Electricity Short Term Load Forecasting Using Elman Recurrent Neural Network

The proposed work aimed to forecasting the load by using Artificial Neural Networks (ANN). Short term load forecasting plays an important role for the planning, economic and reliable operation of power systems. Therefore, many statistical methods have been conventionally used for such forecasting, but it has been difficult to construct a proper functional model. This difficulty can be reduced by using artificial neural networks. A neural network is a machine that is designed to model the way in which the human brain performs a particular task. The main aim of the proposed work is to design a neural network model called Elman recurrent network by using MATLAB software to simulate the load forecasting. The work also includes comparing the results obtained by a weather sensitive model and a non weather sensitive model.