基于分时电价和用户侧储能的配电网调度优化策略

doi:10.16180/j.cnki.issn1007-7820.2023.02.002

摘要/Abstract

摘要：

针对分布式电源接入及负荷波动引起配电网线路损耗增加的问题,文中提出将分时电价机制协同用户侧储能参与配电网的优化运行模型。基于分时电价建立用户负荷响应模型,构建以用户日用电成本、配电网网损最小为目标函数的配电网运行优化模型。采用评价函数法将多目标转化成单目标,并在传统遗传算法中引入模拟退火Metropolis准则对用户侧储能充放电策略寻优。仿真结果证明了文中所提策略能有效降低配电网网损及用户用电成本,所提算法寻优速度较快,收敛性能较好。

关键词: 分布式电源, 需求响应, 分时电价, 用户侧储能, 配电网优化, 评价函数法, 遗传算法, 模拟退火算法

Abstract:

In view of the problem of loss increase of distribution network caused by the access of distributed power and the fluctuation of load, this study proposes an optimal operation model that integrates the time-of-use electricity price mechanism with user-side energy storage to participate in the distribution network. Based on the time-of-use electricity price, a user load response model is established, and a distribution network operation optimization model is constructed with the user's daily electricity cost and the minimum distribution network loss as the objective function. The evaluation function method is used to convert multiple objectives into single objectives, and the simulated annealing Metropolis criterion is introduced into the traditional genetic algorithm to optimize the charging and discharging strategy of the user-side energy storage. The simulation results prove that the proposed strategy can effectively reduce the power loss of the distribution network and the cost of user electricity, which verifies that proposed algorithm has a faster optimization speed and better convergence performance.

Key words: distributed generation, demand response, time-of-use price, user side energy storage, distribution network optimization, evaluation function method, genetic algorithm, simulated annealing algorithm

中图分类号:

TP18

王玉梅,王露露. 基于分时电价和用户侧储能的配电网调度优化策略[J]. 电子科技, 2023, 36(2): 7-12.

WANG Yumei,WANG Lulu. Distribution Network Dispatching Optimization Strategy Energy Storage Based on Time-of-Use Electricity Price and User-Side[J]. Electronic Science and Technology, 2023, 36(2): 7-12.

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参考文献 20

[1]	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.
[2]	刘科研, 盛万兴, 马晓晨, 等. 基于多种群遗传算法的分布式光伏接入配电网规划研究[J]. 太阳能学报, 2021, 42(6):146-155.
	Liu Keyan, Sheng Wanxing, Ma Xiaochen, et al. Planning research of distributed photovoltaic source access distribution network based on multi-population genetic algorithm[J]. Acta Energiae Solaris Sinica, 2021, 42(6):146-155.
[3]	Palanisamy R, Muthusamy S K. Optimal siting and sizing of multiple distributed generation units in radial distribution system using ant lion optimization algorithm[J]. Journal of Electrical Engineering and Technology, 2021, 16(1):79-89. doi: 10.1007/s42835-020-00569-5
[4]	Xia Y X, Xu Q S, Zhao J, et al. Two-stage robust optimisation of user-side cloud energy storage configuration considering load fluctuation and energy storage loss[J]. IET Generation, Transmission & Distribution, 2020, 14(16):3278-3287. doi: 10.1049/iet-gtd.2019.1832
[5]	赵福林, 张通, 马光, 等. 考虑源-荷波动的电力系统灵活性运行域研究[J]. 浙江大学学报(工学版), 2021, 55(5):935-947.
	Zhao Fulin, Zhang Tong, Ma Guang, et al. Study on flexible operation region of power system considering source and load fluctuation[J]. Journal of Zhejiang University (Engineering Science), 2021, 55(5):935-947.
[6]	王鹏, 刘敏. 计及需求响应的主动配电网优化调度[J]. 电力科学与工程, 2019, 35(8):17-23.
	Wang Peng, Liu Min. Day-ahead dispatching optimization of active distribution network considering demand response[J]. Electric Power Science and Engineering, 2019, 35(8):17-23.
[7]	郭久亿, 刘洋, 郭焱林, 等. 不同典型用户侧储能配置评估与运行优化模型[J]. 电网技术, 2020, 44(11):4245-4254.
	Guo Jiuyi, Liu Yang, Guo Yanlin, et al. Configuration evaluation and operation optimization model of energy storage in different typical user-side[J]. Power System Technology, 2020, 44(11):4245-4254.
[8]	董军, 张晓虎, 李春雪, 等. 自动需求响应背景下考虑用户满意度的分时电价最优制定策略[J]. 电力自动化设备, 2016, 36(7):67-73.
	Dong Jun, Zhang Xiaohu, Li Chunxue, et al. Optimal TOU pricing strategy considering user satisfaction in automated demand response backgroud[J]. Electric Power Automation Equipment, 2016, 36(7):67-73.
[9]	陈沧杨, 胡博, 谢开贵, 等. 计入电力系统可靠性与购电风险的峰谷分时电价模型[J]. 电网技术, 2014, 38(8):2141-2148.
	Chen Cangyang, Hu Bo, Xie Kaigui, et al. A peak-valley TOU price model considering power system reliability and power purchase risk[J]. Power System Technology, 2014, 38(8):2141-2148.
[10]	麻秀范, 陈静, 余思雨, 等. 计及容量市场的用户侧储能优化配置研究[J]. 电工技术学报, 2020, 35(19):4028-4037.
	Ma Xiufan, Chen Jing, Yu Siyu, et al. Research on user side energy storage optimization configuration considering capacity market[J]. Transactions of China Electrotechnical Society, 2020, 35(19):4028-4037.
[11]	曹锐鑫, 张瑾, 朱嘉坤. 用户侧电化学储能装置最优系统配置与充放电策略研究[J]. 储能科学与技术, 2020, 9(6):1890-1896.
	Cao Ruixin, Zhang Jin, Zhu Jiakun. Study of optimal system configuration and charge-discharge strategy of user-side battery energy storage[J]. Energy Storage Science and Technology, 2020, 9(6):1890-1896.
[12]	王钤, 刘丽娜, 徐备, 等. 改善农网低电压与网损的分布式储能系统规划方案研究[J]. 东北电力大学学报, 2017, 37(5):19-24.
	Wang Qian, Liu Lina, Xu Bei, et al. Planning of distributed energy storage system for improving low voltage and network loss in rural network[J]. Journal of Northeast Electric Power University, 2017, 37(5):19-24.
[13]	吴峰, 黄绮彦, 史林军, 等. 考虑优化充放电策略的分布式储能容量配置方法[J]. 供用电, 2019, 36(5):85-92.
	Wu Feng, Huang Qiyan, Shi Linjun, et al. Distributed energy storage system capacity configuration considering optimized charging and discharging strategy[J]. Distribution & Utilization, 2019, 36(5):85-92.
[14]	Khojasteh M, Faria P, Vale Z. Energy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput concept[J]. International Journal of Electrical Power & Energy Systems, 2021, 133:1-11.
[15]	刘继春, 陈雪, 向月. 考虑共享模式的市场机制下售电公司储能优化配置及投资效益分析[J]. 电网技术, 2020, 44(5):1740-1750.
	Liu Jichun, Chen Xue, Xiang Yue. Optimal sizing and investment benefit analysis for energy storage of electricity retailers under market mechanisms considering shared mode[J]. Power System Technology, 2020, 44(5):1740-1750.
[16]	杜鹏, 藏二彬. 用户侧分布式储能接入对配电网网损的影响[J]. 黑龙江电力, 2018, 40(3):211-215.
	Du Peng, Zang Erbin. Impact on power distribution network loss by accessing distributed energy storage on user side[J]. Heilongjiang Electric Power, 2018, 40(3):211-215.
[17]	黄剑平, 陈皓勇, 林镇佳, 等. 需求侧响应背景下分时电价研究与实践综述[J]. 电力系统保护与控制, 2021, 49(9):178-187.
	Huang Jianping, Chen Haoyong, Lin Zhenjia, et al. A summary of time-of-use research and practice in a demand response environment[J]. Power System Protection and Control, 2021, 49(9):178-187.
[18]	韩子延, 卜赫男, 景旭文, 等. 基于熵值法的船舶涂装工艺多目标评价模型[J]. 船舶工程, 2019, 41(12):148-152.
	Han Ziyan, Bu Henan, Jing Xuwen, et al. Multi-objective evaluation model of ship coating process based on entropy method[J]. Ship Engineering, 2019, 41(12):148-152.
[19]	Goswami S, Basu S. A new algorithm for the reconfiguration of distribution feeders for loss minimization[J]. IEEE Transactions on Power Delivery, 1992, 7(3):1484-1491. doi: 10.1109/61.141868
[20]	杨卫红, 赖清平, 兰宇, 等. 基于调节潜力指标的用户用电行为聚类分析算法研究[J]. 电力建设, 2018, 39(6):96-104. doi: 10.3969/j.issn.1000-7229.2018.06.013
	Yang Weihong, Lai Qingping, Lan Yu, et al. Research on clustering analysis algorithm based on adjustable potential index for user power consumption behavior[J]. Electric Power Construction, 2018, 39(6):96-104. doi: 10.3969/j.issn.1000-7229.2018.06.013

场景	用户日用电成本/元	配电网网损/kW
场景1	3 617.55	1 958.15
场景2	3 331.78	1 777.71
场景3	3 018.89	1 637.55
场景4	3 017.55	1 590.75