Real-time battery management algorithm for peak demand shaving in small energy communities
Real-time battery management algorithm for peak demand shaving in small energy communities
复制标题
用于小型能源社区调峰的实时电池管理算法
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Stuart A. Norman
中科院分区：
文献类型：
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作者：
S. Pholboon;M. Sumner;E. Christopher;Stuart A. Norman
解决由于高光伏（PV）功率渗透引起的高峰需求和电网不稳定性的问题的解决方案之一是部署电池存储系统。提出了一种实时电池管理算法（BMA）的小能源社区与并网光伏系统的调峰需求。BMA旨在通过测量社区的瞬时功耗来控制社区电池存储的充电/放电。管理电池的充电/放电时会考虑社区日常能源消耗和可用可再生能源的历史数据记录。仿真结果表明，BMA的有效性，这是能够减少35%的峰值能耗，增加光伏自耗的47%，并减少输电线路损耗在高峰期的56%相比，光伏系统没有电池存储。
One of the solutions to tackle the problems of high peak demand and grid instability due to high photovoltaic (PV) power penetration is to deploy a battery storage system. This paper presents a real-time battery management algorithm (BMA) for peak demand shaving in small energy communities with grid-connected PV systems. The BMA aims to control the charge/discharge of the community battery storage using measurement of the instantaneous power consumption of the community. Historical data records of community daily energy consumption and available renewable energy are taken into account to manage the charge/discharge of the battery. Simulation results show the effectiveness of the BMA which is able to reduce the peak energy consumption by 35%, increase PV self-consumption by 47% and reduce transmission line losses during the peak period by 56% when compared to a PV system without the battery storage.