Quantum-inspired particle swarm optimization for power system operations considering wind power uncertainty and carbon tax in Australia

Title: Quantum-inspired particle swarm optimization for power system operations considering wind power uncertainty and carbon tax in Australia
Creator: Yao, Fang; Dong, Zhao Yang; Meng, Ke; Xu, Zhao; Iu, Herbert Ho-Ching; Wong, Kit Po
Relation: IEEE Transactions on Industrial Informatics Vol. 8, Issue 4, p. 880-888
Publisher Link: http://dx.doi.org/10.1109/TII.2012.2210431
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: journal article
Date: 2012
Description: 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.
Subject: wind power; carbon tax; economic load dispatch; particle swarm optimization; stochastic optimization
Identifier: http://hdl.handle.net/1959.13/1327875
Identifier: uon:25767
Identifier: ISSN:1551-3203
Language: eng
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