Field Investigation of Solar Photovoltaic Modules Digression Against Manufacture's Claim and Application of Machine Learning Model in Life Prediction: A Case Study

Abstract

Renewable energy is being produced through various resources, mostly natural and abundantly available, such as wind, solar, and geothermal. Solar PV technology is a novice alternate renewable energy system which is becoming popular during 21st century. In Solar Photovoltaic (SPV) power systems, the major component are polycrystalline PV modules which have a shelf-life of around 25 years, as claimed by most of the PV module producers. Most of the installations started 10 years ago and there is a need to investigate the ageing upshot or digression of PV modules. To this end, a seven-year-old large-scale PV plant is considered for case study. Field experiments are conducted to know the power output of these modules and the manufactures claim of 25 years life with indicated digression is validated with the field values. Also, machine learning technique is used to derive an empirical relation for the power output of age old PV modules. Finally, conclusions are drawn with respect to ageing upshot and life predictions of PV Modules.