Fuzzy Logic Controller Based on a Micro-genetic Algorithm for STATCOM
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- 英文论文题名：Fuzzy Logic Controller Based on a Micro-genetic Algorithm for STATCOM
- 论文作者：Zhennan Hong ; Ting Li ; Junhong Li
- 英文论文作者：Zhennan Hong ; Ting Li ; Junhong Li ; School of Electrical Engineering ; University of South China
- 年：2017
- 作者机构：School of Electrical Engineering,University of South China;
- 英文论文关键词：Fuzzy controller ; STATCOM ; lead-lag compensator ; micro-GA ; simulation
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP273.4
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：5
- 文件大小：157k
- 原文格式：D
- 会议级别：全国
摘要
A new fuzzy control approach of STATCOM has been designed according to micro-genetic algorithm in this paper. Initial membership functions and control rules of FLC were fast obtained by fuzzy toolbox of MATLAB and selecting input and output observed signals, membership functions and control rules are optimized simultaneously by micro-GA. Simulation experiments for four machines power system with STATCOM were carried out by three control algorithms, which are optimal FLC, non-optimal FLC, conventional lead-lag compensator, and three controllers were tested by varying loading condition.Digital simulation results show that the new fuzzy controller has not only robust performance of control, high stability and minimum response time but also unsensitive quality for the change of load and disturbance of power system. On the other way, it can maintain good damping property for power system.
A new fuzzy control approach of STATCOM has been designed according to micro-genetic algorithm in this paper. Initial membership functions and control rules of FLC were fast obtained by fuzzy toolbox of MATLAB and selecting input and output observed signals, membership functions and control rules are optimized simultaneously by micro-GA. Simulation experiments for four machines power system with STATCOM were carried out by three control algorithms, which are optimal FLC, non-optimal FLC, conventional lead-lag compensator, and three controllers were tested by varying loading condition.Digital simulation results show that the new fuzzy controller has not only robust performance of control, high stability and minimum response time but also unsensitive quality for the change of load and disturbance of power system. On the other way, it can maintain good damping property for power system.
A new fuzzy control approach of STATCOM has been designed according to micro-genetic algorithm in this paper. Initial membership functions and control rules of FLC were fast obtained by fuzzy toolbox of MATLAB and selecting input and output observed signals, membership functions and control rules are optimized simultaneously by micro-GA. Simulation experiments for four machines power system with STATCOM were carried out by three control algorithms, which are optimal FLC, non-optimal FLC, conventional lead-lag compensator, and three controllers were tested by varying loading condition.Digital simulation results show that the new fuzzy controller has not only robust performance of control, high stability and minimum response time but also unsensitive quality for the change of load and disturbance of power system. On the other way, it can maintain good damping property for power system.
引文
[1]Wei Wenhui,Liu Wenhua,Song Qiang,et al.Research on fast dynamic control of static synchronous compensator using cascade multilevel inverters[J].Proceedings of the CSEE,2005,25(3):23-28.
[2]Haniyeh Marefatjou,Iman Soltani.Optimal placement of STATCOM to voltage stability improvement and reducepower losses by using QPSO algorithm[J].Journal of Science and Engineering,2013,2(2):105-119.
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[7]Margaliot.M,Langholz G.Fuzzy Lyapunov-based approach to the design of controller.Fuzzy Sets System,1999,106:49-59.
[8]Mak L O,Ni Y X.STATCOM with Fuzzy Controllers for Interconnected Power Systems.Electric Power Systems Research,2000,54(2):101-111.
[9]Mohaddes M,Gole A M,Mclaren P G.A neural network controlled optimal pulse-width modulated STATCOM.IEEETrans on Power.Delivery,1999,14(2):481-488.
[2]Haniyeh Marefatjou,Iman Soltani.Optimal placement of STATCOM to voltage stability improvement and reducepower losses by using QPSO algorithm[J].Journal of Science and Engineering,2013,2(2):105-119.
[3]Hu Wei,Sun Jianjun,Ma Qian,et al.Interaction analysis of multiple paralleled grid-connected inverters[J].Power System Technology,2014,38(9):2511-2518.
[4]Sirisukprasert S,Huang A Q,Lai J S.Modelling,analysis and control of cascaded-multilevel converter-based STATCOM[C]//IEEE-PES General Meeting.Toronto:IEEE,2003:13-17.
[5]Shengqing Li,Lilin Zeng,Xiaodong Luo,et al.Reactive power optimization of power system based on multi-objective concordance evolutionary algorithm[C]//2011International Conference on Electrical and Control Engineering.Yichang:IEEE,2011:4878-4881.
[6]Lehn P W.Exact modeling of the voltage source converter[J].IEEE Transactions on Power Delivery,2002,17(1):217-222.
[7]Margaliot.M,Langholz G.Fuzzy Lyapunov-based approach to the design of controller.Fuzzy Sets System,1999,106:49-59.
[8]Mak L O,Ni Y X.STATCOM with Fuzzy Controllers for Interconnected Power Systems.Electric Power Systems Research,2000,54(2):101-111.
[9]Mohaddes M,Gole A M,Mclaren P G.A neural network controlled optimal pulse-width modulated STATCOM.IEEETrans on Power.Delivery,1999,14(2):481-488.