Energy Yield Database Management System Based on Solar Photovoltaic Cell Using Internet of Things Technology

Abstract

This article presents an analysis of solar cell electric power generation system performance at Prince of Songkla University, Surat Thani Campus. It emphasizes the importance of evaluating photovoltaic system efficiency and highlights the challenges in identifying malfunctions, which necessitates the use of electrical current and voltage measurement devices. A linear regression analysis was performed to determine the relationship between current and electrical energy in each phase, predicting the system's efficiency. The Mean Absolute Error for Phases A, B, and C were 0.00133, 0.00137 and 0.00216, respectively. These predictions help in scheduling maintenance, reducing greenhouse gas emissions, and preventing short circuits. Results are accessible through a dashboard for easy data review. The novel linear regression equation provided is beneficial for studying and analyzing solar cell systems in various applications.

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