Short Term Load Forecasting for Shiraz Region Using Adaptive Back Propagation Neural Network

In this paper, the goal is to develop a model to forecast 24 hours ahead electrical load of Shiraz which located in Iran. To achieve this goal, the adaptive back propagation neural network has been studied. It should be noted that only climate and time factors have been taken into account as input causal factors in load forecasting. This model has been tested on the hourly electrical load data between March 21, 2009 and March 20, 2010 for Shiraz region. Experimental results demonstrate that the proposed model has favorable performance.