The Impact of Influence Range Fuzzy Subtractive Clustering Modification to Accuracy Anomalous Load Forecasting

1st Annual Applied Science and Engineering Conference

工业技术;自然科学

Respati, F.A.^1 ; Abdullah, A.G.^1 ; Mulyadi, Y.^1

Program Studi Teknik Elektro, FPTK Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 207, Bandung, Indonesia^1

关键词: Economic operations;    Electrical power system;    Error values;    Fuzzy subtractive clustering;    Load condition;    Load demand;    Load forecasting;    Short term load forecasting;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/180/1/012292/pdf
DOI  :  10.1088/1757-899X/180/1/012292

来源: IOP

【 摘 要 】

Short term load forecasting (STLF) has an important role for reliability and economic operation of electrical power system. In this paper, fuzzy subtractive clustering (FSC) method is used in STLF of electrical power system for special days in anomalous load conditions. These anomalous loads occur during national holidays. This method is applied on dataset of Region 2 Java-Bali to forecast the load demand on half-hour in national holidays (anomalous load). The proposed methodology has been to decrease the forecasted error value. Finally, the result shows that FSC implementation for STLF of regional load have more accuracy and better outcomes.