Publications Details

Foresee the Future: Using Machine Learning, Climate, and Site Characteristics to Predict PV Solar Plant Generation

Gunda, Thushara; Cai, May

Accurately predicting power generation for PV sites is critical for prioritizing relevant operations & maintenance activities, thereby extending the lifetime of a system and increasing the amount of revenue generated. Machine learning techniques can help us in this regard by providing more accurate predictions of PV power production, such that the forecasts take into account not only a site's system design characteristics, but also important weather and climate information. This type of research is important because we can leverage the vast amounts of SCADA data we collect to build more effective, accurate models that can help improve our performance management.