Using neural networks to forecast the electricity generation in Kurdistan region-IRAQ

Abstract EN

Forecasting the future behavior of time series is an essential issue in statistical sciences since it is required in many aspects of life.

Iraq and its region are facing a real problem in electrical power generation.

For this purpose, forecasting the power generation has drawn the attention.

Electric power generation in the Kurdistan Regain Iraqi (KRI) is crucial because it distributes the power in the region, Kirkuk and Mosul.

Data were collected from (Iraqi-Kurdistan Regional Government Ministry of Electricity, General Directorate of Control & Communication, Kurdistan Dispatch Control Center).

in this research were used Artificial neural networks were used by the method of inverse propagation of error and the selection of the best model using to forecasting elect the minimum value of MSE (Mean Square Error) by using the statistical criteria to forecasting this data.