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Short term load forecasting using interval type-2 fuzzy logic systems

Khosravi, Abbas, Nahavandi, Saeid and Creighton, Doug 2011, Short term load forecasting using interval type-2 fuzzy logic systems, in FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems, IEEE, Piscataway, N. J., pp. 502-508.

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Title Short term load forecasting using interval type-2 fuzzy logic systems
Author(s) Khosravi, Abbas
Nahavandi, Saeid
Creighton, Doug
Conference name International Conference on Fuzzy Systems (2011 : Taipei, Taiwan)
Conference location Taipei, Taiwan
Conference dates 27-30 Jun. 2011
Title of proceedings FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems
Editor(s) [Unknown]
Publication date 2011
Conference series IEEE International Conference on Fuzzy Systems
Start page 502
End page 508
Total pages 7
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) load forecasting
type-2 fuzzy logic
Summary Accurate 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.
ISBN 9781424473168
9781424473151
ISSN 1098-7584
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
090607 Power and Energy Systems Engineering (excl Renewable Power)
Socio Economic Objective 850601 Energy Services and Utilities
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044774

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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