Gaussian Process Regression (GPR) Forecasting Electricity Consumption for Mascara City

Electric power forecasting is crucial for efficient resource planning, grid stability, cost optimization, demand response programs, renewable energy integration, and energy market operations. Accurate forecasting allows electric utilities to effectively allocate resources, balance supply and demand, and minimize operating costs. In this investigation, a forecasting model has been established to predict the purchase of electricity at the electricity distribution unit of Mascara, taking into account historical energy purchase patterns, the number of customers, and weather conditions. The performance of the regression model used in the prediction of energy consumption has shown excellent results, with an accuracy of aver 90 % and a financial gain of approximately <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1,362,252,500.00$</tex> DA at the distribution unit of Mascara from January 2014 to December 2022.