Application Of Interval Type-2 Fuzzy Inference System And Big Bang Big Crunch Algorithm In Short Term Load Forecasting New Year Holiday

Jamaaluddin, Imam Robandi, Izza Anshory, Mahfudz, Robbi Rahim

Celebration of New Year In Indonesian is constituting one of the visits to Indonesian tourism. This event course changes the load of electrical energy.The provider's electrical power that control and operation of electrical in Java and Bali (Java, Bali Electrical System) are required to be able to assure continuity of load demand at this time, and forecast for the hereafter. Short-term load forecasting very needs to be supported by computational methods for simulation and validation. One of the computation's ways is Interval Type – 2 Fuzzy Inference System (IT-2 FIS). It is appropriate to be used in load forecasting because it has a very flexible advantage in changing trace uncertainty (FOU), thus supporting the formation of initial processing of time series, computing, simulation and system model validation. The method employed in this forecasting is to IT-2FIS. The optimization of FOU (Foot Of Uncertainty) done by using the Big Bang Big Crunch Algorithm obtained a better result. The predict procedure has done analyzing the expenses incurred on that day and four days in the first place in the year before forecasting. Furthermore, the information will be an examination by using IT- 2FIS. And then, it will take the load forecasting value on the same day in the following year. From the effects of this research on getting the results of forecasting by using IT-2 FIS- BBBC has an error value that is smaller than when using IT-2 FIS. The outcomes of this survey show that the average Percentage Error forecast in 2014, 2015, 2016 and 2017 amounted to 0.56% by using IT-2 FIS-BBBC. Whereas when using IT-2 FIS obtained Average Percentage Error of 0,73%. It can reason that the IT- 2 FIS-BBBC can utilize for the short-term load forecasting process.

Volume 12 | Issue 2

Pages: 216-225

DOI: 10.5373/JARDCS/V12I2/S202010024