Performance analysis of photovoltaic inverter system for predicting energy yield

The paper aimed to explore the model which can be considered to investigate the environmental factors affect energy yield based on photovoltaic inverter system. The multiple regression analysis was employed for predicting of energy yield. The data were collected through the Net ECO system database at the Prince of Songkla University, Surat Thani Campus. The results showed that the maximum level of energy yield was in July followed by May and, June. The results suggested that the amounts of energy yields were positively correlated with the irradiance factor. The irradiance factor could explain variation in the existence of energy yield which can predict the effect for 96.49%. The model can be used to create a system automatically tracking and notifying the energy yield based on the measured environmental factors. (C) 2022 The Author(s). Published by Elsevier Ltd.