卞一帆, 谢丽蓉, 鲁宗相, 叶林, 路朋, 马伟. 基于多主体投资的双储能系统分层优化配置方案[J]. 电力系统自动化, 2023, 47(1): 63-73.
引用本文: 卞一帆, 谢丽蓉, 鲁宗相, 叶林, 路朋, 马伟. 基于多主体投资的双储能系统分层优化配置方案[J]. 电力系统自动化, 2023, 47(1): 63-73.
BIAN Yifan, XIE Lirong, LU Zongxiang, YE Lin, LU Peng, MA Wei. Multi-agent Investment Based Hierarchical Optimal Configuration Scheme for Dual Energy Storage System[J]. Automation of Electric Power Systems, 2023, 47(1): 63-73.
Citation: BIAN Yifan, XIE Lirong, LU Zongxiang, YE Lin, LU Peng, MA Wei. Multi-agent Investment Based Hierarchical Optimal Configuration Scheme for Dual Energy Storage System[J]. Automation of Electric Power Systems, 2023, 47(1): 63-73.

基于多主体投资的双储能系统分层优化配置方案

Multi-agent Investment Based Hierarchical Optimal Configuration Scheme for Dual Energy Storage System

  • 摘要: 储能电站的建设可缓解中国“三北”地区的“弃风限电”问题,提升当地电网消纳弃风的能力,但单主体投资储能的高昂成本限制了储能的推广与应用。针对此问题,构建了一种基于多主体投资的双储能系统分层优化配置模型。首先,提出了考虑循环寿命的双储能协调运行策略,以减小频繁充放电切换导致的寿命损耗;然后,为实现多投资主体的利益最大化,提出了双层优化经济性模型,上层优化以风电场和电网运营商年收益最大为目标,下层优化以双储能充放电能力指标值之和最小为目标,并采用改进多目标黏菌算法和模糊隶属度函数对模型进行求解;最后,以中国新疆哈密某风电场实时运行数据为例,验证了所提方法的有效性。

     

    Abstract: The construction of energy storage power stations can alleviate the problem of“abandoned wind and power curtailment”in“Three North”regions in China, and improve the ability of local power grids to accommodate the abandoned wind. However,the high cost of energy storage invested by a single investor limits the popularization and application of energy storage. Aiming at this problem, a hierarchical optimal configuration model of dual energy storage system based on multi-agent investment is constructed. First, a coordinated operation strategy of dual energy storage considering cycle life is proposed to reduce the life loss caused by frequent charge-discharge switching. Then, in order to maximize the benefits of multiple investors, a two-layer optimization economic model is proposed. The upper layer optimization aims to maximize the annual income of the wind farm and the power grid operator, while the lower layer optimization aims to minimize the sum of the charging and discharging capacity indices of dual energy storage. The improved multi-objective slime mould algorithm and fuzzy membership function are used to solve the model. Finally, taking the real-time operation data of a wind farm in Hami, Xinjiang Uygur Autonomous Region, China as an example, the effectiveness of the proposed method is verified.

     

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