Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65885
Title: Pareto optimal prediction intervals of electricity price
Authors: Wan, C
Niu, M
Song, Y
Xu, Z 
Keywords: Electricity price
Extreme learning machine
NSGA-II
Prediction intervals
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on power systems, 2017, v. 32, no. 1, 7448478, p. 817-819 How to cite?
Journal: IEEE transactions on power systems 
Abstract: This letter proposes a novel Pareto optimal prediction interval construction approach for electricity price combing extreme learning machine and non-dominated sorting genetic algorithm II (NSGA-II). The Pareto optimal prediction intervals are produced with respect to the formulated two objectives reliability and sharpness. The effectiveness of proposed approach has been verified through the numerical studies on Australia electricity market data.
URI: http://hdl.handle.net/10397/65885
ISSN: 0885-8950
EISSN: 1558-0679
DOI: 10.1109/TPWRS.2016.2550867
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