Long-term load forecast modelling using a fuzzy logic approach

Abstract

The importance of long-term load forecasting in the power industries cannot be over-emphasised, as it provides the industries with future power demand that may be useful in generating, transmitting and distributing power reliably and economically. In recent times, many techniques have been used in load forecasting, but artificial intelligence techniques (fuzzy logic and ANN) provide greater efficiency compared to conventional techniques (e.g., regression and time series). In this paper, a fuzzy logic model for long-term load forecasting is presented. A fuzzy logic model is developed based on the weather parameters (temperature and humidity) and historical load data for the town of Mubi in Adamawa state to forecast a year-ahead load. The fuzzy logic model forecast a year-ahead load with a MAPE of 6.9% and efficiency of 93.1%. The result obtained reveal that the proposed model is capable of predicting future load.