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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Short term load forecasting using interval type-2 fuzzy logic systems
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
1424473160 9781424473168
ISSN
1098-7584
Language
eng
Field of Research
080108 Neural, Evolutionary and Fuzzy Computation 090607 Power and Energy Systems Engineering (excl Renewable Power)
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