The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various faul...The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system （FACTS） in this paper is an advanced super-conducting magnetic energy storage （ASMES）. Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller （FMRLC） is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters （i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met）. Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system （i.e., single machine-infinite bus （SMIB） system）, under various fault conditions and disturbances.展开更多
Congo River has abundant hydropower resources,and large-scale cascade power stations,such as the Grand Inga,can be constructed in downstream locations.However,the fragile economic foundations of the Democratic Republi...Congo River has abundant hydropower resources,and large-scale cascade power stations,such as the Grand Inga,can be constructed in downstream locations.However,the fragile economic foundations of the Democratic Republic of the Congo and neighbor!ng Central African countries,and the small-scale regional power consumption market prohibit the implementation of large-scale hydro power projects.As the high-voltage,I on g-dista nee power transmission tech no logy matures,hydropower from the Grand Inga can be delivered to load centers in other regions of Africa.This study establishes a 6 dime nsional comprehe nsive assessment model using the best-worst method to evaluate large-scale,I on g-distance,cross-border power intercon necti on projects.The model is applied to evaluate all the can didate in ter-regional power delivery schemes of the Inga III hydropower station,and the evaluation results can effectively help investment institutions and policy makers in policy making and potential market targeting.展开更多
This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated envi...This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.展开更多
文摘The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system （FACTS） in this paper is an advanced super-conducting magnetic energy storage （ASMES）. Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller （FMRLC） is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters （i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met）. Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system （i.e., single machine-infinite bus （SMIB） system）, under various fault conditions and disturbances.
基金National Key Reaearch and Development Program of China(2016YFB0900400).
文摘Congo River has abundant hydropower resources,and large-scale cascade power stations,such as the Grand Inga,can be constructed in downstream locations.However,the fragile economic foundations of the Democratic Republic of the Congo and neighbor!ng Central African countries,and the small-scale regional power consumption market prohibit the implementation of large-scale hydro power projects.As the high-voltage,I on g-dista nee power transmission tech no logy matures,hydropower from the Grand Inga can be delivered to load centers in other regions of Africa.This study establishes a 6 dime nsional comprehe nsive assessment model using the best-worst method to evaluate large-scale,I on g-distance,cross-border power intercon necti on projects.The model is applied to evaluate all the can didate in ter-regional power delivery schemes of the Inga III hydropower station,and the evaluation results can effectively help investment institutions and policy makers in policy making and potential market targeting.
文摘This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.
