考虑两阶段碳交易的多园区综合能源微网混合博弈优化运行方法

doi:10.19595/j.cnki.1000-6753.tces.241302

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摘要

制定合理的多园区综合能源微网的碳交易策略能够有效引导园区低碳运行,推进“双碳”目标的实现。为此,本文提出了一种考虑两阶段碳交易的多园区综合能源微网混合博弈优化运行方法。首先,提出了在第一阶段碳交易中由微网运营商向各园区综合能源微网购售碳配额,在第二阶段碳交易中由微网运营商参与外部碳交易市场的两阶段碳交易策略。其次,构建了以微网运营商作为领导者,多园区综合能源微网为跟随者的主从博弈模型,并考虑微网间电能交易,构建了多园区综合能源微网间的合作博弈模型;在此基础上,构建了由微网运营商与多园区综合能源微网的主从博弈和多园区综合能源微网间合作博弈组成的混合博弈模型。最后,采用二分法和交替方向乘子法分布式求解该混合博弈模型,并通过仿真验证了本文所提方法的优越性。

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关键词 ：多园区综合能源微网, 低碳优化运行, 混合博弈, 纳什议价, 分布式优化

Abstract：

The park's integrated energy microgrid covers the production, transmission, storage and utilization of energy, and combines electricity, thermal units and energy storage to improve energy utilization and reduce carbon emissions in the system. However, with the increasing number of entities in the microgrid, the existing carbon trading mechanism cannot meet the interests of each entity. In this context, how to take into account the interests of multiple parties and build a multi-level carbon trading strategy corresponding to the energy system is a key constraint for low-carbon operation of multi-park integrated energy microgrids. Therefore, this paper proposes a hybrid game optimization operation method for multi-park integrated energy microgrids that considers two-stage carbon trading. The aim is to formulate a reasonable carbon trading strategy of multi-park integrated energy microgrids to effectively guide the low-carbon operation of the park and promote the realization of the "double carbon" goal.
First, a two-stage carbon trading mechanism is proposed in which microgrid operators buy and sell carbon quotas to integrated energy microgrids in various parks in the first stage of carbon trading. In the second stage of carbon trading, microgrid operator s participate in external carbon trading markets. The purpose is that the operators of the microgrid will set time-varying carbon prices through the carbon quota purchase and sale information fed back by each microgrid, so as to guide the low-carbon operation of each microgrid, and enable the multi-park integrated energy microgrids to form an effective interaction with the upper market under the carbon trading mechanism. Secondly, a master-slave game model with the microgrid operators as the leader and the multi-park integrated energy microgrids as the follower are constructed, and a cooperative game model between the multi-park integrated energy microgrids is constructed considering the electricity transaction between the microgrid. On this basis, the cooperative alliance built by the multi-park integrated energy microgrids cooperation game model is taken as the follower of the master-slave game, and the microgrid operator is taken as the leader of the master-slave game, and the multi-park integrated energy microgrids hybrid game model is constructed. Among them, microgrid operators are the leaders, with the goal of maximizing their own interests, setting carbon prices and distributing them to the integrated energy microgrid of each park. The multi-park integrated energy microgrids are the follower, with the goal of minimizing the comprehensive cost, and responds to the strategy of microgrid operators through cooperation. Finally, the cooperative game model of multi-park integrated energy microgrids is transformed into two sub-problems by Nash bargaining theory, and then the mixed game model is solved by dichotomy and alternating direction multiplier method. The superiority of the proposed method is verified by simulation.
The results show that: (1) The two-stage carbon trading strategy proposed in this paper can improve the economy and low-carbon performance of each microgrid, and ensure the low-carbon operation of each microgrid in the system; (2) The multi-microgrid hybrid game optimization model constructed in this paper improves the economy of both microgrid operators and each microgrid in the system and guarantees the economy of each entity; (3) Using dichotomy and alternating direction multiplier method can solve the mixed game model efficiently on the basis of protecting the privacy of each entity.

Key words： Multi-park integrated energy microgrids low carbon optimized operation hybrid game Nash bargaining distributed optimization

收稿日期: 2024-07-22

PACS:

TM7

基金资助:

国家自然科学基金资助项目（52177084）

通讯作者: 刘浩, 男,1999年生,硕士研究生,研究方向为综合能源系统优化运行。E-mail：lh17303223906@163.com

作者简介: 李鹏, 男,1965年生,博士,教授,研究方向为新能源电力系统、综合能源系统与微网、储能技术应用、人工智能在智慧能源中的应用。E-mail：ncepulp@ncepu.edu.cn

引用本文:

李鹏, 刘浩, 李雨薇. 考虑两阶段碳交易的多园区综合能源微网混合博弈优化运行方法[J]. 电工技术学报, 0, (): 1302-7. LI Peng, LIU Hao, LI Yuwei. Multi-park Integrated Energy Microgrids Hybrid Game Optimization Strategy Considering Two-stage Carbon Trading. Transactions of China Electrotechnical Society, 0, (): 1302-7.

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[1] Li Peng, Wang Zixuan, Liu Haitao, et al.Bi-level optimal configuration strategy of community integrated energy system with coordinated planning and operation[J]. Energy, 2021, 236: 121539.
[2] 董雷, 杨子民, 乔骥, 等. 基于分层约束强化学习的综合能源多微网系统优化调度[J]. 电工技术学报, 2024, 39(5): 1436-1453.
Dong Lei, Yang Zimin, Qiao Ji, et al.Optimal scheduling of integrated energy multi-microgrid system based on hierarchical constraint reinforcement learning[J]. Transactions of China Electrotechnical Society, 2024, 39(5): 1436-1453.
[3] 闫佳佳, 滕云, 邱实, 等. 计及供能可靠性动态约束与碳减排的充能型微电网互联系统优化模型[J]. 电工技术学报, 2022, 37(23): 5956-5975.
Yan Jiajia, Teng Yun, Qiu Shi, et al.Optimization model of charging microgrid interconnection system considering dynamic constraints of energy supply reliability and carbon emission reduction[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 5956-5975.
[4] Li Peng, Wang Zixuan, Wang Jiahao, et al.A multi-time-space scale optimal operation strategy for a distributed integrated energy system[J]. Applied Energy, 2021, 289: 116698.
[5] Wang Zixuan, Li Peng, Zhou Yue, et al.Coordinated configuration strategy of multi-energy systems based on capacity-energy-information sharing[J]. Energy, 2023, 277: 127699.
[6] Sun Hongxia, Yang Jie.Optimal decisions for competitive manufacturers under carbon tax and cap-and-trade policies[J]. Computers & Industrial Engineering, 2021, 156: 107244.
[7] Li Xiaojuan, Xie Wanjun, Xu Le, et al.Holistic life-cycle accounting of carbon emissions of prefabricated buildings using LCA and BIM[J]. Energy and Buildings, 2022, 266: 112136.
[8] 李嘉祺, 陈艳波, 陈来军, 等. 工业园区综合能源系统低碳经济优化运行模型[J]. 高电压技术, 2022, 48(8): 3190-3200.
Li Jiaqi, Chen Yanbo, Chen Laijun, et al.Low-carbon economy optimization model of integrated energy system in industrial parks[J]. High Voltage Engineering, 2022, 48(8): 3190-3200.
[9] 岳子宜, 刘华志, 李永刚. 基于多阶段双重博弈的多园区随机场景低碳分布式调度优化[J/OL]. 中国电机工程学报: 1-13[2024-05-07]. https://doi.org/10.13334/j.0258-8013.pcsee.231246.
Yue Ziyi, Liu Zhihua, Li Yonggang. Low-carbon distributed scheduling optimization for multi-park stochastic situations based on a multi-stage dual game[J/OL]. Proceedings of the CSEE: 1-13[2024-05-07]. https://doi.org/10.13334/j.0258-8013.pcsee.231246.
[10] 瞿凯平, 黄琳妮, 余涛, 等. 碳交易机制下多区域综合能源系统的分散调度[J]. 中国电机工程学报, 2018, 38(3): 697-707.
Qu Kaiping, Huang Linni, Yu Tao, et al.Decentralized dispatch of multi-area integrated energy systems with carbon trading[J]. Proceedings of the CSEE, 2018, 38(3): 697-707.
[11] 刘英培, 黄寅峰. 考虑碳排权供求关系的多区域综合能源系统联合优化运行[J]. 电工技术学报, 2023, 38(13): 3459-3472.
Liu Yingpei, Huang Yinfeng.Joint optimal operation of multi-regional integrated energy system considering the supply and demand of carbon emission rights[J]. Transactions of China Electrotechnical Society, 2023, 38(13): 3459-3472.
[12] 李军徽, 邵岩, 朱星旭, 等. 计及碳排放量约束的多区域互联电力系统分布式低碳经济调度[J]. 电工技术学报, 2023, 38(17): 4715-4728.
Li Junhui, Shao Yan, Zhu Xingxu, et al.Carbon emissions constraint distributed low-carbon economic dispatch of power system[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4715-4728.
[13] 孙晓聪, 丁一, 包铭磊, 等. 考虑发电商多时间耦合决策的碳-电市场均衡分析[J]. 电力系统自动化, 2023, 47(21): 1-11.
Sun Xiaocong, Ding Yi, Bao Minglei, et al.Carbon-electricity market equilibrium analysis considering multi-time coupling decision of power producers[J]. Automation of Electric Power Systems, 2023, 47(21): 1-11.
[14] 葛少云, 程雪颖, 刘洪, 等. 园区多微网P2P电-碳耦合交易市场设计[J]. 高电压技术, 2023, 49(4): 1341-1349.
Ge Shaoyun, Cheng Xueying, Liu Hong, et al.Market design of P2P electricity carbon coupling transaction among multi-microgrids in a zone[J]. High Voltage Engineering, 2023, 49(4): 1341-1349.
[15] 刘靓颖, 蒋凯, 刘念, 等. 基于主从博弈的园区多主体能量-碳配额共享机制[J]. 中国电机工程学报, 2024, 44(6): 2119-2131.
Liu Liangying, Jiang Kai, Liu Nian, et al.Multi-agent energy-carbon sharing mechanism for parks based on Stackelberg game[J]. Proceedings of the CSEE, 2024, 44(6): 2119-2131.
[16] Tushar W, Saha T K, Yuen C, et al.A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid[J]. Applied Energy, 2019, 243: 10-20.
[17] 宋晓通, 陈佳琪, 师芊芊. 多主体博弈背景下的综合能源微网优化调度[J]. 高电压技术, 2023, 49(8): 3163-3178.
Song Xiaotong, Chen Jiaqi, Shi Qianqian.Optimal scheduling of integrated energy microgrid under the background of multi-agent game[J]. High Voltage Engineering, 2023, 49(8): 3163-3178.
[18] 李鹏, 吴迪凡, 李雨薇, 等. 基于综合需求响应和主从博弈的多微网综合能源系统优化调度策略[J]. 中国电机工程学报, 2021, 41(4): 1307-1321, 1538.
Li Peng, Wu Difan, Li Yuwei, et al.Optimal dispatch of multi-microgrids integrated energy system based on integrated demand response and Stackelberg game[J]. Proceedings of the CSEE, 2021, 41(4): 1307-1321, 1538.
[19] 潘郑楠, 邓长虹, 徐慧慧, 等. 考虑灵活性补偿的高比例风电与多元灵活性资源博弈优化调度[J]. 电工技术学报, 2023, 38(增刊1): 56-69.
Pan Zhengnan, Deng Changhong, Xu Huihui, et al.Game optimization scheduling of high proportion wind power and multiple flexible resources considering flexibility compensation[J]. Transactions of China Electrotechnical Society, 2023, 38(S1): 56-69.
[20] 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.
[21] 崔明勇, 宣名阳, 卢志刚, 等. 基于合作博弈的多综合能源服务商运行优化策略[J]. 中国电机工程学报, 2022, 42(10): 3548-3564.
Cui Mingyong, Xuan Mingyang, Lu Zhigang, et al.Operation optimization strategy of multi integrated energy service companies based on cooperative game theory[J]. Proceedings of the CSEE, 2022, 42(10): 3548-3564.
[22] 董雷, 李扬, 陈盛, 等. 考虑多重不确定性与电碳耦合交易的多微网合作博弈优化调度[J]. 电工技术学报, 2024, 39(9): 2635-2651.
Dong Lei, Li Yang, Chen Sheng, et al.Multi-microgrid cooperative game optimization scheduling considering multiple uncertainties and coupled electricity-carbon transactions[J]. Transactions of China Electrotechnical Society, 2024, 39(9): 2635-2651.
[23] 王再闯, 陈来军, 李笑竹, 等. 基于合作博弈的产销者社区分布式光伏与共享储能容量优化[J]. 电工技术学报, 2022, 37(23): 5922-5932.
Wang Zaichuang, Chen Laijun, Li Xiaozhu, et al.Capacity optimization of distributed PV and shared energy storage of prosumer community based on cooperative game[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 5922-5932.
[24] 林墨涵, 刘佳, 唐早, 等. 考虑多能耦合共享储能的微网多智能体混合博弈协调优化[J]. 电力系统自动化, 2024, 48(4): 132-141.
Lin Mohan, Liu Jia, Tang Zao, et al.Coordinated optimization of mixed microgrid multi-agent game considering multi-energy coupled shared energy storage[J]. Automation of Electric Power Systems, 2024, 48(4): 132-141.
[25] 张忠会, 熊骁跃, 万昶, 等. 计及电-碳交易与综合贡献率的多微网合作运行优化策略[J]. 电网技术, 2024, 48(8): 3258-3268.
Zhang Zhonghui, Xiong Xiaoyue, Wan Chang, et al.Multi-microgrids cooperative operation optimization strategy considering electricity-carbon trading and comprehensive contribution rate[J]. Power System Technology, 2024, 48(8): 3258-3268.
[26] Yan Mingyu, Shahidehpour M, Alabdulwahab A, et al.Blockchain for transacting energy and carbon allowance in networked microgrids[J]. IEEE Transactions on Smart Grid, 2021, 12(6): 4702-4714.
[27] Cheng Yaohua, Zhang Ning, Zhang Baosen, et al.Low-carbon operation of multiple energy systems based on energy-carbon integrated prices[J]. IEEE Transactions on Smart Grid, 2020, 11(2): 1307-1318.
[28] 孔令国, 史立昊, 石振宇, 等. 基于交替方向乘子法的园区电-氢-热系统低碳优化调度[J]. 电工技术学报, 2023, 38(11): 2932-2944.
Kong Lingguo, Shi Lihao, Shi Zhenyu, et al.Low-carbon optimal dispatch of electric-hydrogen-heat system in park based on alternating direction method of multipliers[J]. Transactions of China Electrotechnical Society, 2023, 38(11): 2932-2944.