Time Series Modeling to Forecast on Consuming Electricity: A case study Analysis of electrical consumption in Erbil City from 2014 to 2018

Abstract

Time series analysis and forecasting have become a major tool in different applications in hydrology and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). Approach: In this study, we used Box-Jenkins methodology to build ARIMA model for electricity consumption data taken for Erbil region station for the period from 2014-2018. Results: In this research, ARIMA (1, 1, 1) (0, 1, 1)12 model was developed. This model is used to forecasting the monthly consumption for the upcoming 2019 year in each month to help decision makers establish priorities in terms of electricity demand management. Conclusion/Recommendations: An intervention time series analysis could be used to forecast the peak values of producing electricity in megawatt for Erbil city.