含分布式风电的配电网预防性重构

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摘要分布式风电的接入不仅改变了放射状配电网的潮流分布, 且其出力的随机性与间歇性给配电网运行带来了一定的风险。本文考虑风电功率预测, 并结合配变负荷预测数据, 以线路过载和电压越限两个指标构造风险目标函数, 搜索未来24h风险最低的网络结构, 通过预防性重构, 降低电网的运行风险。针对预防性重构提出了一种混合粒子群算法, 采用无不可行解的编码规则, 既提高了搜索速度又有助于找到全局最优解。算例仿真证实了本模型和算法的有效性。

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	陈春
	汪沨
	黎灿兵
	刘蓓
	谢夏慧
	董旭柱
	何荣涛

关键词 ：分布式风电, 配电网, 预防性重构, 混合粒子群算法

Abstract：The connection of distributed wind power has not only changes the power flow distribution of radial distribution network, but also its intermittent and fluctuant pose certain risks to the operation of distribution network. This paper is based on prediction of wind output power and load, using two indexes--the line overload and voltage over-limit to construct a risk objective function, searching the network structure with minimum risk in the next 24 hours, reducing the risk of grid operation through preventive reconfiguration. In this paper, a hybrid particle swarm algorithm is proposed, and a new encoding rule is taken which can avoid creating infeasible solutions. The algorithm can improve the searching speed and be easier to find out the global optimum solution. Simulation examples show the effectiveness of the model and algorithm.

Key words： Distributed wind power distribution network preventive reconfiguration hybrid particle swarm algorithm

收稿日期: 2012-09-20 出版日期: 2014-03-25

PACS:	TM27
	TM614

基金资助:国家高技术研究发展计划(863计划)资助项目(2011AA05A114)

作者简介: 陈春男, 1987年生, 博士研究生, 主要从事智能配电网运行优化控制研究。汪沨男, 1972年生, 教授, 博士生导师, 主要研究方向为高电压绝缘及气体放电。

引用本文:

陈春, 汪沨, 黎灿兵, 刘蓓, 谢夏慧, 董旭柱, 何荣涛. 含分布式风电的配电网预防性重构[J]. 电工技术学报, 2013, 28(9): 172-177. Chen Chun, Wang Feng, Li Canbing, Liu Bei, Xie Xiahui, Dong Xuzhu, He Rongtao. Preventive Reconfiguration of Distribution Networks with Distributed Wind Power. Transactions of China Electrotechnical Society, 2013, 28(9): 172-177.

链接本文:

http://dgjsxb.ces-transaction.com/CN/Y2013/V28/I9/172

[1] 刘吉臻, 柳玉, 曾德良, 等. 单一风电场的短期负荷调度优化策略[J]. 中国科学E辑, 2012, 42(4): 437- 442.
Liu Jizhen, Liu Yu, Zeng Deliang, et al. Optimal short-term load dispatch strategy in wind form[J]. Science in China(Series E), 2012, 42(4): 437-442.
[2] 何禹清, 彭建春, 文明, 等. 含风电的配电网重构场景模型及算法[J]. 中国电机工程学报2010, 30(28): 15-18.
He Yuqing, Peng Jianchun, Wen Ming, et al. Scenario model and algorithm for the reconfiguration of distribution network with wind power generators[J]. Proceedings of the CSEE, 2010, 30(28): 15-18.
[3] Koichi Nara, Atsushi Shiose, Minoru Kitagawa, Toshihisa Ishihara. Implementation of genetic algorithm for distribution systems loss minimum reconfiguration[J]. Transactions on Power Systems, 1992, 7(3): 1044-1050.
[4] Juan Carlos Cebrian, Nelson Kagan. Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms[J]. Electric Power Systems Research, 2010, 80(1): 53-62.
[5] Anil Swarnkar, Nikhil Gupta, K R Niazi, A novel codification for meta-heuristic techniques used in distribution network reconfiguration[J]. Electric Power Systems Research, 2011, 81(7): 1619-1626.
[6] R C Eberhart, Y Shi. Comparing inertia weights and constriction factors in particle swarm optimization[C]. in: Proceeding of the IEEE Congress on Evolutionary Computation, San Diego, USA, 2000: 84-88.
[7] 张栋, 张刘春, 傅正财. 基于改进禁忌算法的配电网络重构[J]. 电工技术学报, 2005, 20 (11): 60-64.
Zhong Dong, Zhang Liuchun, Fu Zhengcai. Network reconfiguration in distribution systems using a modified TS algorithm[J]. Transactions of China Electrotechnical Society, 2005, 20(11): 60-64.
[8] Enrico Carpaneto, Gianfranco Chicco. Distribution system minimum loss reconfiguration in the Hyper- Cube ant colony optimization framework[J]. Electric
Power Systems Research, 2008, 78: 2037-2045.
[9] 刘自发, 葛少云, 余贻鑫. 一种混合智能算法在配电网络重构中的应用[J]. 中国电机工程学报, 2005, 25(15): 73-78.
Liu Zifa, Ge Shaoyuan, Yu Yixin, A hybrid intelligent algorithm for loss minimum reconfiguration in distribution networks[J]. Proceedings of the CSEE, 2005, 25(15): 73-78
[10] Ahmed R. Abul’Wafa. A new heuristic approach for optimal reconfiguration in distribution systems[J]. Electric Power Systems Research, 2011, 81: 282-289.
[11] A Y Abdelaziz, F M Mohammed, S F Mekhamer, et al. Distribution systems reconfiguration using a modified particle swarm optimization algorithm[J]. Electric Power Systems Research, 2009, 79: 1521-1530.
[12] 刘健, 毕鹏翔, 杨文宇, 等. 配电网理论及应用[M]. 北京: 中国水利水电出版社, 2007.
[13] 孙元章, 吴俊, 李国杰, 等. 基于风速预测和随机规划的含风电场电力系统动态经济调度[J]. 中国电机工程学报, 2009, 29(4): 41-47.
Sun Yuanzhang, Wu Jun, Li Guojie, et al. Dynamic economic dispatch considering wind power pene- tration based on wind speed forecasting and stochastic programming[]J. Proceedings of the CSEE, 2009, 29(4): 41-47.
[14] James W Taylor, Patrick E McSharry, Roberto Buizza, et al. Wind power density forecasting using ensemble predictions and time series models[J]. IEEE Transactions on Energy Conversion, 2009, 24(3): 775-782.
[15] 李振坤, 陈星莺, 余昆, 等. 配电网重构的混合粒子群算法[J]. 中国电机工程学报, 2008, 28(31): 35-41.
Li Zhenkun, Chen Xingying, Yu Kun. Hybrid particle swarm optimization for distribution network recon- figuration[J]. Proceedings of the CSEE, 2008, 28(31): 35-41.