Combining data with physics to monitor solar panels

Abstract

In countries such as India with low grid prices, energy firms are offering competitive PPA tariffs for solar farms. Given lower mar- gins in operating these farms, there is great sensitivity to panels under-performing. To detect under-performance, condition- monitoring methods compare generated power with an ideal yield calculated for localised weather. Applying such methods to a 1.2MW farm with 6 different PV technologies over 3 years, we ob- served prediction errors large enough to mask under-performance. To reduce this error, we explicitly modelled the Maximum Power Point Tracker (MPPT) in a two-step prediction method. In doing so, we combine a regression method on weather data with physical modelling of IV-characteristics of panels, resulting in an average reduction in error by 16%.