Using Inverter MPPT Voltage to Detect Vegetation Shading in Solar Farms

• Published in: IEEE journal of photovoltaics Vol. 13; no. 6; pp. 979 - 985
• Main Authors: Liu, Haohui, Zhao, Lu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anomaly detection; Asset management; Dispersion; Electric potential; Farming; Inverters; MPPT; photovoltaic; Photovoltaic systems; Shading; solar energy; Solar power generation; Temperature measurement; Vegetation growth; Vegetation mapping; vegetation shading; Voltage; Voltage measurement
• ISSN: 2156-3381; 2156-3403
• DOI: 10.1109/JPHOTOV.2023.3318828

Underperformances in PV solar farms pose great risks to project returns and financial health. It is important to adopt proactive asset management and O&M practices to ensure good performance. Among the various possible causes of underperformance, those due to external factors such as snow, soiling, and extraordinary shading from vegetation growth can usually be mitigated. However, there is a lack of cost effective and reliable method to detect these phenomena. In this work, we explore the possibility of utilizing inverter MPPT voltage readings available from common SCADA and monitoring systems to detect vegetation shading. It is found that vegetation shading can cause significant deviation in voltage characteristics. This includes increased discrepancy among MPPT inputs, decrease in voltage level, and excessive voltage fluctuation under clear sky. Based on these signature patterns, it is possible to design algorithms to detect vegetation growth episodes and issue performance alerts to remote operators.