Interval type-2 fuzzy logic systems for load forecasting : a comparative study

Khosravi, Abbas, Nahavandi, Saeid, Creighton, Doug and Srinivasan, Dipti 2012, Interval type-2 fuzzy logic systems for load forecasting : a comparative study, IEEE transactions on power systems, vol. 27, no. 3, pp. 1274-1282.

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Title Interval type-2 fuzzy logic systems for load forecasting : a comparative study
Author(s) Khosravi, AbbasORCID iD for Khosravi, Abbas
Nahavandi, SaeidORCID iD for Nahavandi, Saeid
Creighton, DougORCID iD for Creighton, Doug
Srinivasan, Dipti
Journal name IEEE transactions on power systems
Volume number 27
Issue number 3
Start page 1274
End page 1282
Total pages 9
Publisher IEEE
Place of publication Piscataway, N. J
Publication date 2012
ISSN 0885-8950
Keyword(s) load forecasting
prediction interval
type 2 fuzzy logic system
Summary Accurate short term load forecasting (STLF) is essential for a variety of decision-making processes. However, forecasting accuracy can drop due to the 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 additional degrees of freedom, are an excellent tool for handling uncertainties and improving the prediction accuracy. Experiments conducted with real datasets show that IT2 FLS models precisely approximate future load demands with an acceptable accuracy. Furthermore, they demonstrate an encouraging degree of accuracy superior to feedforward neural networks and traditional type-1 Takagi-Sugeno-Kang (TSK) FLSs.
Language eng
Field of Research 080110 Simulation and Modelling
Socio Economic Objective 850699 Energy Storage, Distribution and Supply not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, IEEE
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Created: Mon, 13 Aug 2012, 12:35:36 EST

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