摘要
随着“碳达峰、碳中和”目标的提出,储能在新能源高渗透率条件下参与需求响应以及电网调控得到极大的重视。针对大量储能集群的有效调控问题,提出了一种基于多智能体分布式协同的储能集群指令自适应跟踪方法。该方法分为2个部分:第1部分是指令的事前分配,利用离线迭代的方式,将外部指令按照一定的比例分配到集群中各个储能单元上;第2部分,利用实时反馈的荷电状态(state of charge,SoC)控制方法,在保持对指令追踪的同时,实现SoC的平衡。通过仿真实验验证SoC控制后的各储能单元功率和用电量分配。仿真模拟结果表明,所提出的方法能使各储能单元达到SoC一致并且跟踪外部指令。与传统的集中式框架相比,采用分布式储能集群,能够对规模化储能集群进行有效管控,可降低系统通信数据量,且隐私性好。
The acceptance of new energy sources in microgrids and the goal of"carbon neutrality"have led to the active participation of consumer appliances in demand response.We propose an adaptive tracking method for energy storage clusters based on multi-agent collaboration for energy storage units,which are important components of microgrids.Firstly,external commands are allocated to each energy storage unit of the energy storage cluster system according to a certain ratio through prior command allocation.Secondly,the instructions are tracked using a real-time state-of-charge(SoC)control method.The power and power consumption allocation of each energy storage unit after SoC control is verified by simulation experiments.The experimental results show that the proposed method can make each energy storage unit achieve SoC consistency and track external commands.Compared with the traditional centralized framework,the proposed method uses distributed energy storage clusters,which can improve the economics of microgrids,feature reduced system communication data,good privacy,high processing efficiency,and better scalability and flexibility.
作者
王振宇
王宇
孙贝贝
肖楚鹏
许静
WANG Zhenyu;WANG Yu;SUN Beibei;XIAO Chupeng;XU Jing(Nari Group Corporation/State Grid Electric Power Research Institute R&D Department,Nanjing 210002,China;State Grid Electric Power Research Institute Wuhan Energy Efficiency Evaluation R&D Department,Wuhan 430074,China;State Grid Jibei Electric Power Company Limited,Beijing 100052,China)
出处
《控制工程》
CSCD
北大核心
2023年第12期2307-2312,共6页
Control Engineering of China
基金
国家电网有限公司科技项目(5100-202114296A-0-0-00)。
关键词
多智能体
储能集群
SoC一致
自适应跟踪
Multi-agent
energy storage cluster
SoC consistency
adaptive tracking