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储能系统技术 ★ 5.0

基于共享储能的电能与备用协同DSO-VPP运行框架:一种混合博弈方法

Coordinated DSO-VPP operation framework with energy and reserve integrated from shared energy storage: A mixed game method

作者 Mohan Lin · Jia Liu · Zao Tang · Yue Zhou · Biao Jiang · Pingliang Zeng · Xinghua Zhou
期刊 Applied Energy
出版日期 2025年1月
卷/期 第 379 卷
技术分类 储能系统技术
相关度评分 ★★★★★ 5.0 / 5.0
关键词 Mixed game method combining Stackelberg game and Cooperative game is built.
语言:

中文摘要

摘要 虚拟电厂(VPPs)通过整合分布式可再生资源、优化能源生产与消费模式以及促进电网动态管理,提升了配电系统的灵活性与经济性。然而,在多虚拟电厂协调运行时仍面临诸多挑战,包括复杂的时空相关特性以及多主体决策中的利益冲突。共享储能(SES)作为共享经济背景下的产物,能够更加灵活地协助VPP消纳分布式可再生能源发电。因此,针对VPP之间的互补性问题与利益冲突,并提升分布式可再生能源的利用率,本文提出了一种由配电网运营商(DSO)主导、多VPP与SES共同参与的电能-备用协同优化模型。首先,为DSO-VPP系统设计了一种斯塔克尔伯格-合作混合博弈(SC-混合博弈)框架,其中DSO作为领导者,通过斯塔克尔伯格博弈优化DSO与各VPP之间的交易电价,同时利用合作博弈求解多VPP的运行策略。此外,本文为SES提出了一个考虑六种备用模式的电能-备用联合模型,以进一步挖掘SES的备用潜力并保障其提供备用的能力。同时,提出一种定制化的交替方向乘子法(ADMM),结合二分法,用于高效求解所构建的SC-混合博弈模型。最后,通过多个算例分析验证了所提模型的有效性。

English Abstract

Abstract Virtual power plants (VPPs) contribute to the flexibility and economy of distributed system by leveraging integrated distributed renewable resources , optimizing energy production and consumption patterns, and facilitating dynamic grid management. However, challenges arise when multi-VPPs coordinated operate, including complex spatial and temporal correlation characteristics and conflicting interests in multi-agent decision-making. Shared energy storage (SES), as a product of the sharing economy, can be more flexible to help VPPs consume power generation from distributed renewable resources. Hence, focusing on the complementary problems and conflicts of interest between VPPs and improving the utilization of distributed renewable resources, this paper proposes an energy-reserve coordinated optimization model led by the distribution system operator (DSO) and involves the participation of both multi-VPPs and SES. Firstly, a Stackelberg-cooperative mixed game (SC-mixed game) framework is proposed for the DSO-VPP system, which leverages the DSO as the leader. The transactional electricity price between DSO and VPPs is optimized via the Stackelberg game, and the operation strategies for multi-VPPs can be calculated by the Cooperative game. Besides, an energy-reserve model is proposed for SES, which considers six reserve modes for further exploring the reserve potential of SES and guarantee the reserve provision ability. Additionally, a tailored alternating direction method of multipliers (ADMM), integrating a bisection method , is proposed to solve the SC-mixed game model efficiently. Finally, several case studies are conducted to validate the effectiveness of the proposed model.
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SunView 深度解读

该DSO-VPP协调运行框架对阳光电源ST系列储能变流器和PowerTitan系统具有重要应用价值。论文提出的共享储能能量-备用联合优化模型,可指导我司储能系统在多VPP场景下的双层博弈控制策略开发。六种备用模式设计可深度挖掘ST-PCS的调频调峰潜力,结合iSolarCloud平台实现分布式光储资源的协同优化调度。ADMM分布式求解算法适配我司GFM/VSG控制技术,提升多主体利益平衡下的储能利用率和新能源消纳能力,为构建源网荷储协同生态提供技术支撑。