-01-01

    In power systems, reserves are essential to ensure system security, certainly when challenges of predictability (inaccurate forecast) and variability (imperfect correlation of renewable generation and system load) are causing power imbalances. Different techniques can be used to size and allocate

  16. Power capability prediction for lithium-ion batteries based on multiple constraints analysis

    International Nuclear Information System (INIS)

    Pan, Rui; Wang, Yujie; Zhang, Xu; Yang, Duo; Chen, Zonghai

    2017-01-01

    Highlights: • Multiple constraints for peak power capability prediction are deeply analyzed. • Multi-limited method is proposed for the peak power capability prediction of LIBs. • The EKF is used for the model based peak power capability prediction. • The FUDS and UDDS profiles are executed to evaluate the proposed method. - Abstract: The power capability of the lithium-ion battery is a key performance indicator for electric vehicle, and it is intimately correlated with the acceleration, regenerative braking and gradient climbing power requirements. Therefore, an accurate power capability or state-of-power prediction is critical to a battery management system, which can help the battery to work in suitable area and prevent the battery from over-charging and over-discharging. However, the power capability is easily affected by dynamic load, voltage variation and temperature. In this paper, three different constraints in power capability prediction are introduced, and the advantages and disadvantages of the three methods are deeply analyzed. Furthermore, a multi-limited approach for the power capability prediction is proposed, which can overcome the drawbacks of the three methods. Subsequently, the extended Kalman filter algorithm is employed for model based state-of-power prediction. In order to verify the proposed method, diverse experiments are executed to explore the efficiency, robustness, and precision. The results indicate that the proposed method can improve the precision and robustness obviously.

  17. Maximally incompatible quantum observables

    Energy Technology Data Exchange (ETDEWEB)

    Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy); Ziman, Mario, E-mail: ziman@savba.sk [RCQI, Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, 84511 Bratislava (Slovakia); Faculty of Informatics, Masaryk University, Botanická 68a, 60200 Brno (Czech Republic)

    2014-05-01

    The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.

  18. Maximally incompatible quantum observables

    International Nuclear Information System (INIS)

    Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro; Ziman, Mario

    2014-01-01

    The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.

  19. ELMO model predicts the price of electric power

    International Nuclear Information System (INIS)

    Antila, H.

    2001-01-01

    Electrowatt-Ekono has developed a new model, by which it is possible to make long-term prognoses on the development of electricity prices in the Nordic Countries. The ELMO model can be used as an analysis service of the electricity markets and estimation of the profitability of long-term power distribution contracts with different scenarios. It can also be applied for calculation of technical and economical fundamentals for new power plants, and for estimation of the effects of different taxation models on the emissions of power generation. The model describes the whole power generation system, the power and heat consumption and transmission. The Finnish power generation system is based on the Electrowatt-Ekono's boiler database by combining different data elements. Calculation is based on the assumption that the Nordic power generation system is used optimally, and that the production costs are minimised. In practise the effectively operated electricity markets ensure the optimal use of the production system. The market area to be described consists of Finland and Sweden. The spot prices have long been the same. Norway has been treated as a separate market area. The most potential power generation system, the power consumption and the power transmission system are presumed for the target year during a normal rainfall situation. The basic scenario is calculated on the basis of the preconditional data. The calculation is carried out on hourly basis, which enables the estimation of the price variation of electric power between different times during the day and seasons. The system optimises the power generation on the basis of electricity and heat consumption curves and fuel prices. The result is an hourly limit price for electric power. Estimates are presented as standard form reports. Prices are presented as average annuals, in the seasonal base, and in hourly or daily basis for different seasons

  20. Significant change of predictions related to the future of nuclear power

    International Nuclear Information System (INIS)

    Dumitrache, Ion

    2002-01-01

    .6 Gwe (minimal), or 20.7 Gwe (maximal); in Taiwan, from 4.884 Gwe (1999) to 7.514 Gwe (2020, ref.); in India, from 1.897 Gwe (1999) to 7.571 Gwe (2020, ref.); in Japan, from 43.7 Gwe (1999) to 56.6 Gwe (2020, ref.); in Korea, from 13.0 Gwe (1999), to 22.1 Gwe (2020, ref.). An ambitious increase is related to the prognosis in Brazil, from 0.626 Gwe (1999) to 3.084 Gwe (2020, ref.) For the group of the all non-developed countries, other than the Eastern European ones, the predicted increase of the installed nuclear power is from 25.466 Gwe (1999) to 65.824 Gwe (2020, ref.). The decrease of the fission contribution in the European countries that are against new NPP is not very fast in the 1999-2020 period of forecast: Germany, from 21.122 Gwe to 13.134 Gwe; Sweden, from 9.432 Gwe to 6.077 Gwe; Belgium, from 5.712 Gwe to 3.966 Gwe. In Romania, a National Nuclear Plan will schedule the commissioning of the next Cernavoda NPP Units. The intention to complete the work for all the 5 Units before 2020 is clear. There are predictions that indicate 5 Units in operation at Cernavoda NPP several years earlier. A major change in the nuclear power field is related to the advanced reactors. The 'Generation III' will cover the needs for the next 10-20 years. These advanced reactors are significantly safer, cheaper, and the initial time for construction and commissioning is reduced. Most of the already available designs are based on the 'innovative concepts' and, mainly, on the 'evolutionary solutions' related to the operation of the existent NPP. The 'Generation IV' is one of the main R and D tasks of DOE, USA. Any concept and idea is accepted for development and evaluation. The needed advanced reactors are expected in the 2020-2030 period. In conclusion, the recent forecasts of the future of fission based nuclear power indicate a significant contribution to the electricity generation worldwide, at least for the first half of the century. (author)

  1. Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

    International Nuclear Information System (INIS)

    Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

    2016-01-01

    Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

  2. Short-term wind power prediction based on LSSVM–GSA model

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

    2015-01-01

    Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

  3. Acute Postexercise Time Course Responses of Hypertrophic vs. Power-Endurance Squat Exercise Protocols on Maximal and Rapid Torque of the Knee Extensors.

    Science.gov (United States)

    Conchola, Eric C; Thiele, Ryan M; Palmer, Ty B; Smith, Doug B; Thompson, Brennan J

    2015-05-01

    The aim of this study was to examine the effects of a medium-intensity high-volume vs. explosive squat protocol on the postexercise time course responses of maximal and rapid strength of the knee extensors. Seventeen resistance-trained men (mean ± SD: age = 22.0 ± 2.6 years) performed maximal voluntary contractions (MVCs) of the knee extensors before and after performing a squat workout using either a low-intensity fast velocity (LIFV) (5 × 16 at 40% 1 repetition maximum) or a traditional high-intensity slow velocity (TISV) (5 × 8 at 80% 1RM) exercise protocol. For each MVC, peak torque (PT), peak rate of torque development (RTDpeak), absolute (RTDabs), and relative RTD (RTDnorm) at early (0-50 milliseconds) and late (100-200 milliseconds) phases of muscle contraction were examined at pre- (Pre) and post-exercise at 0, 7, 15, and 30 (Post0...30) minutes. There were no intensity × time interactions for any variables (p = 0.098-0.832). Peak torque was greater at Pre than Post0 and Post7 (p = 0.001-0.016) but was not greater than Post15 and Post30 (p = 0.010-0.189). RTDpeak and early absolute RTD (RTD50abs) were greater at Pre than all postexercise time phases (p = 0.001-0.050); however, later absolute RTD (RTD100-200abs) was only greater at Pre than Post0 and Post30 (p = 0.013-0.048). Early relative RTD (RTD50norm) was only higher at Pre compared with Post0 (p = 0.023), whereas no differences were observed for later relative RTD (RTD100-200norm) (p = 0.920-0.990). Low-intensity fast velocity and TISV squat protocols both yielded acute decreases in maximal and rapid strength capacities following free-weight squats, with rapid strength showing slower recovery characteristics than maximal strength.

  4. Modelling of physical properties - databases, uncertainties and predictive power

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    in the estimated/predicted property values, how to assess the quality and reliability of the estimated/predicted property values? The paper will review a class of models for prediction of physical and thermodynamic properties of organic chemicals and their mixtures based on the combined group contribution – atom......Physical and thermodynamic property in the form of raw data or estimated values for pure compounds and mixtures are important pre-requisites for performing tasks such as, process design, simulation and optimization; computer aided molecular/mixture (product) design; and, product-process analysis...

  5. Reactive Power Impact on Lifetime Prediction of Two-level Wind Power Converter

    DEFF Research Database (Denmark)

    Zhou, Dao; Blaabjerg, Frede; Lau, M.

    2013-01-01

    The influence of reactive power injection on the dominating two-level wind power converter is investigated and compared in terms of power loss and thermal behavior. Then the lifetime of both the partial-scale and full-scale power converter is estimated based on the widely used Coffin-Manson model...

  6. Optimization of maintenance for power system equipment using a predictive health model

    NARCIS (Netherlands)

    Bajracharya, G.; Koltunowicz, T.; Negenborn, R.R.; Papp, Z.; Djairam, D.; Schutter, B.D. de; Smit, J.J.

    2009-01-01

    In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based

  7. Maximizers versus satisficers

    OpenAIRE

    Andrew M. Parker; Wandi Bruine de Bruin; Baruch Fischhoff

    2007-01-01

    Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions...

  8. Maximal combustion temperature estimation

    International Nuclear Information System (INIS)

    Golodova, E; Shchepakina, E

    2006-01-01

    This work is concerned with the phenomenon of delayed loss of stability and the estimation of the maximal temperature of safe combustion. Using the qualitative theory of singular perturbations and canard techniques we determine the maximal temperature on the trajectories located in the transition region between the slow combustion regime and the explosive one. This approach is used to estimate the maximal temperature of safe combustion in multi-phase combustion models

  9. Sludge pipe flow pressure drop prediction using composite power ...

    African Journals Online (AJOL)

    2011-09-30

    Sep 30, 2011 ... 3Department of Chemical Engineering, IIT Kanpur, India. Abstract. When predicting pressure gradients for the flow of sludges in pipes, the rheology of the fluid ..... implicit in the stability analysis of Ryan and Johnson (1959).

  10. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  11. A study on the characteristics, predictions and policies of China’s eight main power grids

    International Nuclear Information System (INIS)

    Wang, Jianzhou; Dong, Yao; Jiang, He

    2014-01-01

    Highlights: • Indian blackout is analyzed as a warning for China’s power system. • Issues and recommendations of China’s eight power grids are presented. • Five models are employed for scenario analysis on power generation and consumption. • The optimized combined model outperforms other models. • Methods towards balancing power generation and environmental impacts are proposed. - Abstract: Electricity is an indispensable energy source for modern social and economic development. However, large-scale blackouts can cause incalculable loss to society. In 2012, three major Indian power grids collapsed, resulting in the interruption of the electricity supply to over 600 million people. To avoid an event like that, China needs to forecast the power generation and consumption of eight power grids effectively. This paper first analyzes the characteristics of eight power grids and then proposes a combined model based on three improved grey models optimized by a differential evolution algorithm to predict electricity production and consumption of each power grid. The optimized combined forecasting model provides a better prediction than other models, and it is also the most workable and satisfactory model. Experiment results show electricity production and consumption would increase. In consideration of the real situation and existing problems, some suggestions are proposed. The government could decrease thermal power and exploit renewable energy power, like hydroelectric power, wind power and solar power, to ensure the safe and reliable operation of China’s major power grids and protect environment

  12. Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

    Science.gov (United States)

    Locke, Kenneth D; Heller, Sonja

    2017-01-01

    Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

  13. The predictive power of zero intelligence in financial markets.

    Science.gov (United States)

    Farmer, J Doyne; Patelli, Paolo; Zovko, Ilija I

    2005-02-08

    Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations.

  14. The predictive power of zero intelligence in financial markets

    Science.gov (United States)

    Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

    2005-02-01

    Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. double auction market | market microstructure | agent-based models

  15. Lifetime prediction of high-power press-pack IGBTs in wind power applications

    DEFF Research Database (Denmark)

    Busca, Cristian

    The Wind Turbine (WT) industry is advancing at a rapid pace and the power rating of new WTs is continuously growing. The next generation large WTs are likely to be realized with full-scale power converters due to the advantages they offer in terms of grid code compliance, power density and decoup......The Wind Turbine (WT) industry is advancing at a rapid pace and the power rating of new WTs is continuously growing. The next generation large WTs are likely to be realized with full-scale power converters due to the advantages they offer in terms of grid code compliance, power density...... and decoupling of the generator and grid sides. Press-Pack (PP) Insulated Gate Bipolar Transistors (IGBTs) are promising semiconductor devices for the next generation large WTs due to the advantages they offer in terms of power capability, power density and thermal cycling capability. PP IGBTs require proper...

  16. Maximally multipartite entangled states

    Science.gov (United States)

    Facchi, Paolo; Florio, Giuseppe; Parisi, Giorgio; Pascazio, Saverio

    2008-06-01

    We introduce the notion of maximally multipartite entangled states of n qubits as a generalization of the bipartite case. These pure states have a bipartite entanglement that does not depend on the bipartition and is maximal for all possible bipartitions. They are solutions of a minimization problem. Examples for small n are investigated, both analytically and numerically.

  17. Prediction on corrosion rate of pipe in nuclear power system based on optimized grey theory

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Chen Dengke; Jiang Wei

    2007-01-01

    For the prediction of corrosion rate of pipe in nuclear power system, the pre- diction error from the grey theory is greater, so a new method, optimized grey theory was presented in the paper. A comparison among predicted results from present and other methods was carried out, and it is seem that optimized grey theory is correct and effective for the prediction of corrosion rate of pipe in nuclear power system, and it provides a fundamental basis for the maintenance of pipe in nuclear power system. (authors)

  18. Maximizing the persuasiveness of a salesperson: An exploratory study of the effects of nonverbal immediacy and language power on the extent of persuasion

    Directory of Open Access Journals (Sweden)

    Natavan M. Gadzhiyeva

    2017-07-01

    Full Text Available The present study investigated the effects of a salesperson's use of language power and nonverbal immediacy on the persuasiveness of the salesperson. A high level of language power and a high level of nonverbal immediacy were hypothesized to singularly and jointly increase a salesperson's level of persuasiveness. A sample of 211 undergraduate students voluntarily completed an online survey, which displayed a video clip of a sales presentation. Each participant randomly viewed one of four video clips, which differed in terms of the salesperson's levels of language power (powerful vs. powerless and nonverbal immediacy (high vs. low. A three-way ANOVA indicated that language power had a significant main effect on persuasion in the expected direction, and also revealed a significant interaction between nonverbal immediacy and participant biological sex. However, there were no main effects for nonverbal immediacy and participant biological sex, and no interaction effect was found between language power and nonverbal immediacy. Subsequent data analysis revealed that the perceived power of the speaker mediated the relationship between language power and the extent of persuasion. We conclude the article with a discussion of the implications of our findings for both researchers and practitioners.

  19. Basic study on dynamic reactive-power control method with PV output prediction for solar inverter

    Directory of Open Access Journals (Sweden)

    Ryunosuke Miyoshi

    2016-01-01

    Full Text Available To effectively utilize a photovoltaic (PV system, reactive-power control methods for solar inverters have been considered. Among the various methods, the constant-voltage control outputs less reactive power compared with the other methods. We have developed a constant-voltage control to reduce the reactive-power output. However, the developed constant-voltage control still outputs unnecessary reactive power because the control parameter is constant in every waveform of the PV output. To reduce the reactive-power output, we propose a dynamic reactive-power control method with a PV output prediction. In the proposed method, the control parameter is varied according to the properties of the predicted PV waveform. In this study, we performed numerical simulations using a distribution system model, and we confirmed that the proposed method reduces the reactive-power output within the voltage constraint.

  20. Design and implementation of predictive filtering system for current reference generation of active power filter

    Energy Technology Data Exchange (ETDEWEB)

    Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

    2007-02-15

    The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

  1. Is CP violation maximal

    International Nuclear Information System (INIS)

    Gronau, M.

    1984-01-01

    Two ambiguities are noted in the definition of the concept of maximal CP violation. The phase convention ambiguity is overcome by introducing a CP violating phase in the quark mixing matrix U which is invariant under rephasing transformations. The second ambiguity, related to the parametrization of U, is resolved by finding a single empirically viable definition of maximal CP violation when assuming that U does not single out one generation. Considerable improvement in the calculation of nonleptonic weak amplitudes is required to test the conjecture of maximal CP violation. 21 references

  2. Megaproject Eemscentrale. Part 3. Maximal environmental care at the new power plant `Eemscentrale`, Netherlands; Megaproject Eemscentrale. Deel 3. Bij nieuwe Eemscentrale maximale zorg voor het milieu

    Energy Technology Data Exchange (ETDEWEB)

    Crone, K. [Crone Communicatie, Diemen (Netherlands)

    1996-01-01

    In a series of 8 articles attention is paid to several aspects of the Netherlands largest Energy Construction project, the gas-fired power plant `Eemscentrale`. In this article the environmental protection measures taken are briefly discussed. 3 ills.

  3. Improving nuclear power plant reliability through predictive maintenance

    International Nuclear Information System (INIS)

    Geilhausen, R.; Kunze, U.

    1996-01-01

    Maintenance strategies can be assigned to one of three categories: failure maintenance, periodic maintenance or condition-oriented maintenance. The optimum maintenance scheme can be selected on the basis of a cost-benefit analysis but the safety of life and limb or the political climate for NPP can hardly expressed in numbers. The implementation of preventive maintenance needs two preconditions: high-performance instrumentation in the form of stationary and mobile monitoring systems for the determination of the condition of the nuclear power plant components and provision of a tool that can handle both the organization of the work and the evaluation of the results obtained. (authors)

  4. THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM

    Directory of Open Access Journals (Sweden)

    Fatih Ozdemir

    2016-07-01

    Full Text Available The purpose of the present study was to predict ambivalent sexism (including hostile sexism and benevolent sexism with religious orientation types as intrinsic religiosity, extrinsic religiosity and quest religiosity. In addition, the effect of demographic variables (including age, gender, education on sexist attitudes was tested. 583 (N_female= 318; N_male= 265 university students who study in different universities of Ankara/Turkey (M_age= 22.10; SD = 2.33 completed Ambivalent Sexism Inventory, and Religious Orientation Scale. Findings indicated significant gender differences on study variables and significant associations between ambivalent sexism and religious orientation types within university students sample in Turkey.

  5. On-line test of power distribution prediction system for boiling water reactors

    International Nuclear Information System (INIS)

    Nishizawa, Y.; Kiguchi, T.; Kobayashi, S.; Takumi, K.; Tanaka, H.; Tsutsumi, R.; Yokomi, M.

    1982-01-01

    A power distribution prediction system for boiling water reactors has been developed and its on-line performance test has proceeded at an operating commercial reactor. This system predicts the power distribution or thermal margin in advance of control rod operations and core flow rate change. This system consists of an on-line computer system, an operator's console with a color cathode-ray tube, and plant data input devices. The main functions of this system are present power distribution monitoring, power distribution prediction, and power-up trajectory prediction. The calculation method is based on a simplified nuclear thermal-hydraulic calculation, which is combined with a method of model identification to the actual reactor core state. It has been ascertained by the on-line test that the predicted power distribution (readings of traversing in-core probe) agrees with the measured data within 6% root-mean-square. The computing time required for one prediction calculation step is less than or equal to 1.5 min by an HIDIC-80 on-line computer

  6. The predictive power of Japanese candlestick charting in Chinese stock market

    Science.gov (United States)

    Chen, Shi; Bao, Si; Zhou, Yu

    2016-09-01

    This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

  7. Plug-in hybrid electric vehicles as a way to maximize the integration of variable renewable energy in power systems: The case of wind generation in northeastern Brazil

    International Nuclear Information System (INIS)

    Soares MC Borba, Bruno; Szklo, Alexandre; Schaeffer, Roberto

    2012-01-01

    Several studies have proposed different tools for analyzing the integration of variable renewable energy into power grids. This study applies an optimization tool to model the expansion of the electric power system in northeastern Brazil, enabling the most efficient dispatch of the variable output of the wind farms that will be built in the region over the next 20 years. The expected combined expansion of wind generation with conventional inflexible generation facilities, such as nuclear plants and run-of-the-river hydropower plants, poses risks of future mismatch between supply and demand in northeastern Brazil. Therefore, this article evaluates the possibility of using a fleet of plug-in hybrid electric vehicles (PHEVs) to regularize possible energy imbalances. Findings indicate that a dedicated fleet of 500 thousand PHEVs in 2015, and a further 1.5 million in 2030, could be recharged overnight to take advantage of the surplus power generated by wind farms. To avoid the initial costs of smart grids, this article suggests, as a first step, the use of a governmental PHEV fleet that allows fleet managers to control battery charging times. Finally, the study demonstrates the advantages of optimizing simultaneously the power and transport sectors to test the strategy suggested here. -- Highlights: ► We evaluated the use of plug-in hybrid electric vehicles (PHEV) to regularize possible energy imbalances in northeastern Brazil. ► This imbalance might result from the large-scale wind power penetration along with conventional inflexible power plants in the region. ► We adapted the MESSAGE optimization tool to the base conditions of the Brazilian power system. ► 500 thousand PHEVs in 2015 and 1.5 million in 2030 could be recharged taking advantage of wind energy surplus.

  8. Prediction of speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relano-Iborra, Helia; May, Tobias; Zaar, Johannes

    A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speechbased envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envel...

  9. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    Science.gov (United States)

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  10. The prediction and prevention of voltage collapse in the Finnish power system

    Energy Technology Data Exchange (ETDEWEB)

    Bastman, J; Lakervi, E [Tampere Univ. of Tech. (Finland); Hirvonen, R; Kuronen, P; Hagman, E [IVO Group (Finland)

    1994-12-31

    The Finnish power system is a part of the Nordic power system (NORDEL), which includes Finland, Sweden, Norway and the eastern part of Denmark. In NORDEL the transmission distances are long, which implies that the power transmission capacities are determined by stability criteria . The methods to prevent and predict the voltage collapse during severe disturbances are studied using advances simulation program. Results are presented. (author) 10 figs., 1 tab.

  11. Is the β phase maximal?

    International Nuclear Information System (INIS)

    Ferrandis, Javier

    2005-01-01

    The current experimental determination of the absolute values of the CKM elements indicates that 2 vertical bar V ub /V cb V us vertical bar =(1-z), with z given by z=0.19+/-0.14. This fact implies that irrespective of the form of the quark Yukawa matrices, the measured value of the SM CP phase β is approximately the maximum allowed by the measured absolute values of the CKM elements. This is β=(π/6-z/3) for γ=(π/3+z/3), which implies α=π/2. Alternatively, assuming that β is exactly maximal and using the experimental measurement sin(2β)=0.726+/-0.037, the phase γ is predicted to be γ=(π/2-β)=66.3 o +/-1.7 o . The maximality of β, if confirmed by near-future experiments, may give us some clues as to the origin of CP violation

  12. Emotion dysregulation and social competence: stability, change and predictive power.

    Science.gov (United States)

    Berkovits, L D; Baker, B L

    2014-08-01

    Social difficulties are closely linked to emotion dysregulation among children with typical development (TD). Children with developmental delays (DD) are at risk for poor social outcomes, but the relationship between social and emotional development within this population is not well understood. The current study examines the extent to which emotion dysregulation is related to social problems across middle childhood among children with TD or DD. Children with TD (IQ ≥ 85, n = 113) and children with DD (IQ ≤ 75, n = 61) participated in a longitudinal study. Annual assessments were completed at ages 7, 8 and 9 years. At each assessment, mothers reported on children's emotion dysregulation, and both mothers and teachers reported on children's social difficulties. Children with DD had higher levels of emotion dysregulation and social problems at each age than those with TD. Emotion dysregulation and social problems were significantly positively correlated within both TD and DD groups using mother report of social problems, and within the TD group using teacher report of social problems. Among children with TD, emotion dysregulation consistently predicted change in social problems from one year to the next. However, among children with DD, emotion dysregulation offered no unique prediction value above and beyond current social problems. Results suggested that the influence of emotion regulation abilities on social development may be a less salient pathway for children with DD. These children may have more influences, beyond emotion regulation, on their social behaviour, highlighting the importance of directly targeting social skill deficits among children with DD in order to ameliorate their social difficulties. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

  13. MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM

    Directory of Open Access Journals (Sweden)

    I. Elzein

    2015-01-01

    Full Text Available The purpose of this paper is to present an alternative maximum power point tracking, MPPT, algorithm for a photovoltaic module, PVM, to produce the maximum power, Pmax, using the optimal duty ratio, D, for different types of converters and load matching.We present a state-based approach to the design of the maximum power point tracker for a stand-alone photovoltaic power generation system. The system under consideration consists of a solar array with nonlinear time-varying characteristics, a step-up converter with appropriate filter.The proposed algorithm has the advantages of maximizing the efficiency of the power utilization, can be integrated to other MPPT algorithms without affecting the PVM performance, is excellent for Real-Time applications and is a robust analytical method, different from the traditional MPPT algorithms which are more based on trial and error, or comparisons between present and past states. The procedure to calculate the optimal duty ratio for a buck, boost and buck-boost converters, to transfer the maximum power from a PVM to a load, is presented in the paper. Additionally, the existence and uniqueness of optimal internal impedance, to transfer the maximum power from a photovoltaic module using load matching, is proved.

  14. Capacity Maximizing Constellations

    Science.gov (United States)

    Barsoum, Maged; Jones, Christopher

    2010-01-01

    Some non-traditional signal constellations have been proposed for transmission of data over the Additive White Gaussian Noise (AWGN) channel using such channel-capacity-approaching codes as low-density parity-check (LDPC) or turbo codes. Computational simulations have shown performance gains of more than 1 dB over traditional constellations. These gains could be translated to bandwidth- efficient communications, variously, over longer distances, using less power, or using smaller antennas. The proposed constellations have been used in a bit-interleaved coded modulation system employing state-ofthe-art LDPC codes. In computational simulations, these constellations were shown to afford performance gains over traditional constellations as predicted by the gap between the parallel decoding capacity of the constellations and the Gaussian capacity

  15. 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.

  16. 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)

  17. Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

    Science.gov (United States)

    Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

    2013-05-01

    This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

  18. THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM

    Directory of Open Access Journals (Sweden)

    Gul Ulubayram

    2016-07-01

    Full Text Available Objective: The purpose of this study is to examine stress and stress related factors in tuberculosis patients. In addition, to determine the impact of socio-demographic variables such as age, gender and educational level over stress symptoms hereby comprises a further objective of this study. Method: The study included totally 129 tuberculosis patients and 161 non-patients (normal group participants. Tuberculosis patients registered in Ankara Tuberculosis Dispensary No.4, and Atatürk Chest Diseases and Chest Surgery Hospital. There are 75 Pulmonary Tuberculosis (AC TB and 54 Extra- Pulmonary Tuberculosis (AD TB patients. As regards data collection tools; Demographic Information Form, Brief Symptom Inventory, Stress Symptoms Scale, Stress Vulnerability Scale, and Stress Coping Scale were used. Results: Within the context of diagnosis groups; it was found that; stress symptoms of tuberculosis patients are higher than the normal group, they use their ineffective coping ways more and their life satisfactions are lower. There exists no gender and diagnosis group main effect in terms of the psychological symptoms of stress, however “gender x diagnosis group” interaction effect draws attention herein. In tuberculosis patients, ineffective coping the stress and relation pleasure variables are confronted as joint variables which are predicting both the psychological and physical health. Another point which draws attention in regression analyzes is that; “education” variable takes place among the variables which predict the psychological symptoms of stress in tuberculosis patients. Conclusion: Under the light of these findings, tuberculosis patients, during their treatment processes, may be encouraged to attend various training programs prepared for stress management and effective dealing strategies with stress. By increasing the patients’ motivation towards the treatment, these programs may provide supplementary benefits to the treatment by

  19. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  20. 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.

  1. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Directory of Open Access Journals (Sweden)

    Milos Bogdanovic

    2013-08-01

    Full Text Available Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  2. ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-08-15

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  3. A new wind power prediction method based on chaotic theory and Bernstein Neural Network

    International Nuclear Information System (INIS)

    Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

    2016-01-01

    The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

  4. A variable capacitance based modeling and power capability predicting method for ultracapacitor

    Science.gov (United States)

    Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

    2018-01-01

    Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

  5. Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

    Directory of Open Access Journals (Sweden)

    Dongmyung Kim

    2018-05-01

    Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.

  6. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  7. Maximal Voluntary Activation of the Elbow Flexors Is under Predicted by Transcranial Magnetic Stimulation Compared to Motor Point Stimulation Prior to and Following Muscle Fatigue

    Directory of Open Access Journals (Sweden)

    Edward W. J. Cadigan

    2017-09-01

    Full Text Available Transcranial magnetic (TMS and motor point stimulation have been used to determine voluntary activation (VA. However, very few studies have directly compared the two stimulation techniques for assessing VA of the elbow flexors. The purpose of this study was to compare TMS and motor point stimulation for assessing VA in non-fatigued and fatigued elbow flexors. Participants performed a fatigue protocol that included twelve, 15 s isometric elbow flexor contractions. Participants completed a set of isometric elbow flexion contractions at 100, 75, 50, and 25% of maximum voluntary contraction (MVC prior to and following fatigue contractions 3, 6, 9, and 12 and 5 and 10 min post-fatigue. Force and EMG of the bicep and triceps brachii were measured for each contraction. Force responses to TMS and motor point stimulation and EMG responses to TMS (motor evoked potentials, MEPs and Erb's point stimulation (maximal M-waves, Mmax were also recorded. VA was estimated using the equation: VA% = (1−SITforce/PTforce × 100. The resting twitch was measured directly for motor point stimulation and estimated for both motor point stimulation and TMS by extrapolation of the linear regression between the superimposed twitch force and voluntary force. MVC force, potentiated twitch force and VA significantly (p < 0.05 decreased throughout the elbow flexor fatigue protocol and partially recovered 10 min post fatigue. VA was significantly (p < 0.05 underestimated when using TMS compared to motor point stimulation in non-fatigued and fatigued elbow flexors. Motor point stimulation compared to TMS superimposed twitch forces were significantly (p < 0.05 higher at 50% MVC but similar at 75 and 100% MVC. The linear relationship between TMS superimposed twitch force and voluntary force significantly (p < 0.05 decreased with fatigue. There was no change in triceps/biceps electromyography, biceps/triceps MEP amplitudes, or bicep MEP amplitudes throughout the fatigue protocol at

  8. Recent advances in prediction of emission of hazardous air pollutants from coal-fired power plants

    International Nuclear Information System (INIS)

    Senior, C.L.; Helble, J.J.; Sarofim, A.F.

    2000-01-01

    Coal-fired power plants are a primary source of mercury discharge into the atmosphere along with fine particulates containing arsenic, selenium, cadmium, and other hazardous air pollutants. Information regarding the speciation of these toxic metals is necessary to accurately predict their atmospheric transport and fate in the environment. New predictive tools have been developed to allow utilities to better estimate the emissions of toxic metals from coal-fired power plants. These prediction equations are based on fundamental physics and chemistry and can be applied to a wide variety of fuel types and combustion conditions. The models have significantly improved the ability to predict the emissions of air toxic metals in fine particulate and gas-phase mercury. In this study, the models were successfully tested using measured mercury speciation and mass balance information collected from coal-fired power plants

  9. Critical power prediction by CATHARE2 of the OECD/NRC BFBT benchmark

    Energy Technology Data Exchange (ETDEWEB)

    Lutsanych, Sergii, E-mail: s.lutsanych@ing.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy); Sabotinov, Luben, E-mail: luben.sabotinov@irsn.fr [Institut for Radiological Protection and Nuclear Safety (IRSN), 31 avenue de la Division Leclerc, 92262 Fontenay-aux-Roses (France); D’Auria, Francesco, E-mail: francesco.dauria@dimnp.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy)

    2015-03-15

    Highlights: • We used CATHARE code to calculate the critical power exercises of the OECD/NRC BFBT benchmark. • We considered both steady-state and transient critical power tests of the benchmark. • We used both the 1D and 3D features of the CATHARE code to simulate the experiments. • Acceptable prediction of the critical power and its location in the bundle is obtained using appropriate modelling. - Abstract: This paper presents an application of the French best estimate thermal-hydraulic code CATHARE 2 to calculate the critical power and departure from nucleate boiling (DNB) exercises of the International OECD/NRC BWR Fuel Bundle Test (BFBT) benchmark. The assessment activity is performed comparing the code calculation results with available in the framework of the benchmark experimental data from Japanese Nuclear Power Engineering Corporation (NUPEC). Two-phase flow calculations on prediction of the critical power have been carried out both in steady state and transient cases, using one-dimensional and three-dimensional modelling. Results of the steady-state critical power tests calculation have shown the ability of CATHARE code to predict reasonably the critical power and its location, using appropriate modelling.

  10. Maximal Entanglement in High Energy Physics

    Directory of Open Access Journals (Sweden)

    Alba Cervera-Lierta, José I. Latorre, Juan Rojo, Luca Rottoli

    2017-11-01

    Full Text Available We analyze how maximal entanglement is generated at the fundamental level in QED by studying correlations between helicity states in tree-level scattering processes at high energy. We demonstrate that two mechanisms for the generation of maximal entanglement are at work: i $s$-channel processes where the virtual photon carries equal overlaps of the helicities of the final state particles, and ii the indistinguishable superposition between $t$- and $u$-channels. We then study whether requiring maximal entanglement constrains the coupling structure of QED and the weak interactions. In the case of photon-electron interactions unconstrained by gauge symmetry, we show how this requirement allows reproducing QED. For $Z$-mediated weak scattering, the maximal entanglement principle leads to non-trivial predictions for the value of the weak mixing angle $\\theta_W$. Our results are a first step towards understanding the connections between maximal entanglement and the fundamental symmetries of high-energy physics.

  11. Using data-driven approach for wind power prediction: A comparative study

    International Nuclear Information System (INIS)

    Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.

    2016-01-01

    Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the

  12. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2013-01-01

    Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

  13. Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

    Science.gov (United States)

    Dedes, I.; Dudek, J.

    2018-03-01

    We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

  14. An information maximization model of eye movements

    Science.gov (United States)

    Renninger, Laura Walker; Coughlan, James; Verghese, Preeti; Malik, Jitendra

    2005-01-01

    We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

  15. PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Altab Hossain

    2009-01-01

    Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

  16. PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Altab Md. Hossain

    2009-12-01

    Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

  17. K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

    Directory of Open Access Journals (Sweden)

    Lv Tao

    2017-01-01

    Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

  18. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  19. Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

    Science.gov (United States)

    Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

    2017-10-01

    We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

  20. State-space model predictive control method for core power control in pressurized water reactor nuclear power stations

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Guo Xu; Wu, Jie; Zeng, Bifan; Wu, Wangqiang; Ma, Xiao Qian [School of Electric Power, South China University of Technology, Guangzhou (China); Xu, Zhibin [Electric Power Research Institute of Guangdong Power Grid Corporation, Guangzhou (China)

    2017-02-15

    A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

  1. Guinea pig maximization test

    DEFF Research Database (Denmark)

    Andersen, Klaus Ejner

    1985-01-01

    Guinea pig maximization tests (GPMT) with chlorocresol were performed to ascertain whether the sensitization rate was affected by minor changes in the Freund's complete adjuvant (FCA) emulsion used. Three types of emulsion were evaluated: the oil phase was mixed with propylene glycol, saline...

  2. A novel method for predicting the power outputs of wave energy converters

    Science.gov (United States)

    Wang, Yingguang

    2018-03-01

    This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

  3. Achieving quasi-adiabatic thermal environment to maximize resolution power in very high-pressure liquid chromatography: Theory, models, and experiments.

    Science.gov (United States)

    Gritti, Fabrice; Gilar, Martin; Jarrell, Joseph A

    2016-04-29

    A cylindrical vacuum chamber (inner diameter 5 cm) housing a narrow-bore 2.1 mm×100 mm column packed with 1.8 μm HSS-T3 fully porous particles was built in order to isolate thermally the chromatographic column from the external air environment. Consistent with statistical physics and the mean free path of air molecules, the experimental results show that natural air convection and conduction are fully eliminated for housing air pressures smaller than 10(-4) Torr. Heat radiation is minimized by wrapping up the column with low-emissivity aluminum-tape (emissivity coefficient ϵ=0.03 vs. 0.28 for polished stainless steel 316). Overall, the heat flux at the column wall is reduced by 96% with respect to standard still-air ovens. From a practical viewpoint, the efficiency of the column run at a flow rate of 0.6 mL/min at a constant 13,000 psi pressure drop (the viscous heat power is around 9 W/m) is improved by up to 35% irrespective of the analyte retention. Models of heat and mass transfer reveal that (1) the amplitude of the radial temperature gradient is significantly reduced from 0.30 to 0.01 K and (2) the observed improvement in resolution power stems from a more uniform distribution of the flow velocity across the column diameter. The eddy dispersion term in the van Deemter equation is reduced by 0.8±0.1 reduced plate height unit, a significant gain in column performance. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2015-12-01

    Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

  5. Model predictive control for power flows in networks with limited capacity

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Bendtsen, Jan Dimon

    2012-01-01

    this problem can be formulated as an optimization problem, leading directly to the design of a model predictive controller. Using this scheme, we are able to incorporate predictions of future consumption and exploit knowledge of link limitations such that the intelligent consumers are utilized ahead of time......We consider an interconnected network of consumers powered through an electrical grid of limited capacity. A subset of the consumers are intelligent consumers and have the ability to store energy in a controllable fashion; they can be filled and emptied as desired under power and capacity...... limitations. We address the problem of maintaining power balance between production and consumption using the intelligent consumers to ensure smooth power consumption from the grid. Further, certain capacity limitations to the links interconnecting the consumers must be honored. In this paper, we show how...

  6. Automatic Power Control for Daily Load-following Operation using Model Predictive Control Method

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Keuk Jong; Kim, Han Gon [KH, Daejeon (Korea, Republic of)

    2009-10-15

    Under the circumstances that nuclear power occupies more than 50%, nuclear power plants are required to be operated on load-following operation in order to make the effective management of electric grid system and enhanced responsiveness to rapid changes in power demand. Conventional reactors such as the OPR1000 and APR1400 have a regulating system that controls the average temperature of the reactor core relation to the reference temperature. This conventional method has the advantages of proven technology and ease of implementation. However, this method is unsuitable for controlling the axial power shape, particularly the load following operation. Accordingly, this paper reports on the development of a model predictive control method which is able to control the reactor power and the axial shape index. The purpose of this study is to analyze the behavior of nuclear reactor power and the axial power shape by using a model predictive control method when the power is increased and decreased for a daily load following operation. The study confirms that deviations in the axial shape index (ASI) are within the operating limit.

  7. Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

    DEFF Research Database (Denmark)

    Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

    2017-01-01

    This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded...... into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers...

  8. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  9. Prediction of small hydropower plant power production in Himreen Lake dam (HLD using artificial neural network

    Directory of Open Access Journals (Sweden)

    Ali Thaeer Hammid

    2018-03-01

    Full Text Available In developing countries, the power production is properly less than the request of power or load, and sustaining a system stability of power production is a trouble quietly. Sometimes, there is a necessary development to the correct quantity of load demand to retain a system of power production steadily. Thus, Small Hydropower Plant (SHP includes a Kaplan turbine was verified to explore its applicability. This paper concentrates on applying on Artificial Neural Networks (ANNs by approaching of Feed-Forward, Back-Propagation to make performance predictions of the hydropower plant at the Himreen lake dam-Diyala in terms of net turbine head, flow rate of water and power production that data gathered during a research over a 10 year period. The model studies the uncertainties of inputs and output operation and there's a designing to network structure and then trained by means of the entire of 3570 experimental and observed data. Furthermore, ANN offers an analyzing and diagnosing instrument effectively to model performance of the nonlinear plant. The study suggests that the ANN may predict the performance of the plant with a correlation coefficient (R between the variables of predicted and observed output that would be higher than 0.96. Keywords: Himreen Lake Dam, Small Hydropower plants, Artificial Neural Networks, Feed forward-back propagation model, Generation system's prediction

  10. Using Unsupervised Machine Learning for Outlier Detection in Data to Improve Wind Power Production Prediction

    OpenAIRE

    Åkerberg, Ludvig

    2017-01-01

    The expansion of wind power for electrical energy production has increased in recent years and shows no signs of slowing down. This unpredictable source of energy has contributed to destabilization of the electrical grid causing the energy market prices to vary significantly on a daily basis. For energy producers and consumers to make good investments, methods have been developed to make predictions of wind power production. These methods are often based on machine learning were historical we...

  11. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

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

    Science.gov (United States)

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

    2011-12-01

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

  13. Tri-maximal vs. bi-maximal neutrino mixing

    International Nuclear Information System (INIS)

    Scott, W.G

    2000-01-01

    It is argued that data from atmospheric and solar neutrino experiments point strongly to tri-maximal or bi-maximal lepton mixing. While ('optimised') bi-maximal mixing gives an excellent a posteriori fit to the data, tri-maximal mixing is an a priori hypothesis, which is not excluded, taking account of terrestrial matter effects

  14. A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2017-01-01

    Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.

  15. Development of equipment reliability process using predictive technologies at Hamaoka Nuclear Power Station

    International Nuclear Information System (INIS)

    Taniguchi, Yuji; Sakuragi, Futoshi; Hamada, Seiichi

    2014-01-01

    Development of equipment reliability(ER) process, specifically for predictive maintenance (PdM) technologies integrated condition based maintenance (CBM) process, at Hamaoka Nuclear Power Station is introduced in this paper. Integration of predictive maintenance technologies such as vibration, oil analysis and thermo monitoring is more than important to establish strong maintenance strategies and to direct a specific technical development. In addition, a practical example of CBM is also presented to support the advantage of the idea. (author)

  16. Prediction of reflood behavior for tests with differing axial power shapes using WCOBRA/TRAC

    International Nuclear Information System (INIS)

    Bajorek, S.M.; Hochreiter, L.E.

    1991-01-01

    The rector core power shape can vary over the fuel cycle due to load follow, control rod movement, burnup effects and Xenon transients. a best estimate thermal-hydraulic code must be able to accurately predict the reflooding behavior for different axial power shapes in order to find the power shapes effects on the loss-of-coolant peak cladding temperature. Several different reflood heat transfer experiments have been performed at the same or similar PWR reflood conditions with different axial power shapes. These experiments have different rod diameters, were full length, 3.65 m (12 feet) in height, and had simple egg crate grids. The WCOBRA/TRAC code has been used to model several different tests from these three experiments to examine the code's capability to predict the reflood transient for different power shapes, with a consistent model and noding scheme. This paper describes these different experiments, their power shapes, and the test conditions. The WCOBRA/TRAC code is described as well as the noding scheme, and the calculated results will be compared in detail with the test data rod temperatures. An overall assessment of the code's predictions of these experiments is presented

  17. Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2012-01-01

    management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching...

  18. Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2014-01-01

    Full Text Available Reliable power and temperature control in pressurized water reactor (PWR nuclear power plant is necessary to guarantee high efficiency and plant safety. Since the nuclear plants are quite nonlinear, the paper presents nonlinear fuzzy model predictive control (MPC, by incorporating the realistic constraints, to realize the plant optimization. T-S fuzzy modeling on nuclear power plant is utilized to approximate the nonlinear plant, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC scheme in order to solve the nonlinear constraint optimization problem. Improved performance compared to the traditional PID controller for a TMI-type PWR is obtained in the simulation.

  19. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

  20. Attracted to power: challenge/threat and promotion/prevention focus differentially predict the attractiveness of group power

    Science.gov (United States)

    Scholl, Annika; Sassenrath, Claudia; Sassenberg, Kai

    2015-01-01

    Depending on their motivation, individuals prefer different group contexts for social interactions. The present research sought to provide more insight into this relationship. More specifically, we tested how challenge/threat and a promotion/prevention focus predict attraction to groups with high- or low-power. As such, we examined differential outcomes of threat and prevention focus as well as challenge and promotion focus that have often been regarded as closely related. According to regulatory focus, individuals should prefer groups that they expect to “feel right” for them to join: Low-power groups should be more attractive in a prevention (than a promotion) focus, as these groups suggest security-oriented strategies, which fit a prevention focus. High-power groups should be more attractive in a promotion (rather than a prevention) focus, as these groups are associated with promotion strategies fitting a promotion focus (Sassenberg et al., 2007). In contrast, under threat (vs. challenge), groups that allow individuals to restore their (perceived) lack of control should be preferred: Low-power groups should be less attractive under threat (than challenge) because they provide low resources which threatened individuals already perceive as insufficient and high-power groups might be more attractive under threat (than under challenge), because their high resources allow individuals to restore control. Two experiments (N = 140) supported these predictions. The attractiveness of a group often depends on the motivation to engage in what fits (i.e., prefer a group that feels right in the light of one’s regulatory focus). However, under threat the striving to restore control (i.e., prefer a group allowing them to change the status quo under threat vs. challenge) overrides the fit effect, which may in turn guide individuals’ behavior in social interactions. PMID:25904887

  1. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...... predicted was the need for special living facilities and support at discharge from a rehabilitation hospital, as well as six months later; 53 stroke patients with age median 68 years were included in this prospective study. It was shown that a combination of Barthel Index and CT50 had a stronger predictive...

  2. Prediction of requirements on labor force in the fuel and power generation sector

    International Nuclear Information System (INIS)

    Kaveckova, R.

    1990-01-01

    One of the aspects of socio-economic assessment of development is quantification of the expected requirements on the number of personnel. Predictions are discussed for the period before the year 2005 for solid fuel mining and treatment, gas production and bitumen mining, power and heat generation and also for the production of electricity and heat by nuclear power plants. They are based on an analysis of past development and the present state, on presumed implementation of various concept variants, on the type structure of nuclear power plants, on the rules of the electric power supply system, and also on foreign materials. It is expected that in 2005, nuclear power will employ 15,654 personnel. (M.D.). 4 tabs., 16 refs

  3. Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

    Science.gov (United States)

    Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

    2018-02-01

    Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.

  4. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  5. Research Design and the Predictive Power of Measures of Self-Efficacy

    Science.gov (United States)

    Moriarty, Beverley

    2014-01-01

    The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…

  6. Analyzing power in pp scattering at low energies: the Paris potential predictions

    International Nuclear Information System (INIS)

    Cote, J.; Pires, P.; Tourreil, R. de; Lacombe, M.; Loiseau, B.; Vinh Mau, R.

    1979-12-01

    Predictions of the Paris potential for the analyzing power in pp scattering at low energies are compared with recent high precision measurements at 6.14MeV and earlier measurements at 10 and 16MeV. Phase shift values are also presented and discussed in view of previous analyses

  7. Loneliness among University Students: Predictive Power of Sex Roles and Attachment Styles on Loneliness

    Science.gov (United States)

    Ilhan, Tahsin

    2012-01-01

    This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…

  8. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...

  9. Model Predictive Current Control for High-Power Grid-Connected Converters with Output LCL Filter

    DEFF Research Database (Denmark)

    Delpino, Hernan Anres Miranda; Teodorescu, Remus; Rodriguez, Pedro

    2009-01-01

    A model predictive control strategy for a highpower, grid connected 3-level neutral clamped point converter is presented. Power losses constraints set a limit on commutation losses so reduced switching frequency is required, thus producing low frequency current harmonics. To reduce these harmonics...

  10. Getting data for prediction of electricity generation from photovoltaic power plants

    International Nuclear Information System (INIS)

    Majer, V.; Hejtmankova, P.

    2012-01-01

    This paper deals with the short term prediction of generated electricity from photovoltaic power plants. This way of electricity generation is strongly dependent on the actual weather, mainly solar radiation and temperature. In this paper the simple method for getting solar radiation data is presented. (Authors)

  11. Model Predictive Control for Flexible Power Consumption of Large-Scale Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Stoustrup, Jakob; Rasmussen, Henrik

    2014-01-01

    A model predictive control (MPC) scheme is introduced to directly control the electrical power consumption of large-scale refrigeration systems. Deviation from the baseline of the consumption is corresponded to the storing and delivering of thermal energy. By virtue of such correspondence...

  12. Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relaño-Iborra, Helia; May, Tobias; Zaar, Johannes

    2016-01-01

    A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436–446] with a correlation back end inspired by the sh...

  13. Achievement Motivation Revisited: New Longitudinal Data to Demonstrate Its Predictive Power

    Science.gov (United States)

    Hustinx, Paul W. J.; Kuyper, Hans; van der Werf, Margaretha P. C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary school students. Two measures of achievement…

  14. Achievement motivation revisited : New longitudinal data to demonstrate its predictive power

    NARCIS (Netherlands)

    Hustinx, P.W.J.; Kuyper, H.; Van der Werf, M.P.C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary

  15. Explicit model predictive control applications in power systems: an AGC study for an isolated industrial system

    DEFF Research Database (Denmark)

    Jiang, Hao; Lin, Jin; Song, Yonghua

    2016-01-01

    Model predictive control (MPC), that can consider system constraints, is one of the most advanced control technology used nowadays. In power systems, MPC is applied in a way that an optimal control sequence is given every step by an online MPC controller. The main drawback is that the control law...

  16. Prediction of Full-Scale Propulsion Power using Artificial Neural Networks

    DEFF Research Database (Denmark)

    Pedersen, Benjamin Pjedsted; Larsen, Jan

    2009-01-01

    Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature from four different loading conditions, together with hind cast data of wind and sea properties; and noon report data has been used to train an Artificial Neural Network for prediction...

  17. Aggression in Primary Schools: The Predictive Power of the School and Home Environment

    Science.gov (United States)

    Kozina, Ana

    2015-01-01

    In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

  18. The Prediction Power of Servant and Ethical Leadership Behaviours of Administrators on Teachers' Job Satisfaction

    Science.gov (United States)

    Güngör, Semra Kiranli

    2016-01-01

    The purpose of this study is to identify servant leadership and ethical leadership behaviors of administrators and the prediction power of these behaviors on teachers' job satisfaction according to the views of schoolteachers. This research, figured in accordance with the quantitative research processes. The target population of the research has…

  19. Identification of the Predictive Power of Five Factor Personality Traits for Individual Instrument Performance Anxiety

    Science.gov (United States)

    Özdemir, Gökhan; Dalkiran, Esra

    2017-01-01

    This study, with the aim of identifying the predictive power of the five-factor personality traits of music teacher candidates on individual instrument performance anxiety, was designed according to the relational screening model. The study population was students attending the Music Education branch of Fine Arts Education Departments in…

  20. Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2015-01-01

    Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

  1. Modelos para predição da carga máxima no teste clínico de esforço cardiopulmonar Maximal workload prediction models in the clinical cardio-pulmonary effort test

    Directory of Open Access Journals (Sweden)

    Fernando dos Santos Nogueira

    2006-08-01

    Full Text Available OBJETIVO: Este estudo buscou derivar equações generalizadas para predição da carga máxima para homens e mulheres jovens. MÉTODOS: O método da ergoespirometria direta (Aerosport® TEEM 100, Estados Unidos da América do Norte foi empregado para determinar o VO2máx e a carga máxima (Wmáx, no cicloergômetro (Monark®, Brasil, de 30 homens (25 ± 5 anos, 75,0 ± 10,7 kg; 48,4 ± 8,8 mL . kg -1 . min -1 e 243 ± 51 Watts e 30 mulheres (26 ± 5 anos, 56,7 ± 5,9 kg, 39,8 ± 7,6 mL . kg -1 . min -1 e 172 ± 37 Watts. A idade e a massa corporal foram empregadas como variáveis independentes. Para todos os testes estatísticos aceitou-se o nível de significância de p OBJECTIVE: This study sought to derive generalized equations for predicting maximal workload for young men and women. METHODS: Direct ergospirometry (Aerosport® TEEM 100, USA was used to determine VO2máx and the maximal work load (Wmax on the cycle ergometer test (Monark®, Brazil of thirty men (25 ± 5 years, 75.0 ± 10.7 kg; 48.4 ± 8.8 mL . kg -1 . min -1 and 243 ± 51 Watts and thirty women (26 ± 5 years, 56.7 ± 5.9 kg, 39.8 ± 7.6 mL . kg -1 . min -1 and 172 ± 37 Watts. Age and body mass were used as independent variables. For all statistic tests, a p < 0.05 significance level was adopted. RESULTS: In the multiple linear adjustment, the maximal workload was explained by age and body mass as 54% (r = 0.73 for men, and as 76% (r = 0.87 for women, with standard errors of 0.66 W . kg -1 and 25 Watts. The proposed equations were cross-validated using another sample with similar age and VO2máx characteristics comprised of fifteen men and fifteen women. The intraclass correlation between the predicted Wmax values and those measures by ergospirometry were 0.70 and 0.69, with standard errors of 28.4 and 15.8 Watts, respectively, for men and women. CONCLUSIONS: This study exhibits valid generalized equations for determining the maximal cycle ergonometer workload for men and

  2. Is It Really Self-Control? Examining the Predictive Power of the Delay of Gratification Task

    Science.gov (United States)

    Duckworth, Angela L.; Tsukayama, Eli; Kirby, Teri A.

    2013-01-01

    This investigation tests whether the predictive power of the delay of gratification task (colloquially known as the “marshmallow test”) derives from its assessment of self-control or of theoretically unrelated traits. Among 56 school-age children in Study 1, delay time was associated with concurrent teacher ratings of self-control and Big Five conscientiousness—but not with other personality traits, intelligence, or reward-related impulses. Likewise, among 966 preschool children in Study 2, delay time was consistently associated with concurrent parent and caregiver ratings of self-control but not with reward-related impulses. While delay time in Study 2 was also related to concurrently measured intelligence, predictive relations with academic, health, and social outcomes in adolescence were more consistently explained by ratings of effortful control. Collectively, these findings suggest that delay task performance may be influenced by extraneous traits, but its predictive power derives primarily from its assessment of self-control. PMID:23813422

  3. Quantitative Prediction of Power Loss for Damaged Photovoltaic Modules Using Electroluminescence

    Directory of Open Access Journals (Sweden)

    Timo Kropp

    2018-05-01

    Full Text Available Electroluminescence (EL is a powerful tool for the qualitative mapping of the electronic properties of solar modules, where electronic and electrical defects are easily detected. However, a direct quantitative prediction of electrical module performance purely based on electroluminescence images has yet to be accomplished. Our novel approach, called “EL power prediction of modules” (ELMO as presented here, used just two electroluminescence images to predict the electrical loss of mechanically damaged modules when compared to their original (data sheet power. First, using this method, two EL images taken at different excitation currents were converted into locally resolved (relative series resistance images. From the known, total applied voltage to the module, we were then able to calculate absolute series resistance values and the real distribution of voltages and currents. Then, we reconstructed the complete current/voltage curve of the damaged module. We experimentally validated and confirmed the simulation model via the characterization of a commercially available photovoltaic module containing 60 multicrystalline silicon cells, which were mechanically damaged by hail. Deviation between the directly measured and predicted current/voltage curve was less than 4.3% at the maximum power point. For multiple modules of the same type, the level of error dropped below 1% by calibrating the simulation. We approximated the ideality factor from a module with a known current/voltage curve and then expand the application to modules of the same type. In addition to yielding series resistance mapping, our new ELMO method was also capable of yielding parallel resistance mapping. We analyzed the electrical properties of a commercially available module, containing 72 monocrystalline high-efficiency back contact solar cells, which suffered from potential induced degradation. For this module, we predicted electrical performance with an accuracy of better

  4. Method of critical power prediction based on film flow model coupled with subchannel analysis

    International Nuclear Information System (INIS)

    Tomiyama, Akio; Yokomizo, Osamu; Yoshimoto, Yuichiro; Sugawara, Satoshi.

    1988-01-01

    A new method was developed to predict critical powers for a wide variety of BWR fuel bundle designs. This method couples subchannel analysis with a liquid film flow model, instead of taking the conventional way which couples subchannel analysis with critical heat flux correlations. Flow and quality distributions in a bundle are estimated by the subchannel analysis. Using these distributions, film flow rates along fuel rods are then calculated with the film flow model. Dryout is assumed to occur where one of the film flows disappears. This method is expected to give much better adaptability to variations in geometry, heat flux, flow rate and quality distributions than the conventional methods. In order to verify the method, critical power data under BWR conditions were analyzed. Measured and calculated critical powers agreed to within ±7%. Furthermore critical power data for a tight-latticed bundle obtained by LeTourneau et al. were compared with critical powers calculated by the present method and two conventional methods, CISE correlation and subchannel analysis coupled with the CISE correlation. It was confirmed that the present method can predict critical powers more accurately than the conventional methods. (author)

  5. MAXIM: The Blackhole Imager

    Science.gov (United States)

    Gendreau, Keith; Cash, Webster; Gorenstein, Paul; Windt, David; Kaaret, Phil; Reynolds, Chris

    2004-01-01

    The Beyond Einstein Program in NASA's Office of Space Science Structure and Evolution of the Universe theme spells out the top level scientific requirements for a Black Hole Imager in its strategic plan. The MAXIM mission will provide better than one tenth of a microarcsecond imaging in the X-ray band in order to satisfy these requirements. We will overview the driving requirements to achieve these goals and ultimately resolve the event horizon of a supermassive black hole. We will present the current status of this effort that includes a study of a baseline design as well as two alternative approaches.

  6. 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.

  7. Prediction of power ramp defects - development of a physically based model and evaluation of existing criteria

    International Nuclear Information System (INIS)

    Notley, M.J.F.; Kohn, E.

    2001-01-01

    Power-ramp induced fuel failure is not a problem in the present CANDU reactors. The current empirical correlations that define probability of failure do not agree one-with-another and do not allow extrapolation outside the database. A new methodology, based on physical processes, is presented and compared to data. The methodology calculates the pre-ramp sheath stress and the incremental stress during the ramp, and whether or not there is a defect is predicted based on a failure threshold stress. The proposed model confirms the deductions made by daSilva from an empirical 'fit' to data from the 1988 PNGS power ramp failure incident. It is recommended that daSilvas' correlation be used as reference for OPG (Ontario Power Generation) power reactor fuel, and that extrapolation be performed using the new model. (author)

  8. Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage

    Science.gov (United States)

    Cepowski, Tomasz

    2017-06-01

    The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.

  9. Predicting Power Output of Upper Body using the OMNI-RES Scale

    Directory of Open Access Journals (Sweden)

    Bautista Iker J.

    2014-12-01

    Full Text Available The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males ( voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94 between rating of perceived exertion (RPE and mean bar velocity (Velmean. The Pearson correlation analysis between real power output (PotReal and estimated power (PotEst showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

  10. Predicting Power Output of Upper Body using the OMNI-RES Scale.

    Science.gov (United States)

    Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

    2014-12-09

    The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

  11. Evaluation of Maxim Module-Integrated Electronics at the DOE Regional Test Centers: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Deline, C.; Sekulic, B.; Stein, J.; Barkaszi, S.; Yang, J.; Kahn, S.

    2014-07-01

    Module-embedded power electronics developed by Maxim Integrated are under evaluation through a partnership with the Department of Energy's Regional Test Center (RTC) program. Field deployments of both conventional modules and electronics-enhanced modules are designed to quantify the performance advantage of Maxim's products under different amounts of inter-row shading, and their ability to be deployed at a greater ground-coverage-ratio than conventional modules. Simulations in PVSYST have quantified the predicted performance difference between conventional modules and Maxim's modules from inter-row shading. Initial performance results have identified diffuse irradiance losses at tighter row spacing for both the Maxim and conventional modules. Comparisons with published models show good agreement with models predicting the greatest diffuse irradiance losses. At tighter row spacing, all of the strings equipped with embedded power electronics outperformed their conventional peers. An even greater performance advantage is predicted to occur in the winter months when the amount of inter-row shading mismatch is at a maximum.

  12. Simulation research on multivariable fuzzy model predictive control of nuclear power plant

    International Nuclear Information System (INIS)

    Su Jie

    2012-01-01

    To improve the dynamic control capabilities of the nuclear power plant, the algorithm of the multivariable nonlinear predictive control based on the fuzzy model was applied in the main parameters control of the nuclear power plant, including control structure and the design of controller in the base of expounding the math model of the turbine and the once-through steam generator. The simulation results show that the respond of the change of the gas turbine speed and the steam pressure under the algorithm of multivariable fuzzy model predictive control is faster than that under the PID control algorithm, and the output value of the gas turbine speed and the steam pressure under the PID control algorithm is 3%-5% more than that under the algorithm of multi-variable fuzzy model predictive control. So it shows that the algorithm of multi-variable fuzzy model predictive control can control the output of the main parameters of the nuclear power plant well and get better control effect. (author)

  13. Self-Powered Wireless Sensor Network for Automated Corrosion Prediction of Steel Reinforcement

    Directory of Open Access Journals (Sweden)

    Dan Su

    2018-01-01

    Full Text Available Corrosion is one of the key issues that affect the service life and hinders wide application of steel reinforcement. Moreover, corrosion is a long-term process and not visible for embedded reinforcement. Thus, this research aims at developing a self-powered smart sensor system with integrated innovative prediction module for forecasting corrosion process of embedded steel reinforcement. Vibration-based energy harvester is used to harvest energy for continuous corrosion data collection. Spatial interpolation module was developed to interpolate corrosion data at unmonitored locations. Dynamic prediction module is used to predict the long-term corrosion based on collected data. Utilizing this new sensor network, the corrosion process can be automated predicted and appropriate mitigation actions will be recommended accordingly.

  14. Application of neural networks to signal prediction in nuclear power plant

    International Nuclear Information System (INIS)

    Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

    1993-01-01

    This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

  15. Multivariate power-law models for streamflow prediction in the Mekong Basin

    Directory of Open Access Journals (Sweden)

    Guillaume Lacombe

    2014-11-01

    New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%. A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.

  16. A THEORY OF MAXIMIZING SENSORY INFORMATION

    NARCIS (Netherlands)

    Hateren, J.H. van

    1992-01-01

    A theory is developed on the assumption that early sensory processing aims at maximizing the information rate in the channels connecting the sensory system to more central parts of the brain, where it is assumed that these channels are noisy and have a limited dynamic range. Given a stimulus power

  17. Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

    Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

  18. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    Science.gov (United States)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  19. A Model Predictive Control-Based Power Converter System for Oscillating Water Column Wave Energy Converters

    Directory of Open Access Journals (Sweden)

    Gimara Rajapakse

    2017-10-01

    Full Text Available Despite the predictability and availability at large scale, wave energy conversion (WEC has still not become a mainstream renewable energy technology. One of the main reasons is the large variations in the extracted power which could lead to instabilities in the power grid. In addition, maintaining the speed of the turbine within optimal range under changing wave conditions is another control challenge, especially in oscillating water column (OWC type WEC systems. As a solution to the first issue, this paper proposes the direct connection of a battery bank into the dc-link of the back-to-back power converter system, thereby smoothening the power delivered to the grid. For the second issue, model predictive controllers (MPCs are developed for the rectifier and the inverter of the back-to-back converter system aiming to maintain the turbine speed within its optimum range. In addition, MPC controllers are designed to control the battery current as well, in both charging and discharging conditions. Operations of the proposed battery direct integration scheme and control solutions are verified through computer simulations. Simulation results show that the proposed integrated energy storage and control solutions are capable of delivering smooth power to the grid while maintaining the turbine speed within its optimum range under varying wave conditions.

  20. A numerical approach for size optimization and performance prediction of solar P V-hybrid power systems

    International Nuclear Information System (INIS)

    Zahedi, A.; Calia, N.

    2001-10-01

    Iran is blessed with an abundance of sunlight almost all year round. so obviously, with the right planning and strategies that are coupled to the right technology and development in the market, the potential for the new renewable energies, specially solar photovoltaic, as an alternative source of power looks promising and is constantly gaining popularity. Development and application of new renewable energy in Iran, however, is still in its infancy and will require active support by government, utilities and financing institutions. some experts might argue that Iran has plenty of natural resources like oil and gas. We should not forget, however, that even in countries with cheap fossil energy, the P V system is an economical option in supplying electricity for remote located communities and facilities. But there are good reasons suggesting that like many other countries in the world, Iran also needs to be active in utilization of sun energy. The objectives of this paper are: to give a comprehensive overview on the current solar photovoltaic energy technology. (Authors of this paper believe that Photovoltaic is the most appropriate renewable energy technology for Iran); to present the results obtained from a study which has been carried out on the size optimization, cost calculation of the photovoltaic systems for climate conditions of Iran. The method presented in this paper can be used for systems of any size and application. A further objective of this paper is to present a numerical approach for evaluating the performance of P V-Hybrid power systems. A method is developed to predict the performance of all components integrated into a P V-hybrid system. The system under investigation is a hybrid power system, in which the integrated components are P V array, a battery bank for backing up the system and a diesel generator set for supporting the battery bank. State of charge of batteries is used as a measure for the performance of the system. The running time of

  1. Reserve design to maximize species persistence

    Science.gov (United States)

    Robert G. Haight; Laurel E. Travis

    2008-01-01

    We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and...

  2. 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.

  3. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2011-01-01

    The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid speed overshoots and oscillations for lifetime considerations. Model Predictive...... Direct Current Control (MPDCC) leads to an increase of torque control performance taking into account the discrete nature of inverters but temporary offsets and poor responses to load torque variations are still issues in speed control. A load torque estimator is proposed in this paper in order...

  4. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  5. Model Predictive Control of Grid Connected Modular Multilevel Converter for Integration of Photovoltaic Power Systems

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; Shahirinia, Amir

    2017-01-01

    Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...

  6. Validation of Lifetime Prediction of IGBT Modules Based on Linear Damage Accumulation by Means of Superimposed Power Cycling Tests

    DEFF Research Database (Denmark)

    Choi, Ui-Min; Ma, Ke; Blaabjerg, Frede

    2018-01-01

    In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime ...... prediction of IGBT modules under power converter applications.......In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime...... model in respect to junction temperature swing duration. This model has been built based on 39 power cycling test results of 600-V 30-A three-phase-molded IGBT modules. Six tests are performed under three superimposed power cycling conditions using an advanced power cycling test setup. The experimental...

  7. 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...

  8. PID and predictive control of electrical drives and power converters using MATLAB/Simulink

    CERN Document Server

    Wang, Liuping; Yoo, Dae; Gan, Lu; Ng, Ki

    2015-01-01

    A timely introduction to current research on PID and predictive control by one of the leading authors on the subject PID and Predictive Control of Electric Drives and Power Supplies using MATLAB/Simulink examines the classical control system strategies, such as PID control, feed-forward control and cascade control, which are widely used in current practice.  The authors share their experiences in actual design and implementation of the control systems on laboratory test-beds, taking the reader from the fundamentals through to more sophisticated design and analysis.    The book contains secti

  9. Predicting the radioactive contamination of the surroundings near a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Khristova, M; Paskalev, Z

    1975-01-01

    Predicting the radioactive contamination requires determining the concentration of radioactive material emitted from the stack of a nuclear power plant into the air and deposited on the earth's surface. The main factors determining the degree of contamination are the distance from the stack, the wind velocity and air turbulence. Formulas are presented for predicting the amount of radioactivity as a function of the initial concentration of activity, the distance from the stack and the meteorological condition. Formulas are given for the maximum deposition of radioactive aerosols at a distance R from the stack under wet and dry condtions. 2 refs. (SJR)

  10. Restricted conformal invariance in QCD and its predictive power for virtual two-photon processes

    CERN Document Server

    Müller, D

    1998-01-01

    The conformal algebra provides powerful constraints, which guarantee that renormalized conformally covariant operators exist in the hypothetical conformal limit of the theory, where the $\\beta$-function vanishes. Thus, in this limit also the conformally covariant operator product expansion on the light cone holds true. This operator product expansion has predictive power for two-photon processes in the generalized Bjorken region. Only the Wilson coefficients and the anomalous dimensions that are known from deep inelastic scattering are required for the prediction of all other two-photon processes in terms of the process-dependent off-diagonal expectation values of conformal operators. It is checked that the next-to-leading order calculations for the flavour non-singlet meson transition form factors are consistent with the corrections to the corresponding Wilson coefficients in deep inelasitic scattering.

  11. Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components

    Energy Technology Data Exchange (ETDEWEB)

    Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc

    2017-06-27

    The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.

  12. Prediction and attendance of Angra 2 nuclear power plant cycle extension

    International Nuclear Information System (INIS)

    Dias, Amory; Ferreira Junior, Decio Brandes M.; Morgado, Mario Monteiro; Santos, Barbara Oliveira dos; Oliveira, Monica Georgia Nunes

    2007-01-01

    The Report Project Nuclear and Thermohydraulic (RPNT) of the Nuclear Power Plant Angra 2 previews extension of the cycle, using a feedback of core reactor reactivity, through the reduction of the moderator average temperature and power. In this phase, the reactor power remains almost invariable. Furthermore, the extension of cycle can be stretch after the limit of the temperature reduction has been reached, through of reactor power fall until the determined date for the end cycle and the start outage for the next cycle. The proposal of this work is to show the Power Plant results during the phase of moderator temperature reduction and to compare with the predict values obtained from reactivity balance calculation methodology used for the Reactor Physics. In general, the results of this work can collaborate for the extension behavior evaluation of the cycles of the Nuclear Power Plant 2, being used the procedure of cooling reduction average temperature, as well as, it will also collaborate for methodology qualification applied for the Reactor Physics during the reactivity balance calculation. (author)

  13. Artificial Neural Networks to Predict the Power Output of a PV Panel

    Directory of Open Access Journals (Sweden)

    Valerio Lo Brano

    2014-01-01

    Full Text Available The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs for the power energy output forecasting of photovoltaic (PV modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP, a recursive neural network (RNN, and a gamma memory (GM trained with the back propagation. In order to investigate the influence of climate variability on the electricity production, the ANNs were trained using weather data (air temperature, solar irradiance, and wind speed along with historical power output data available for the two test modules. The model validation was performed by comparing model predictions with power output data that were not used for the network's training. The results obtained bear out the suitability of the adopted methodology for the short-term power output forecasting problem and identified the best topology.

  14. 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.

  15. Comparison of Comet Enflow and VA One Acoustic-to-Structure Power Flow Predictions

    Science.gov (United States)

    Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

    2010-01-01

    Comet Enflow is a commercially available, high frequency vibroacoustic analysis software based on the Energy Finite Element Analysis (EFEA). In this method the same finite element mesh used for structural and acoustic analysis can be employed for the high frequency solutions. Comet Enflow is being validated for a floor-equipped composite cylinder by comparing the EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) results from the commercial software program VA One from ESI Group. Early in this program a number of discrepancies became apparent in the Enflow predicted response for the power flow from an acoustic space to a structural subsystem. The power flow anomalies were studied for a simple cubic, a rectangular and a cylindrical structural model connected to an acoustic cavity. The current investigation focuses on three specific discrepancies between the Comet Enflow and the VA One predictions: the Enflow power transmission coefficient relative to the VA One coupling loss factor; the importance of the accuracy of the acoustic modal density formulation used within Enflow; and the recommended use of fast solvers in Comet Enflow. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 16 Hz to 4000 Hz.

  16. Adaptive on-line prediction of the available power of lithium-ion batteries

    Science.gov (United States)

    Waag, Wladislaw; Fleischer, Christian; Sauer, Dirk Uwe

    2013-11-01

    In this paper a new approach for prediction of the available power of a lithium-ion battery pack is presented. It is based on a nonlinear battery model that includes current dependency of the battery resistance. It results in an accurate power prediction not only at room temperature, but also at lower temperatures at which the current dependency is substantial. The used model parameters are fully adaptable on-line to the given state of the battery (state of charge, state of health, temperature). This on-line adaption in combination with an explicit consideration of differences between characteristics of individual cells in a battery pack ensures an accurate power prediction under all possible conditions. The proposed trade-off between the number of used cell parameters and the total accuracy as well as the optimized algorithm results in a real-time capability of the method, which is demonstrated on a low-cost 16 bit microcontroller. The verification tests performed on a software-in-the-loop test bench system with four 40 Ah lithium-ion cells show promising results.

  17. Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power

    Directory of Open Access Journals (Sweden)

    Mashud Rana

    2016-10-01

    Full Text Available Solar energy generated from PhotoVoltaic (PV systems is one of the most promising types of renewable energy. However, it is highly variable as it depends on the solar irradiance and other meteorological factors. This variability creates difficulties for the large-scale integration of PV power in the electricity grid and requires accurate forecasting of the electricity generated by PV systems. In this paper we consider 2D-interval forecasts, where the goal is to predict summary statistics for the distribution of the PV power values in a future time interval. 2D-interval forecasts have been recently introduced, and they are more suitable than point forecasts for applications where the predicted variable has a high variability. We propose a method called NNE2D that combines variable selection based on mutual information and an ensemble of neural networks, to compute 2D-interval forecasts, where the two interval boundaries are expressed in terms of percentiles. NNE2D was evaluated for univariate prediction of Australian solar PV power data for two years. The results show that it is a promising method, outperforming persistence baselines and other methods used for comparison in terms of accuracy and coverage probability.

  18. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

  19. Hierarchical model-based predictive control of a power plant portfolio

    DEFF Research Database (Denmark)

    Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp

    2011-01-01

    One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...... optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...

  20. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    DEFF Research Database (Denmark)

    Murcia Leon, Juan Pablo; Réthoré, Pierre-Elouan; Natarajan, Anand

    2015-01-01

    (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses...... distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against...... the traditional binning method with trapezoidal and Simpson's integration rules. The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model...

  1. Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    M. Hameedullah

    2010-01-01

    Full Text Available Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM. It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivity

  2. Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

    Institute of Scientific and Technical Information of China (English)

    LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming

    2004-01-01

    Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.

  3. Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

    International Nuclear Information System (INIS)

    Johnson, G.; Lawrence, D.; Yu, H.

    2000-01-01

    The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety function (for the distribution of conditions under which it is expected to respond) upon demand with no unintended functions that might affect system safety. The ultimate objective is to use the identified measures to develop a method for predicting the potential quantitative reliability of a digital system. The reliability prediction models proposed in this report are conceptual in nature. That is, possible prediction techniques are proposed and trial models are built, but in order to become a useful tool for predicting reliability, the models must be tested, modified according to the results, and validated. Using methods outlined by this project, models could be constructed to develop reliability estimates for elements of software systems. This would require careful review and refinement of the models, development of model parameters from actual experience data or expert elicitation, and careful validation. By combining these reliability estimates (generated from the validated models for the constituent parts) in structural software models, the reliability of the software system could then be predicted. Modeling digital system reliability will also require that methods be developed for combining reliability estimates for hardware and software. System structural models must also be developed in order to predict system reliability based upon the reliability

  4. Some Comparisons of Measured and Predicted Primary Radiation Levels in the Aagesta Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Aalto, E; Sandlin, R; Krell, Aa

    1968-05-15

    Neutron fluxes and gamma exposure rates in the primary shields of the Aagesta nuclear plant have been measured and the results compared with values predicted during shield design, and with values obtained later by the NRN bulk shielding code. The input data for the problems are given. The radial predictions are conservative by a factor of not more than 2 close to the reactor and by an unknown, higher factor further out. The conservatism is explainable by the differences between the true local conditions and core power distributions and those assumed in the predictions. The axial flux levels based on streaming calculations are found to agree quite well with the estimated values. The conservatism here is not so large and it seems to be necessary to be very careful when handling streaming problems. The experience gained shows that a power plant is less suitable for studying the accuracy of the shield design codes as such, but the practical results from the combined application of massive shield codes and void streaming predictions to complicated problems give information about the true degree of conservatism present.

  5. Computerized heat balance models to predict performance of operating nuclear power plants

    International Nuclear Information System (INIS)

    Breeding, C.L.; Carter, J.C.; Schaefer, R.C.

    1983-01-01

    The use of computerized heat balance models has greatly enhanced the decision making ability of TVA's Division of Nuclear Power. These models are utilized to predict the effects of various operating modes and to analyze changes in plant performance resulting from turbine cycle equipment modifications with greater speed and accuracy than was possible before. Computer models have been successfully used to optimize plant output by predicting the effects of abnormal condenser circulating water conditions. They were utilized to predict the degradation in performance resulting from installation of a baffle plate assembly to replace damaged low-pressure blading, thereby providing timely information allowing an optimal economic judgement as to when to replace the blading. Future use will be for routine performance test analysis. This paper presents the benefits of utility use of computerized heat balance models

  6. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  7. Kicking Back Cognitive Ageing: Leg Power Predicts Cognitive Ageing after Ten Years in Older Female Twins.

    Science.gov (United States)

    Steves, Claire J; Mehta, Mitul M; Jackson, Stephen H D; Spector, Tim D

    2016-01-01

    Many observational studies have shown a protective effect of physical activity on cognitive ageing, but interventional studies have been less convincing. This may be due to short time scales of interventions, suboptimal interventional regimes or lack of lasting effect. Confounding through common genetic and developmental causes is also possible. We aimed to test whether muscle fitness (measured by leg power) could predict cognitive change in a healthy older population over a 10-year time interval, how this performed alongside other predictors of cognitive ageing, and whether this effect was confounded by factors shared by twins. In addition, we investigated whether differences in leg power were predictive of differences in brain structure and function after 12 years of follow-up in identical twin pairs. A total of 324 healthy female twins (average age at baseline 55, range 43-73) performed the Cambridge Neuropsychological Test Automated Battery (CANTAB) at two time points 10 years apart. Linear regression modelling was used to assess the relationships between baseline leg power, physical activity and subsequent cognitive change, adjusting comprehensively for baseline covariates (including heart disease, diabetes, blood pressure, fasting blood glucose, lipids, diet, body habitus, smoking and alcohol habits, reading IQ, socioeconomic status and birthweight). A discordant twin approach was used to adjust for factors shared by twins. A subset of monozygotic pairs then underwent magnetic resonance imaging. The relationship between muscle fitness and brain structure and function was assessed using linear regression modelling and paired t tests. A striking protective relationship was found between muscle fitness (leg power) and both 10-year cognitive change [fully adjusted model standardised β-coefficient (Stdβ) = 0.174, p = 0.002] and subsequent total grey matter (Stdβ = 0.362, p = 0.005). These effects were robust in discordant twin analyses, where within

  8. New Method of Preparation of Isomers of the (Ca0.1La0.9)(Ba1.6.5La0.35)Cu3Oy Superconductor with Predicted Maximal Tc

    International Nuclear Information System (INIS)

    Knizhnik, A.; Reisner, G.M.; Men, A.; Eckstein, Y.

    1998-01-01

    C only peaks of (c) remain (having the same width as the peaks of (c) prepared via the usual method). After oxygenation to the optimal oxygen doping (y = 7.137) we found that its maximal T c was 63K as predicted. This research was supported by the Israel Science Foundation administered by the Israel Academy of Sciences and Humanities and by the Center of Absorption in Science, Ministry of Immigrant Absorption, State of Israel

  9. Predicting the long tail of book sales: Unearthing the power-law exponent

    Science.gov (United States)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2010-06-01

    The concept of the long tail has recently been used to explain the phenomenon in e-commerce where the total volume of sales of the items in the tail is comparable to that of the most popular items. In the case of online book sales, the proportion of tail sales has been estimated using regression techniques on the assumption that the data obeys a power-law distribution. Here we propose a different technique for estimation based on a generative model of book sales that results in an asymptotic power-law distribution of sales, but which does not suffer from the problems related to power-law regression techniques. We show that the proportion of tail sales predicted is very sensitive to the estimated power-law exponent. In particular, if we assume that the power-law exponent of the cumulative distribution is closer to 1.1 rather than to 1.2 (estimates published in 2003, calculated using regression by two groups of researchers), then our computations suggest that the tail sales of Amazon.com, rather than being 40% as estimated by Brynjolfsson, Hu and Smith in 2003, are actually closer to 20%, the proportion estimated by its CEO.

  10. Maximal Bell's inequality violation for non-maximal entanglement

    International Nuclear Information System (INIS)

    Kobayashi, M.; Khanna, F.; Mann, A.; Revzen, M.; Santana, A.

    2004-01-01

    Bell's inequality violation (BIQV) for correlations of polarization is studied for a product state of two two-mode squeezed vacuum (TMSV) states. The violation allowed is shown to attain its maximal limit for all values of the squeezing parameter, ζ. We show via an explicit example that a state whose entanglement is not maximal allow maximal BIQV. The Wigner function of the state is non-negative and the average value of either polarization is nil

  11. The predictive power of SIMION/SDS simulation software for modeling ion mobility spectrometry instruments

    Science.gov (United States)

    Lai, Hanh; McJunkin, Timothy R.; Miller, Carla J.; Scott, Jill R.; Almirall, José R.

    2008-09-01

    The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOSFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene, 2,7-dinitrofluorene, and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: (1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; (2) a drift gas composition study evaluates the accuracy in predicting the resolution; (3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.

  12. A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

    Science.gov (United States)

    Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

    2018-05-02

    An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (ppredictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

  13. ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

    2007-07-01

    This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.

  14. Wind power application research on the fusion of the determination and ensemble prediction

    Science.gov (United States)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  15. Does the intensity of diffuse thyroid gland uptake on F-18 fluorodeoxyglucose positron emission tomography/computed tomography scan predict the severity of hypothyroidism? Correlation between maximal standardized uptake value and serum thyroid stimulating hormone levels

    International Nuclear Information System (INIS)

    Pruthi, Ankur; Choudhury, Partha Sarathi; Gupta, Manoj; Taywade, Sameer

    2015-01-01

    F-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) scan and hypothyroidism. The aim was to determine whether the intensity of diffuse thyroid gland uptake on F-18 FDG PET/CT scans predicts the severity of hypothyroidism. A retrospective analysis of 3868 patients who underwent F-18 FDG PET/CT scans, between October 2012 and June 2013 in our institution for various oncological indications was done. Out of them, 106 (2.7%) patients (79 females, 27 males) presented with bilateral diffuse thyroid gland uptake as an incidental finding. These patients were investigated retrospectively and various parameters such as age, sex, primary cancer site, maximal standardized uptake value (SUVmax), results of thyroid function tests (TFTs) and fine-needle aspiration cytology results were noted. The SUVmax values were correlated with serum thyroid stimulating hormone (S. TSH) levels using Pearson's correlation analysis. Pearson's correlation analysis. Clinical information and TFT (serum FT3, FT4 and TSH levels) results were available for 31 of the 106 patients (27 females, 4 males; mean age 51.5 years). Twenty-six out of 31 patients (84%) were having abnormal TFTs with abnormal TSH levels in 24/31 patients (mean S. TSH: 22.35 μIU/ml, median: 7.37 μIU/ml, range: 0.074-211 μIU/ml). Among 7 patients with normal TSH levels, 2 patients demonstrated low FT3 and FT4 levels. No significant correlation was found between maximum standardized uptake value and TSH levels (r = 0.115, P > 0.05). Incidentally detected diffuse thyroid gland uptake on F-18 FDG PET/CT scan was usually associated with hypothyroidism probably caused by autoimmune thyroiditis. Patients should be investigated promptly irrespective of the intensity of FDG uptake with TFTs to initiate replacement therapy and a USG examination to look for any suspicious nodules

  16. Maximally Symmetric Composite Higgs Models.

    Science.gov (United States)

    Csáki, Csaba; Ma, Teng; Shu, Jing

    2017-09-29

    Maximal symmetry is a novel tool for composite pseudo Goldstone boson Higgs models: it is a remnant of an enhanced global symmetry of the composite fermion sector involving a twisting with the Higgs field. Maximal symmetry has far-reaching consequences: it ensures that the Higgs potential is finite and fully calculable, and also minimizes the tuning. We present a detailed analysis of the maximally symmetric SO(5)/SO(4) model and comment on its observational consequences.

  17. Computational models for residual creep life prediction of power plant components

    International Nuclear Information System (INIS)

    Grewal, G.S.; Singh, A.K.; Ramamoortry, M.

    2006-01-01

    All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)

  18. Discrete Model Predictive Control-Based Maximum Power Point Tracking for PV Systems: Overview and Evaluation

    DEFF Research Database (Denmark)

    Lashab, Abderezak; Sera, Dezso; Guerrero, Josep M.

    2018-01-01

    The main objective of this work is to provide an overview and evaluation of discrete model predictive controlbased maximum power point tracking (MPPT) for PV systems. A large number of MPC based MPPT methods have been recently introduced in the literature with very promising performance, however......, an in-depth investigation and comparison of these methods have not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC based MPPT methods applied to various common power converter topologies. The performance of MPC based MPPT is directly linked...... with the converter topology, and it is also affected by the accurate determination of the converter parameters, sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers are assessed according to the EN 50530 standard, using detailed simulation models...

  19. Application of an estimation model to predict future transients at US nuclear power plants

    International Nuclear Information System (INIS)

    Hallbert, B.P.; Blackman, H.S.

    1987-01-01

    A model developed by R.A. Fisher was applied to a set of Licensee Event Reports (LERs) summarizing transient initiating events at US commercial nuclear power plants. The empirical Bayes model was examined to study the feasibility of estimating the number of categories of transients which have not yet occurred at nuclear power plants. An examination of the model's predictive ability using an existing sample of data provided support for use of the model to estimate future transients. The estimate indicates that an approximate fifteen percent increase in the number of categories of transient initiating events may be expected during the period 1983--1993, assuming a stable process of transients. Limitations of the model and other possible applications are discussed. 10 refs., 1 fig., 3 tabs

  20. Model Predictive Control of Offshore Power Stations With Waste Heat Recovery

    DEFF Research Database (Denmark)

    Pierobon, Leonardo; Chan, Richard; Li, Xiangan

    2016-01-01

    The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive...... control (MPC) coupled with a steady-state performance optimizer has been developed in the SIMULINK language and is documented in the paper. The test case is the regulation of a power system serving an oil and gas platform in the Norwegian Sea. One of the three gas turbines is combined with an organic...... Rankine cycle (ORC) turbogenerator to increase the energy conversion efficiency. Results show a potential reduction of frequency drop up to 40%for a step in the load set-point of 4 MW, compared to proportional–integral control systems. Fuel savings in the range of 2–3% are also expected by optimizing on...

  1. Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

    Institute of Scientific and Technical Information of China (English)

    Yi Zhang; Xiangjie Liu; Bin Qu

    2017-01-01

    Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

  2. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    International Nuclear Information System (INIS)

    Murcia, J P; Réthoré, P E; Natarajan, A; Sørensen, J D

    2015-01-01

    Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules.The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case. (paper)

  3. A Study of Performance in Low-Power Tokamak Reactor with Integrated Predictive Modeling Code

    International Nuclear Information System (INIS)

    Pianroj, Y.; Onjun, T.; Suwanna, S.; Picha, R.; Poolyarat, N.

    2009-07-01

    Full text: A fusion hybrid or a small fusion power output with low power tokamak reactor is presented as another useful application of nuclear fusion. Such tokamak can be used for fuel breeding, high-level waste transmutation, hydrogen production at high temperature, and testing of nuclear fusion technology components. In this work, an investigation of the plasma performance in a small fusion power output design is carried out using the BALDUR predictive integrated modeling code. The simulations of the plasma performance in this design are carried out using the empirical-based Mixed Bohm/gyro Bohm (B/gB) model, whereas the pedestal temperature model is based on magnetic and flow shear (δ α ρ ζ 2 ) stabilization pedestal width scaling. The preliminary results using this core transport model show that the central ion and electron temperatures are rather pessimistic. To improve the performance, the optimization approach are carried out by varying some parameters, such as plasma current and power auxiliary heating, which results in some improvement of plasma performance

  4. Model Predictive Control of Power Converters for Robust and Fast Operation of AC Microgrids

    DEFF Research Database (Denmark)

    Dragicevic, Tomislav

    2018-01-01

    the load power at the same time. Those functionalities are conventionally achieved by hierarchical linear control loops. However, they have limited transient response and high sensitivity to parameter variations. This paper aims to mitigate these problems by firstly introducing an improvement of the FCS......This paper proposes the application of a finite control set model predictive control (FCS-MPC) strategy in standalone ac microgrids (MGs). AC MGs are usually built from two or more voltage source converters (VSCs) which can regulate the voltage at the point of common coupling, while sharing......-MPC strategy for a single VSC based on tracking of derivative of the voltage reference trajectory. Using only a single step prediction horizon, the proposed strategy exhibits low computational expense but provides steady state performance comparable to PWM, while its transient response and robustness...

  5. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  6. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

    2012-03-15

    To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Nuclear power plant maintenance personnel reliability prediction (NPP/MPRP) effort at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Knee, H.E.; Haas, P.M.; Siegel, A.I.

    1981-01-01

    Human errors committed during maintenance activities are potentially a major contribution to the overall risk associated with the operation of a nuclear power plant (NPP). An NRC-sponsored program at Oak Ridge National Laboratory is attempting to develop a quantitative predictive technique to evaluate the contribution of maintenance errors to the overall NPP risk. The current work includes a survey of the requirements of potential users to ascertain the need for and content of the proposed quantitative model, plus an initial job/task analysis to determine the scope and applicability of various maintenance tasks. In addition, existing human reliability prediction models are being reviewed and assessed with respect to their applicability to NPP maintenance tasks. This paper discusses the status of the program and summarizes the results to date

  8. Model predictive control technologies for efficient and flexible power consumption in refrigeration systems

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Edlund, Kristian

    2012-01-01

    . In this paper we describe a novel economic-optimizing Model Predictive Control (MPC) scheme that reduces operating costs by utilizing the thermal storage capabilities. A nonlinear optimization tool to handle a non-convex cost function is utilized for simulations with validated scenarios. In this way we...... explicitly address advantages from daily variations in outdoor temperature and electricity prices. Secondly, we formulate a new cost function that enables the refrigeration system to contribute with ancillary services to the balancing power market. This involvement can be economically beneficial...... of the system models allows us to describe and handle model as well as prediction uncertainties in this framework. This means we can demonstrate means for robustifying the performance of the controller....

  9. Prediction of critical flow rates through power-operated relief valves

    International Nuclear Information System (INIS)

    Abdollahian, D.; Singh, A.

    1983-01-01

    Existing single-phase and two-phase critical flow models are used to predict the flow rates through the power-operated relief valves tested in the EPRI Safety and Relief Valve test program. For liquid upstream conditions, Homogeneous Equilibrium Model, Moody, Henry-Fauske and Burnell two-phase critical flow models are used for comparison with data. Under steam upstream conditions, the flow rates are predicted either by the single-phase isentropic equations or the Homogeneous Equilibrium Model, depending on the thermodynamic condition of the fluid at the choking plane. The results of the comparisons are used to specify discharge coefficients for different valves under steam and liquid upstream conditions and evaluate the existing approximate critical flow relations for a wide range of subcooled water and steam conditions

  10. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    International Nuclear Information System (INIS)

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

    2012-01-01

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  11. Principles of maximally classical and maximally realistic quantum ...

    Indian Academy of Sciences (India)

    Principles of maximally classical and maximally realistic quantum mechanics. S M ROY. Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India. Abstract. Recently Auberson, Mahoux, Roy and Singh have proved a long standing conjecture of Roy and Singh: In 2N-dimensional phase space, ...

  12. Comparison of LOFT zero power physics testing measurement results with predicted values

    International Nuclear Information System (INIS)

    Rushton, B.L.; Howe, T.M.

    1978-01-01

    The results of zero power physics testing measurements in LOFT have been evaluated to assess the adequacy of the physics data used in the safety analyses performed for the LOFT FSAR and Technical Specifications. Comparisons of measured data with computed data were made for control rod worths, temperature coefficients, boron worths, and pressure coefficients. Measured boron concentrations at exact critical points were compared with predicted concentrations. Based on these comparisons, the reactivity parameter values used in the LOFT safety analyses were assessed for conservatism

  13. Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

    DEFF Research Database (Denmark)

    Ohlrich, Mogens

    2011-01-01

    of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan......Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source...

  14. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2010-01-01

    In drive systems the most used control structure is the cascade control with an inner torque, i.e. current and an outer speed control loop. The fairly small converter switching frequency in high power applications, e.g. wind turbines lead to modest speed control performance. An improvement bring...... the use of a current controller which takes into account the discrete states of the inverter, e.g. DTC or a more modern approach: Model Predictive Direct Current Control (MPDCC). Moreover overshoots and oscillations in the speed are not desired in many applications, since they lead to mechanical stress...

  15. Prediction of accident sequence probabilities in a nuclear power plant due to earthquake events

    International Nuclear Information System (INIS)

    Hudson, J.M.; Collins, J.D.

    1980-01-01

    This paper presents a methodology to predict accident probabilities in nuclear power plants subject to earthquakes. The resulting computer program accesses response data to compute component failure probabilities using fragility functions. Using logical failure definitions for systems, and the calculated component failure probabilities, initiating event and safety system failure probabilities are synthesized. The incorporation of accident sequence expressions allows the calculation of terminal event probabilities. Accident sequences, with their occurrence probabilities, are finally coupled to a specific release category. A unique aspect of the methodology is an analytical procedure for calculating top event probabilities based on the correlated failure of primary events

  16. On accuracy of the wave finite element predictions of wavenumbers and power flow: A benchmark problem

    Science.gov (United States)

    Søe-Knudsen, Alf; Sorokin, Sergey

    2011-06-01

    This rapid communication is concerned with justification of the 'rule of thumb', which is well known to the community of users of the finite element (FE) method in dynamics, for the accuracy assessment of the wave finite element (WFE) method. An explicit formula linking the size of a window in the dispersion diagram, where the WFE method is trustworthy, with the coarseness of a FE mesh employed is derived. It is obtained by the comparison of the exact Pochhammer-Chree solution for an elastic rod having the circular cross-section with its WFE approximations. It is shown that the WFE power flow predictions are also valid within this window.

  17. Aging predictions in nuclear power plants: Crosslinked polyolefin and EPR cable insulation materials

    International Nuclear Information System (INIS)

    Gillen, K.T.; Clough, R.L.

    1991-06-01

    In two earlier reports, we derived a time-temperature-dose rate superposition methodology, which, when applicable, can be used to predict cable degradation versus dose rate, temperature and exposure time. This methodology results in long-term predictive capabilities at the low dose rates appropriate to ambient nuclear power plant aging environments. The methodology was successfully applied to numerous important cable materials used in nuclear applications and the extrapolated predictions were verified by comparisons with long-term (7 to 12 year) results for similar or identical materials aged in nuclear environments. In this report, we test the methodology on three crosslinked polyolefin (CLPO) and two ethylene propylene rubber (EPR) cable insulation materials. The methodology applies to one of the CLPO materials and one of the EPR materials, allowing predictions to be made for these materials under low dose-rate, low temperature conditions. For the other materials, it is determined that, at low temperatures, a decrease in temperature at a constant radiation dose rate leads to an increase in the degradation rate for the mechanical properties. Since these results contradict the fundamental assumption underlying time-temperature-dose rate superposition, this methodology cannot be applied to such data. As indicated in the earlier reports, such anomalous results might be expected when attempting to model data taken across the crystalline melting region of semicrystalline materials. Nonetheless, the existing experimental evidence suggests that these CLPO and EPR materials have substantial aging endurance for typical reactor conditions. 28 refs., 26 figs., 3 tabs

  18. Prediction of crack coalescence of steam generator tubes in nuclear power plants

    International Nuclear Information System (INIS)

    Abou-Hanna, Jeries; McGreevy, Timothy E.; Majumdar, Saurin

    2004-01-01

    Prediction of failure pressures of cracked steam generator tubes of nuclear power plants is an important ingredient in scheduling inspection and repair of tubes. Prediction is usually based on nondestructive evaluation (NDE) of cracks. NDE often reveals two neighboring cracks. If the cracks interact, the tube pressure under which the ligament between the two cracks fails could be much lower than the critical burst pressure of an individual equivalent crack. The ability to accurately predict the ligament failure pressure, called ''coalescence pressure,'' is important. The failure criterion was established by nonlinear finite element model (FEM) analyses of coalescence of two 100% through-wall collinear cracks. The ligament failure is precipitated by local instability of the ligament under plane strain conditions. As a result of this local instability, the ligament thickness in the radial direction decreases abruptly with pressure. Good correlation of FEM analysis results with experimental data obtained at Argonne National Laboratory's Energy Technology Division demonstrated that nonlinear FEM analyses are capable of predicting the coalescence pressure accurately for 100% through-wall cracks. This failure criterion and FEA work have been extended to axial cracks of varying ligament width, crack length, and cases where cracks are offset by axial or circumferential ligaments

  19. Power Transformer Operating State Prediction Method Based on an LSTM Network

    Directory of Open Access Journals (Sweden)

    Hui Song

    2018-04-01

    Full Text Available The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the transformer panorama information are analyzed. The degree of relative deterioration is used to characterize the deterioration of the transformer state. The membership relationship between the relative deterioration degree of each indicator and the transformer state is obtained through fuzzy processing. Through the long short-term memory (LSTM network, the evolution of the transformer status is extracted, and a data-driven state prediction model is constructed to realize preliminary warning of a potential fault of the equipment. Through the LSTM network, the quantitative index and qualitative index are organically combined in order to perceive the corresponding relationship between the characteristic parameters and the operating state of the transformer. The results of different time-scale prediction cases show that the proposed method can effectively predict the operation status of power transformers and accurately reflect their status.

  20. Short-term prediction of windfarm power output - from theory to practice

    International Nuclear Information System (INIS)

    Landberg, L.

    1998-01-01

    From the very complicated and evolved theories of boundary-layer meteorology encompassing the equations of turbulence and mean flow, a model has been derived to predict the power output from wind farms. For practical dispatching purposes the predictions must reach as far into the future as 36 hours. The model has been put into an operation frame-work where the predictions for a number of wind farms scattered all over Europe are available on-line on the World Wide Web. The system is very versatile and new wind farms can be included within a few days. The system is made up of predictions from the Danish Meteorological Institute HIRLAM model which are refined using the WASP model from Risoe National Laboratory. The paper will describe this operation set-up, give examples of the performance of the model of wind farms in the UK, Denmark, Greece and the US. An analysis of the error for a one-year period will also be presented. Finally, possible improvements will be discussed. These include Kalman filtering and other statistical methods. (Author)

  1. A new solar power output prediction based on hybrid forecast engine and decomposition model.

    Science.gov (United States)

    Zhang, Weijiang; Dang, Hongshe; Simoes, Rolando

    2018-06-12

    Regarding to the growing trend of photovoltaic (PV) energy as a clean energy source in electrical networks and its uncertain nature, PV energy prediction has been proposed by researchers in recent decades. This problem is directly effects on operation in power network while, due to high volatility of this signal, an accurate prediction model is demanded. A new prediction model based on Hilbert Huang transform (HHT) and integration of improved empirical mode decomposition (IEMD) with feature selection and forecast engine is presented in this paper. The proposed approach is divided into three main sections. In the first section, the signal is decomposed by the proposed IEMD as an accurate decomposition tool. To increase the accuracy of the proposed method, a new interpolation method has been used instead of cubic spline curve (CSC) fitting in EMD. Then the obtained output is entered into the new feature selection procedure to choose the best candidate inputs. Finally, the signal is predicted by a hybrid forecast engine composed of support vector regression (SVR) based on an intelligent algorithm. The effectiveness of the proposed approach has been verified over a number of real-world engineering test cases in comparison with other well-known models. The obtained results prove the validity of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Seismic response prediction for cabinets of nuclear power plants by using impact hammer test

    Energy Technology Data Exchange (ETDEWEB)

    Koo, Ki Young [Department of Civil and Structural Engineering, University of Sheffield, Sheffield (United Kingdom); Gook Cho, Sung [JACE KOREA, Gyeonggi-do (Korea, Republic of); Cui, Jintao [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of); Kim, Dookie, E-mail: kim2kie@kunsan.ac.k [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of)

    2010-10-15

    An effective method to predict the seismic response of electrical cabinets of nuclear power plants is developed. This method consists of three steps: (1) identification of the earthquake-equivalent force based on the idealized lumped-mass system of the cabinet, (2) identification of the state-space equation (SSE) model of the system using input-output measurements from impact hammer tests, and (3) seismic response prediction by calculating the output of the identified SSE model under the identified earthquake-equivalent force. A three-dimensional plate model of cabinet structures is presented for the numerical verification of the proposed method. Experimental validation of the proposed method is carried out on a three-story frame which represents the structure of a cabinet. The SSE model of the frame is accurately identified by impact hammer tests with high fitness values over 85% of the actual frame characteristics. Shaking table tests are performed using El Centro, Kobe, and Northridge earthquakes as input motions and the acceleration responses are measured. The responses of the model under the three earthquakes are predicted and then compared with the measured responses. The predicted and measured responses agree well with each other with fitness values of 65-75%. The proposed method is more advantageous over other methods that are based on finite element (FE) model updating since it is free from FE modeling errors. It will be especially effective for cabinet structures in nuclear power plants where conducting shaking table tests may not be feasible. Limitations of the proposed method are also discussed.

  3. Maximizing ROI (return on information)

    Energy Technology Data Exchange (ETDEWEB)

    McDonald, B.

    2000-05-01

    The role and importance of managing information are discussed, underscoring the importance by quoting from the report of the International Data Corporation, according to which Fortune 500 companies lost $ 12 billion in 1999 due to inefficiencies resulting from intellectual re-work, substandard performance , and inability to find knowledge resources. The report predicts that this figure will rise to $ 31.5 billion by 2003. Key impediments to implementing knowledge management systems are identified as : the cost and human resources requirement of deployment; inflexibility of historical systems to adapt to change; and the difficulty of achieving corporate acceptance of inflexible software products that require changes in 'normal' ways of doing business. The author recommends the use of model, document and rule-independent systems with a document centered interface (DCI), employing rapid application development (RAD) and object technologies and visual model development, which eliminate these problems, making it possible for companies to maximize their return on information (ROI), and achieve substantial savings in implementation costs.

  4. On the way towards a generalized entropy maximization procedure

    International Nuclear Information System (INIS)

    Bagci, G. Baris; Tirnakli, Ugur

    2009-01-01

    We propose a generalized entropy maximization procedure, which takes into account the generalized averaging procedures and information gain definitions underlying the generalized entropies. This novel generalized procedure is then applied to Renyi and Tsallis entropies. The generalized entropy maximization procedure for Renyi entropies results in the exponential stationary distribution asymptotically for q element of (0,1] in contrast to the stationary distribution of the inverse power law obtained through the ordinary entropy maximization procedure. Another result of the generalized entropy maximization procedure is that one can naturally obtain all the possible stationary distributions associated with the Tsallis entropies by employing either ordinary or q-generalized Fourier transforms in the averaging procedure.

  5. The Predictive Power of Evolutionary Biology and the Discovery of Eusociality in the Naked Mole-Rat.

    Science.gov (United States)

    Braude, Stanton

    1997-01-01

    Discusses how biologists use evolutionary theory and provides examples of how evolutionary biologists test hypotheses on specific modes of selection and evolution. Presents an example of the successful predictive power of one evolutionary hypothesis. Contains 38 references. (DDR)

  6. Natural maximal νμ-ντ mixing

    International Nuclear Information System (INIS)

    Wetterich, C.

    1999-01-01

    The naturalness of maximal mixing between myon- and tau-neutrinos is investigated. A spontaneously broken nonabelian generation symmetry can explain a small parameter which governs the deviation from maximal mixing. In many cases all three neutrino masses are almost degenerate. Maximal ν μ -ν τ -mixing suggests that the leading contribution to the light neutrino masses arises from the expectation value of a heavy weak triplet rather than from the seesaw mechanism. In this scenario the deviation from maximal mixing is predicted to be less than about 1%. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  7. A GLOBAL ASSESSMENT OF SOLAR ENERGY RESOURCES: NASA's Prediction of Worldwide Energy Resources (POWER) Project

    Science.gov (United States)

    Zhang, T.; Stackhouse, P. W., Jr.; Chandler, W.; Hoell, J. M.; Westberg, D.; Whitlock, C. H.

    2010-12-01

    NASA's POWER project, or the Prediction of the Worldwide Energy Resources project, synthesizes and analyzes data on a global scale. The products of the project find valuable applications in the solar and wind energy sectors of the renewable energy industries. The primary source data for the POWER project are NASA's World Climate Research Project (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Release 3.0) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (V 4.0.3). Users of the POWER products access the data through NASA's Surface meteorology and Solar Energy (SSE, Version 6.0) website (http://power.larc.nasa.gov). Over 200 parameters are available to the users. The spatial resolution is 1 degree by 1 degree now and will be finer later. The data covers from July 1983 to December 2007, a time-span of 24.5 years, and are provided as 3-hourly, daily and monthly means. As of now, there have been over 18 million web hits and over 4 million data file downloads. The POWER products have been systematically validated against ground-based measurements, and in particular, data from the Baseline Surface Radiation Network (BSRN) archive, and also against the National Solar Radiation Data Base (NSRDB). Parameters such as minimum, maximum, daily mean temperature and dew points, relative humidity and surface pressure are validated against the National Climate Data Center (NCDC) data. SSE feeds data directly into Decision Support Systems including RETScreen International clean energy project analysis software that is written in 36 languages and has greater than 260,000 users worldwide.

  8. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System

    Directory of Open Access Journals (Sweden)

    Long Wu

    2018-02-01

    Full Text Available Solid oxide fuel cell (SOFC is widely considered as an alternative solution among the family of the sustainable distributed generation. Its load flexibility enables it adjusting the power output to meet the requirements from power grid balance. Although promising, its control is challenging when faced with load changes, during which the output voltage is required to be maintained as constant and fuel utilization rate kept within a safe range. Moreover, it makes the control even more intractable because of the multivariable coupling and strong nonlinearity within the wide-range operating conditions. To this end, this paper developed a multiple model predictive control strategy for reliable SOFC operation. The resistance load is regarded as a measurable disturbance, which is an input to the model predictive control as feedforward compensation. The coupling is accommodated by the receding horizon optimization. The nonlinearity is mitigated by the multiple linear models, the weighted sum of which serves as the final control execution. The merits of the proposed control structure are demonstrated by the simulation results.

  9. Rainfall prediction using fuzzy inference system for preliminary micro-hydro power plant planning

    Science.gov (United States)

    Suprapty, B.; Malani, R.; Minardi, J.

    2018-04-01

    East Kalimantan is a very rich area with water sources, in the form of river streams that branch to the remote areas. The conditions of natural potency like this become alternative solution for area that has not been reached by the availability of electric energy from State Electricity Company. The river water in selected location (catchment area) which is channelled to the canal, pipeline or penstock can be used to drive the waterwheel or turbine. The amount of power obtained depends on the volume/water discharge and headwater (the effective height between the reservoir and the turbine). The water discharge is strongly influenced by the amount of rainfall. Rainfall is the amount of water falling on the flat surface for a certain period measured, in units of mm3, above the horizontal surface in the absence of evaporation, run-off and infiltration. In this study, the prediction of rainfall is done in the area of East Kalimantan which has 13 watersheds which, in principle, have the potential for the construction of Micro Hydro Power Plant. Rainfall time series data is modelled by using AR (Auto Regressive) Model based on FIS (Fuzzy Inference System). The FIS structure of the training results is then used to predict the next two years rainfall.

  10. HEPS4Power - Extended-range Hydrometeorological Ensemble Predictions for Improved Hydropower Operations and Revenues

    Science.gov (United States)

    Bogner, Konrad; Monhart, Samuel; Liniger, Mark; Spririg, Christoph; Jordan, Fred; Zappa, Massimiliano

    2015-04-01

    In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps. The new Swiss Competence Centers in Energy Research (SCCER) targets at boosting research related to energy issues in Switzerland. The objective of HEPS4POWER is to demonstrate that operational extended-range hydro meteorological forecasts have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). The first task of the HEPS4POWER will be the downscaling and post-processing of ensemble extended-range meteorological forecasts (EPS). The goal is to provide well-tailored forecasts of probabilistic nature that should be reliable in statistical and localized at catchment or even station level. The hydrology related task will consist in feeding the post-processed meteorological forecasts into a HEPS using a multi-model approach by implementing models with different complexity. Also in the case of the hydrological ensemble predictions, post-processing techniques need to be tested in order to improve the quality of the

  11. Predictive Ability of the Medicine Ball Chest Throw and Vertical Jump Tests for Determining Muscular Strength and Power in Adolescents

    Science.gov (United States)

    Hackett, Daniel A.; Davies, Timothy B.; Ibel, Denis; Cobley, Stephen; Sanders, Ross

    2018-01-01

    This study examined the predictive ability of the medicine ball chest throw and vertical jump for muscular strength and power in adolescents. One hundred and ninety adolescents participated in this study. Participants performed trials of the medicine ball chest throw and vertical jump, with vertical jump peak power calculated via an estimation…

  12. Predictive value of pretreatment metabolic activity measured by fluorodeoxyglucose positron emission tomography in patients with metastatic advanced gastric cancer: the maximal SUV of the stomach is a prognostic factor

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jun Chul; Cheoi, Kungseok; Chung, Hyunsoo; Lee, Hyuk; Shin, Sung Kwan; Lee, Sang Kil; Lee, Yong Chan [Yonsei University College of Medicine, Department of Internal Medicine and Institute of Gastroenterology, Seoul (Korea, Republic of); Lee, Jae-Hoon; Yun, Mi Jin [Yonsei University College of Medicine, Department of Nuclear Medicine, Seoul (Korea, Republic of)

    2012-07-15

    Few studies have evaluated metabolic activity by {sup 18}F-FDG PET as a prognostic factor in advanced gastric cancer (AGC). We investigated its prognostic role in metastatic AGC. We enrolled 82 patients with metastatic AGC, who were treatment-naive and underwent pretreatment {sup 18}F-FDG PET/CT scanning. In each patient, the maximal standardized uptake value (SUVmax) was measured in each target lesion. Stomach{sub SUVmax} was defined as SUVmax in the stomach, while Total{sub SUVmax} was defined as the highest SUVmax among all the target lesions. The stomach was the organ most frequently displaying the highest SUVmax among all the target lesions (in 67.1 % of patients). A Total{sub SUVmax} value of 11.5 was the value with the maximum sum of sensitivity and specificity from receiver-operating characteristic curves for progression-free survival (PFS). PFS was significantly longer in patients with a Total{sub SUVmax} value <11.5 than in those with a Total{sub SUVmax} value {>=}11.5 (P = 0.023); however, overall survival (OS) was not (P = 0.055). A Stomach{sub SUVmax} value of 6.0 was derived by similar methods. PFS and OS were significantly longer in those with a Stomach{sub SUVmax} value <6.0 than in those with a Stomach{sub SUVmax} value {>=}6.0 (P = 0.001 and P = 0.006, respectively). Furthermore, those with a low Total{sub SUVmax} and those with a low Stomach{sub SUVmax} showed better chemotherapeutic responses (P = 0.016 and P = 0.034, respectively). Among patients with histologically undifferentiated carcinomas, those with lower Total{sub SUVmax} and those with lower Stomach{sub SUVmax} showed longer median PFS (P = 0.027 and P = 0.005, respectively) and OS (P = 0.009 and P <0.001, respectively). Multivariate analysis demonstrated Stomach{sub SUVmax} as an independent predictor of PFS (P = 0.002) and OS (P = 0.038). Pretreatment metabolic activity may be a useful prognostic marker in patients with metastatic AGC undergoing palliative chemotherapy. Notably

  13. Decentralized model predictive based load frequency control in an interconnected power system

    Energy Technology Data Exchange (ETDEWEB)

    Mohamed, T.H., E-mail: tarekhie@yahoo.co [High Institute of Energy, South Valley University (Egypt); Bevrani, H., E-mail: bevrani@ieee.or [Dept. of Electrical Engineering and Computer Science, University of Kurdistan (Iran, Islamic Republic of); Hassan, A.A., E-mail: aahsn@yahoo.co [Faculty of Engineering, Dept. of Electrical Engineering, Minia University, Minia (Egypt); Hiyama, T., E-mail: hiyama@cs.kumamoto-u.ac.j [Dept. of Electrical Engineering and Computer Science, Kumamoto University, Kumamoto (Japan)

    2011-02-15

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  14. Predicting the outcomes of performance error indicators on accreditation status in the nuclear power industry

    International Nuclear Information System (INIS)

    Wilson, P.A.

    1986-01-01

    The null hypothesis for this study suggested that there was no significant difference in the types of performance error indicators between accredited and non-accredited programs on the following types of indicators: (1) number of significant event reports per unit, (2) number of forced outages per unit, (3) number of unplanned automatic scrams per unit, and (4) amount of equivalent availability per unit. A sample of 90 nuclear power plants was selected for this study. Data were summarized from two data bases maintained by the Institute of Nuclear Power Operations. Results of this study did not support the research hypothesis. There was no significant difference between the accredited and non-accredited programs on any of the four performance error indicators. The primary conclusions of this include the following: (1) The four selected performance error indicators cannot be used individually or collectively to predict accreditation status in the nuclear power industry. (2) Annual performance error indicator ratings cannot be used to determine the effects of performance-based training on plant performance. (3) The four selected performance error indicators cannot be used to measure the effect of operator job performance on plant effectiveness

  15. Decentralized model predictive based load frequency control in an interconnected power system

    International Nuclear Information System (INIS)

    Mohamed, T.H.; Bevrani, H.; Hassan, A.A.; Hiyama, T.

    2011-01-01

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  16. Mid-term load forecasting of power systems by a new prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    Mid-term load forecasting (MTLF) becomes an essential tool for today power systems, mainly in those countries whose power systems operate in a deregulated environment. Among different kinds of MTLF, this paper focuses on the prediction of daily peak load for one month ahead. This kind of load forecast has many applications like maintenance scheduling, mid-term hydro thermal coordination, adequacy assessment, management of limited energy units, negotiation of forward contracts, and development of cost efficient fuel purchasing strategies. However, daily peak load is a nonlinear, volatile, and nonstationary signal. Besides, lack of sufficient data usually further complicates this problem. The paper proposes a new methodology to solve it, composed of an efficient data model, preforecast mechanism and combination of neural network and evolutionary algorithm as the hybrid forecast technique. The proposed methodology is examined on the EUropean Network on Intelligent TEchnologies (EUNITE) test data and Iran's power system. We will also compare our strategy with the other MTLF methods revealing its capability to solve this load forecast problem

  17. Evaluation of Haddam Neck (Connecticut Yankee) Nuclear Power Plant, environmental impact prediction, based on monitoring programs

    International Nuclear Information System (INIS)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Mahaffey, J.A.; Waton, D.G.

    1976-12-01

    A study was undertaken by the U.S. Nuclear Regulatory Commission (NRC) to evaluate the nonradiological environmental data obtained from three nuclear power plants operating for a period of one year or longer. The document presented reports the second of three nuclear power plants to be evaluated in detail by Battelle, Pacific Northwest Laboratories. Haddam Neck (Connecticut Yankee) Nuclear Power Plant nonradiological monitoring data were assessed to determine their effectiveness in the measurement of environmental impacts. Efforts were made to determine if: (1) monitoring programs, as designed, can detect environmental impacts, (2) appropriate statistical analyses were performed and if they were sensitive enough to detect impacts, (3) predicted impacts could be verified by monitoring programs, and (4) monitoring programs satisfied the requirements of the Environmental Technical Specifications. Both preoperational and operational monitoring data were examined to test the usefulness of baseline information in evaluating impacts. This included an examination of the methods used to measure ecological, chemical, and physical parameters, and an assessment of sampling periodicity and sensitivity where appropriate data sets were available. From this type of analysis, deficiencies in both preoperational and operational monitoring programs may be identified and provide a basis for suggested improvement

  18. Nitrogen oxides emissions from thermal power plants in china: current status and future predictions.

    Science.gov (United States)

    Tian, Hezhong; Liu, Kaiyun; Hao, Jiming; Wang, Yan; Gao, Jiajia; Qiu, Peipei; Zhu, Chuanyong

    2013-10-01

    Increasing emissions of nitrogen oxides (NOx) over the Chinese mainland have been of great concern due to their adverse impacts on regional air quality and public health. To explore and obtain the temporal and spatial characteristics of NOx emissions from thermal power plants in China, a unit-based method is developed. The method assesses NOx emissions based on detailed information on unit capacity, boiler and burner patterns, feed fuel types, emission control technologies, and geographical locations. The national total NOx emissions in 2010 are estimated at 7801.6 kt, of which 5495.8 kt is released from coal-fired power plant units of considerable size between 300 and 1000 MW. The top provincial emitter is Shandong where plants are densely concentrated. The average NOx-intensity is estimated at 2.28 g/kWh, markedly higher than that of developed countries, mainly owing to the inadequate application of high-efficiency denitrification devices such as selective catalytic reduction (SCR). Future NOx emissions are predicted by applying scenario analysis, indicating that a reduction of about 40% by the year 2020 can be achieved compared with emissions in 2010. These results suggest that NOx emissions from Chinese thermal power plants could be substantially mitigated within 10 years if reasonable control measures were implemented effectively.

  19. Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

    Energy Technology Data Exchange (ETDEWEB)

    Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev; Tang, Zhijun; Smith, Kandler; Shi, Ying

    2016-08-01

    This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of battery aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.

  20. Prediction of concrete compressive strength considering humidity and temperature in the construction of nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Seung Hee; Jang, Kyung Pil [Department of Civil and Environmental Engineering, Myongji University, Yongin (Korea, Republic of); Bang, Jin-Wook [Department of Civil Engineering, Chungnam National University, Daejeon (Korea, Republic of); Lee, Jang Hwa [Structural Engineering Research Division, Korea Institute of Construction Technology (Korea, Republic of); Kim, Yun Yong, E-mail: yunkim@cnu.ac.kr [Structural Engineering Research Division, Korea Institute of Construction Technology (Korea, Republic of)

    2014-08-15

    Highlights: • Compressive strength tests for three concrete mixes were performed. • The parameters of the humidity-adjusted maturity function were determined. • Strength can be predicted considering temperature and relative humidity. - Abstract: This study proposes a method for predicting compressive strength developments in the early ages of concretes used in the construction of nuclear power plants. Three representative mixes with strengths of 6000 psi (41.4 MPa), 4500 psi (31.0 MPa), and 4000 psi (27.6 MPa) were selected and tested under various curing conditions; the temperature ranged from 10 to 40 °C, and the relative humidity from 40 to 100%. In order to consider not only the effect of the temperature but also that of humidity, an existing model, i.e. the humidity-adjusted maturity function, was adopted and the parameters used in the function were determined from the test results. A series of tests were also performed in the curing condition of a variable temperature and constant humidity, and a comparison between the measured and predicted strengths were made for the verification.

  1. Exploring the predictive power of interaction terms in a sophisticated risk equalization model using regression trees.

    Science.gov (United States)

    van Veen, S H C M; van Kleef, R C; van de Ven, W P M M; van Vliet, R C J A

    2018-02-01

    This study explores the predictive power of interaction terms between the risk adjusters in the Dutch risk equalization (RE) model of 2014. Due to the sophistication of this RE-model and the complexity of the associations in the dataset (N = ~16.7 million), there are theoretically more than a million interaction terms. We used regression tree modelling, which has been applied rarely within the field of RE, to identify interaction terms that statistically significantly explain variation in observed expenses that is not already explained by the risk adjusters in this RE-model. The interaction terms identified were used as additional risk adjusters in the RE-model. We found evidence that interaction terms can improve the prediction of expenses overall and for specific groups in the population. However, the prediction of expenses for some other selective groups may deteriorate. Thus, interactions can reduce financial incentives for risk selection for some groups but may increase them for others. Furthermore, because regression trees are not robust, additional criteria are needed to decide which interaction terms should be used in practice. These criteria could be the right incentive structure for risk selection and efficiency or the opinion of medical experts. Copyright © 2017 John Wiley & Sons, Ltd.

  2. Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling.

    Science.gov (United States)

    Townsend, Nathan E; Nichols, David S; Skiba, Philip F; Racinais, Sebastien; Périard, Julien D

    2017-01-01

    Purpose: Develop a prediction equation for critical power (CP) and work above CP (W') in hypoxia for use in the work-balance ([Formula: see text]) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W' at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W' at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W' were used to compute W' during HIIT using differential ([Formula: see text]) and integral ([Formula: see text]) forms of the [Formula: see text] model. Results: CP decreased at altitude ( P equations for CP and W' developed in this study are suitable for use with the [Formula: see text] model in acute hypoxia. This enables the application of [Formula: see text] modelling to training prescription and competition analysis at altitude.

  3. A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

    International Nuclear Information System (INIS)

    Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan

    2013-01-01

    This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.

  4. SIEX design predictions for the PNC fuel pins in the HEDL P-E01 power-to-melt test

    International Nuclear Information System (INIS)

    1979-01-01

    During the design phase of the HEDL P-E01 power-to-melt test, a series of design predictions were generated for the three PNC pins using the SIEX fuel pin modeling code. This document tabulates a series of selected PNC pin design predictions as requested by M. Shinohara during his visit to HEDL

  5. Gray model prediction of the sea wall profile survey in the first process of Qinshan Nuclear Power Plant

    International Nuclear Information System (INIS)

    Zang Deyan

    1998-01-01

    Based on gray system theory, the information about deformation observation of the first stage Qinshan nuclear power plant is analysed and predicted as well. The gray system theory is applied to engineering prediction and a large-scale building deformation observation. It is convenient to apply the model and it a has high degree of accuracy

  6. What currency do bumble bees maximize?

    Directory of Open Access Journals (Sweden)

    Nicholas L Charlton

    2010-08-01

    Full Text Available In modelling bumble bee foraging, net rate of energetic intake has been suggested as the appropriate currency. The foraging behaviour of honey bees is better predicted by using efficiency, the ratio of energetic gain to expenditure, as the currency. We re-analyse several studies of bumble bee foraging and show that efficiency is as good a currency as net rate in terms of predicting behaviour. We suggest that future studies of the foraging of bumble bees should be designed to distinguish between net rate and efficiency maximizing behaviour in an attempt to discover which is the more appropriate currency.

  7. A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Yanzi Wang

    2016-01-01

    Full Text Available Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for an active parallel battery-UC HESS. The proposed power management strategy; the inputs for which are the vehicle speed; the current electric power demand and the predicted electric power demand; is used to distribute the electrical power between the battery bank and the UC bank. In this way; the battery bank power is limited to a certain range; and the peak and average charge/discharge power of the battery bank and overall loss incurred by the whole HESS are also reduced. Simulations and scaled-down experimental platforms are constructed to verify the proposed power management strategy. The simulations and experimental results demonstrate the advantages; feasibility and effectiveness of the fuzzy-logic power management strategy based on Markov random prediction.

  8. Implications of maximal Jarlskog invariant and maximal CP violation

    International Nuclear Information System (INIS)

    Rodriguez-Jauregui, E.; Universidad Nacional Autonoma de Mexico

    2001-04-01

    We argue here why CP violating phase Φ in the quark mixing matrix is maximal, that is, Φ=90 . In the Standard Model CP violation is related to the Jarlskog invariant J, which can be obtained from non commuting Hermitian mass matrices. In this article we derive the conditions to have Hermitian mass matrices which give maximal Jarlskog invariant J and maximal CP violating phase Φ. We find that all squared moduli of the quark mixing elements have a singular point when the CP violation phase Φ takes the value Φ=90 . This special feature of the Jarlskog invariant J and the quark mixing matrix is a clear and precise indication that CP violating Phase Φ is maximal in order to let nature treat democratically all of the quark mixing matrix moduli. (orig.)

  9. Prediction of Decommissioning Cost for Kijang Research Reactor Using Power Data of DACCORD

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Yun Jeong; Jin, Hyung Gon; Park, Hee Seong; Park, Seung Kook [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    There are 3 types of cost estimate that can be used, and each have a different level of accuracy: (i) Order of magnitude estimate: One without detailed engineering data, where an estimate is prepared using scale-up or -down factors and approximate ratios. It is likely that the overall scope of the project has not been well defined. The level of accuracy expected is -30% to +50%. The cost plans to predict referring to abroad examples as decommissioning cost estimation has still not developed and been commercial method for Kijang research reactor. In Kijang research reactor case, overall scope of business isn't yet decided. Then it is supposed to estimate cost with type (i). The IAEA project, entitled 'DACCORD' (Data Analysis and Collection for Costing of Research Reactor Decommissioning) performs decommissioning costing after collecting and analyzing the information related to research reactors around the world for several years. Also decommissioning costing method development tends to increase in the each country. This paper aims to estimate preliminary decommissioning cost based on total decommissioning cost per thermal power rate of research reactor presented in DACCORD project' data which is collected by member state. In this paper, preliminary decommissioning cost is estimated based on total decommissioning cost per thermal power rate of research reactor presented in DACCORD data which is collected by member state. Although there exists a general tendency for costs to increase with increasing thermal power, the limited data available show that decommissioning costs at any given power level can vary widely, with increased variability at higher power levels. Variations in decommissioning cost for the research reactors of the same or similar thermal power are caused by differences in reactor types and design, decommissioning project scopes, country- specific unit workforce costs, and other reactor or project factors. An important factor for the

  10. Predictive maintenance: A new approach in maintenance of nuclear power plants

    International Nuclear Information System (INIS)

    Benvenuto, F.; Ferrari, L.

    2005-01-01

    The maintenance services for a Nuclear Power Plant are in general aimed at reaching the following goals: - Increase component availability and consequently decrease intervention frequency; - Reduce unexpected costs from unexpected repairs; - Progressively decrease the time of each intervention; - Improve the spare parts supply efficiency; - Improve spare parts and consumable warehouse managing; - Decrease maintenance costs. Most of the currently used maintenance activities refer to run-to-failure or preventive approaches: - Run-to-failure or Corrective Maintenance means that work is only carried out when a component or system is faulty and unable to perform its critical function. Non critical components such as filters or components with spare may be maintained in this way; - Preventive or Scheduled Maintenance involves a regular pre-set schedule programme of maintenance work. Programme outlined by the manufacturer of the component in question based on the design life of the component and based on past experience by operation. One step further than Preventive Maintenance is represented by Predictive Maintenance. Whereas Preventive Maintenance bases its schedules on past performance data, a predictive system acquires condition data from the machine to be maintained whilst the machine is in operation. The information obtained from this analysis indicates the condition in real time, provides a diagnosis of wear and shows any trend towards critical conditions. Predictive maintenance mainly consists of the following interventions: - Lubricant analysis; - Collection / analysis of functional parameters, such as motor absorption, flow rate, pressure, temperature, noise, vibration of rotating equipment, thermal efficiency, etc; - Periodical test of lifting systems; - Other operations to acquire sensitive equipment parameters. Predictive Maintenance can reduce the accidental intervention and extend the components life, and, in the end, is increasing the global availability

  11. Phenomenology of maximal and near-maximal lepton mixing

    International Nuclear Information System (INIS)

    Gonzalez-Garcia, M. C.; Pena-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.

    2001-01-01

    The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ε(equivalent to)1-2sin 2 θ ex and quantify the present experimental status for |ε| e mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10 -8 eV 2 ∼ 2 ∼ -7 eV 2 . In the mass ranges Δm 2 ∼>1.5x10 -5 eV 2 and 4x10 -10 eV 2 ∼ 2 ∼ -7 eV 2 the full interval |ε| e mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay

  12. Maximal quantum Fisher information matrix

    International Nuclear Information System (INIS)

    Chen, Yu; Yuan, Haidong

    2017-01-01

    We study the existence of the maximal quantum Fisher information matrix in the multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various trade-off relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. (paper)

  13. Power Prediction and Technoeconomic Analysis of a Solar PV Power Plant by MLP-ABC and COMFAR III, considering Cloudy Weather Conditions

    Directory of Open Access Journals (Sweden)

    M. Khademi

    2016-01-01

    Full Text Available The prediction of power generated by photovoltaic (PV panels in different climates is of great importance. The aim of this paper is to predict the output power of a 3.2 kW PV power plant using the MLP-ABC (multilayer perceptron-artificial bee colony algorithm. Experimental data (ambient temperature, solar radiation, and relative humidity was gathered at five-minute intervals from Tehran University’s PV Power Plant from September 22nd, 2012, to January 14th, 2013. Following data validation, 10665 data sets, equivalent to 35 days, were used in the analysis. The output power was predicted using the MLP-ABC algorithm with the mean absolute percentage error (MAPE, the mean bias error (MBE, and correlation coefficient (R2, of 3.7, 3.1, and 94.7%, respectively. The optimized configuration of the network consisted of two hidden layers. The first layer had four neurons and the second had two neurons. A detailed economic analysis is also presented for sunny and cloudy weather conditions using COMFAR III software. A detailed cost analysis indicated that the total investment’s payback period would be 3.83 years in sunny periods and 4.08 years in cloudy periods. The results showed that the solar PV power plant is feasible from an economic point of view in both cloudy and sunny weather conditions.

  14. 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.

  15. Factors in Maximal Power Production and in Exercise Endurance Relative to Maximal Power

    Science.gov (United States)

    1988-10-13

    Mechanical efficiency of fast -and slow - twitch muscle fibers in mnan during cycling. J. ADLi Physiol.:Reespirat. Environ. Exercise Physiol. 47: 263- 267...R.S. Hikida, and F.C. Hagerman. Myofibrillar ATPase activity in hu-man muscle fast - twitch subtypes. Histochem. 78: 405-408, 1983. 31. Suzuki, Y...capacity and muscle fibre composition in mnan. J. Physiol (London) 354: 73P, 1984. 21. Margaria, R., P. Aghemo, and E. Rovelli. Measurement of muscular

  16. Probabilistic methods for condition assessment and life prediction of concrete structures in nuclear power plants

    International Nuclear Information System (INIS)

    Ellingwood, B.R.; Mori, Yasuhiro

    1993-01-01

    A probability-based methodology is being developed in support of the NRC Structural Aging Program to assist in evaluating the reliability of existing concrete structures in nuclear power plants under potential future operating loads and extreme evironmental and accidental events. The methodology includes models to predict structural deterioration due to environmental stressors, a database to support the use of these models, and methods for analyzing time-dependent reliability of concrete structural components subjected to stochastic loads. The methodology can be used to support a plant license extension application by providing evidence that safety-related concrete structures in their current (service) condition are able to withstand future extreme events with a level of reliability sufficient for public health and safety. (orig.)

  17. Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility......The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... observed for the different interferers. None of the standardized models successfully describe these data....

  18. Kinetic model for predicting the composition of chlorinated water discharged from power plant cooling systems

    International Nuclear Information System (INIS)

    Lietzke, M.H.

    1977-01-01

    A kinetic model for predicting the composition of chlorinated water discharged from power plant cooling systems has been developed. The model incorporates the most important chemical reactions that are known to occur when chlorine is added to natural fresh waters. The simultaneous differential equations, which describe the rates of these chemical reactions, are solved numerically to give the composition of the water as a function of time. A listing of the computer program is included, along with a description of the input variables. A worked-out example illustrates the application of the program to an actual cooling system. An appendix contains a compilation of the known equilibrium and kinetic data for many of the chemical reactions that might be encountered in chlorinating natural fresh waters

  19. Maximize x(a - x)

    Science.gov (United States)

    Lange, L. H.

    1974-01-01

    Five different methods for determining the maximizing condition for x(a - x) are presented. Included is the ancient Greek version and a method attributed to Fermat. None of the proofs use calculus. (LS)

  20. Finding Maximal Quasiperiodicities in Strings

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Pedersen, Christian N. S.

    2000-01-01

    of length n in time O(n log n) and space O(n). Our algorithm uses the suffix tree as the fundamental data structure combined with efficient methods for merging and performing multiple searches in search trees. Besides finding all maximal quasiperiodic substrings, our algorithm also marks the nodes......Apostolico and Ehrenfeucht defined the notion of a maximal quasiperiodic substring and gave an algorithm that finds all maximal quasiperiodic substrings in a string of length n in time O(n log2 n). In this paper we give an algorithm that finds all maximal quasiperiodic substrings in a string...... in the suffix tree that have a superprimitive path-label....

  1. On the maximal diphoton width

    CERN Document Server

    Salvio, Alberto; Strumia, Alessandro; Urbano, Alfredo

    2016-01-01

    Motivated by the 750 GeV diphoton excess found at LHC, we compute the maximal width into $\\gamma\\gamma$ that a neutral scalar can acquire through a loop of charged fermions or scalars as function of the maximal scale at which the theory holds, taking into account vacuum (meta)stability bounds. We show how an extra gauge symmetry can qualitatively weaken such bounds, and explore collider probes and connections with Dark Matter.

  2. Prediction of Francis Turbine Prototype Part Load Pressure and Output Power Fluctuations with Hydroelectric Model

    Science.gov (United States)

    Alligné, S.; Nicolet, C.; Béguin, A.; Landry, C.; Gomes, J.; Avellan, F.

    2017-04-01

    The prediction of pressure and output power fluctuations amplitudes on Francis turbine prototype is a challenge for hydro-equipment industry since it is subjected to guarantees to ensure smooth and reliable operation of the hydro units. The European FP7 research project Hyperbole aims to setup a methodology to transpose the pressure fluctuations induced by the cavitation vortex rope from the reduced scale model to the prototype generating units. A Francis turbine unit of 444MW with a specific speed value of ν = 0.29, is considered as case study. A SIMSEN model of the power station including electrical system, controllers, rotating train and hydraulic system with transposed draft tube excitation sources is setup. Based on this model, a frequency analysis of the hydroelectric system is performed for all technologies to analyse potential interactions between hydraulic excitation sources and electrical components. Three technologies have been compared: the classical fixed speed configuration with Synchronous Machine (SM) and the two variable speed technologies which are Doubly Fed Induction Machine (DFIM) and Full Size Frequency Converter (FSFC).

  3. Past as Prediction: Newcomb, Huxley, The Eclipse of Thales, and The Power of Science

    Science.gov (United States)

    Stanley, Matthew

    2009-12-01

    The ancient eclipse of Thales was an important, if peculiar, focus of scientific attention in the 19th century. Victorian-era astronomers first used it as data with which to calibrate their lunar theories, but its status became strangely malleable as the century progressed. The American astronomer Simon Newcomb re-examined the eclipse and rejected it as the basis for lunar theory. But strangely, it was the unprecedented accuracy of Newcomb's calculations that led the British biologist T.H. Huxley to declare the eclipse to be the quintessential example of the power of science. Huxley argued that astronomy's ability to create "retrospective prophecy” showed how scientific reasoning was superior to religion (and incidentally, helped support Darwin's theories). Both Newcomb and Huxley declared that prediction (of past and future) was what gave science its persuasive power. The eclipse of Thales's strange journey through Victorian astronomy reveals how these two influential scientists made the case for the social and cultural authority of science.

  4. Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Roberto Carlos dos; Pereira, Iraci Martinez, E-mail: rcsantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

  5. Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

    International Nuclear Information System (INIS)

    Santos, Roberto Carlos dos; Pereira, Iraci Martinez

    2011-01-01

    This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

  6. DR2DI: a powerful computational tool for predicting novel drug-disease associations

    Science.gov (United States)

    Lu, Lu; Yu, Hua

    2018-05-01

    Finding the new related candidate diseases for known drugs provides an effective method for fast-speed and low-risk drug development. However, experimental identification of drug-disease associations is expensive and time-consuming. This motivates the need for developing in silico computational methods that can infer true drug-disease pairs with high confidence. In this study, we presented a novel and powerful computational tool, DR2DI, for accurately uncovering the potential associations between drugs and diseases using high-dimensional and heterogeneous omics data as information sources. Based on a unified and extended similarity kernel framework, DR2DI inferred the unknown relationships between drugs and diseases using Regularized Kernel Classifier. Importantly, DR2DI employed a semi-supervised and global learning algorithm which can be applied to uncover the diseases (drugs) associated with known and novel drugs (diseases). In silico global validation experiments showed that DR2DI significantly outperforms recent two approaches for predicting drug-disease associations. Detailed case studies further demonstrated that the therapeutic indications and side effects of drugs predicted by DR2DI could be validated by existing database records and literature, suggesting that DR2DI can be served as a useful bioinformatic tool for identifying the potential drug-disease associations and guiding drug repositioning. Our software and comparison codes are freely available at https://github.com/huayu1111/DR2DI.

  7. The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems.

    Science.gov (United States)

    Reafee, Waleed; Salim, Naomie; Khan, Atif

    2016-01-01

    The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy.

  8. Basic tuning of hydrogen powered car and artificial intelligent prediction of hydrogen engine characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Ho, Tien [School of Engineering, University of Tasmania, GPO Box 252-65, Hobart, Tasmania, 7001 (Australia); Karri, Vishy [Australian College of Kuwait, P.O. Box 1411, Safat 13015 (Kuwait)

    2010-09-15

    Many studies of renewable energy have shown hydrogen is one of the major green energy in the future. This has lead to the development of many automotive application of using hydrogen as a fuel especially in internal combustion engine. Nonetheless, there has been a slow growth and less knowledge details in building up the prototype and control methodology of the hydrogen internal combustion engine. In this paper, The Toyota Corolla 4 cylinder, 1.8l engine running on petrol was systematically modified in such a way that it could be operated on either gasoline or hydrogen at the choice of the driver. Within the scope of this project, several ancillary instruments such as a new inlet manifold, hydrogen fuel injection, storage system and leak detection safety system were implemented. Attention is directed towards special characteristics related to the basic tuning of hydrogen engine such as: air to fuel ratio operating conditions, ignition timing and injection timing in terms of different engine speed and throttle position. Based on the experimental data, a suite of neural network models were tested to accurately predict the effect of different engine operating conditions (speed and throttle position) on the hydrogen powered car engine characteristics. Predictions were found to be {+-}3% to the experimental values for all of case studies. This work provided better understanding of the effect of hydrogen engine characteristic parameters on different engine operating conditions. (author)

  9. DR2DI: a powerful computational tool for predicting novel drug-disease associations

    Science.gov (United States)

    Lu, Lu; Yu, Hua

    2018-04-01

    Finding the new related candidate diseases for known drugs provides an effective method for fast-speed and low-risk drug development. However, experimental identification of drug-disease associations is expensive and time-consuming. This motivates the need for developing in silico computational methods that can infer true drug-disease pairs with high confidence. In this study, we presented a novel and powerful computational tool, DR2DI, for accurately uncovering the potential associations between drugs and diseases using high-dimensional and heterogeneous omics data as information sources. Based on a unified and extended similarity kernel framework, DR2DI inferred the unknown relationships between drugs and diseases using Regularized Kernel Classifier. Importantly, DR2DI employed a semi-supervised and global learning algorithm which can be applied to uncover the diseases (drugs) associated with known and novel drugs (diseases). In silico global validation experiments showed that DR2DI significantly outperforms recent two approaches for predicting drug-disease associations. Detailed case studies further demonstrated that the therapeutic indications and side effects of drugs predicted by DR2DI could be validated by existing database records and literature, suggesting that DR2DI can be served as a useful bioinformatic tool for identifying the potential drug-disease associations and guiding drug repositioning. Our software and comparison codes are freely available at https://github.com/huayu1111/DR2DI.

  10. A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System

    Directory of Open Access Journals (Sweden)

    Xiaoliang Yang

    2017-07-01

    Full Text Available A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS. The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances and to satisfy the stator power response of the system. Within the proposed control method, the control scheme for the rotor side converter (RSC is developed on the model predictive control. Firstly, the self-adaptive reference trajectory is established from the deduced discrete state-space equation of the generator. Then, the rotor voltage is calculated by minimizing the global performance index under the current prediction steps at the sampling instant. Through the control scheme for the grid side converter (GSC and wind turbine, we have re-applied the conventional control. The effectiveness of the proposed control strategy is verified via time domain simulation of a 150 kW-575 V DFIG-WECS using Matlab/Simulink. The simulation result shows that the control of the DFIG with the proposed control method can enhance the steady and dynamic response capability better than the conventional ones when the system faces errors due to the parameter perturbations, external disturbances and the rotor speed.

  11. Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data

    Directory of Open Access Journals (Sweden)

    Alexander P. Kartun-Giles

    2018-04-01

    Full Text Available A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does not depend on the order in which nodes are sampled. Despite a large variety of non-equilibrium (growing and equilibrium (static sparse complex network models that are widely used in network science, how to reconcile sparseness (constant average degree with the desired statistical properties of projectivity and exchangeability is currently an outstanding scientific problem. Here we propose a network process with hidden variables which is projective and can generate sparse power-law networks. Despite the model not being exchangeable, it can be closely related to exchangeable uncorrelated networks as indicated by its information theory characterization and its network entropy. The use of the proposed network process as a null model is here tested on real data, indicating that the model offers a promising avenue for statistical network modelling.

  12. 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)

  13. Char characterization and DTF assays as tools to predict burnout of coal blends in power plants

    Energy Technology Data Exchange (ETDEWEB)

    C. Ulloa; A.G. Borrego; S. Helle; A.L. Gordon; X. Garcia [Universidad de Concepcion, Concepcion (Chile). Departamento de Ingenieria Quimica

    2005-02-01

    The aim of this study is to predict efficiency deviations in the combustion of coal blends in power plants. Combustion of blends, as compared to its single coals, shows that for some blends the behavior is non-additive in nature. Samples of coal feed and fly ashes from combustion of blends at two power plants, plus chars of the parent coals generated in a drop-tube furnace (DTF) at temperatures and heating rates similar to those found in the industrial boilers were used. Intrinsic kinetic parameters, burning profiles and petrographic characteristics of these chars correlated well with the burnout in power plants and DTF experiments. The blend combustion in a DTF reproduces both positive and negative burnout deviations from the expected weighted average. These burnout deviations have been previously attributed to parallel or parallel-series pathways of competition for oxygen. No deviations were found for blends of low rank coals of similar characteristics yielding chars close in morphology, optical texture and reactivity. Negative deviations were found for blends of coals differing moderately in rank and were interpreted as associated with long periods of competition. In this case, fly-ashes were enriched in material derived from the least reactive char, but also unburnt material attributed to the most reactive char was identified. Improved burnout compared to the weighted average was observed for blends of coals very different in rank, and interpreted as the result of a short interaction period, followed by a period where the less reactive char burns under conditions that are more favorable to its combustion. In this case, only unburned material from the least reactive char was identified in the fly-ashes. 20 refs., 9 figs., 5 tabs.

  14. Evaluation of a Trapezoidal Predictive Controller for a Four-Wire Active Power Filter for Utility Equipment of Metro Railway, Power-Land Substations

    Directory of Open Access Journals (Sweden)

    Sergio Salas-Duarte

    2016-01-01

    Full Text Available The realization of an improved predictive current controller based on a trapezoidal model is described, and the impact of this technique is assessed on the performance of a 2 kW, 21.6 kHz, four-wire, Active Power Filter for utility equipment of Metro Railway, Power-Land Substations. The operation of the trapezoidal predictive current controller is contrasted with that of a typical predictive control technique, based on a single Euler approximation, which has demonstrated generation of high-quality line currents, each using a 400 V DC link to improve the power quality of an unbalanced nonlinear load of Metro Railway. The results show that the supply current waveforms become virtually sinusoidal waves, reducing the current ripple by 50% and improving its power factor from 0.8 to 0.989 when the active filter is operated with a 1.6 kW load. The principle of operation of the trapezoidal predictive controller is analysed together with a description of its practical development, showing experimental results obtained with a 2 kW prototype.

  15. Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

    Science.gov (United States)

    Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

    1999-01-01

    Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

  16. Optimization and Annual Average Power Predictions of a Backward Bent Duct Buoy Oscillating Water Column Device Using the Wells Turbine.

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Christopher S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bull, Diana L [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Willits, Steven M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Fontaine, Arnold A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-08-01

    This Technical Report presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, the sizing of the power electronics, and number of turbines. Also included in this Technical Report are further details on how rotor thrust and torque are estimated, along with further details on the type of variable frequency drive selected.

  17. Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems

    International Nuclear Information System (INIS)

    Su, Yan; Chan, Lai-Cheong; Shu, Lianjie; Tsui, Kwok-Leung

    2012-01-01

    Highlights: ► We develop online prediction models for solar photovoltaic system performance. ► The proposed prediction models are simple but with reasonable accuracy. ► The maximum monthly average minutely efficiency varies 10.81–12.63%. ► The average efficiency tends to be slightly higher in winter months. - Abstract: This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R 2 . The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9 am to 4 pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months.

  18. Maximization

    Directory of Open Access Journals (Sweden)

    A. Garmroodi Asil

    2017-09-01

    To further reduce the sulfur dioxide emission of the entire refining process, two scenarios of acid gas or air preheats are investigated when either of them is used simultaneously with the third enrichment scheme. The maximum overall sulfur recovery efficiency and highest combustion chamber temperature is slightly higher for acid gas preheats but air preheat is more favorable because it is more benign. To the best of our knowledge, optimization of the entire GTU + enrichment section and SRU processes has not been addressed previously.

  19. Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The ...... process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.......A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data....... The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech...

  20. A neural network based computational model to predict the output power of different types of photovoltaic cells.

    Science.gov (United States)

    Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

    2017-01-01

    In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

  1. A neural network based computational model to predict the output power of different types of photovoltaic cells.

    Directory of Open Access Journals (Sweden)

    WenBo Xiao

    Full Text Available In this article, we introduced an artificial neural network (ANN based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-, multi-crystalline (multi-, and amorphous (amor- crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

  2. The power within: The experimental manipulation of power interacts with trait BDD symptoms to predict interoceptive accuracy.

    Science.gov (United States)

    Kunstman, Jonathan W; Clerkin, Elise M; Palmer, Kateyln; Peters, M Taylar; Dodd, Dorian R; Smith, April R

    2016-03-01

    This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power.. Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms.. This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as

  3. Different Predictive Control Strategies for Active Load Management in Distributed Power Systems with High Penetration of Renewable Energy Sources

    DEFF Research Database (Denmark)

    Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver

    2013-01-01

    In order to achieve a Danish energy supply based on 100% renewable energy from combinations of wind, biomass, wave and solar power in 2050 and to cover 50% of the Danish electricity consumption by wind power in 2020, it requires more renewable energy in buildings and industries (e.g. cold stores......, greenhouses, etc.), and to coordinate the management of large numbers of distributed energy resources with the smart grid solution. This paper presents different predictive control (Genetic Algorithm-based and Model Predictive Control-based) strategies that schedule controlled loads in the industrial...... and residential sectors, based on dynamic power price and weather forecast, considering users’ comfort settings to meet an optimization objective, such as maximum profit or minimum energy consumption. Some field tests were carried out on a facility for intelligent, active and distributed power systems, which...

  4. Maximizing Entropy over Markov Processes

    DEFF Research Database (Denmark)

    Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

    2013-01-01

    The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....

  5. Maximizing entropy over Markov processes

    DEFF Research Database (Denmark)

    Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

    2014-01-01

    The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...

  6. Prediction of hydrogen concentration in nuclear power plant containment under severe accidents using cascaded fuzzy neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Geon Pil; Kim, Dong Yeong; Yoo, Kwae Hwan; Na, Man Gyun, E-mail: magyna@chosun.ac.kr

    2016-04-15

    Highlights: • We present a hydrogen-concentration prediction method in an NPP containment. • The cascaded fuzzy neural network (CFNN) is used in this prediction model. • The CFNN model is much better than the existing FNN model. • This prediction can help prevent severe accidents in NPP due to hydrogen explosion. - Abstract: Recently, severe accidents in nuclear power plants (NPPs) have attracted worldwide interest since the Fukushima accident. If the hydrogen concentration in an NPP containment is increased above 4% in atmospheric pressure, hydrogen combustion will likely occur. Therefore, the hydrogen concentration must be kept below 4%. This study presents the prediction of hydrogen concentration using cascaded fuzzy neural network (CFNN). The CFNN model repeatedly applies FNN modules that are serially connected. The CFNN model was developed using data on severe accidents in NPPs. The data were obtained by numerically simulating the accident scenarios using the MAAP4 code for optimized power reactor 1000 (OPR1000) because real severe accident data cannot be obtained from actual NPP accidents. The root-mean-square error level predicted by the CFNN model is below approximately 5%. It was confirmed that the CFNN model could accurately predict the hydrogen concentration in the containment. If NPP operators can predict the hydrogen concentration in the containment using the CFNN model, this prediction can assist them in preventing a hydrogen explosion.

  7. Modeling and Predicting the EUR/USD Exchange Rate: The Role of Nonlinear Adjustments to Purchasing Power Parity

    OpenAIRE

    Jesús Crespo Cuaresma; Anna Orthofer

    2010-01-01

    Reliable medium-term forecasts are essential for forward-looking monetary policy decisionmaking. Traditionally, predictions of the exchange rate tend to be linked to the equilibrium concept implied by the purchasing power parity (PPP) theory. In particular, the traditional benchmark for exchange rate models is based on a linear adjustment of the exchange rate to the level implied by PPP. In the presence of aggregation effects, transaction costs or uncertainty, however, economic theory predict...

  8. Lack of predictive power of trait fear and anxiety for conditioned pain modulation (CPM).

    Science.gov (United States)

    Horn-Hofmann, Claudia; Priebe, Janosch A; Schaller, Jörg; Görlitz, Rüdiger; Lautenbacher, Stefan

    2016-12-01

    In recent years the association of conditioned pain modulation (CPM) with trait fear and anxiety has become a hot topic in pain research due to the assumption that such variables may explain the low CPM efficiency in some individuals. However, empirical evidence concerning this association is still equivocal. Our study is the first to investigate the predictive power of fear and anxiety for CPM by using a well-established psycho-physiological measure of trait fear, i.e. startle potentiation, in addition to two self-report measures of pain-related trait anxiety. Forty healthy, pain-free participants (female: N = 20; age: M = 23.62 years) underwent two experimental blocks in counter-balanced order: (1) a startle paradigm with affective picture presentation and (2) a CPM procedure with hot water as conditioning stimulus (CS) and contact heat as test stimulus (TS). At the end of the experimental session, pain catastrophizing (PCS) and pain anxiety (PASS) were assessed. PCS score, PASS score and startle potentiation to threatening pictures were entered as predictors in a linear regression model with CPM magnitude as criterion. We were able to show an inhibitory CPM effect in our sample: pain ratings of the heat stimuli were significantly reduced during hot water immersion. However, CPM was neither predicted by self-report of pain-related anxiety nor by startle potentiation as psycho-physiological measure of trait fear. These results corroborate previous negative findings concerning the association between trait fear/anxiety and CPM efficiency and suggest that shifting the focus from trait to state measures might be promising.

  9. The role of predictive on-line monitoring systems in the power generation industry

    Energy Technology Data Exchange (ETDEWEB)

    Gittings, S.D.; Baldwin, J. [AEA Technology Energy plc (United Kingdom)

    1998-12-31

    It has been apparent in the power generation sector for some time that utilities are moving away from large scale, labour intensive, inspection and overhaul programmes. These are being replaced by targeted inspection and replacement programmes supported by engineering assessment. Such engineering assessments address the predominant long-term damage mechanisms and are aimed at predicting failure timescales based upon historic operating data. From these predictions extended inspection intervals can be justified and replacement schedules planned in advance, ensuring maximum plant availability and deferred capital expenditure. However, as these assessments are based upon an examination of past operating history they must be periodically re-visited and up-dated. The cost of such reassessments is usually close to that performed initially, although cost savings can arise from reductions in work-scope which have been previously justified. As computers have become more advanced (and significantly cheaper) some of the expertise used in these assessments has been transferred into software based products. However, these products are generally aimed at replacing specific parts of the desk-based analysis, necessitating a suite of products to be used in order to address all of the components and damage mechanisms, which must be assessed. As these products require specialized knowledge to be used effectively they are often employed by consultants and rarely by plant operators, except in the largest of organisations which can support an in-house team of `experts`. This has in essence led to an increase in the number of companies capable of offering assessment services, but has maintained, in the majority of cases, the plant operators reliance upon external consultants. These software based assessment methods rely upon historic operating data (in the same manner as their desk- based counterparts) and hence also need to be periodically up-dated. However, as previous assessments can

  10. The role of predictive on-line monitoring systems in the power generation industry

    Energy Technology Data Exchange (ETDEWEB)

    Gittings, S D; Baldwin, J [AEA Technology Energy plc (United Kingdom)

    1999-12-31

    It has been apparent in the power generation sector for some time that utilities are moving away from large scale, labour intensive, inspection and overhaul programmes. These are being replaced by targeted inspection and replacement programmes supported by engineering assessment. Such engineering assessments address the predominant long-term damage mechanisms and are aimed at predicting failure timescales based upon historic operating data. From these predictions extended inspection intervals can be justified and replacement schedules planned in advance, ensuring maximum plant availability and deferred capital expenditure. However, as these assessments are based upon an examination of past operating history they must be periodically re-visited and up-dated. The cost of such reassessments is usually close to that performed initially, although cost savings can arise from reductions in work-scope which have been previously justified. As computers have become more advanced (and significantly cheaper) some of the expertise used in these assessments has been transferred into software based products. However, these products are generally aimed at replacing specific parts of the desk-based analysis, necessitating a suite of products to be used in order to address all of the components and damage mechanisms, which must be assessed. As these products require specialized knowledge to be used effectively they are often employed by consultants and rarely by plant operators, except in the largest of organisations which can support an in-house team of `experts`. This has in essence led to an increase in the number of companies capable of offering assessment services, but has maintained, in the majority of cases, the plant operators reliance upon external consultants. These software based assessment methods rely upon historic operating data (in the same manner as their desk- based counterparts) and hence also need to be periodically up-dated. However, as previous assessments can

  11. With age a lower individual breathing reserve is associated with a higher maximal heart rate.

    Science.gov (United States)

    Burtscher, Martin; Gatterer, Hannes; Faulhaber, Martin; Burtscher, Johannes

    2018-01-01

    Maximal heart rate (HRmax) is linearly declining with increasing age. Regular exercise training is supposed to partly prevent this decline, whereas sex and habitual physical activity do not. High exercise capacity is associated with a high cardiac output (HR x stroke volume) and high ventilatory requirements. Due to the close cardiorespiratory coupling, we hypothesized that the individual ventilatory response to maximal exercise might be associated with the age-related HRmax. Retrospective analyses have been conducted on the results of 129 consecutively performed routine cardiopulmonary exercise tests. The study sample comprised healthy subjects of both sexes of a broad range of age (20-86 years). Maximal values of power output, minute ventilation, oxygen uptake and heart rate were assessed by the use of incremental cycle spiroergometry. Linear multivariate regression analysis revealed that in addition to age the individual breathing reserve at maximal exercise was independently predictive for HRmax. A lower breathing reserve due to a high ventilatory demand and/or a low ventilatory capacity, which is more pronounced at a higher age, was associated with higher HRmax. Age explained the observed variance in HRmax by 72% and was improved to 83% when the variable "breathing reserve" was entered. The presented findings indicate an independent association between the breathing reserve at maximal exercise and maximal heart rate, i.e. a low individual breathing reserve is associated with a higher age-related HRmax. A deeper understanding of this association has to be investigated in a more physiological scenario. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Maximal near-field radiative heat transfer between two plates

    OpenAIRE

    Nefzaoui, Elyes; Ezzahri, Younès; Drevillon, Jérémie; Joulain, Karl

    2013-01-01

    International audience; Near-field radiative transfer is a promising way to significantly and simultaneously enhance both thermo-photovoltaic (TPV) devices power densities and efficiencies. A parametric study of Drude and Lorentz models performances in maximizing near-field radiative heat transfer between two semi-infinite planes separated by nanometric distances at room temperature is presented in this paper. Optimal parameters of these models that provide optical properties maximizing the r...

  13. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  14. Discussion of “Prediction intervals for short-term wind farm generation forecasts” and “Combined nonparametric prediction intervals for wind power generation”

    DEFF Research Database (Denmark)

    Pinson, Pierre; Tastu, Julija

    2014-01-01

    A new score for the evaluation of interval forecasts, the so-called coverage width-based criterion (CWC), was proposed and utilized.. This score has been used for the tuning (in-sample) and genuine evaluation (out-ofsample) of prediction intervals for various applications, e.g., electric load [1......], electricity prices [2], general purpose prediction [3], and wind power generation [4], [5]. Indeed, two papers by the same authors appearing in the IEEE Transactions On Sustainable Energy employ that score and use it to conclude on the comparative quality of alternative approaches to interval forecasting...

  15. Towards more accurate wind and solar power prediction by improving NWP model physics

    Science.gov (United States)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  16. Optimal Active Power Control of A Wind Farm Equipped with Energy Storage System based on Distributed Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...

  17. No Mikheyev-Smirnov-Wolfenstein Effect in Maximal Mixing

    OpenAIRE

    Harrison, P. F.; Perkins, D. H.; Scott, W. G.

    1996-01-01

    We investigate the possible influence of the MSW effect on the expectations for the solar neutrino experiments in the maximal mixing scenario suggested by the atmospheric neutrino data. A direct numerical calculation of matter induced effects in the Sun shows that the naive vacuum predictions are left completely undisturbed in the particular case of maximal mixing, so that the MSW effect turns out to be unobservable. We give a qualitative explanation of this result.

  18. Experience and benefits from using the EPRI MOV Performance Prediction Methodology in nuclear power plants

    International Nuclear Information System (INIS)

    Walker, T.; Damerell, P.S.

    1999-01-01

    The EPRI MOV Performance Prediction Methodology (PPM) is an effective tool for evaluating design basis thrust and torque requirements for MOVs. Use of the PPM has become more widespread in US nuclear power plants as they close out their Generic Letter (GL) 89-10 programs and address MOV periodic verification per GL 96-05. The PPM has also been used at plants outside the US, many of which are implementing programs similar to US plants' GL 89-10 programs. The USNRC Safety Evaluation of the PPM and the USNRC's discussion of the PPM in GL 96-05 make the PPM an attractive alternative to differential pressure (DP) testing, which can be costly and time-consuming. Significant experience and benefits, which are summarized in this paper, have been gained using the PPM. Although use of PPM requires a commitment of resources, the benefits of a solidly justified approach and a reduced need for DP testing provide a substantial safety and economic benefit. (author)

  19. Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

    International Nuclear Information System (INIS)

    Shi Chunsheng; Meng Dapeng

    2011-01-01

    The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

  20. Chamaebatiaria millefolium (Torr.) Maxim.: fernbush

    Science.gov (United States)

    Nancy L. Shaw; Emerenciana G. Hurd

    2008-01-01

    Fernbush - Chamaebatiaria millefolium (Torr.) Maxim. - the only species in its genus, is endemic to the Great Basin, Colorado Plateau, and adjacent areas of the western United States. It is an upright, generally multistemmed, sweetly aromatic shrub 0.3 to 2 m tall. Bark of young branches is brown and becomes smooth and gray with age. Leaves are leathery, alternate,...