A spatial load density forecasting method based on cloud theory and fuzzy analytic hierarchy process

Spatial load density forecasting is the basis of distribution network planning. In view of the features of spatial power load density forecasting and the uncertainty of human´s judgment, this paper presents a spatial load forecasting method based on cloud theory and fuzzy analytic hierarchy process (AHP) to improve the forecast inaccuracy. Cloud generators and inference rules were established to quantize the qualitative factors and obtain the objective weights of the influencing factors. Triangular fuzzy number is introduced to the model for indicating the judgments of experts while the AHP is used for dealing with the judgments so as to obtain optimal subjective weights of different factors. The spatial load density was forecasted by using the synthetically weights. An example demonstrates the superiority of the proposed model in spatial load density forecasting.