1 Spatial Load Forecasting Using Fuzzy Logic

During the last four decades various load forecasting methods have been created. However, these methods cannot forecast future loads in case of sever lack of data, when only few loads are measured in nonconsecutive years. This paper proposes and describes the general methodology to use fuzzy logic to fuse the available information for spatial load forecasting. The proposed scheme can provide distribution planners other alternatives to aggregate their information for spatial load forecasting. A new spatial load forecasting method using non-uniform areas has been established. The result is a method that requires substantially less manpower and data than existing grid-based methods. In addition, this method results in a closed-form solution for spatial loading as a function of time. The algorithm has been tested on the Ghaen City (North-East of IRAN), Khurasan Province as a benchmark for present and projected land uses. The results provide a reasonable projection of the loads in the Ghaen City area, in line with the expectations. The algorithm accurately constrained the growth within the forecast area to the overall projected demand