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。
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.
作者
尹喜阳
王忠钰
刘乙召
卢志鑫
吕国远
潘超
YIN Xiyang;WANG Zhongyu;LIU Yizhao;LU Zhixin;LÜGuoyuan;PAN Chao(Information and Telecommunication Branch,State Grid Tianjin Electric Power Company,Tianjin 300010,China;School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China)
出处
《电网与清洁能源》
CSCD
北大核心
2024年第8期97-102,共6页
Power System and Clean Energy
基金
国家电网有限公司总部管理科技项目(5700-202112191A-0-0-00)。
关键词
储能调控
5G基站
削峰填谷
强化学习
energy storage dispatch
5G base station
peak shaving and valley filling
reinforcement learning
作者简介
尹喜阳(1978—),男,本科,高级工程师,研究方向为5G融合配电网;王忠钰(1995—),男,硕士,工程师,研究方向为5G融合配电网;刘乙召(1990—),男,工程师,研究方向为5G融合配电网;卢志鑫(1993—),男,工程师,研究方向为5G融合配电网;吕国远(1978—),男,高级工程师,研究方向为5G融合配电网;通讯作者:潘超(1998—),男,博士研究生,研究方向为基站储能调度、5G基站参与需求响应等。
