A prototype for a real-time power fluctuation events prediction and mitigation engine for photovoltaic (PV) grid-tied systems - Goh, Shu Mei (2024)
Power fluctuation events could occur within a minute in solar photovoltaic (PV) grid-tied systems due to the fast-moving clouds, which leads to power quality issues in the power network and decreases the reliability of PV systems. Although a battery energy storage system (BESS) coupled in PV grid-tied system can be controlled to smoothen PV power generation, the occurrence of power fluctuation events is unknown to the BESS. Frequent charges/discharges will have a substantial impact on its cost-effectiveness, and inadequate power supply could deteriorate the power system. These issues can be improved with the integration of a very short-term PV power and power fluctuation event prediction engine alongside a reliable BESS-based mitigation controller. The prediction engine predicts power fluctuation events before they occur, prompting the battery controller to take action and smooth the power fluctuation events at the grid. Herein, this work proposed a novel artificial intelligence (AI) supported hardware-based prediction engine to enable automatic real-time prediction and mitigation of power fluctuation events. It takes in three inputs which are solar irradiance, air temperature and PV power to predict PV power and power fluctuation event in the forecast horizon of 30-second. The prediction outcomes, obtained in real-time before the power fluctuation occurrence, are used to control a BESS-based rule-based controller to mitigate the events in a custom-built laboratory-scale PV grid-tied system. The overall system forms a closed hardware-in-the-loop (HIL).