基于采样数据的大规模储能系统一致性控制

针对大规模储能系统中储能电池的荷电状态(SOC)不一致问题,提出了一种储能多智能体系统一致性控制方法,实现了SOC和输出功率的一致性.该方法应用简化的大规模储能系统模型,基于采样数据进行了一致性控制协议设计,并进行了收敛性分析.从而使本地储能单元智能体仅在特定采样时间点接收邻接储能单元智能体的状态信息,就能够产生本地储能单元控制信号,解决了大规模储能多智能体系统因通讯复杂而带来的计算量过大的问题.考虑了采样数据和系统需求,进行了系统控制参数设计.同时,对瞬时功率过大的问题,进行了带功率限制的一致性控制改进.最后,在满足定理条件、不满足定理条件和功率限制等三种场景下进行了仿真,验证了该方法的有效性.

Sampled-Data-Based Consensus Control for Large-Scale Energy Storage System

Aiming at the inconsistent problem of state of charge(SOC) caused by the energy storage batteries in large-scale energy storage systems, a consensus control method for multi-agent energy storage systems is proposed, which realizes consistency of the SOC and the output power. The simplified large-scale energy storage system model is applied, and the consensus control protocol is designed based on the sampled data, and the convergence is analyzed. The local energy storage agent only receives the state information of the adjacent energy storage agents at a specific sampling time point, and can generate the local energy storage control signal, which solves the problem of large-scale multi-agent energy storage system due to the large calculation burden because of the complex communication. Considering the sampling data and system requirements, the system control parameters are designed. At the same time, taking into account the excessive instantaneous power, the consistency control with power limitation is improved. Finally, simulations are studied in three scenarios:meeting the theorem conditions, not satisfying the theorem conditions, and power limitation. The effectiveness of the method is verified.