Remote Online Condition Monitoring and Fault Diagnostic System for Photovoltaic Farms

Description

Photovoltaic (PV) systems have been widely exploited in today’s environmentally-conscious world. Some professional organizations have even offered financial and technical support to bring innovative and sustainable PV-based electrical infrastructure to the poorest and most energy-deprived regions in the world. The last four decades have witnessed extensive research and development efforts on advancing the conversion efficiency of the PV cells and the energy efficiency of the power conversion stage in processing precious solar energy. Due to long life expectancy of PV panels, a condition monitoring and fault diagnostic system for PV panels is becoming crucial as it can provide users with a warning of system failure or high failure risks, and thus help shorten the time interval with reduced or no energy production. An optimized failure prediction system will be developed which considers the accuracy of the warning with the maximized prediction time. Therefore, the time interval of reduced or no energy production is shortened. This project aims to develop an online diagnostic system that utilizes advanced evolutionary computation technique to keep tracking the change of the intrinsic parameters of individual panel and report to the central control center when any abnormalities are found. A prototype system will be built and evaluated on a small-scale 5kW PV system that has been installed in CityU.