A modeling approach for short-term load forcasting using fuzzy logic type-2 in sulselrabar system - Muhammad Ruswandi Djalal (International Journal of Artificial Intelligence Research, 2018)
This research proposed a modeling approach for 24-hour short-term load forcasting based on fuzzy logic type-2. In this research we get an approach in designing load forecasting model, where previously still using conventional fuzzy logic. Implementation of load forecasting in this research is done on electrical system 150 kV Sulselrabar. Sulselrabar electrical system in its development has grown rapidly, therefore needed a study that to improve system performance, one of which is the study of short-term load forcasting. As the input data used load data from 2010 to 2016 on the same day that is January 8th. To see the accuracy of the results, two approaches are performed, ie fuzzy logic type-1 modeled using Simulink and fuzzy logic type-2 modeled using m-file Matlab. From the analysis results obtained, Mean Percentage Error (MAPE) is the smallest by using Fuzzy Logic Type-2 method, compared with Fuzzy Logic Type-1 method.. Where, MAPE for fuzzy logic type-1 method is 2.133371219%, and by using fuzzy logic type-2 method, MAPE is 1.729778866%.