Three-Component Weather-Sensitive Load Forecast Using Smart Methods

EasyChair Preprint no. 6053

Abstract

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 (baseload). The impact of the weather-sensitive component includes the summer and winter periods, without 
distinguishing between them. 
The characteristics and specifications of this component (weather-sensitive component) differ in summer and winter due 
to the different loads in the seasons, so it is best to separate these two components into two independent components. The 
research provides a method for separating the weather-sensitive electrical load into three components, the summer 
component, the winter component, and the base component. 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 in the research.

Keyphrases: Artificial Neural Network, IRAQI Loads, Mean Squared Error, Weather Sensitive Load Forecast

@Booklet{EasyChair:6053,
  author = {Yamama Al-Nasiri and Majid Al-Hafidh},
  title = {Three-Component Weather-Sensitive Load Forecast Using  Smart Methods},
  howpublished = {EasyChair Preprint no. 6053},

  year = {EasyChair, 2021}}