Abstract
Load forecasting has always been the essential part of efficient power system planning and operation. The objective of this paper is to propose load forecasting technique based on similarity, which is useful for power system operator in case traditional approach requiring modeling cannnot be utilized to forecast power load. This paper presents Fuzzy Neural Network(FNN)for next day peak load forecasting based on peak load for similar day. In order to obtain accurate next day peak load, the FNN is used to estimate correction factor to modify power load on similar day. The FNN can be trained to perfect fuzzy logic rules and to find optimal membership functions for input and output variables. This technique has the advantage of dealing with not only the nonlinear part of power load curve but also with load forecasting on weekend. The suitability of the proposed approach is illustrated through an application to actual load data of the Okinawa Electric Power Company in Japan.
