面向配电网削峰填谷的5G基站储能调控方法
Energy Storage Dispatch of 5G Base Station Energy Storage for Peak Shaving and Valley Filling of Distribution Networks
尹喜阳 1王忠钰 1刘乙召 1卢志鑫 1吕国远 1潘超2
作者信息
- 1. 国网天津市电力公司信息通信公司,天津 300010
- 2. 华北电力大学电气与电子工程学院,北京 102206
- 折叠
摘要
针对现有 5G基站储能参与配电网调控所面临的集中调控方法计算复杂度高、难以适配配电网负荷波动、无法感知基站储能电池能量与电池损耗等挑战,提出 5G基站储能分布式自主调控架构,支撑 5G分布式储能资源灵活接入配电网.在此基础上,提出一种基于电池状态感知上置信区间的 5G基站储能调控算法,综合考虑基站储能电池容量约束与电池损耗成本,最大化储能调控效益和配电网负荷曲线方差的加权差,实现电池能量与电池损耗感知,辅助配电网削峰填谷.仿真结果表明:相较于现有 2 种对比算法,所提方法可以使基站储能调控效益与配电网负荷曲线方差的加权差分别提高 12.73%和 22.33%.研究成果能够很好地满足5G基站储能参与配电网削峰填谷的需求,实现配电网与 5G基站储能双向互动.
Abstract
The existing 5G base station energy storage participating in the distribution grid dispatch faces several challenges,such as high computational complexity of centralized dispatch methods,difficulty in adapting to load fluctuations of distribution grid,and inability to perceive battery energy and battery loss of the base station energy storage.Therefore,a distributed autonomous dispatch architecture of 5G base station energy storage is proposed in this paper to support the flexible access of distributed 5G energy storage resources to distribution networks.On this basis,a 5G base station energy storage dispatch algorithm base on battery state-aware upper confidence bound is proposed.The objective is to maximize the weighted difference between the base station energy storage dispatch benefit and the distribution network load curve variance,achieve battery energy and battery loss awareness,and assist in peak shaving and valley filling of distribution networks while considering the constraints of base station energy storage battery capacity and battery loss costs comprehensively.The simulation results show that compared with the existing two comparison algorithms,the proposed algorithm can improve the weighted difference between the base station energy storage dispatch benefit and the distribution grid load curve variance by 12.73%and 22.33%.The research results can well meet the demand of 5G base station energy storage participating in the peak shaving and valley filling of the distribution network,and realize the two-way interaction between the distribution network and 5G base station energy storage.
关键词
储能调控/5G基站/削峰填谷/强化学习Key words
energy storage dispatch/5G base station/peak shaving and valley filling/reinforcement learning引用本文复制引用
基金项目
国家电网有限公司总部管理科技项目(5700-202112191A-0-0-00)
出版年
2024
NETL
NSTL
万方数据