Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34051
Title: Quantum-inspired particle swarm optimization for power system operations considering wind power uncertainty and carbon tax in Australia
Authors: Yao, F
Dong, ZY
Meng, K
Xu, Z 
Iu, HHC
Wong, KP
Keywords: Carbon tax
economic load dispatch
particle swarm optimization
stochastic optimization
wind power
Issue Date: 2012
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial informatics, 2012, v. 8, no. 4, 6249753, p. 880-888 How to cite?
Journal: IEEE transactions on industrial informatics 
Abstract: In this paper, a computational framework for integrating wind power uncertainty and carbon tax in economic dispatch (ED) model is developed. The probability of stochastic wind power based on nonlinear wind power curve and Weibull distribution is included in the model. In order to solve the revised dispatch strategy, quantum-inspired particle swarm optimization (QPSO) is also adopted, which shows stronger search ability and quicker convergence speed. The dispatch model is tested on a modified IEEE benchmark system involving six thermal units and two wind farms using the real wind speed data obtained from two meteorological stations in Australia.
URI: http://hdl.handle.net/10397/34051
ISSN: 1551-3203
EISSN: 1941-0050
DOI: 10.1109/TII.2012.2210431
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