Abstract—Subsidy reduction and the increased importance of\ud
photovoltaic energy generation have triggered the need to develop\ud
accurate approaches to measure, estimate and possibly forecast\ud
energy production with the goal of enabling early detection and\ud
diagnosis of parametric faults before they become catastrophic\ud
and lead to partial or full shut down of the plant. Moreover the\ud
ability of accurately predicting the energy output of a photovoltaic\ud
plant is becoming increasingly important to operate efficiently\ud
the existing power grid infrastructure that has difficulties with\ud
intermittent, unpredictable power sources. In this paper a new\ud
model of photovoltaic solar parks designed to estimate efficiency,\ud
predict energy production and enable early fault detection is\ud
presented. The proposed model is based on an equivalent electrothermal\ud
model of the PhotoVoltaic (PV) cell, which takes as input\ud
the irradiance, ambient temperature and wind speed measured by\ud
existing sensors and data-logging equipment used in most solar\ud
PV parks. The proposed model is demonstrated to accurately\ud
predict the performance of real-life MW scale plants. By directly\ud
comparing predicted vs. actual energy production, it also allows\ud
easy and early identification and diagnose of malfunctions and\ud
efficiency drops of PV systems