4.8 Article

Quantum-Inspired Particle Swarm Optimization for Power System Operations Considering Wind Power Uncertainty and Carbon Tax in Australia

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 8, Issue 4, Pages 880-888

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2012.2210431

Keywords

Carbon tax; economic load dispatch; particle swarm optimization; stochastic optimization; wind power

Funding

  1. Hong Kong RGC GRF Grant [515110]
  2. State Key Laboratory of Power Transmission Equipment and System Security and New Technology (Chongqing University) [2007DA10512711401]

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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.

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