基于博弈论的含DG配电网动态重构研究

doi:10.16180/j.cnki.issn1007-7820.2021.04.009

摘要/Abstract

摘要：

文中针对含DG配电网的清洁能源输出功率消纳问题进行了研究。采用多目标的合作博弈对配电网划分的各个时段进行重构。在以多个重构目标为博弈者进行合作博弈的基础上,建立多目标动态重构模型。以模拟退火法思想改进后的果蝇寻优算法路交换法对该模型进行求解,得到每个时段上的最优解,再根据时段划分得到研究对象的最优动态重构方案。此外,对含有风力发电站和光伏发电站的IEEE33节点配电系统做了算例仿真,得到了兼顾运行成本和清洁能源利用率的配电网最优动态重构方案。该方案使得整个重构过程中只需动作14次,网络损耗减少31%且DG消纳量增加了115%,证明了提出的数学模型及解题方案的有效性。

关键词: 博弈论, 果蝇寻优算法, 模拟退火法, 多目标重构, 有源配电网, 全局寻优思想, 清洁能源消纳量, 合作博弈

Abstract:

In this study, the problem of clean energy output power dissipation in distribution network with DG in invertigated. The multi-objective cooperative game is used to reconstruct the distribution network in each period. A multi-objective dynamic reconstruction model is established on the basis of cooperative games with multiple reconstruction targets as players. The model is solved by the route exchange method of the drosophila optimization algorithm improved by the idea of simulated annealing method to obtain the optimal solution in each time period, and then the most dynamic reconstruction scheme of the research object is obtained according to the time period division.The IEEE33-node power distribution system including wind power station and photovoltaic power station is simulated, and the optimal dynamic reconfiguration scheme of power distribution network considering both operation cost and clean energy utilization rate is obtained. During the whole reconfiguration process, only 14 actions are taken, the network loss is reduced by 31% and the DG consumption is increased by 115%, which verifies the effectiveness of the proposed mathematical model and solution scheme.

Key words: game theory, drosophila optimization algorithm, simulated annealing, multi-objective reconstruction, active power distribution network, global optimization idea, consumption of clean energy, cooperative game

中图分类号:

TP183

王玉梅,杨文亮. 基于博弈论的含DG配电网动态重构研究[J]. 电子科技, 2021, 34(4): 52-58.

WANG Yumei,YANG Wenliang. Research on Dynamic Reconfiguration of Distribution Network with DG Based on Game Theory[J]. Electronic Science and Technology, 2021, 34(4): 52-58.

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参考文献 23

[1]	Bo R. Network reconfiguration for loss reduction in distribution network with distributed generation[C]. Beijing:IEEE Proceedings of IEEE International Conference on Power and Renewable Energ, 2016.
[2]	李文云, 曹敏, 李坤 , 等. 考虑合环调电约束的配电网快速重构方法[J]. 电力系统保护与控制, 2019,47(16):159-165.
	Li Wenyun, Cao Min, Li Kun , et al. A method for rapid reconfiguration of distribution network considering hybrid ring adjustment[J]. Power System Protection and Control, 2019,47(16):159-165.
[3]	Lopez J C, Lavorato M, Rider M J. Optimal reconfiguration of electrical distribution systems considering reliability indices improvement[J]. International Journal of Electrical Power and Energy Systems, 2016,78(78):837-845.
[4]	许火炬, 缪希仁. 交直流混合配电方式及其故障保护研究综述[J]. 电力系统保护与控制, 2017,45(5):139-146.
	Xu Huoju, Miao Xiren. Overview of AC/DC hybrid distribution mode and its fault protection[J]. Power System Protection and Control, 2017,45(5):139-146.
[5]	张大海, 江世芳, 赵建国. 配电网重构研究的现状与展望[J]. 电力自动化设备, 2002(2):75-76,82.
	Zhang Dahai, Jiang Shifang, Zhao Jianguo. Current status and prospects of research on distribution network reconfiguration[J]. Power Automation Equipment, 2002(2):75-76,82.
[6]	杨明, 翟鹤峰, 马嘉翼 , 等. 计及分布式电源发电不平衡度约束的三相不对称配电网动态重构[J]. 中国电机工程学报, 2019,39(12):3486-3499.
	Yang Ming, Zhai Hefeng, Ma Jiayi , et al. Dynamic reconstruction of three-phase asymmetrical distribution network considering unbalanced constraints of distributed power generation[J]. Proceedings of the CSEE, 2019,39(12):3486-3499.
[7]	张磐, 唐萍, 丁一 , 等. 考虑分布式发电波动性的有源配电网故障恢复策略[J]. 电力系统及其自动化学报, 2018,30(1):115-120.
	Zhang Pan, Tang Ping, Ding Yi , et al. Active distribution network fault recovery strategy considering distributed power generation volatility[J]. Journal of Power Systems and Automation, 2018,30(1):115-120.
[8]	毕鹏翔, 刘健, 张文元. 配电网络重构的改进支路交换法[J]. 中国电机工程学报, 2001(8):99-104.
	Bi Pengxiang, Liu Jian, Zhang Wenyuan. Improved branch exchange method for distribution network reconfiguration[J]. Chinese Society for Electrical Engineering, 2001(8):99-104.
[9]	李振兴, 田斌, 尹项根 , 等. 含分布式电源与随机负荷的主动配电网保护[J]. 高电压技术, 2017,43(4):1231-1238.
	Li Zhenxing, Tian Bin, Yin Xianggen , et al. Active distribution network protection with distributed power supply and random load[J]. High Voltage Engineering, 2017,43(4):1231-1238.
[10]	李本瑜, 翟海燕, 赵明 , 等. 电力系统零序网络最优控制技术研究[J]. 电力系统保护与控制, 2016,44(18):152-156.
	Li Benyu, Zhai Haiyan, Zhao Ming , et al. Study on optimal control technology of zero sequence network in power system[J]. Power System Protection and Control, 2016,44(18):152-156.
[11]	郭小璇, 龚仁喜, 鲍海波 , 等. 含新能源电力系统机会约束经济调度的二阶锥规划方法[J]. 电力系统保护与控制, 2015,43(22):85-91.
	Guo Xiaoxuan, Gong Renxi, Bao Haibo , et al. Second-order cone programming method for opportunistic constrained economic dispatch of new energy power systems[J]. Power System Protection and Control, 2015,43(22):85-91.
[12]	易茗, 王仕龙, 范雨萌. 引入加权系数的交直流混合微电网潮流计算[J]. 电子科技, 2019,32(4):90-95.
	Yi Ming, Wang Shilong, Fan Yumeng. Power flow calculation of AC/DC hybrid microgrid with weighted coefficient[J]. Electronic Science and Technology, 2019,32(4):90-95.
[13]	陈强, 刘瑾, 杨海马 , 等. 基于改进遗传算法的配电网无功优化研究[J]. 电子科技, 2019,32(5):11-15,37.
	Chen Qiang, Liu Jin, Yang Haima , et al. Research on reactive power optimization of distribution network based on improved genetic algorithm[J]. Electronic Science and Technology, 2019,32(5):11-15,37.
[14]	庄剑. 基于神经网络算法的配电网重构研究[J]. 计算机与数字工程, 2019,47(8):2094-2101.
	Zhuang Jian. Research on distribution network reconfiguration based on neural network algorithm[J]. Computer and Digital Engineering, 2019,47(8):2094-2101.
[15]	王晓, 何悦星, 李立波 , 等. 分布式光伏电源接入的配电网馈线重构技术[J]. 自动化技术与应用, 2019,38(7):94-99.
	Wang Xiao, He Yuexing, Li Libo , et al. Retribution technology of distribution network feeder reconstruction with distributed photovoltaic power supply[J]. Automation Technology and Application, 2019,38(7):94-99.
[16]	贾勇晨, 葛丽娟, 解治中 , 等. 基于并行人工蜂群算法的含DG的配电网重构[J]. 内蒙古农业大学学报(自然科学版), 2019,40(4):58-63.
	Jia Yongchen, Ge Lijuan, Jie Zhizhong , et al. Reconstruction of distribution network with DG based on parallel artificial bee colony algorithm[J]. Journal of Inner Mongolia Agricultural University(Natural Science Edition), 2019,40(4):58-63.
[17]	范宏, 刘自超, 郭翔. 基于差分进化入侵杂草算法的含分布式电源配电网重构[J]. 可再生能源, 2019,37(4):545-551.
	Fan Hong, Liu Zichao, Guo Xiang. Reconstruction of distributed power distribution network based on differential evolution intrusive weed algorithm[J]. Renewable Energy, 2019,37(4):545-551.
[18]	李锰, 王利利, 刘向实 , 等. 基于门当户对遗传算法的配电网多目标主动重构研究[J]. 电力系统保护与控制, 2019,47(7):30-38.
	Li Meng, Wang Lili, Liu Xiangshi , et al. Study on multi-objective active reconstruction of distribution network based on genetic algorithm[J]. Power System Protection and Control, 2019,47(7):30-38.
[19]	瞿合祚, 李晓明, 杨玲君 , 等. 考虑负荷和分布式电源时变性的配电网多目标动态重构和DG调度[J]. 高电压技术, 2019,45(3):873-881.
	Qu Hezuo, Li Xiaoming, Yang Lingjun , et al. Multi-objective dynamic reconstruction and DG scheduling of distribution network considering load and distributed power supply time-varying[J]. High Voltage Technology, 2019,45(3):873-881.
[20]	黄泰相, 陈波, 管鑫 , 等. 基于电子搜索算法的电力系统无功优化[J]. 电子科技, 2019,32(1):58-61,71.
	Huang Taixiang, Chen Bo, Guan Xin , et al. Reactive Power Optimization of Power System Based on Electronic Search Algorithm[J]. Electronic Science and Technology, 2019,32(1):58-61,71.
[21]	丁阳, 汪沨, 宾峰 , 等. 基于博弈论的多目标配电网重构[J]. 电力自动化设备, 2019,39(2):28-35.
	Ding Yang, Wang Feng, Bin Feng , et al. Multi-objective distribution network reconfiguration based on game theory[J]. Electric Power Automation Equipment, 2019,39(2):28-35.
[22]	朱勇, 陶用伟, 李泽群 , 等. 基于随机约束粒子群算法的配电网重构[J]. 计算机与数字工程, 2019,47(1):122-129.
	Zhu Yong, Tao Yongwei, Li Zequn , et al. Reconfiguration of distribution network based on stochastic constrained particle swarm optimization algorithm[J]. Computer and Digital Engineering, 2019,47(1):122-129.
[23]	王健, 贾俊, 李然 , 等. 基于改进遗传算法的配电网重构研究[J]. 信息技术, 2019,43(1):108-112.
	Wang Jian, Jia Jun, Li Ran , et al. Research on distribution network reconfiguration based on improved genetic algorithm[J]. Information Technology, 2019,43(1):108-112.

联络开关	环路内开关编码
1 9-15	9 10 11 12 13 14 15
2 8-21	19 20 21 8 7 6 5 4 3 2
3 12-22	21 22 12 11 10 9 8
4 25-29	3 4 5 6 26 27 28 29 25 24 23
5 18-33	6 7 8 9 15 16 17 18 33 32 31 30 29 28 27 26

接入节点	DG类型	容量/kW	功率因数
10,27	光伏电池	200	1.0
16,31	风电机组	500	0.9

目标	断开支路	网络损耗/kW	DG消纳量/kW	动作次数
初始状态	8-21,9-15,12-22, 18-33,25-29	226.351	532.457	0
网络损耗最优	6:00-7:00 6-26,8-21,12-22,31-32,23-24	135.754	416.253	13
	10:00-11:00 5-6,8-21,21-22,25-29,31-32
	21:00-22:00 6-26,13-14,12-22,31-32,23-24
	23:00-24:00 6-26,8-21,12-22,25-29,31-32
DG消纳量最优	6:00-7:00 5-6,13-14,8-9,18-33,23-24	215.534	651.753	17
	11:00-12:00 5-6,8-21,21-22,18-33,23-24
	20:00-21:00 6-26,13-14,12-22,31-32,23-24
	23:00-24:00 5-6,13-14,8-9,31-32,23-24
多目标合作博弈	6:00-7:00 5-6,13-14,8-9,31-32,23-24	157.432	612.346	14
	11:00-12:00 6-26,13-14,12-22,31-32,23-24
	20:00-21:00 6-26,13-14,21-22,31-32,23-24
	23:00-24:00 5-6,8-21,12-22,18-33,31-32