Linear and non-linear load forecasting performance comparison of algorithms for Guney Town

In this work, Firstly load estimates methods have been analyzed. From these estimates regression analyze and artificial Neural Networks have been chosen to make an analyze for the town of Güney in Denizli and the obtained data were studied to minimize the error by creating the hybrid system. In this work not only calculating the load estimation of a small region and the factors influcing the estimation of the load in these regions and the importance of the calculation but the external factors influencing the estimation have also been studied. Güney's electricity grid network has been studied and information about this grid network has been provided. Using Güneytown?s present electricity system data for the year 2011 short term and midterm load estimations have been made. The load taken annually from the Güney feeders has been estimated seasonally and annually and external factors influencing load estimation by processing the seasonal changes have been analyzed the best method to estimate has been derived by comparing the failures with all kinds of methods available.