Estrategias para la Integración Eficiente de Energía Solar en la Red eléctrica de la UTPL mediante Tecnologías IoT

Abstract

Abstract: This research analyzed the energy performance of the photovoltaic system installed at the central building of Universidad Técnica Particular de Loja using real operational data, K-means clustering techniques, and a multiple linear regression model. The study evaluated the influence of solar irradiance and module temperature on photovoltaic generation, demonstrating that irradiance has a direct positive impact on power output, while increased module temperature reduces system efficiency. The historical maximum demand analysis identified an energy requirement of approximately 27 kW, which exceeds the current nominal installed capacity (~15 kW). By adjusting the regression model, it was verified that the system should reach a capacity close to 42 kW to significantly improve energy self-sufficiency. The results confirm that the developed model is an effective tool for photovoltaic system sizing and distributed generation planning in institutional environments.