基于双向主从博弈的储能电站与综合能源系统经济运行策略

doi:10.19595/j.cnki.1000-6753.tces.221164

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (1067 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

When connected to energy supply entities such as active distribution networks (ADNs), energy storage stations (ESPSs) and natural gas networks, the energy supply reliability of the integrated energy system (IES) can be effectively improved. However, with the participation of ESPSs in market transactions, how to improve the initiative of ESPSs to realize the economic operation between the IES and the ESPS is an urgent problem to be addressed. Making full use of the interest relationship between various entities to game is an important way to achieve the economic operation of the IES and the ESPS. However, the game model adopted by the traditional economic operation method did not consider the duality of the participating subjects as both leaders and followers. This kind of game model cannot fully mobilize the initiative of the participating subjects.
To this end, a bidirectional master-slave game-based economic operation strategy is proposed for ESPS and IES in this paper. First, aiming at the economic benefits of the IES, ADN and ESPS, the corresponding economic operation models are established respectively. The models consider the constraints of each subject and the loss in energy transmission. Then, based on the duality of the ESPS as the energy supplier and the energy user, an energy interaction mechanism for the ADN, ESPS, and IES is constructed. The energy interaction mechanism considers the master-slave and competition relationship between the ADN and ESPS. Third, a bidirectional master-slave game model with the ADN as the leader, the ESPS as the secondary leader and the IES as the follower is proposed. The existence of the unique equilibrium solution of the proposed game strategy is proved theoretically in this paper. Finally, a simulation model is built based on the IEEE 33 node distribution network and Belgium’s 20 node natural gas network. The bi-level particle swarm optimization algorithm and CPLEX solver are used to perform the numerical simulation. Three kinds of economic operation schemes are set up for comparative analysis. Scheme 1 is the economic operation strategy proposed in this paper. In scheme 2, the dynamic electricity price of ADN is considered, and no ESPS participates in the economic operation. In scheme 3, both ADN and ESPS adopt fixed electricity prices, and there is no game relationship between each subject. Simulation results show that, compared with scheme 2 and scheme 3, the overall system benefit of scheme 1 is increased by 8.1% and 28.6%, respectively. This comparison results verify the superiority of the proposed strategy in improving economic benefits.
The following conclusions can be drawn from the simulation analysis:(1) The proposed strategy gives full play to the initiative of the ESPS participating in the economic operation. (2) The proposed strategy comprehensively considers the master-slave and competitive relationship between the ADN and ESPS, which is suitable for the actual scenario of the IES economic operation. (3) The proposed strategy can make full use of the game relationship between all subjects, improve the overall economic benefits of the system, and achieve mutual benefit and win-win results for all subjects.

Key words： Integrated energy system energy storage power station bidirectional master-slave game economical operation

Received: 20 June 2022

PACS:

TM732

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Wang Can
	Zhang Yu
	Tian Fuyin
	Xi Lei
	Ling Kai

Cite this article:

Wang Can,Zhang Yu,Tian Fuyin等. Economic Operation of Energy Storage Power Stations and Integrated Energy Systems Based on Bidirectional Master-Slave Game[J]. Transactions of China Electrotechnical Society, 0, (): 221164-221164.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.221164 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/221164

[1] 张沈习, 王丹阳, 程浩忠, 等. 双碳目标下低碳综合能源系统规划关键技术及挑战[J]. 电力系统自动化, 2022, 46(8): 189-207.
Zhang Shenxi, Wang Danyang, Cheng Haozhong, et al.Key technologies and challenges of low-carbon integrated energy system planning for carbon emission peak and carbon neutrality[J]. Automation of Electric Power Systems, 2022, 46(8): 189-207.
[2] 边晓燕, 史越奇, 裴传逊, 等. 计及经济性和可靠性因素的区域综合能源系统双层协同优化配置[J]. 电工技术学报, 2021, 36(21): 4529-4543.
Bian Xiaoyan, Shi Yueqi, Pei Chuanxun, et al.Bi-level collaborative configuration optimization of integrated community energy system considering economy and reliability[J]. Transactions of China Electrotechnical Society, 2021, 36(21): 4529-4543.
[3] 陈岑, 武传涛, 林湘宁, 等. 计及上下游市场的园区综合能源商购售能策略[J]. 电工技术学报, 2022, 37(1): 220-231.
Chen Cen, Wu Chuantao, Lin Xiangning, et al.Purchase and sale strategies of park integrated energy suppliers in wholesale and retail markets[J]. Transactions of China Electrotechnical Society, 2022, 37(1): 220-231.
[4] 李勇, 姚天宇, 乔学博, 等. 基于联合时序场景和源网荷协同的分布式光伏与储能优化配置[J]. 电工技术学报, 2022, 37(13): 3289-3303.
Li Yong, Yao Tianyu, Qiao Xuebo, et al.Optimal configuration of distributed photovoltaic and energy storage system based on joint sequential scenario and source-network-load coordination[J]. Transactions of China Electrotechnical Society, 2022, 37(13): 3289-3303.
[5] 张大海, 贠韫韵, 王小君, 等. 考虑广义储能及光热电站的电热气互联综合能源系统经济调度[J]. 电力系统自动化, 2021, 45(19): 33-42.
Zhang Dahai, Yun Yunyun, Wang Xiaojun, et al.Economic dispatch of integrated electricity-heat-gas energy system considering generalized energy storage and concentrating solar power plant[J]. Automation of Electric Power Systems, 2021, 45(19): 33-42.
[6] 吴盛军, 李群, 刘建坤, 等. 基于储能电站服务的冷热电多微网系统双层优化配置[J]. 电网技术, 2021, 45(10): 3822-3832.
Wu Shengjun, Li Qun, Liu Jiankun, et al.Bi-level optimal configuration for combined cooling heating and power multi-microgrids based on energy storage station service[J]. Power System Technology, 2021, 45(10): 3822-3832.
[7] 杨永标, 于建成, 李奕杰, 等. 含光伏和蓄能的冷热电联供系统调峰调蓄优化调度[J]. 电力系统自动化, 2017, 41(6): 6-12, 29.
Yang Yongbiao, Yu Jiancheng, Li Yijie, et al.Optimal load leveling dispatch of CCHP incorporating photovoltaic and storage[J]. Automation of Electric Power Systems, 2017, 41(6): 6-12, 29.
[8] 李鹏, 周益斌, 李明哲, 等. 基于谈判博弈的含储能站利益主体的多能源站协同优化运行方法[J]. 高电压技术, 2021, 47(5): 1666-1677.
Li Peng, Zhou Yibin, Li Mingzhe, et al.Cooperative optimal operation method of multiple energy stations with stakeholder of energy storage station based on negotiation game[J]. High Voltage Engineering, 2021, 47(5): 1666-1677.
[9] 孙偲, 郑天文, 陈来军, 等. 基于组合双向拍卖的共享储能机制研究[J]. 电网技术, 2020, 44(5): 1732-1739.
Sun Cai, Zheng Tianwen, Chen Laijun, et al.Energy storage sharing mechanism based on combinatorial double auction[J]. Power System Technology, 2020, 44(5): 1732-1739.
[10] 金力, 房鑫炎, 蔡振华, 等. 考虑特性分布的储能电站接入的电网多时间尺度源储荷协调调度策略[J]. 电网技术, 2020, 44(10): 3641-3650.
Jin Li, Fang Xinyan, Cai Zhenhua, et al.Multiple time-scales source-storage-load coordination scheduling strategy of grid connected to energy storage power station considering characteristic distribution[J]. Power System Technology, 2020, 44(10): 3641-3650.
[11] Cheng Shan, Wang Rui, Xu Jianyu, et al.Multi-time scale coordinated optimization of an energy hub in the integrated energy system with multi-type energy storage systems[J]. Sustainable Energy Technologies and Assessments, 2021, 47: 101327.
[12] 王雪纯, 陈红坤, 陈磊. 提升区域综合能源系统运行灵活性的多主体互动决策模型[J]. 电工技术学报, 2021, 36(11): 2207-2219.
Wang Xuechun, Chen Hongkun, Chen Lei.Multi-player interactive decision-making model for operational flexibility improvement of regional integrated energy system[J]. Transactions of China Electrotechnical Society, 2021, 36(11): 2207-2219.
[13] 王海洋, 李珂, 张承慧, 等. 基于主从博弈的社区综合能源系统分布式协同优化运行策略[J]. 中国电机工程学报, 2020, 40(17): 5435-5445.
Wang Haiyang, Li Ke, Zhang Chenghui, et al.Distributed coordinative optimal operation of community integrated energy system based on stackelberg game[J]. Proceedings of the CSEE, 2020, 40(17): 5435-5445.
[14] 马丽, 刘念, 张建华, 等. 基于主从博弈策略的社区能源互联网分布式能量管理[J]. 电网技术, 2016, 40(12): 3655-3662.
Ma Li, Liu Nian, Zhang Jianhua, et al.Distributed energy management of community energy Internet based on leader-followers game[J]. Power System Technology, 2016, 40(12): 3655-3662.
[15] Ma Li, Liu Nian, Zhang Jianhua, et al.Energy management for joint operation of CHP and PV prosumers inside a grid-connected microgrid: a game theoretic approach[J]. IEEE Transactions on Industrial Informatics, 2016, 12(5): 1930-1942.
[16] 王瑞, 程杉, 汪业乔, 等. 基于多主体主从博弈的区域综合能源系统低碳经济优化调度[J]. 电力系统保护与控制, 2022, 50(5): 12-21.
Wang Rui, Cheng Shan, Wang Yeqiao, et al.Low-carbon and economic optimization of a regional integrated energy system based on a master-slave game with multiple stakeholders[J]. Power System Protection and Control, 2022, 50(5): 12-21.
[17] 李咸善, 马凯琳, 程杉. 含多区域综合能源系统的主动配电网双层博弈优化调度策略[J]. 电力系统保护与控制, 2022, 50(1): 8-22.
Li Xianshan, Ma Kailin, Cheng Shan.Dispatching strategy of an active distribution network with multiple regional integrated energy systems based on two-level game optimization[J]. Power System Protection and Control, 2022, 50(1): 8-22.
[18] 吴利兰, 荆朝霞, 吴青华, 等. 基于Stackelberg博弈模型的综合能源系统均衡交互策略[J]. 电力系统自动化, 2018, 42(4): 142-150, 207.
Wu Lilan, Jing Zhaoxia, Wu Qinghua, et al.Equilibrium strategies for integrated energy systems based on stackelberg game model[J]. Automation of Electric Power Systems, 2018, 42(4): 142-150, 207.
[19] 芮涛, 李国丽, 王群京, 等. 配电侧多微电网日前电能交易纳什议价方法[J]. 电网技术, 2019, 43(7): 2576-2585.
Rui Tao, Li Guoli, Wang Qunjing, et al.Nash bargaining method for multi-microgrid energy trading in distribution network[J]. Power System Technology, 2019, 43(7): 2576-2585.
[20] 田晓翠, 董常龙, 杨正然, 等. 天然气管输损耗分析与控制综述[J]. 当代化工, 2014, 43(7): 1322-1325.
Tian Xiaocui, Dong Changlong, Yang Zhengran, et al.Review of analysis and control for gas loss of pipeline[J]. Contemporary Chemical Industry, 2014, 43(7): 1322-1325.
[21] 孙鹏, 滕云, 回茜, 等. 考虑异质能流输运特性的多能源系统惯量极限优化[J]. 中国电机工程学报, 2022, 42(10): 3642-3656.
Sun Peng, Teng Yun, Hui Qian, et al.Inertia limit optimization of multi-energy system considering the transport characteristics of heterogeneous energy flow[J]. Proceedings of the CSEE, 2022, 42(10): 3642-3656.
[22] Paudel A, Chaudhari K, Long Chao, et al.Peer-to-peer energy trading in a prosumer-based community microgrid: a game-theoretic model[J]. IEEE Transactions on Industrial Electronics, 2019, 66(8): 6087-6097.
[23] Yu Mengmeng, Hong S H.A real-time demand-response algorithm for smart grids: a stackelberg game approach[J]. IEEE Transactions on Smart Grid, 2016, 7(2): 879-888.
[24] 刁涵彬, 李培强, 吕小秀, 等. 考虑多元储能差异性的区域综合能源系统储能协同优化配置[J]. 电工技术学报, 2021, 36(1): 151-165.
Diao Hanbin, Li Peiqiang, Lü Xiaoxiu, et al.Coordinated optimal allocation of energy storage in regional integrated energy system considering the diversity of multi-energy storage[J]. Transactions of China Electrotechnical Society, 2021, 36(1): 151-165.
[25] 谢畅, 王蓓蓓, 赵盛楠, 等. 基于双层粒子群算法求解电力市场均衡[J]. 电网技术, 2018, 42(4): 1170-1177.
Xie Chang, Wang Beibei, Zhao Shengnan, et al.Equilibrium solution for electricity market based on Bi-level particle swarm optimization algorithm[J]. Power System Technology, 2018, 42(4): 1170-1177.