基于原始产量预测的户用光伏智能电池管理系统

F. Spertino, A. Ciocia, P. Leo, Gabriele Malgaroli, A. Russo
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引用次数: 4

摘要

基本的电池管理系统(BMS)允许电池的安全充放电和负载的供应。电池受到保护,以避免快速退化:不超过最小和最大充电状态(SOC)限制,不允许快速充放电循环。一个更复杂的BMS连接到一个光伏(PV)发电机也可以起到保护存储和减少峰值需求的双重作用。通过存储减少峰值通常需要预测消费和光伏发电概况来执行临时能量平衡。要做到这一点,需要有关于生产概况的准确信息,也就是说,要有准确的天气预报,这是不容易获得的。在本工作中,描述了一种高效的住宅用户并网光伏电站BMS。从1天前的原始天气预报和消费预测开始,拟议的BMS在预计高负荷和低光伏产量时保留电池电量,并在自给自足减少的情况下进行调峰。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Smart Battery Management System for Photovoltaic Plants in Households Based on Raw Production Forecast
A basic battery management system (BMS) permits the safe charge/discharge of the batteries and the supply of loads. Batteries are protected to avoid fast degradation: the minimum and maximum state-of-charge ( SOC ) limits are not exceeded and fast charge/discharge cycles are not permitted. A more sophisticated BMS connected to a photovoltaic (PV) generator could also work with the double purpose of protecting storage and reducing peak demand. Peak reduction by storage generally requires the forecast of consumption and PV generation profiles to perform a provisional energy balance. To do it, it is required to have accurate information about production profiles, that is, to have at disposal accurate weather forecasts, which are not easily available. In the present work, an efficient BMS in grid-connected PV plants for residential users is described. Starting from raw 1-day ahead weather forecast and prediction of consumption, the proposed BMS preserves battery charge when it is expected high load and low PV production and performs peak shaving with a negligible reduction in self-sufficiency.
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