Source-Grid-Load Multi-agent Coordinated Interactive Planning in Power Market Environment

doi:10.12204/j.issn.1000-7229.2024.02.013

Abstract

Abstract:

The emergence of a large number of new agents and power market transactions are crucial characteristics of new power systems. A planning model for source-network-load multiagent coordination and interaction based on game theory is proposed to comprehensively consider the interests of multiple subjects and market factors. First, the market relationship of each agent in the distribution network is analyzed, and the distribution locational marginal price is integrated into the optimal configuration model of the distributed power operators, distribution network operators, and power users. Second, a demand side response model is established based on the power utility function of the user. Third, combined with the game relationship between the three, a source-network-load coordinated interaction model is constructed, and an iterative search method based on the particle swarm optimization algorithm is used to solve it. Finally, the improved IEEE 33-bus system and the actual 9-bus system are used for the example analysis. The results show that considering the interest relationship of each subject in the electricity market environment can slow down the investment of lines and distributed power sources while ensuring the balance of interests among the subjects, which has practical significance.

Key words: game theory, power market, distribution network planning, multi-stakeholder, demand response, distributed generation

CLC Number:

TM715

KANG Yiming, QIN Wenping, YAO Hongmin, XING Yahong, HU Yingying, JIA Xingping. Source-Grid-Load Multi-agent Coordinated Interactive Planning in Power Market Environment[J]. ELECTRIC POWER CONSTRUCTION, 2024, 45(2): 147-159.

Figures/Tables 23

Fig.1 The market relationship of source-network-load in distribution network

Table 1 Definition of game elements

Fig.2 Source-network-load coordinated interactive planning model diagram

Fig.3 Game model solving flow chart

Table 2 Simulation parameters

Fig.4 IEEE 33-node distribution network

Fig.5 Electricity price change curve

Fig.6 Comparison chart of typical daily load curve

Table 3 The bus cost situation of the typical day 元

Table 4 The planning results of different planning models

Table 5 DG investment operator fees 万元

Table 6 Distribution network operator fees 万元

Table 7 Planning results based on different electricity price mechanisms

Fig.7 The fees changes of distribution network operator

Fig.8 A 9-bus distribution network system in Shanxi province (example bus diagram)

Table 8 The planning results of different planning models in the 9-bus actual distribution network system

Table 9 DG investment operator fees in the 9-bus actual distribution network system 万元

Fig.9 The fees changes of distribution network operators with different planning models

Table 10 Planning results based on different electricity price mechanisms in the 9-bus actual distribution network system

Fig.10 The fees changes of distribution network operators under different electricity price mechanism

Table A1 9-bus distribution network system load node parameters

Table A2 9-bus distribution network system operating parameters

Table A3 9-bus distribution network system to be accessed line parameters

References 35

[1]	丁一, 谢开, 庞博, 等. 中国特色、全国统一的电力市场关键问题研究(1):国外市场启示、比对与建议[J]. 电网技术, 2020, 44(7): 2401-2410.
	DING Yi, XIE Kai, PANG Bo, et al. Key issues of national unified electricity market with Chinese characteristics(1): enlightenment, comparison and suggestions from foreign countries[J]. Power System Technology, 2020, 44(7): 2401-2410.
[2]	武昭原, 周明, 王剑晓, 等. 双碳目标下提升电力系统灵活性的市场机制综述[J]. 中国电机工程学报, 2022, 42(21): 7746-7764.
	WU Zhaoyuan, ZHOU Ming, WANG Jianxiao, et al. Review on market mechanism to enhance the flexibility of power system under the dual carbon target[J]. Proceedings of the CSEE, 2022, 42(21): 7746-7764.
[3]	国家发展改革委国家能源局. 关于加快建设全国统一电力市场体系的指导意见[R/OL]. (2022-01-18)[2023-03-10]. https://www.ndrc.gov.cn/xxgk/zcfb/tz/202201/t20220128_1313653.html.
[4]	赵海波, 邢亚虹, 康一鸣, 等. 计及运行灵活性的配电网双层规划[J]. 现代电力, 2023, 40(5): 817-826.
	ZHAO Haibo, XING Yahong, KANG Yiming, et al. Bi-level planning of distribution network considering operation flexibility[J]. Modern Electric Power, 2023, 40(5): 817-826.
[5]	杨修宇, 刘沛烨, 孙勇, 等. 考虑灵活性需求演化规律的灵活性资源动态规划方法[J]. 电力建设, 2023, 44(9): 3-12. doi: 10.12204/j.issn.1000-7229.2023.09.001
	YANG Xiuyu, LIU Peiye, SUN Yong, et al. Dynamic planning method for flexible resources considering evolution of flexibility requirements[J]. Electric Power Construction, 2023, 44(9): 3-12. doi: 10.12204/j.issn.1000-7229.2023.09.001
[6]	杨楠, 李希喆, 刘毅, 等. 电力市场环境下基于多边不完全信息演化博弈的配电网规划方法研究[J]. 电网技术, 2023, 47(11): 4658-4673.
	YANG Nan, LI Xizhe, LIU Yi, et al. Research on distribution network planning method based on multi-lateral incomplete information evolutionary game in power market[J]. Power System Technology, 2023, 47(11): 4658-4673.
[7]	华晔. 电力市场环境下区域配电网规划方法研究[D]. 北京: 华北电力大学, 2018.
[8]	张永明, 郭晨雨, 何英静, 等. 开放售电市场环境下考虑DG和ILR的配电网双层规划[J]. 电力科学与技术学报, 2020, 35(3): 107-113.
	ZHANG Yongming, GUO Chenyu, HE Yingjing, et al. Distribution network planning considering DG and ILR under the environment of power sales side liberalization[J]. Journal of Electric Power Science and Technology, 2020, 35(3): 107-113.
[9]	NAZAR M S, HAGHIFAM M R, NAŽAR M. A scenario driven multiobjective primary-secondary distribution system expansion planning algorithm in the presence of wholesale-retail market[J]. International Journal of Electrical Power & Energy Systems, 2012, 40(1): 29-45. doi: 10.1016/j.ijepes.2012.02.002 URL
[10]	VAHIDINASAB V, TABARZADI M, ARASTEH H, et al. Overview of electric energy distribution networks expansion planning[J]. IEEE Access, 2020, 8: 34750-34769. doi: 10.1109/Access.6287639 URL
[11]	宋卓然, 程孟增, 牛威, 等. 面向能源互联网的零碳园区优化规划关键技术与发展趋势[J]. 电力建设, 2022, 43(12): 15-26. doi: 10.12204/j.issn.1000-7229.2022.12.002
	SONG Zhuoran, CHENG Mengzeng, NIU Wei, et al. Key technologies and development trends of zero-carbon park optimization planning for energy internet[J]. Electric Power Construction, 2022, 43(12): 15-26. doi: 10.12204/j.issn.1000-7229.2022.12.002
[12]	黄志鹏, 李黄强, 舒征宇, 等. 基于配电自动化故障管理的配电网扩展规划方法[J]. 智慧电力, 2022, 50(4): 66-72.
	HUANG Zhipeng, LI Huangqiang, SHU Zhengyu, et al. Expansion planning method of distribution system based on distribution automation fault management[J]. Smart Power, 2022, 50(4): 66-72.
[13]	刘建伟, 李学斌, 刘晓鸥. 有源配电网中分布式电源接入与储能配置[J]. 发电技术, 2022, 43(3): 476-484. doi: 10.12096/j.2096-4528.pgt.21068
	LIU Jianwei, LI Xuebin, LIU Xiaoou. Distributed power access and energy storage configuration in active distribution network[J]. Power Generation Technology, 2022, 43(3): 476-484. doi: 10.12096/j.2096-4528.pgt.21068
[14]	江知瀚, 陈金富. 计及不确定性和多投资主体需求指标的分布式电源优化配置方法研究[J]. 中国电机工程学报, 2013, 33(31): 34-42, 4.
	JIANG Zhihan, CHEN Jinfu. Optimal distributed generator allocation method considering uncertainties and requirements of different investment entities[J]. Proceedings of the CSEE, 2013, 33(31): 34-42, 4.
[15]	李逐云, 雷霞, 邱少引, 等. 考虑“源-网-荷”三方利益的主动配电网协调规划[J]. 电网技术, 2017, 41(2): 378-387.
	LI Zhuyun, LEI Xia, QIU Shaoyin, et al. Coordinated planning of active distribution network considering “source-grid-load” benefits[J]. Power System Technology, 2017, 41(2): 378-387.
[16]	冯喜春, 韩璟琳, 赵辉, 等. 主从博弈框架下配电网规划运行多目标协同优化方法[J]. 南方电网技术, 2023, 17(1): 26-34, 72.
	FENG Xichun, HAN Jinglin, ZHAO Hui, et al. Multi-objective cooperative optimization method of distribution network planning and operation under the stackelberg game framework[J]. Southern Power System Technology, 2023, 17(1): 26-34, 72.
[17]	张渊, 黄河, 朱海宇, 等. 计及多主体效益的增量配电网优化规划方法[J]. 南京理工大学学报, 2022, 46(1): 61-68.
	ZHANG Yuan, HUANG He, ZHU Haiyu, et al. Incremental distribution network optimization planning method considering multi-agent benefits[J]. Journal of Nanjing University of Science and Technology, 2022, 46(1): 61-68.
[18]	胡晶, 陈红坤, 陈磊, 等. 考虑多主体利益与需求响应的分布式电源优化配置[J]. 电力系统保护与控制, 2021, 49(15): 38-46.
	HU Jing, CHEN Hongkun, CHEN Lei, et al. Distributed generation planning in an active distribution network considering multi-agent interests and demand response[J]. Power System Protection and Control, 2021, 49(15): 38-46.
[19]	曾鸣. 电力需求侧响应原理及其在电力市场中的应用[M]. 北京: 中国电力出版社, 2011.
[20]	高岩. 基于需求侧管理实时电价优化方法综述[J]. 上海理工大学学报, 2022, 44(2): 103-111, 121.
	GAO Yan. A review on real-time electricity price optimization methods based on demand side management[J]. Journal of University of Shanghai for Science and Technology, 2022, 44(2): 103-111, 121.
[21]	陈倩, 王维庆, 王海云. 基于需求侧响应的主动配电网双层优化方法[J]. 电力系统保护与控制, 2022, 50(16): 1-13.
	CHEN Qian, WANG Weiqing, WANG Haiyun. Bi-level optimization model of an active distribution network based on demand response[J]. Power System Protection and Control, 2022, 50(16): 1-13.
[22]	王永利, 王晓海, 王硕, 等. 基于输配电价改革的电网运维成本分摊方法研究[J]. 电网技术, 2020, 44(1): 332-339.
	WANG Yongli, WANG Xiaohai, WANG Shuo, et al. A method allocating operation and maintenance cost of power grid project based on transmission and distribution price reform[J]. Power System Technology, 2020, 44(1): 332-339.
[23]	邱辰. 可再生能源分布式发电市场化交易试点“过网费”价格机制分析与建议[J]. 水力发电, 2022, 48(9): 104-107.
	QIU Chen. Analysis and suggestions on the pricing mechanism of transmission and distribution fee of pilot distributed power generation nearby trading[J]. Water Power, 2022, 48(9): 104-107.
[24]	詹祥澎, 杨军, 王昕妍, 等. 考虑实时市场联动的电力零售商鲁棒定价策略[J]. 电网技术, 2022, 46(6): 2141-2153.
	ZHAN Xiangpeng, YANG Jun, WANG Xinyan, et al. Robust pricing strategy of power retailer considering linkage of real-time market[J]. Power System Technology, 2022, 46(6): 2141-2153.
[25]	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.
[26]	刘自发, 张子腾. 考虑多主体博弈的配电网源网荷储协同规划[J]. 电网技术, 2023, 47(12): 5046-5058.
	LIU Zifa, ZHANG Ziteng. Collaborative planning of distribution network source-network-load-storage considering multi-agent game[J]. Power System Technology, 2023, 47(12): 5046-5058.
[27]	熊威. 基于多主体博弈的分布式电源投资决策与交易策略研究[D]. 北京: 华北电力大学, 2022.
	XIONG Wei. Research on investment decision and trading strategy of distributed generation based on multi-agent game[D]. Beijing: North China Electric Power University, 2022.
[28]	董邦天. 不确定环境下考虑多主体博弈的增量配电网规划方法研究[D]. 宜昌: 三峡大学, 2019.
	DONG Bangtian. Research on incremental distribution network planning method considering multi-agent game in uncertain environment[D]. Yichang: China Three Gorges University, 2019.
[29]	杨楠, 董邦天, 黄禹, 等. 考虑不确定性和多主体博弈的增量配电网源网荷协同规划方法[J]. 中国电机工程学报, 2019, 39(9): 2689-2702.
	YANG Nan, DONG Bangtian, HUANG Yu, et al. Incremental distribution network source-load collaborative planning method considering uncertainty and multi-agent game[J]. Proceedings of the CSEE, 2019, 39(9): 2689-2702.
[30]	彭一海, 刘继春, 刘俊勇. 两级电力市场环境下考虑多类型零售套餐的售电公司购售电策略[J]. 电网技术, 2022, 46(3): 944-957.
	PENG Yihai, LIU Jichun, LIU Junyong. Electricity purchasing and selling strategies for electricity retailers considering multiple types of retail packages in two level electricity market[J]. Power System Technology, 2022, 46(3): 944-957.
[31]	陈玥, 刘锋, 魏韡, 等. 需求侧能量共享:概念、机制与展望[J]. 电力系统自动化, 2021, 45(2): 1-11.
	CHEN Yue, LIU Feng, WEI Wei, et al. Energy sharing at demand side: concept, mechanism and prospect[J]. Automation of Electric Power Systems, 2021, 45(2): 1-11.
[32]	CHAI B, CHEN J M, YANG Z Y, et al. Demand response management with multiple utility companies: a two-level game approach[J]. IEEE Transactions on Smart Grid, 2014, 5(2): 722-731. doi: 10.1109/TSG.2013.2295024 URL
[33]	KAMYAB F, AMINI M, SHEYKHHA S, et al. Demand response program in smart grid using supply function bidding mechanism[J]. IEEE Transactions on Smart Grid, 2016, 7(3): 1277-1284. doi: 10.1109/TSG.2015.2430364 URL
[34]	张忠会, 赖飞屹, 谢义苗. 基于纳什均衡理论的电力市场三方博弈分析[J]. 电网技术, 2016, 40(12): 3671-3679.
	ZHANG Zhonghui, LAI Feiyi, XIE Yimiao. Analysis of trilateral game in electricity market based on Nash equilibrium theory[J]. Power System Technology, 2016, 40(12): 3671-3679.
[35]	刘广一. 主动配电网规划与运行[M]. 北京: 中国电力出版社, 2017.