Cover
Vol. 10 No. 1 (2014)

Published: September 30, 2014

Pages: 42-47

Original Article

Short Term Load Forecasting Based Artificial Neural Network

Adel M. Dakhil 1
1Department of Electrical Engineering Misan University Iraq- Misan
History
  • Received: July 30, 2014
  • Available Online: September 30, 2014
DOI

https://doi.org/10.37917/ijeee.10.1.5

Abstract

Present study develops short term electric load forecasting using neural network; based on historical series of power demand the neural network chosen for this network is feed forward network, this neural network has five input variables ( hour of the day, the day of the week, the load for the previous hour, the load of the pervious day, the load for the previous week). Short term load forecast is very important due to accurate for power system operation and analysis system security among other mandatory function. The trained artificial neural network shows good accuracy and robust in forecasting future load demands for the daily operation, mean absolute percentage error (MAPE) was calculated and it is maximum value is 0.75% in load forecasting on Monday.

Keywords

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