考虑拓扑影响的风电场无功优化策略研究
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摘要
双馈风电机组(DFIG)机群的拓扑结构对风电场无功优化有较大影响。分析了DFIG的无功出力极限,将DFIG作为风电场连续无功源,计及风电场有载调压变压器分接头设置对DFIG机端电压的影响。以风电场内部有功损耗最小为优化目标建立风电场无功优化模型。最后,以丹麦Horns Rev1离岸风电场为例,采用粒子群优化算法对所建立的无功优化模型进行求解。仿真结果验证了所提优化控制策略的安全性和经济性。
The topology of doubly fed induction generators(DFIGs) has a greater impact on optimal reactive power dispatch(ORPD) problem within wind farm. The reactive power limits of DFIG are analyzed, DFIGs are regarded as continuous reactive power sources participating reactive power compensation within wind farm and the impact of on-load tap changing transformers(OLTCs) tap on DFIG terminal voltage is considered. The optimal reactive power dispatch model within a wind farm is formulated with an objective of minimizing active power loss. Finally, the problem of optimal reactive power dispatch within Horns Rev1 wind farm in Denmark is formulated and a particle swarm optimization(PSO) algorithm is proposed to get the optimal solution. The test results demonstrate the security and economy of the proposed method in achieving optimal solution.
The topology of doubly fed induction generators(DFIGs) has a greater impact on optimal reactive power dispatch(ORPD) problem within wind farm. The reactive power limits of DFIG are analyzed, DFIGs are regarded as continuous reactive power sources participating reactive power compensation within wind farm and the impact of on-load tap changing transformers(OLTCs) tap on DFIG terminal voltage is considered. The optimal reactive power dispatch model within a wind farm is formulated with an objective of minimizing active power loss. Finally, the problem of optimal reactive power dispatch within Horns Rev1 wind farm in Denmark is formulated and a particle swarm optimization(PSO) algorithm is proposed to get the optimal solution. The test results demonstrate the security and economy of the proposed method in achieving optimal solution.
引文
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[15]ABIDO M.Optimal power flow using particle swarm optimization[J].International Journal of Electrical Power and Energy Systems,2002,24(7):563-571.
[16]KENNEDY J,EBERHART R.Particle Swarm Optimization[C]//Proceedings of the 1995 Ieee International Conference on Neural Networks,1995:1942-1948.
[17]王娜,周有庆,邵霞.基于混合神经网络的风电场风资源评估[J].电工技术学报,2015,30(14):370-376.WANG Na,ZHOU Youqing,SHAO Xia.Wind energy resource assessment of wind farm based on hybrid neural network[J].Transactions of China Electrotechnical Society,2015,30(14):370-376.
[18]苏海滨,高孟泽,常海松.基于粒子群算法的微电网有功无功下垂控制[J].电工技术学报,2015,30(增刊1):365-369.SU Haibin,GAO Mengze,CHANG Haisong.Microgrid droop control of active and reactive power based on PSO[J].Transactions of China Electrotechnical Society,2015,30(S1):365-369.
[2]张元,郝丽丽,戴嘉祺.风电场等值建模研究综述[J].电力系统保护与控制,2015,43(6):138-146.ZHANG Yuan,HAO Lili,DAI Jiaqi.Overview of the equivalent model research for wind farms[J].Power System Protection and Control,2015,43(6):138-146.
[3]付文秀,范春菊.SVG在双馈风力发电系统电压无功控制中的应用[J].电力系统保护与控制,2015,43(3):61-68.FU Wenxiu,FAN Chunju.Application of SVG in voltage and reactive power control of doubly-fed induction generation system[J].Power System Protection and Control,2015,43(3):61-68.
[4]郎永强,张学广,徐殿国,等.双馈电机风电场无功功率分析及控制策略[J].中国电机工程学报,2007,27(9):77-82.LANG Yongqiang,ZHANG Xueguang,XU Dianguo,et al.Reactive power analysis and control of doubly fed induction generator wind farm[J].Proceedings of the CSEE,2007,27(9):77-82.
[5]严干贵,孙兆键,穆钢,等.面向集电系统电压调节的风电场无功电压控制策略[J].电工技术学报,2015,30(18):140-146.YAN Gangui,SUN Zhaojian,MU Gang,et al.Collector system voltage regulation oriented reactive power control strategy for wind farm[J].Transactions of China Electrotechnical Society,2015,30(18):140-146.
[6]符杨,潘翔龙,黄玲玲.考虑双馈机组无功调节能力的海上风电场无功优化[J].电网技术,2014,38(8):2168-2173.FU Yang,PAN Xianglong,HUANG Lingling.Reactive power optimization for offshore wind farm considering reactive power regulation capability of doubly-fed induction generators[J].Power System Technology,2014,38(8):2168-2173.
[7]秦涛,吕跃刚,徐大平.采用双馈机组的风电场无功功率控制技术[J].电网技术,2009,33(2):105-110.QIN Tao,LüYuegang,XU Daping.Reactive power control of wind farm adopting doubly-fed induction generators[J].Power System Technology,2009,33(2):105-110.
[8]EL-SHIMY M.Modeling and analysis of reactive power in grid-connected onshore and offshore DFIG-based wind farms[J].Wind Energy,2014,17(2):279-295.
[9]ZHAO J,LI X,HAO J,et al.Reactive power control of wind farm made up with doubly fed induction generators in distribution system[J].Electric Power Systems Research,2010,80(6):698-706.
[10]SANTOS-MARTIN D,ARNALTES S,RODRIGUEZ AMENEDO J.Reactive power capability of doubly fed asynchronous generators[J].Electric Power Systems Research,2008,78(11):1837-1840.
[11]杨硕,王伟胜,刘纯,等.双馈风电场无功电压协调控制策略[J].电力系统自动化,2013,37(12):1-6.YANG Shuo,WANG Weisheng,LIU Chun,et al.Reactive power and voltage coordinated control strategy of DFIG wind farm[J].Automation of Electric Power Systems,2013,37(12):1-6.
[12]KANNA B,SINGH S N.Towards reactive power dispatch within a wind farm using hybrid PSO[J].International Journal of Electrical Power and Energy Systems,2015,69:232-240.
[13]李丹,贾琳,许晓菲,等.风电机组脱网原因及对策分析[J].电力系统自动化,2011,35(22):41-44.LI Dan,JIA Lin,XU Xiaofei,et al.Cause and countermeasure analysis on wind turbines'trip-off from grid[J].Automation of Electric Power Systems,2011,35(22):41-44.
[14]王松,李庚银,周明.双馈风力发电机组无功调节机理及无功控制策略[J].中国电机工程学报,2014,34(16):2714-2720.WANG Song,LI Gengyin,ZHOU Ming.The reactive power adjusting mechanism&control strategy of doubly fed induction generator[J].Proceedings of the CSEE,2014,34(16):2714-2720.
[15]ABIDO M.Optimal power flow using particle swarm optimization[J].International Journal of Electrical Power and Energy Systems,2002,24(7):563-571.
[16]KENNEDY J,EBERHART R.Particle Swarm Optimization[C]//Proceedings of the 1995 Ieee International Conference on Neural Networks,1995:1942-1948.
[17]王娜,周有庆,邵霞.基于混合神经网络的风电场风资源评估[J].电工技术学报,2015,30(14):370-376.WANG Na,ZHOU Youqing,SHAO Xia.Wind energy resource assessment of wind farm based on hybrid neural network[J].Transactions of China Electrotechnical Society,2015,30(14):370-376.
[18]苏海滨,高孟泽,常海松.基于粒子群算法的微电网有功无功下垂控制[J].电工技术学报,2015,30(增刊1):365-369.SU Haibin,GAO Mengze,CHANG Haisong.Microgrid droop control of active and reactive power based on PSO[J].Transactions of China Electrotechnical Society,2015,30(S1):365-369.