Applications on medium-term forecasting for loads and energy scales by using Artificial Neural Network

In this paper, forecasting estimation for medium- term period by using Artificial Neural Network (ANN) techniques has been implemented. The actual data are obtained from The Egyptian Electric Holding Company (EEHC). The study focused on unexpected peaks on working days of summer seasons that have the dangerous effect on safety of electric power system. Medium-term load forecasting is established by two plans, One-year plan and Five-years plan with different designed techniques. The input consists of many parameters such as past annual loads, population, oil price and so on. The outputs are annual loads or the energy sales or both. The results of these techniques are compared with output of the models calculated by EEPU. So, valuable conclusions and recommendations are obtained.