FORECASTING ENERGY DEMAND A MEANS FOR THE IMPLEMENTATION OF POWER INFRASTRUCTURAL MASTER PLAN USING NEURAL NETWORK

International audienceThe increasing global demand for electrical energy coupled with rise in cost of energy sources necessitates development of intelligent forecasting methods and algorithms. Underestimation of consumption would lead to potential power outages that are devastating to life and the economy, whereas overestimation would lead to unnecessary idle capacity resulting in wastage of financial resources. Therefore, the importance of accurate estimation of energy consumption cannot be over emphasized. Proper Forecast of energy consumption is key to successful planning and policy formulation/implementation. Modelling of energy consumption is usually based on historical consumption. The challenges of energy production and consumption have made energy modelling a subject of widespread interest among engineers and scientists concerned. This paper looks at the infrastructural development of 11KV dedicated feeder of the University of Jos which was provided to check the insufficient and epileptic power supply suffered by the University community for many years and the need for proper sustainability of the network through forecasting future energy demand. The study looks at the past power supply situation before and after construction of the dedicated line. Artificial Neural Network (ANN) has been used to forecast the future energy demand of the University