Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441658
K. Ofuji, S. Kanemoto
In this article, we built a state space model to analyze the price time series in Japan electric power exchange(JEPX) spot market. In building the model, we aimed to achieve the following two goals that the model was able to a) forecast prices with reasonable accuracy, and b) understand the underlying market dynamics by decomposing the price time series into a reasonable set of contributing factors. To capture the time-variability of the contributing factors to price, self-AR(autoregressive) process was introduced to allow continuous change in the magnitude of influence from each explanatory variable. To estimate the model, Kalman Filter algorithm was applied for stepwise recursive estimation. After optimizing the model under the maximum likelihood method(MLM) coupled with minimum AIC(Akaike information criteria) conditions, the model was able to decompose the 15:00-15:30 JEPX spot electricity strip price into a couple of the most contributing factors with significant time-dependencies. Our model also yielded as good a forecasting accuracy with conventional AR econometric model estimated with ordinary least square method(OLS), with a squared error of about 1.12 [yen/kWh] per forecasting period.
本文建立状态空间模型，对日本电力交易所(JEPX)现货市场的价格时间序列进行分析。在构建模型时，我们旨在实现以下两个目标，即模型能够a)以合理的准确性预测价格，以及b)通过将价格时间序列分解为一组合理的促成因素来理解潜在的市场动态。为了捕捉价格贡献因素的时间变异性，引入了自回归(自回归)过程，以允许每个解释变量的影响程度连续变化。为了对模型进行估计，采用卡尔曼滤波算法进行逐步递归估计。在最大似然法(MLM)和最小AIC(Akaike information criteria)条件下对模型进行优化后，该模型能够将15:00-15:30 JEPX现货电价分解为几个贡献最大且具有显著时间依赖性的因素。我们的模型也产生了与传统AR计量经济模型(用普通最小二乘法(OLS)估计)相同的预测精度，每个预测期的平方误差约为1.12[日元/千瓦时]。
{"title":"Price Forecasting of Japan Electric Power Exchange using Time-varying AR Model","authors":"K. Ofuji, S. Kanemoto","doi":"10.1109/ISAP.2007.4441658","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441658","url":null,"abstract":"In this article, we built a state space model to analyze the price time series in Japan electric power exchange(JEPX) spot market. In building the model, we aimed to achieve the following two goals that the model was able to a) forecast prices with reasonable accuracy, and b) understand the underlying market dynamics by decomposing the price time series into a reasonable set of contributing factors. To capture the time-variability of the contributing factors to price, self-AR(autoregressive) process was introduced to allow continuous change in the magnitude of influence from each explanatory variable. To estimate the model, Kalman Filter algorithm was applied for stepwise recursive estimation. After optimizing the model under the maximum likelihood method(MLM) coupled with minimum AIC(Akaike information criteria) conditions, the model was able to decompose the 15:00-15:30 JEPX spot electricity strip price into a couple of the most contributing factors with significant time-dependencies. Our model also yielded as good a forecasting accuracy with conventional AR econometric model estimated with ordinary least square method(OLS), with a squared error of about 1.12 [yen/kWh] per forecasting period.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441586
A. Ugedo, Enrique Lobato
The security criteria of a power system require that branch power flows and bus voltages are within their limits, not only in normal operating conditions but also when any credible contingency occurs. In the Spanish electricity market, voltage constraints are solved by the system operator by connecting a set of off-line generators located in the areas where they occur. Thus, for a market participant it is necessary to predict approximately when its generating units are connected in order to prepare the annual budget and/or decide the time and location of new plants. This paper proposes a methodology to forecast if a non-connected unit will be committed by the system operator in order to remove voltage violations. For that purpose different artificial intelligence techniques are combined: neural networks, decision trees and clustering techniques. The performance of the methodology is illustrated with a study case of a real unit operating in the Spanish market.
{"title":"Generator Load Profiles Estimation Using Artificial Intelligence","authors":"A. Ugedo, Enrique Lobato","doi":"10.1109/ISAP.2007.4441586","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441586","url":null,"abstract":"The security criteria of a power system require that branch power flows and bus voltages are within their limits, not only in normal operating conditions but also when any credible contingency occurs. In the Spanish electricity market, voltage constraints are solved by the system operator by connecting a set of off-line generators located in the areas where they occur. Thus, for a market participant it is necessary to predict approximately when its generating units are connected in order to prepare the annual budget and/or decide the time and location of new plants. This paper proposes a methodology to forecast if a non-connected unit will be committed by the system operator in order to remove voltage violations. For that purpose different artificial intelligence techniques are combined: neural networks, decision trees and clustering techniques. The performance of the methodology is illustrated with a study case of a real unit operating in the Spanish market.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128423875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441693
Woo-Nam Lee, Yun-Won Jeong, Jong-Bae Park, Joong-Rin Shin, K.Y. Lee
This paper presents a windows-based educational simulator with user-friendly graphical user interface (GUI) for the education and training of particle swarm optimization (PSO) technique for mathematical optimization problems and economic dispatch (ED) applications. The main objective for developing the simulator is to provide information with the electrical engineering undergraduate students that the up-to-date artificial intelligent (AI) techniques including PSO are actively used in power system optimization problems. The simulator can be used as a lecturing tool to stimulate an interest in the power system engineering of the undergraduate students. The students can be more familiar with the optimization problems including power system ED problem through the iterative uses of the simulator. Also, they can increase understandings on PSO mechanism by the homework on the optimal design of several control parameters such as inertia weight, acceleration coefficients, and the number of population, etc. In the developed simulator, instructors and students can select the optimization functions and set the parameters that have an influence on PSO performance. The simulator is applied not only to mathematical optimization functions but also to economic dispatch (ED) problems with non-smooth cost functions, which is designed so that users can solve other mathematical functions through simple additional MATLAB coding.
{"title":"Development of an Educational Simulator for Particle Swarm Optimization and Economic Dispatch Applications","authors":"Woo-Nam Lee, Yun-Won Jeong, Jong-Bae Park, Joong-Rin Shin, K.Y. Lee","doi":"10.1109/ISAP.2007.4441693","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441693","url":null,"abstract":"This paper presents a windows-based educational simulator with user-friendly graphical user interface (GUI) for the education and training of particle swarm optimization (PSO) technique for mathematical optimization problems and economic dispatch (ED) applications. The main objective for developing the simulator is to provide information with the electrical engineering undergraduate students that the up-to-date artificial intelligent (AI) techniques including PSO are actively used in power system optimization problems. The simulator can be used as a lecturing tool to stimulate an interest in the power system engineering of the undergraduate students. The students can be more familiar with the optimization problems including power system ED problem through the iterative uses of the simulator. Also, they can increase understandings on PSO mechanism by the homework on the optimal design of several control parameters such as inertia weight, acceleration coefficients, and the number of population, etc. In the developed simulator, instructors and students can select the optimization functions and set the parameters that have an influence on PSO performance. The simulator is applied not only to mathematical optimization functions but also to economic dispatch (ED) problems with non-smooth cost functions, which is designed so that users can solve other mathematical functions through simple additional MATLAB coding.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117015134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441688
R. Liang, Xian-Zong Liu
To maintain the customer voltage profile within a specified region is very important when a dispersed generation system (DGS) is connected to a power distribution system. This paper presents an approach based on an artificial neural network (ANN) combined with a fuzzy system to solve the coordination control problem in a distribution system with DGS. The main purpose is to find the proper tap position for the main transformer under load tap changer (ULTC) and reactive power outputs for the static var compensator (SVC) and DGS, i.e., using the proposed approach to design a coordination controller, such that the reactive power flow through the main transformer can be restrained and voltage profiles on the buses improved. To reduce the repair cost for the main transformer ULTC, the number of operating ULTCs must be minimized. The constraints that must be considered include the voltage limits on the secondary bus and DGS bus, and the reactive power output limits for the SVC and DGS. To demonstrate the usefulness of the proposed coordination control scheme based on the ANN and fuzzy system, a simplified distribution system is performed. The results show that a proper coordination can be reached using the proposed approach.
{"title":"Neuro-Fuzzy Based Coordination Control in a Distribution System with Dispersed Generation System","authors":"R. Liang, Xian-Zong Liu","doi":"10.1109/ISAP.2007.4441688","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441688","url":null,"abstract":"To maintain the customer voltage profile within a specified region is very important when a dispersed generation system (DGS) is connected to a power distribution system. This paper presents an approach based on an artificial neural network (ANN) combined with a fuzzy system to solve the coordination control problem in a distribution system with DGS. The main purpose is to find the proper tap position for the main transformer under load tap changer (ULTC) and reactive power outputs for the static var compensator (SVC) and DGS, i.e., using the proposed approach to design a coordination controller, such that the reactive power flow through the main transformer can be restrained and voltage profiles on the buses improved. To reduce the repair cost for the main transformer ULTC, the number of operating ULTCs must be minimized. The constraints that must be considered include the voltage limits on the secondary bus and DGS bus, and the reactive power output limits for the SVC and DGS. To demonstrate the usefulness of the proposed coordination control scheme based on the ANN and fuzzy system, a simplified distribution system is performed. The results show that a proper coordination can be reached using the proposed approach.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126518855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441675
J. H. Van Sickel, Kwang Y. Lee, J. Heo
Differential evolution has seen growing popularity as an effective yet simple evolutionary algorithm. Its main feature is that the difference between population members is used for the mutation process instead of randomly generated values. Its ease of use and implementation make it a more attractive approach to evolutionary algorithms as it is simpler to explain the choice of parameters to fit a given cost function. This paper provides a brief overview of differential evolution, and shows its uses in two applications. The first application is using differential evolution in a reference governor to generate optimal set points for the control of a power plant. The second application uses differential evolution as a gain tuning algorithm for the same power plant. Both applications include a comparison of multiple differential evolution strategies as well as a comparison with prominent particle swarm optimization techniques. Also included in this paper is a method of speeding up the convergence of differential evolution by combining it with aspects of standard evolutionary algorithms.
{"title":"Differential Evolution and its Applications to Power Plant Control","authors":"J. H. Van Sickel, Kwang Y. Lee, J. Heo","doi":"10.1109/ISAP.2007.4441675","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441675","url":null,"abstract":"Differential evolution has seen growing popularity as an effective yet simple evolutionary algorithm. Its main feature is that the difference between population members is used for the mutation process instead of randomly generated values. Its ease of use and implementation make it a more attractive approach to evolutionary algorithms as it is simpler to explain the choice of parameters to fit a given cost function. This paper provides a brief overview of differential evolution, and shows its uses in two applications. The first application is using differential evolution in a reference governor to generate optimal set points for the control of a power plant. The second application uses differential evolution as a gain tuning algorithm for the same power plant. Both applications include a comparison of multiple differential evolution strategies as well as a comparison with prominent particle swarm optimization techniques. Also included in this paper is a method of speeding up the convergence of differential evolution by combining it with aspects of standard evolutionary algorithms.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124421448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441611
J. Teng, Chan-nan Lu
Due to the difficulty in power network reinforcement and the interconnection of more distributed generations, fault current level has become a serious problem in transmission and distribution system operations. The utilization of fault current limiters (FCLs) in power system provides an effective way to suppress fault currents and result in considerable saving in the investment of high capacity circuit breakers. In a loop power system, the advantages would depend on the numbers and locations of FCL installations. This paper presents a method to determine optimum numbers and locations for FCL placement in terms of installing smallest FCL parameters to restrain short-circuit currents under circuit breakers' interrupting ratings. In the proposed approach, sensitivity factors of bus fault current reduction due to changes in the branch parameters are derived and used to choose candidates for FCL installations. A genetic-algorithm-based method is then designed to include the sensitivity information in searching for best locations and parameters of FCL to meet the requirements. Test results demonstrate the efficiency and accuracy of the proposed method.
{"title":"Optimum Fault Current Limiter Placement","authors":"J. Teng, Chan-nan Lu","doi":"10.1109/ISAP.2007.4441611","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441611","url":null,"abstract":"Due to the difficulty in power network reinforcement and the interconnection of more distributed generations, fault current level has become a serious problem in transmission and distribution system operations. The utilization of fault current limiters (FCLs) in power system provides an effective way to suppress fault currents and result in considerable saving in the investment of high capacity circuit breakers. In a loop power system, the advantages would depend on the numbers and locations of FCL installations. This paper presents a method to determine optimum numbers and locations for FCL placement in terms of installing smallest FCL parameters to restrain short-circuit currents under circuit breakers' interrupting ratings. In the proposed approach, sensitivity factors of bus fault current reduction due to changes in the branch parameters are derived and used to choose candidates for FCL installations. A genetic-algorithm-based method is then designed to include the sensitivity information in searching for best locations and parameters of FCL to meet the requirements. Test results demonstrate the efficiency and accuracy of the proposed method.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121598482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441649
T. Hiyama, Wei Zhang, S. Wakasugi
This paper presents an eigenvalue based wide area stability control of electric power systems. Different types of intelligent agents are also proposed to realize the proposed wide area stability control system: monitoring agents for gathering required information to evaluate the stability of the study system, control agents which perform the actual control action, and a supervisor agent for the real time monitoring of dynamic stability and the decision of the required dynamic stability control action to keep the pre-specified dynamic stability margin. The supervisor agent sends commands to a selected unit to keep the stability margin within the pre-specified range, whenever the stability margin is violated in the study system. To demonstrate the efficiency of the proposed eigenvalue based wide area dynamic stability control system, real time non-linear simulations have been performed on a PC based real time power system simulator.
{"title":"Eigenvalue Based Wide Area Dynamic Stability Control of Electric Power Systems","authors":"T. Hiyama, Wei Zhang, S. Wakasugi","doi":"10.1109/ISAP.2007.4441649","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441649","url":null,"abstract":"This paper presents an eigenvalue based wide area stability control of electric power systems. Different types of intelligent agents are also proposed to realize the proposed wide area stability control system: monitoring agents for gathering required information to evaluate the stability of the study system, control agents which perform the actual control action, and a supervisor agent for the real time monitoring of dynamic stability and the decision of the required dynamic stability control action to keep the pre-specified dynamic stability margin. The supervisor agent sends commands to a selected unit to keep the stability margin within the pre-specified range, whenever the stability margin is violated in the study system. To demonstrate the efficiency of the proposed eigenvalue based wide area dynamic stability control system, real time non-linear simulations have been performed on a PC based real time power system simulator.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124776795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441639
G. Lu, F. Wen, X. Zhao, C. Chung, K. Wong
Stochastic problems existing in many research domains could be solved through three kinds of methods viz. expected value model (EVM), chance-constrained programming (CCP), and dependent chance programming (DCP). However, these methods, sometimes, give different or even contrary results when dealing with the same real world problems. This paper proposes a new stochastic programming method, termed as balance programming between target and chance, based on the concept of effective decision frontier curve, which can solve the stochastic problems in a more rational, flexible, and applicable manner, and can diminish conflicts of the three above-mentioned methods. The effectiveness of the proposed method is demonstrated by building optimal bidding strategies for generation companies with risk management in the electricity market environment. A genetic algorithm with Monte Carlo simulation is employed to solve the programming model.
{"title":"Balance Programming between Target and Chance with Application in Building Optimal Bidding Strategies for Generation Companies","authors":"G. Lu, F. Wen, X. Zhao, C. Chung, K. Wong","doi":"10.1109/ISAP.2007.4441639","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441639","url":null,"abstract":"Stochastic problems existing in many research domains could be solved through three kinds of methods viz. expected value model (EVM), chance-constrained programming (CCP), and dependent chance programming (DCP). However, these methods, sometimes, give different or even contrary results when dealing with the same real world problems. This paper proposes a new stochastic programming method, termed as balance programming between target and chance, based on the concept of effective decision frontier curve, which can solve the stochastic problems in a more rational, flexible, and applicable manner, and can diminish conflicts of the three above-mentioned methods. The effectiveness of the proposed method is demonstrated by building optimal bidding strategies for generation companies with risk management in the electricity market environment. A genetic algorithm with Monte Carlo simulation is employed to solve the programming model.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128893607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441609
Xiangning Lin, Bin Wang, Z. Bo, A. Klimek
A criterion using residual voltage and fuzzy decision to improve the successful rate of reclosing is proposed. Residual voltage of the faulted phase still remains after a single phase to ground fault occurs followed by the faulted phase breaking because distributed parameters of the high-voltage transmission line and coupling capacitance between one phase and another phase transmission lines exist. Therefore, the residual voltage can be used to distinguish between permanent faults and transient faults of transmission lines. However, a permanent fault may be regarded as transient one when permanent single-phase fault to ground occurs near either end of the transmission line according to the existing residual voltage scheme. In this case the system stability will be threaten. In order to overcome this problem, a new scheme using fuzzy decision is proposed in this paper, the information of capacitance coupling voltage and the boundary condition will be used to revise the present criteria, so that the correct rate of judgment can be improved extremely. A classical model with two inputs and one output is used to design the fuzzy controller, a STD industrial control computer system is used as the hardware platform. The analysis and test results show that the new criterion can be widely applied in protective relaying with reclosing, especially digital relaying of power systems.
{"title":"An Intelligent Adaptive Reclosure Scheme for High Voltage Transmission Lines","authors":"Xiangning Lin, Bin Wang, Z. Bo, A. Klimek","doi":"10.1109/ISAP.2007.4441609","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441609","url":null,"abstract":"A criterion using residual voltage and fuzzy decision to improve the successful rate of reclosing is proposed. Residual voltage of the faulted phase still remains after a single phase to ground fault occurs followed by the faulted phase breaking because distributed parameters of the high-voltage transmission line and coupling capacitance between one phase and another phase transmission lines exist. Therefore, the residual voltage can be used to distinguish between permanent faults and transient faults of transmission lines. However, a permanent fault may be regarded as transient one when permanent single-phase fault to ground occurs near either end of the transmission line according to the existing residual voltage scheme. In this case the system stability will be threaten. In order to overcome this problem, a new scheme using fuzzy decision is proposed in this paper, the information of capacitance coupling voltage and the boundary condition will be used to revise the present criteria, so that the correct rate of judgment can be improved extremely. A classical model with two inputs and one output is used to design the fuzzy controller, a STD industrial control computer system is used as the hardware platform. The analysis and test results show that the new criterion can be widely applied in protective relaying with reclosing, especially digital relaying of power systems.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133686786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441656
F. Azevedo, Z. Vale, Paulo Moura Oliveira
Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level plusmn Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.
{"title":"Long-term Price Range Forecast Applied to Risk Management Using Regression Models","authors":"F. Azevedo, Z. Vale, Paulo Moura Oliveira","doi":"10.1109/ISAP.2007.4441656","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441656","url":null,"abstract":"Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level plusmn Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133747060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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