研究分布式电池储能系统的优化控制方法以及电池荷电状态（SOC）均衡策略,提出基于SOC均衡的协同控制策略。利用多智能体系统（MAS）理论,实现电池储能系统的协同控制,并采用多智能体分布式算法,实现功率指令的自适应分配,进而实现SOC动态均衡。针对传统多智能体算法收敛速度较慢的问题,提出一种基于模型预测控制（MPC）的分布式算法,利用MPC对传统多智能体算法进行优化,提高收敛速度。最后利用实际储能功率数据进行仿真,验证了所提策略的有效性和算法在收敛速度上的优势。
Abstract
This paper researches the optimal control method and SOC balance strategy of distributed battery energy storage system, and proposes a cooperative control strategy based on SOC balance. The multi-agent system （MAS） theory was used to realize the cooperative control of battery energy storage system, and the multi-agent distributed algorithm was used to realize the adaptive allocation of power instructions,and then realized SOC dynamic equalization. Aiming at the slow convergence of traditional multi-agent algorithm,a distributed algorithm based on model predictive control （MPC） was proposed. MPC was used to optimize the traditional multi-agent algorithm and improve the convergence speed. Finally, the effectiveness of the proposed strategy and the advantages of the algorithm in convergence speed are verified by simulation with the actual energy storage power data.
关键词
电池储能系统 /
模型预测控制 /
分布式算法 /
协同控制 /
荷电状态
Key words
energy storage system /
model predictive control /
distributed algorithm /
co-control /
state of charge （SOC）
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基金
新疆维吾尔自治区自然科学基金（2021D01C044）; 国家自然科学基金（51667018）
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