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Short term load forecasting using interval type-2 fuzzy logic systems
conference contribution
posted on 2011-01-01, 00:00 authored by Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, Douglas CreightonDouglas CreightonAccurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy may drop due to presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. This paper proposes the application of Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) for the problem of STLF. IT2 FLSs, with extra degrees of freedom, are an excellent tool for handling prevailing uncertainties and improving the prediction accuracy. Experiments conducted with real datasets show that IT2 FLS models appropriately approximate future load demands with an acceptable accuracy. Furthermore, they demonstrate an encouraging degree of accuracy superior to feedforward neural networks used in this study.
History
Event
International Conference on Fuzzy Systems (2011 : Taipei, Taiwan)Pagination
502 - 508Publisher
IEEELocation
Taipei, TaiwanPlace of publication
Piscataway, N. J.Start date
2011-06-27End date
2011-06-30ISSN
1098-7584ISBN-13
9781424473168ISBN-10
1424473160Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2011, IEEETitle of proceedings
FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy SystemsUsage metrics
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