This paper proposes a real-time energy management system (EMS) suitable for rooftop PV installations with battery storage. The EMS is connected to a smart grid where the price signals indirectly control the power output of the PV/battery system in response to the demand variation of the electricity networks. The objective of the EMS is to maximize the revenue over a given time period while meeting the battery stored energy constraint. The optimization problem is solved using the method of Lagrange multipliers. The uniqueness of the proposed EMS remains in the reactive real-time control mechanism that compensates for the PV power forecast error. The proposed EMS requires only forecasting the average PV power output over the total optimization period. This is in contrast to the predictive power scheduling techniques that require accurate instantaneous PV power forecast. The proposed EMS method is verified by benchmarking against the predictive brute-force dynamic programming (DP) approach. The simulation analysis considers days with varying solar irradiance profiles. The simulation analysis shows the proposed EMS operating under practical assumptions, where the battery storage capacity is subject to constraints and the PV power output is not known a priori.

中文翻译：

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一种带电池储能的智能电网集成光伏发电实时能量管理系统

本文提出了一种实时能源管理系统 (EMS)，适用于带电池存储的屋顶光伏装置。EMS 连接到智能电网，其中价格信号间接控制光伏/电池系统的功率输出，以响应电网的需求变化。EMS 的目标是在满足电池存储能量约束的同时，在给定时间段内最大化收入。使用拉格朗日乘子法求解优化问题。所提出的 EMS 的独特性在于补偿 PV 功率预测误差的反应式实时控制机制。建议的 EMS 只需要预测整个优化期间的平均光伏功率输出。这与需要准确的瞬时 PV 功率预测的预测性功率调度技术形成对比。通过对预测蛮力动态规划 (DP) 方法进行基准测试来验证所提出的 EMS 方法。模拟分析考虑了具有不同太阳辐照度分布的天数。仿真分析显示了所提出的 EMS 在实际假设下运行，其中电池存储容量受到限制，并且 PV 功率输出未知。