Five-component load forecast in residential sector using smart methods

The electrical load is affected by the weather conditions in many countries as well as in iraq. the weather-sensitive electrical load is, usually, divided into two components, a weather-sensitive component, and a weather-insensitive component. the research provides a method for separating the weather-sensitive electrical load into five components. and aims to prove the efficiency of the five-component load forecasting model. the artificial neural network was used to predict the weather-sensitive electrical load using the matlab R17A software. weather data and loads were used for one year for Mosul city. the performance of the artificial neural network was evaluated using the mean squared error and the mean absolute percentage error. the results indicate the accuracy of the prediction model used, MAPE equal to 0.0402.