基于纳什谈判的共享储能电站优化运行研究

doi:10.12204/j.issn.1000-7229.2022.02.001

摘要/Abstract

摘要：

可再生能源的消纳推动着储能技术的发展,共享储能因其分散性特征得到了广泛的关注。在共享储能优化调度中,面临多主体之间的利益分配问题,因此提出一种基于纳什谈判理论的共享储能电站运行优化方法。文章构建了共享储能电站及工业用户的联合模型,基于纳什谈判理论建立各运营主体的合作运行模型,根据均值不等式将此非凸非线性问题等效为系统收益最大化和电能交易支付谈判2个子问题,采用交替方向乘子法(alternating direction method of multipliers, ADMM)对其进行分布式求解。算例选取3家典型工业用户参与的共享储能联合系统,通过合作谈判前后对比分析,得出所提优化方法可以有效提高各主体的效益,同时促进新能源的消纳。

关键词: 共享储能电站, 纳什谈判, 运行优化, 交替方向乘子法(ADMM)

Abstract:

The consumption of renewable energy promotes the development of energy storage technology. Shared energy storage has attracted extensive attention because of its decentralized characteristics. In the optimal scheduling of shared energy storage, there is a problem of benefit distribution among multiple subjects. Therefore, this paper proposes an operation optimization method for shared energy-storage power station applying Nash negotiation theory. In this paper, the joint model of shared energy-storage power station and industrial users is constructed, and the cooperative operation model of various operators is established according to Nash negotiation theory. According to the mean inequality, the non-convex nonlinear problem is equivalent to two sub-problems: system revenue maximization and power transaction payment negotiation, which are solved by alternating direction method of multipliers (ADMM). Through the comparative analysis before and after the cooperative negotiation, it is concluded that the optimization method used in this paper can effectively improve the benefits of each subject and promote the consumption of new energy.

Key words: shared energy-storage power station, Nash negotiations, operation optimization, alternating direction method of multiplier(ADMM)

中图分类号:

TM73

黄铖, 刘海涛, 马丙泰, 陆恒. 基于纳什谈判的共享储能电站优化运行研究[J]. 电力建设, 2022, 43(2): 1-9.

HUANG Cheng, LIU Haitao, MA Bingtai, LU Heng. Research on Optimal Operation of Shared Energy-Storage Power Station Applying Nash Negotiation[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(2): 1-9.

图/表 14

图1 共享储能电站虚拟示意

Fig.1 Virtual schematic diagram of shared energy-storage power station

图2 ADMM算法求解流程

Fig.2 Flow chart of ADMM algorithm solving

图3 用户电负荷和光伏出力曲线

Fig.3 Curves of user electric load and photovoltaic output

表1

Table 1 Electricity price

图4 共享储能电站和用户的交互电量

Fig.4 Interactive electricity between shared energy-storage power station and users

图5 用户1的电能交易结果

Fig.5 Electricity transaction results of user 1

图6 用户2的电能交易结果

Fig.6 Electricity transaction results of user 2

图7 用户3的电能交易结果

Fig.7 Electricity transaction results of user 3

图8 共享储能电站的充放电功率和电量状态

Fig.8 Charging/discharging power and electricity state of shared energy-storage power station

图9 各主体间的电能交易价格

Fig.9 Electricity transaction price

表2 共享储能电站合作前后运行收益对比

Table 2 Comparison of operation income before and after cooperation of shared energy-storage power station元

表3 用户1合作前后运行成本对比

Table 3 Comparison of operation cost before and after user 1 cooperation元

表4 用户2合作前后运行成本对比

Table 4 Comparison of operation cost before and after user 2 cooperation元

表5 用户3合作前后运行成本对比

Table 5 Comparison of operation cost before and after user 3 cooperation 元

参考文献 23

[1]	ZHANG X L, ZHANG Y C, ZHAO Y Z, et al. Shared energy storage market operation mechanism to promote new energy consumption[J]. IOP Conference Series: Earth and Environmental Science, 2021, 766(1):012002. doi: 10.1088/1755-1315/766/1/012002 URL
[2]	贾宏杰, 王丹, 徐宪东, 等. 区域综合能源系统若干问题研究[J]. 电力系统自动化, 2015, 39(7):198-207.
	JIA Hongjie, WANG Dan, XU Xiandong, et al. Research on some key problems related to integrated energy systems[J]. Automation of Electric Power Systems, 2015, 39(7):198-207.
[3]	孙伟卿, 刘唯, 张婕. 高比例可再生能源背景下配电网动态重构与移动储能协同优化[J]. 电力系统自动化, 2021, 45(19):80-90.
	SUN Weiqing, LIU Wei, ZHANG Jie. Collaborative optimization for dynamic reconfiguration of distribution network and mobile energy storage in background of high proportion of renewable energy[J]. Automation of Electric Power Systems, 2021, 45(19):80-90.
[4]	寇凌峰, 张颖, 季宇, 等. 分布式储能的典型应用场景及运营模式分析[J]. 电力系统保护与控制, 2020, 48(4):177-187.
	KOU Lingfeng, ZHANG Ying, JI Yu, et al. Typical application scenario and operation mode analysis of distributed energy storage[J]. Power System Protection and Control, 2020, 48(4):177-187.
[5]	LIU D N, ZHAO N N, XU X F, et al. Market-oriented consumption model based on the joint tracking of renewable energy generation curve of “shared energy storage & demand side resources”[J]. IOP Conference Series: Earth and Environmental Science, 2020, 571:012007. doi: 10.1088/1755-1315/571/1/012007 URL
[6]	徐瑞龙, 田佳强, 朱亚运, 等. 基于博弈论的共享储能社区微电网能源管理[C]//第二十届中国系统仿真技术及其应用学术年会(20th CCSSTA 2019)论文集. 乌鲁木齐: 中国科学技术大学出版社, 2019: 493-497.
[7]	王仕俊, 平常, 薛国斌. 考虑共享储能的社区综合能源系统协同优化研究[J]. 中国电力, 2018, 51(8):77-84.
	WANG Shijun, PING Chang, XUE Guobin. Synergic optimization of community energy Internet considering the shared energy storage[J]. Electric Power, 2018, 51(8):77-84.
[8]	孙偲, 陈来军, 邱欣杰, 等. 基于合作博弈的发电侧共享储能规划模型[J]. 全球能源互联网, 2019, 2(4):360-366.
	SUN Cai, CHEN Laijun, QIU Xinjie, et al. A generation-side shared energy storage planning model based on cooperative game[J]. Journal of Global Energy Interconnection, 2019, 2(4):360-366.
[9]	潘倩华, 林健全, 孙伟卿. 考虑多主体电力负荷不确定性的工业园区共享储能配置与运行策略[J]. 软件, 2020, 41(7):260-263,296.
	PAN Qianhua, LIN Jianquan, SUN Weiqing. Configuration and operation strategy of shared energy storage considering multi-body power load uncertainty in industrial Parks[J]. Computer Engineering & Software, 2020, 41(7):260-263,296.
[10]	帅轩越, 王秀丽, 黄晶. 多区域综合能源系统互联下的共享储能容量优化配置[J]. 全球能源互联网, 2021, 4(4):382-392.
	SHUAI Xuanyue, WANG Xiuli, HUANG Jing. Optimal configuration of shared energy storage capacity under multiple regional integrated energy systems interconnection[J]. Journal of Global Energy Interconnection, 2021, 4(4):382-392.
[11]	林玲. 基于典型场景的微能源网多目标优化调度及共享储能容量配置研究[D]. 杭州: 浙江大学, 2021.
	LIN Ling. Research on multi-objective optimal scheduling of micro-energy grid and shared energy storage capacity allocation based on typical scenarios[D]. Hangzhou: Zhejiang University, 2021.
[12]	WALKER A, KWON S. Analysis on impact of shared energy storage in residential community: Individual versus shared energy storage[J]. Applied Energy, 2021, 282:116172. doi: 10.1016/j.apenergy.2020.116172 URL
[13]	梅生伟, 刘锋, 魏韡. 工程博弈论基础及电力系统应用[M]. 北京: 科学出版社, 2016.
[14]	孙茜. 考虑不确定性的综合能源系统非合作博弈优化调度研究[D]. 西安: 西安理工大学, 2020.
	SUN Qian. Research on optimal dispatch of non-cooperative game in integrated energy system considering uncertainty[D]. Xi’an: Xi’an University of Technology, 2020.
[15]	马腾飞, 裴玮, 肖浩, 等. 基于纳什谈判理论的风-光-氢多主体能源系统合作运行方法[J]. 中国电机工程学报, 2021, 41(1):25-39,395.
	MA Tengfei, PEI Wei, XIAO Hao, et al. Cooperative operation method for wind-solar-hydrogen multi-agent energy system based on Nash bargaining theory[J]. Proceedings of the CSEE, 2021, 41(1):25-39,395.
[16]	张进, 胡存刚, 芮涛. 多微电网参与下的配电侧直接电能交易纳什议价模型[J]. 储能科学与技术, 2019, 8(4):645-653.
	ZHANG Jin, HU Cungang, RUI Tao. Nash bargaining model for direct electricity trading on distribution side with multi-microgrids participation[J]. Energy Storage Science and Technology, 2019, 8(4):645-653.
[17]	KIM H, LEE J, BAHRAMI S, et al. Direct energy trading of microgrids in distribution energy market[J]. IEEE Transactions on Power Systems, 2020, 35(1):639-651. doi: 10.1109/TPWRS.2019.2926305 URL
[18]	吴鸣, 寇凌峰, 张进, 等. 多运营主体微电网日前经济优化调度纳什议价方法[J]. 中国电力, 2019, 52(11):19-27, 117.
	WU Ming, KOU Lingfeng, ZHANG Jin, et al. A day-ahead Nash bargaining method for economic dispatch of the multi-operator micro-grid[J]. Electric Power, 2019, 52(11):19-27, 117.
[19]	WANG Y F, WANG X L, SHAO C C, et al. Distributed energy trading for an integrated energy system and electric vehicle charging stations: A Nash bargaining game approach[J]. Renewable Energy, 2020, 155:513-530. doi: 10.1016/j.renene.2020.03.006 URL
[20]	WANG H, HUANG J W. Bargaining-based energy trading market for interconnected microgrids[C]// 2015 IEEE International Conference on Communications (ICC). London, UK: IEEE, 2015: 776-781.
[21]	李淋, 徐青山, 王晓晴, 等. 基于共享储能电站的工业用户日前优化经济调度[J]. 电力建设, 2020, 41(5):100-107.
	LI Lin, XU Qingshan, WANG Xiaoqing, et al. Optimal economic scheduling of industrial customers on the basis of sharing energy-storage station[J]. Electric Power Construction, 2020, 41(5):100-107.
[22]	FAN S L, AI Q, PIAO L J. Bargaining-based cooperative energy trading for distribution company and demand response[J]. Applied Energy, 2018, 226:469-482. doi: 10.1016/j.apenergy.2018.05.095 URL
[23]	BOYD S, PARIKH N, HU E C, et al. Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations & Trends in Machine Learning, 2010, 3(1):1-122.