Very Short-Term Load Forecasting Of Peak Load Time Using Fuzzy Type-2 And Big Bang Big Crunch (Bbbc) Algorithm

Very short-term energy forecasting is done on a day before the day of operation. Forecasting of short-term load is done every 30 minutes of forecasting hours. Very short-term load forecasting is carried out continuing forecasting short-term load with daily intervals, load on a given day or weekly load to be more detailed with very short-term load forecasting. This weight forecasting is done to improve operational effectiveness and efficiency. Forecasting short -term loads have been done using artificial intelligence, nowadays artificial intelligence is attempted to predict a very short term load. In this study, investigated the use of the Fuzzy type-2 (FT-2) and big bang big crunch (BBBC) algorithm for the very short-term load forecasting. Results shows that with the use of FT-2-BBBC, it will get a small error because it uses low computation cost and high convergent speed. In addition, FT-2 also optimizes the foot of uncertainty of the Fuzzy type-1. The results are in the use of FT-2-BBBC hence the very short term load forecasting error value of 0.7278%. This suggests that FT-2-BBBC can be used to perform electrical load forecasting and other forecasting.