Review of Energy Requirement and Load Forecasting for A Medium Agro-Based Industrial Settlement: A Case Study of Oke-Agbo and Imota Villages

Initiatives at promoting sustainable economic growth, enhanced competitiveness of home-grown companies, and job creation have been severely hampered by the unpredictable electric power supply. Utility sector decision-makers must predict the future demand for energy with a minimum error percentage using various predictive models with a lower percentage of inaccuracy if they will be able to load-shrink while maintaining the uninterrupted power supply to consumers and to save cost for utility companies. Efforts at forecasting electricity demand rather make use the hybrid approach which combines two or more predictive models to achieve enhanced prediction performances. The performances are compared in terms of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The two communities of Oke-agbo and Imota provided first-hand information about the trend of energy demand and the market analysis of the transformer and other distribution network components will be done. Additionally, information was also acquired with the aid of former Nigeria Electricity Power Authority (NEPA), Power Holdings Company of Nigeria (PHCN), and Ikeja Electric (IE) employees who had extensive knowledge of all the networks in and around the case towns.