The Impact of Influence Range Fuzzy Subtractive Clustering Modification to Accuracy Anomalous Load Forecasting. (March 2017)

• Record Type: Journal Article
• Authors: Respati, F A; Abdullah, A G; Mulyadi, Y
• Is Part Of: IOP conference series. Volume 180(2017)
• Publication Date: 2017-03
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/180/1/012292
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: 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.