Short-term load forecasting using a fuzzy engineering tool

Abstract

The authors describe a knowledge engineering tool for short-term load forecasting to be used as an aid in operation and planning of distribution systems. This engineering tool is composed by two parts. Firstly, an artificial neural network is trained to produce the first evaluation of forecasted load. Following, a fuzzy expert system manipulate actual and forecasted values of real power and weather conditions to find the final forecasted load. Illustrative examples are presented using Hydro-Quebec Power System data.<>