基于机会约束凸松弛的分区随机无功备用优化方法

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Abstract In order to address the uncertainties of sustainable energy integration and regional characteristics of reactive power,a stochastic optimal reactive reserve dispatch method based on voltage control area is proposed in this paper.At first,agglomerative clustering and modularity index are employed to find the system reactive area.And then the convex relaxation method is adopted to transform the stochastic optimization model into deterministic.Finally,a successive regional optimal reactive reserve optimization method is proposed.Several test cases demonstrate that convex relaxation is able to convert chance constraints accurately.The proposed method transforms the high dimensional original optimization problem into several regional sub-problems with low dimension,which leads to high computational efficiency.The dispatch scheme has significantly enhanced the reactive power reserve and voltage stability margin.The operational risk of the power system is also decreased,which also enhances the voltage profile of N-1 scenarios.

Key words： Convex relaxation of chance constraints voltage control area reactive power reserve successive regional optimization voltage stability margin

Received: 29 December 2014 Published: 08 September 2015

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TM315

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	Articles by authors
	Fang Sidun
	Cheng Haozhong
	Ma Zifeng
	Song Yue
	Zhang Jian
	Li Boqing

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Fang Sidun,Cheng Haozhong,Ma Zifeng等. Stochastic Optimal Reactive Power Reserve Dispatch Based on Convex Relaxation of Chance Constraints Considering Voltage Control Areas[J]. Transactions of China Electrotechnical Society, 2015, 30(15): 73-80.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2015/V30/I15/73

[1] Fang Sidun,Cheng Haozhong,Song Yue.Stochastic optimal reactive power dispatch method based on point estimation considering load margin[C].Proceedings of 2014 IEEE Power Engineering Society General Meeting,Washington,USA,2014:1-5.
[2] Arya L D,Singh P,Titare L S.Anticipatory reactive power reserve maximization using differential evolution[J].International Journal of Electrical Power & Energy Systems,2012,35(1):66-73.
[3] Ruiz P A,Sauer P W.Reactive power reserve issues[C].38th North American Power Symposium,Carbondale,USA,2006:439-445.
[4] Menezes T V,da Silva L C P,da Costa V F.Dynamic VAR sources scheduling for improving voltage stability margin[J].IEEE Transactions on Power Systems,2003,18(2):969-971.
[5] Kataoka Y,Shinoda Y.Voltage stability limit of electric power systems with generator reactive power constraints considered[J].IEEE Transactions on Power Systems,2005,20(2):951-962.
[6] 刘志文,刘明波,林舜江.REI等值技术在多区域无功优化计算中的应用[J].电工技术学报,2011,26(11):191-201.
Liu Zhiwen,Liu Mingbo,Lin Shunjiang.Research on application of REI equivalent technique into multi-area reactive power optimization computing[J].Transactions of China Electrotechnical Society,2011,26(11):191-201.
[7] 王绵斌,谭忠富,张丽英,等.市场环境下电网投资风险评估的集对分析方法[J].中国电机工程学报,2010,30(19):91-99.
Wang Mianbin,Tan Zhongfu,Zhang Liying,et al.Power grid investment risk evaluation model based on set-pair analysis theory in power market[J].Proceedings of the CSEE,2010,30(19):91-99.
[8] Beyer H G,Sendhoff B.Robust optimization-acomprehensive survey[J].Computer Methods in Applied Mechanics and Engineering,2007,196(33-34):3190-3218.
[9] 张晓花,赵晋泉,陈星莺.节能减排多目标机组组合问题的模糊建模及优化[J].中国电机工程学报,2010,30(22):71-76.
Zhang Xiaohua,Zhao Jinquan,Chen Xingying.Multi-objective unit commitment fuzzy modeling and optimization for energy-saving and emission reduction[J].Proceedings of the CSEE,2010,30(22):71-76.
[10]于佳,任建文,周明.基于机会约束规划的风蓄联合动态经济调度[J].电网技术,2013,37(8):2116-2122.
Yu Jia,Ren Jianwen,Zhou Ming.A chance-constrained programming based dynamic economic dispatch of wind farm and pumped-storage power station[J].Power System Technology,2013,37(8):2116-2122.
[11]冯士刚,艾芊.带精英策略的快速非支配排序遗传算法在多目标无功优化中的应用[J].电工技术学报,2007,22(12):145-151.
Feng Shigang,Ai Qian.Application of fast and elitist non-dominated sorting generic algorithm in multi-objective reactive power optimization[J].Transactions of China Electrotechnical Society,2007,22(12):145-151.
[12]陈杉,陈民铀,黄薏宸.含分布式发电的配电网多目标无功优化策略研究[J].电力系统保护与控制,2013,41(10):45-51.
Chen Shan,Chen Minyou,Huang Yichen.Multi-objective reactive power optimization of distribution system penetrated with distributed generation[J].Power System Protection and Control,2013,41(10):45-51.
[13]张聪誉,陈民铀,罗辞勇,等.基于多目标粒子群算法的电力系统无功优化[J].电力系统保护与控制,2010,38(20):153-159.
Zhang Congyu,Chen Minyou,Luo Ciyong,et al.Power system reactive power optimization based on multi-objective particle swarm algorithm[J].Power System Protection and Control,2010,38(20):153-159.
[14]王瑞,林飞,游小杰,等.基于遗传算法的分布式发电系统无功优化控制策略研究[J].电力系统保护与控制,2009,37(2):24-29.
Wang Rui,Lin Fei,You Xiaojie,et al.Research on the reactive power control of distributed generation system based on genetic algorithm[J].Power System Protection and Control,2009,37(2):24-29.
[15]周任军,刘志勇,李献梅,等.采用多随机变量超分位数方法的机组碳捕集率优化决策[J].电网技术,2014,38(11):3006-3011.
Zhou Renjun,Liu Zhiyong,Li Xianmei,et al.Optimal decision of unit carbon capture rate using multiple random variable superquantile[J].Power System Technology,2014,38(11):3006-3011.
[16]Newman M E J.Analysis of weighted networks[J].Physical Review E,2004,70(5):056131.
[17]熊虎岗,程浩忠,孔涛.基于免疫—中心点聚类算法的无功电压控制分区[J].电力系统自动化,2007,31(2):22-26.
Xiong Hugang,Cheng Haozhong,Kong Tao.Network partitioning for reactive power/voltage control based immune-central point clustering algorithm[J].Automation of Electric Power Systems,2007,31(2):22-26.
[18]Nemirovski A,Shapiro A.Convex approximations of chance constrained programs[J].SIAM Journal on Optimization,2006,17(4):969-996.
[19]段玉兵,龚宇雷,谭兴国,等.基于蒙特卡罗模拟的微电网随机潮流计算方法[J].电工技术学报,2011,26(1):274-278.
Duan Yubing,Gong Yulei,Tan Xingguo,et al.Probabilistic power flow calculation in microgrid based on monte-carlo simulation[J].Transactions of China Electrotechnical Society,2011,26(1):274-278.
[20]PSERC.Power System Engineering Research.Matpower 4.1[EB/OL].http://www.pserc.cornell.edu/matpower/.
[21]张沈习,陈楷,龙禹,等.基于混合蛙跳算法的分布式风电源规划[J].电力系统自动化,2013,37(13):76-83.
Zhang Shenxi,Chen Kai,Long Yu,et al.Distributed wind generator planning based on shuffled frog leaping algorithm[J].Automation of Electric Power Systems,2013,37(13):76-83.
[22]方斯顿,程浩忠,徐国栋,等.基于非参数核密度估计的扩展准蒙特卡洛随机潮流方法[J].电力系统自动化,2015,39(7):21-28.
Fang Sidun,Cheng Haozhong,Xu Guodong,et al.An extended quasi Monte-Carlo probabilistic load flow method based on non-parametric kernel density estimation[J].Automation of Electric Power Systems,2015,39(7):21-28.