Short Term Load Forecasting for Weekends in Indonesia: Comparison of Three Methods

This paper compares the three methods used for short-term load forecasting on the electrical system in Indonesia. The three methods are coefficient load method, single exponential smoothing, and fuzzy subtractive clustering that in optimization using adaptive neuro fuzzy inference system (ANFIS). Th...

Full description

Saved in:
Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 288; no. 1; pp. 12119 - 12127
Main Authors Yaqin, E N, Abdullah, A G, Chandra, D, Pratiwi, T A, Adhigunarto, S, Shidiq, A M, Ramadhan, A J, Putra, R P, Alfaridzi, A F, Muttaqin, M F A, Nandiyanto, A B D
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.01.2018
Subjects
Adaptive systems
Artificial neural networks
Clustering
Electrical loads
Forecasting
Fuzzy logic
Optimization
Smoothing
Indonesia
Online AccessGet full text

Cover

More Information
Summary:This paper compares the three methods used for short-term load forecasting on the electrical system in Indonesia. The three methods are coefficient load method, single exponential smoothing, and fuzzy subtractive clustering that in optimization using adaptive neuro fuzzy inference system (ANFIS). The experiments were conducted on seven data of electric load on a weekends in October 2014. The result of simulation showed that single exponential smoothing method is more precision in electrical load forecasting for weekends in Indonesia.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/288/1/012119