Aplicación de inteligencia artificial para pronosticar la demanda energética del sector de Primavera 2 con su respectivo alimentador de la subestación eléctrica Durán sur con nivel de tensión de 69/13.8 KV

Abstract

In this study, the stated objectives, both general and specific, have been fully met in relation to the forecast of energy demand in the Primavera 2 sector, fed by the Durán Sur electrical substation. Historical demand data has been collected and processed using advanced MATLAB® tools, applying Artificial Intelligence principles to generate accurate and reliable predictions. These predictions have been validated through exhaustive analyses, allowing trends and possible growth in energy demand to be identified, which will contribute to improving the operational efficiency of the electrical system and preventing blackouts. The use of Polynomial Regression in the forecast for the months of January and February 2024 has been particularly effective in capturing non-linear trends in historical data, allowing variations in demand to be more accurately forecast. This approach provides a solid foundation for energy planning. On the other hand, the analysis with the Simple Exponential Smoothing (SES) method has offered reliable forecasts for March and April 2024, reflecting both recent trends and seasonal patterns, which constitutes a valuable tool for energy management in the sector. Spring 2.