Daily load forecasting using recursive Artificial Neural Network vs. classic forecasting approaches

The aspects presented in the paper refer to the recursive artificial neural network (ANN) architecture for short term daily load forecasting. The paper emphasizes the importance of choosing the right training set used to teach the recursive ANN (RANN). Using specific data from the Banat region (situated in South-Western Romania), some daily load forecasts based on the proposed method are presented, analyzed and compared to other forecast methods. The results show that the RANN method provides a better load forecast that the traditional methods. On this basis, many useful recommendations are outlined.