Application of Short Term Load Forecasting on Special Days Using Interval Type-2 Fuzzy Inference Systems: Study Case in Bali Indonesia

This paper presents the application of interval type-2 fuzzy inference systems (IT2FIS) in short term load forecasting (STLF) on special days. This is a continuation work of application interval type-2 fuzzy systems (IT2FSs) using Karnik Mendel algorithm. Special days here mean local Balinese holidays such as national and local culture-based public holidays, consecutive holidays, and days preceding or following holidays. In general, the load values of special days tend to decrease due to unlike load behavior of holidays compare with ordinary weekdays during the year. IT2FIS has recently been considerable attention for a short term load forecasting problems due to their simple structure and high identification performance. IT2FIS is the process of formulating and mapping from a given input to an output using interval type-2 fuzzy logic. The Mamdani interval type-2 fuzzy inference models and the design of interval type-2 membership functions and operators are implemented in the interval type-2 fuzzy logic toolbox (IT2FLT). The method has been implemented on the historical peak load data to solve the short term load forecasting during holiday for the Bali electrical system, Indonesia. The results showed that the IT2FIS offer an accurate forecast of the peak load (in MW) on holidays, indicated by small mean absolute percentage error (MAPE) less than 1.5% for the estimation task of the year 2005 and 2006. More detail results and discussion are provided to show the eminence of these methods handling the short term load forecasting task.