Artificial neural networks (ANN) have been used for many application in
various sectors. The learning property of an ANN algorithm in solving both linear
and non-linear problems can be utilized and applied to different forecasting
problems. In the power system operation load forecasting plays a key role in the
process of operation and planning.
This paper present the development of an ANN based short-term hourly load
forecasting model applied to a real data from MIBEL – Iberian power market test
case. The historical data for 2012 and 2013 ware used for a Multilayer Feed
Forward ANN trained by Levenberg-Marquardt algorithm. The forecasted next day
24 hourly peak loads and hourly consumptions are generated based on the
stationary output of the ANN with a performance measured by Mean Squared Error
(MSE) and MAPE (Mean Absolute Percentage Error). The results have shown good
alignment with the actual power system data and have shown proposed method is
robust in forecasting future (short-term) hourly loads/consumptions for the daily
operational planning