基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法

谭慧娟; 李世明; 郭文鑫; 赵瑞锋; 徐展强

doi:10.19912/j.0254-0096.tynxb.2022-0394

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (5) : 468-477. DOI: 10.19912/j.0254-0096.tynxb.2022-0394

基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法

谭慧娟, 李世明, 郭文鑫, 赵瑞锋, 徐展强

作者信息 +

FAST RECONFIGURATION METHOD OF DISTRIBUTION NETWORK WITH HOUSEHOLD ENERGY STORAGE BASED ON CHAOTIC ADAPTIVE ARTIFICIAL FISH SWARM ALGORITHM

Tan Huijuan, Li Shiming, Guo Wenxin, Zhao Ruifeng, Xu Zhanqiang

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文章历史 +

摘要

针对分布式电源接入配电网具有波动性和随机性的特点,提出一种基于混沌自适应人工鱼群算法的含分布式电源配电网快速化重构方法。在风电、光伏和家用储能的数学模型和节点划分基础上,以电网网损、开关次数以及失电负荷成本最小为目标函数,建立基于多目标优化的含分布式电源配电网的优化重构模型。利用混沌自适应人工鱼群算法对模型进行求解,通过对鱼群的混沌初始化和自适应动态调整步长参数,提高了算法的全局搜索能力和收敛速度。根据电化学储能系统出力特性划分配电网网架重构的典型工作场景,通过含分布式电源的IEEE 33节点测试系统仿真实例验证了该文方法的有效性。仿真结果表明,与单独考虑电网网损成本相比,由该文方法得到的配电网优化重构成本降低了50%以上,优化重构时间均小于0.9 s,实现了含分布式电源配电网的快速自愈。

Abstract

In view of the volatility and randomness of distributed power sources in distribution network, a fast reconfiguration method of distribution network with distributed power sources and household energy storage based on chaotic adaptive artificial fish swarm algorithm is proposed in this paper. Based on the mathematical models and node division of wind power, photovoltaic and household energy storage, the optimization and reconstruction model of distribution network with distributed power sources is established according to the minimum operating cost considering network loss, switching times and load cost. The chaos adaptive artificial fish swarm algorithm is used to solve the model, and the global searching ability and convergence speed of the algorithm is improved by the chaotic initialization and adaptive dynamic adjustment of step parameters. According to the output characteristics of household energy storage system, the typical working scenarios of distribution network reconfiguration are divided, and the effectiveness of the proposed method is verified by a simulation example of IEEE 33 node test system with distributed power sources. The simulation results show that compared with the cost of network loss alone, the self-healing reconstruction cost of the system obtained by the method in this paper is reduced by more than 50%, and the optimal reconstruction time of distribution network is less than 0.9 s, which can realize fast self-healing of distribution network with distributed power sources.

导出引用

谭慧娟, 李世明, 郭文鑫, 赵瑞锋, 徐展强. 基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法[J]. 太阳能学报. 2022, 43(5): 468-477 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0394

Tan Huijuan, Li Shiming, Guo Wenxin, Zhao Ruifeng, Xu Zhanqiang. FAST RECONFIGURATION METHOD OF DISTRIBUTION NETWORK WITH HOUSEHOLD ENERGY STORAGE BASED ON CHAOTIC ADAPTIVE ARTIFICIAL FISH SWARM ALGORITHM[J]. Acta Energiae Solaris Sinica. 2022, 43(5): 468-477 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0394

中图分类号： TM727.2

参考文献

[1] 杨丽君, 高鹏, 王伟浩, 等. 考虑时间尺度的配电网故障恢复方法研究[J]. 太阳能学报, 2021, 42(1): 453-459.
YANG L J, GAO P, WANG W H, et al.Research on fault recovery method considering time scale for distribution network[J]. Acta energiae solaris sinica, 2021, 42(1): 453-459.
[2] 杨晓萍, 王李瑾. 基于概率潮流的含分布式电源配电网优化[J]. 太阳能学报, 2021, 42(8): 71-76.
YANG X P, WANG L J.Optimization of distributed power distribution network based on probabilistic load flow[J]. Acta energiae solaris sinica, 2021, 42(8): 71-76.
[3] 丁明, 胡迪, 毕锐, 等. 含高渗透率可再生能源的配电网可靠性分析[J]. 太阳能学报, 2020, 41(2): 194-202.
DING M, HU D, BI R, et al.Reliability analysis of distribution system containing high penetration renewable energy[J]. Acta energiae solaris sinica, 2020, 41(2): 194-202.
[4] 肖峻, 李航, 王博, 等. 分布式电源接入城市配电网的综合匹配评价方法[J]. 电力系统自动化, 2020, 44(15): 44-51.
XIAO J, LI H, WANG B, et al.Comprehensive matching evaluation method for integration of distributed generator into urban distribution network[J]. Automation of electric power systems, 2020, 44(15): 44-51.
[5] 朱文广, 李映雪, 杨为群, 等. 面向区域配电网的分布式电源接入运行方式优化研究[J]. 电测与仪表, 2020, 57(13): 84-90.
ZHU W G, LI Y X, YANG W Q, et al.Research on optimization of distributed power access operation mode for regional distribution network[J]. Electrical measurement & instrumentation, 2020, 57(13): 84-90.
[6] 刘雷, 余小虎, 金鑫, 等. 分布式电源接入配电网适应性分析[J]. 电力系统装备, 2020(23): 46-47.
LIU L, YU X H, JIN X, et al.Adaptive analysis of distributed power access distribution network[J]. Electric power system equipment, 2020(23): 46-47.
[7] 徐渊. 改进粒子群算法在含分布式电源配电网优化重构中的应用[J]. 电测与仪表, 2021, 58(3): 98-104.
XU Y.Application of improved particle swarm optimization in distribution network reconfiguration with distributed generation[J]. Electrical measurement & instrumentation, 2021, 58(3): 98-104.
[8] 郭腾云, 刘艳. 基于博弈方法的含分布式电源配电网重构优化[J]. 电力系统保护与控制, 2017, 45(7): 28-34.
GUO T Y, LIU Y.Game theory-based reconfiguration optimization for distribution network with distributed generations[J]. Power system protection and control, 2017, 45(7): 28-34.
[9] 李超, 苗世洪, 盛万兴, 等. 考虑动态网络重构的主动配电网优化运行策略[J]. 电工技术学报, 2019, 34(18): 3909-3919.
LI C, MIAO S H, SHENG W X, et al.Optimization operation strategy of active distribution network considering dynamic network reconfiguration[J]. Transactions of China Electrotechnical Society, 2019, 34(18): 3909-3919.
[10] 丛鹏伟, 唐巍, 娄铖伟, 等. 含高渗透率可再生能源的主动配电网两阶段柔性软开关与联络开关协调优化控制[J]. 电工技术学报, 2019, 34(6): 1263-1272.
CONG P W, TANG W, LOU C W, et al.Two-stage coordination optimization control of soft open point and tie switch in active distribution network with high penetration renewable energy generation[J]. Transactions of China Electrotechnical Society, 2019, 34(6): 1263-1272.
[11] 林清源, 薛毓强, 曾乙宸. 配电网重构研究综述[J]. 电气开关, 2021, 59(1): 3-8.
LIN Q Y, XUE Y Q, ZENG Y C.Overview of research on distribution network reconfiguration[J]. Electric switcher, 2021, 59(1): 3-8.
[12] 汪芳宗, 王兆丰. 基于混合整数二次锥规划方法的含分布式电源配电网优化重构方法[J]. 电力系统保护与控制, 2016, 44(24): 24-30.
WANG F Z, WANG Z F.An optimum reconfiguration method for distribution networks with DG based on mixed integer second-order cone programming[J]. Power system protection and control, 2016, 44(24): 24-30.
[13] 姚艳, 许家玉, 崔勤越. 基于DistFlow的含分布式电源配电网优化重构模型[J]. 能源工程, 2020(1): 12-16.
YAO Y, XU J Y, CUI Q Y.Study on optimization reconfiguration modelling for distribution networkwith distributed generators based on DistFlow equations[J]. Energy engineering, 2020(1): 12-16.
[14] 张欣, 裴立耕, 王永庆, 等. 基于灰狼算法的多目标配电网重构[J]. 电网与清洁能源, 2020, 36(3): 34-41.
ZHANG X, PEI L G, WANG Y Q, et al.Multi-objective distribution network reconfiguration based on grey wolf algorithmp[J]. Advances of power system & hydroelectric engineering, 2020, 36(3): 34-41.
[15] 徐泽, 杨伟, 张文强, 等. 基于连锁环网与改进离散粒子群算法的多目标配电网重构[J]. 电力系统保护与控制, 2021, 49(6): 114-123.
XU Z, YANG W, ZHANG W Q, et al.Multi-objective distribution network reconfiguration based on chain loops and improved binary particle swarm optimization[J]. Power system protection and control, 2021, 49(6): 114-123.
[16] 蒋黎莉, 李国庆, 戴丽丽. 基于思维进化算法的可用输电能力计算[J]. 东北电力大学学报, 2011, 31(4): 23-29.
JIANG L L, LI G Q, DAI L L.Available transfer capability calculation based on mind evolution algorithm[J]. Journal of Northeast China Institute of Electric Power Engineering, 2011, 31(4): 23-29.
[17] 武晓朦, 李新桥. 基于并行禁忌搜索算法的配电网重构[J]. 西安石油大学学报(自然科学版), 2021, 36(2): 122-126.
WU X M, LI X Q.Distribution network reconfiguration based on parallel tabu search algorithm[J]. Journal of Xi’an Shiyou University(natural science edition), 2021, 36(2): 122-126.
[18] 荣秀婷, 王承民, 叶斌, 等. 基于方向矩阵的PSO算法在配网重构中的应用[J]. 电测与仪表, 2019, 56(9): 63-68.
RONG X T, WANG C M, YE B, et al.Application of PSO algorithm based on direction matrix in distribution network reconfiguration[J]. Electrical measurement & instrumentation, 2019, 56(9): 63-68.
[19] 邹锐, 王超学. 基于改进参数协进化和声搜索算法的配电网重构[J]. 自动化仪表, 2021, 42(7): 53-58,62.
ZOU R, WANG C X.Distribution network reconfiguration based on improved harmony search algorithm with parameters co-evolution[J]. Process automation instrumentation, 2021, 42(7): 53-58,62.
[20] 潘本仁, 王和春, 张妍, 等. 含分布式电源的主动配电网重构策略研究[J]. 电力系统保护与控制, 2020, 48(15): 102-107.
PAN B R, WANG H C, ZHANG Y, et al.Study on an active distribution network reconstruction strategy with distributed power supply[J]. Power system protection and control, 2020, 48(15): 102-107.
[21] 罗雯清, 张焰. 含风光储发电的配电网潮流计算方法[J]. 华东电力, 2013, 41(2): 337-340.
LUO W Q, ZHANG Y.Power flow calculation for distribution network with wind/PV/storage access[J]. East China electric power, 2013, 41(2): 337-340.
[22] 黄涛, 王倩, 谭又宁. 计及分布式电源的配电网重构研究[J]. 电力学报, 2012, 27(3): 199-202, 206.
HUANG T, WANG Q, TAN Y N.Research on the distribution network reconfiguration pondering distributed generation[J]. Journal of electric power, 2012, 27(3): 199-202, 206.
[23] 王日宏, 李祥, 李娜. 基于高斯扰动和混沌初始化的狼群算法[J]. 计算机工程与设计, 2019, 40(10): 2879-2884.
WANG R H, LI X, LI N.Wolf pack algorithm based on Gaussian disturbance and chaotic initialization[J]. Computer engineering and design, 2019, 40(10): 2879-2884.
[24] 杜振鑫. 基于混沌初始化和高斯扰动的烟花算法[J]. 计算机时代, 2016(7): 56-58.
DU Z X.Improved fireworks algorithm based on chaos initialization and Gaussian perturbation[J]. Computer era, 2016(7): 56-58.
[25] 刘东林, 李乐乐. 一种新颖的改进人工鱼群算法[J]. 计算机科学, 2017, 44(4): 281-287.
LIU D L, LI L L.New improved artificial fish swarm algorithm[J]. Computer science, 2017, 44(4): 281-287.
[26] 张晓博, 陈家慧, 彭进业, 等. 基于复合混沌序列的图像加密方法[J]. 计算机应用研究, 2019, 36(11): 3396-3400.
ZANG X B, CHEN J H, PENG J Y, et al.Image encryption algorithm based on complex chaotic sequences[J]. Application research of computers, 2019, 36(11): 3396-3400.
[27] 王联国, 洪毅, 赵付青, 等. 一种改进的人工鱼群算法[J]. 计算机工程, 2008, 34(19): 192-194.
WANG L G, HONG Y, ZHAO F Q, et al.Improved artificial fish swarm algorithm[J]. Computer engineering, 2008, 34(19): 192-194.
[28] 何力, 吕红芳, 李俊甫, 等. 基于模拟退火算法改进的人工鱼群算法(SA_AFSA)的微电网能量优化调度研究[J]. 太阳能学报, 2020, 41(9): 36-43.
HE L, LYU H F, LI J F, et al.Research on optimal scheduling of microgrid energy based on SA_AFSA[J]. Acta energiae solaris sinica, 2020, 41(9): 36-43.
[29] 郑焕坤, 曾凡斐, 傅钰, 等. 基于E-C-K-均值聚类和SOP优化的分布式电源双层规划[J]. 太阳能学报, 2022, 43(2): 127-135.
ZHENG H K, ZENG F F, FU Y, et al.Bi-level distributed power planning based on E-C-K-means clustering and SOP optimization[J]. Acta energiae solaris sinica, 2022, 43(2): 127-135.
[30] 郑梦莲, 胡亚才. 基于储能的家庭需求响应策略和经济性分析[J]. 上海节能, 2016(5): 256-260.
ZHENG M L, HU Y C.Study on family demand response strategy and economic analysis based on energy storage[J]. Shanghai energy conservation, 2016(5): 256-260.