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1.山东大学电气工程学院,山东省济南市 250061
2.山东电力工程咨询院有限公司,山东省济南市 250013
3.国网山东省电力公司青岛供电公司,山东省青岛市 266000
Received:22 June 2024,
Revised:2024-09-21,
Published Online:12 December 2024,
Published:10 January 2025
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WANG Guoying,WANG Chengfu,NIU Yuanfang,et al.Cooperative Optimal Decision-making for Active Distribution Network with Shared Energy Storage Leased by Prosumers[J].Automation of Electric Power Systems,2025,49(1):105-116.
王国英,王成福,牛远方等.含产消者租赁共享储能的主动配电网协同优化决策[J].电力系统自动化,2025,49(1):105-116. DOI: 10.7500/AEPS20240622005.
WANG Guoying,WANG Chengfu,NIU Yuanfang,et al.Cooperative Optimal Decision-making for Active Distribution Network with Shared Energy Storage Leased by Prosumers[J].Automation of Electric Power Systems,2025,49(1):105-116. DOI: 10.7500/AEPS20240622005.
共享储能作为一种新兴储能运营模式,在降低产消者投资成本、提高储能利用效率等方面发挥了重要作用。但是,当前产消者彼此间以及其与共享储能运营商之间的复杂交互和利益竞争加剧了主动配电网优化调控的难度。因此,提出一种含产消者租赁共享储能的主动配电网协同优化决策方法。首先,构建了一种考虑配电系统运营商、产消者和共享储能运营商间交互影响的多主体协同交易框架。其次,建立了计及共享储能参与的点对点电力共享交易机制,并据此提出了产消者租赁共享储能的两阶段定价策略,采用议价因子指标量化价格制定过程中各主体的议价能力。然后,建立了基于改进纳什议价的主动配电网博弈优化模型,在指数项中引入议价因子用以设定其在目标中的权重,实现收益的合理分配。最后,采用改进的IEEE 33节点配电系统进行算例仿真
验证了所提方法的有效性。
As an emerging energy storage operation mode
the shared energy storage plays an important role in reducing the investment cost of prosumers and improving the efficiency of energy storage utilization. However
the current complex interactions and competing interests between prosumers
as well as with the shared energy storage operator (SESO)
have exacerbated the difficulty in optimizing and regulating active distribution network. Therefore
a cooperative optimal decision-making method for the active distribution network with shared energy storage leased by prosumers is proposed. Firstly
the framework of the multi-agent cooperative transaction is constructed
which considers the interaction among distribution system operators
prosumers and SESOs. Secondly
a peer-to-peer power sharing trading mechanism that takes into account the participation of shared energy storage is established. And a two-stage pricing strategy for prosumers leasing shared energy storage is proposed accordingly. A bargaining factor indicator is used to quantify the bargaining power of each entity in the pricing process. Then
a game-based optimization model for active distribution network based on the improved Nash bargaining is established
and the bargaining factor is introduced in the index term to set its weight in the objective to achieve a reasonable distribution of benefits. Finally
an improved IEEE 33-bus distribution system is used to simulate and verify the effectiveness of the proposed method.
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