Very Sort Term Load Forecasting Using Interval Type - 2 Fuzzy Inference System (IT- 2 FIS) (Case Study: Java Bali Electrical System)

International Symposium on Materials and Electrical Engineering 2017

材料科学;电工学

Jamaaluddin, J.^1 ; Hadidjaja, D.^1 ; Sulistiyowati, I.^1 ; Suprayitno, E.A.^1 ; Anshory, I.^1 ; Syahrorini, S.^1 ; Abdullah, A.G.^2

Program Studi Teknik Elektro, Universitas Muhammadiyah Sidoarjo, Jl. Raya Gelam no 250, Sidoarjo, Jawa Timur, Indonesia^1

Sekolah Pascasarjana, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi 229, Bandung

40154, Indonesia^2

关键词: Electrical energy;    Electrical systems;    Footprint of uncertainties;    High flexibility;    Interval type-2 fuzzy;    Short term load forecasting;    Short-term forecasting;    Very short term forecasting;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/384/1/012078/pdf
DOI  :  10.1088/1757-899X/384/1/012078

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

One of the important things to do an electric power system operation is load forecasting. Load forecasting consists of short-term forecasting and short-term forecasting. The very short term load forecasting are required for regulating electrical energy generation, maintenance arrangements and regulating the labor involved. This forecasting is done to decide which plant to operate. The capacity of the plant to be operated adjusts to the load plan to be supplied the next day. The very short-term load forecasting is predicting electrical loads with time intervals every 30 minutes for the next day. In this study using Interval Type-2 Fuzzy Inference System (IT-2FIS) because it delivers a high flexibility that can be developed using other methods (hybrid). Laying out the footprint of uncertainty (FOU) membership function of the Interval Type-2 Fuzzy Inference System (IT-2FIS). This method has been applied for short- term load forecasting and will be employed for very short-term forecasting. In very short-term load forecasting IT-2 FIS has Mean Average Percentage Error (MAPE) arround 0,729%.