Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach
Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach
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DOI：
10.23919/acc55779.2023.10156008
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Amir Farakhor;Yebin Wang;Di Wu;H. Fang
中科院分区：
文献类型：
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作者：
Amir Farakhor;Yebin Wang;Di Wu;H. Fang
优化电源管理(OPM)对于大规模电池储能系统至关重要。由于基于集中式数值优化的设计，今天的方法往往需要巨大的计算工作量。因此，本文研究基于计算的分布式OPM，其中基于单元的代理通过网络通信来协作解决OPM问题。提出了一种加速跟踪交替方向乘子法(ADMM)算法来求解分布式最优路径问题。该算法在ADMM算法中嵌入了动态平均一致性和内斯特罗夫加速技术。该算法不仅完全分布式，不需要融合或聚集节点，而且加快了收敛速度。本文在模型预测控制框架中建立了OPM模型，在满足安全约束的同时，寻求调节每个电池单元的充放电功率，以最小化总功率损失，促进组成单元的平衡使用。文中给出了大量的仿真结果，证明了所提出的分布式OPM在计算和收敛方面的有效性和优越性。
Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates the convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.