* MSc in Power Electrical Engineering, Department of Electrical Engineering, College of Technical and Engineering, Islamic Azad University Saveh Branch, Saveh, Iran
** PhD in Power Electrical Engineering, Assistant Professor, Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Iran
*** PhD in Power Electrical Engineering, Assistant Professor, Department of Electrical Engineering, College of Technical and Engineering, Islamic Azad University, Saveh, Iran
Online published on 9 October, 2015.
In addition to providence investment costs, enabling better planning for the development of power plants and transmission and distribution networks, electrical loads should be forecasted correctly. Electrical load forecasting depending on the forecast period, divided into short term, medium term and long term categories. since the medium term load forecasting playing a vital role in the economic and safe operation of the power systems, here this type of forecasting is presented. In this paper sampling for the five low voltage posts in Sanandaj city with using registers is done. The study for two month including one month with temperate climate and one month with warm climate was done. The sampling consist of four posts with residential loads and one post with commercial loads. The electrical loads are forecasted for the next year with Artificial Neural Network (ANN) in the MATLAB software.
Load, Artificial Neural Network, Medium Term, Load Forecasting
