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1.智慧能源工程技术研究中心,华南理工大学电力学院,广东省广州市 510640
2.广东电网有限责任公司电力调度控制中心,广东省广州市 510062
Received:30 May 2023,
Revised:2023-10-05,
Published Online:04 January 2024,
Published:10 February 2024
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张军,钟康骅,张勇军等.基于混合博弈的多区域电-储共享运营模式与经济效益分析[J].电力系统自动化,2024,48(3):31-41.
ZHANG Jun,ZHONG Kanghua,ZHANG Yongjun,et al.Hybrid Game Based Sharing Operation Mode for Multi-regional Electric Power and Energy Storage and Its Economic Benefit Analysis[J].Automation of Electric Power Systems,2024,48(3):31-41.
张军,钟康骅,张勇军等.基于混合博弈的多区域电-储共享运营模式与经济效益分析[J].电力系统自动化,2024,48(3):31-41. DOI: 10.7500/AEPS20230530002.
ZHANG Jun,ZHONG Kanghua,ZHANG Yongjun,et al.Hybrid Game Based Sharing Operation Mode for Multi-regional Electric Power and Energy Storage and Its Economic Benefit Analysis[J].Automation of Electric Power Systems,2024,48(3):31-41. DOI: 10.7500/AEPS20230530002.
随着用户侧新能源设备与储能装置的广泛接入,如何有效地促进新能源本地消纳与降低储能运行成本变得至关重要。针对多区域间电能与储能资源的共享问题,提出了一种基于主从-演化混合博弈的多区域电能-储能共享运营模式。首先,建立主从博弈模型和演化博弈模型进行优化决策。运营商作为领导者根据各区域供需平衡情况,制定区域内部电价;用户作为跟随者,根据区域电价与跨区交易传输费用信息,基于演化博弈模型调整自身用电量与区域选择概率。其次,考虑到各主体利益诉求不同,建立了运营商和用户的收入与成本模型,并以最大化双方收益、最小化与电网交互电量为目标函数,得到运营商的定价策略、共享储能配置与充放电策略,以及各主体的最终收益。最后,通过算例分析验证了所提运营模式的有效性。
With the extensive access of the renewable energy equipment and energy storage devices on user sides
how to effectively promote the local consumption of renewable energy and reduce the operation costs of energy storage become crucial. Aiming at sharing electric power and energy storage resources among multiple regions
a sharing operation mode for multi-regional electric power and energy storage based on master-slave-evolutionary hybrid game is proposed. Firstly
the master-slave game model and the evolutionary game model are established for the optimal decision. The operator
as a leader
sets the intra-regional tariffs according to the balance of supply and demand in each region. The users
as followers
adjust their own electricity consumption and region selection probability according to the regional tariffs and transmission cost information of inter-regional trades based on the evolutionary game model. Secondly
considering the different interest demands of each entity
the revenue and cost models of operators and users are established
and the pricing strategy of operators
the allocation and charging/discharging strategies of shared energy storages
and the final revenue of each entity are obtained by taking the maximization of the revenue of both parties and the minimization of the electricity quantities interacting with the power grid as the objective functions. Finally
the validity of the proposed operation mode is verified by case study.
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