Medium-Term Load Forecasting for The City of Benghazi Using an Artificial Neural Network Based Time Series Approach

In recent years, an increase in the electricity load at the General Electricity Company of Libya (GECOL) has led to power shortages during the peak summer season. And sometimes there was an acute shortage in the distribution of electricity throughout the country. Due to the interruption of large generation units or transmission lines of the electric power grid. this paper aims to address the issue of electrical load demand forecasting by using the NARX tool on the MATLAB platform to train artificial neural networks (ANN). The forecasting of Benghazi’s electricity consumption is the main topic of this paper. In this work, deep learning is used for the first time to forecast overall energy demand and consumption in Benghazi. The real data acquired by the National Control Center GECOL supports the results that were achieved.