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An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects

Author

Listed:
  • Qun Niu

    (Shanghai Key Laboratory of Power Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Zhuo Zhou

    (Shanghai Key Laboratory of Power Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Hong-Yun Zhang

    (Shanghai Key Laboratory of Power Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Jing Deng

    (Intelligent Systems and Control Group, School of Electronics, Electrical Engineering and Computer Science, Queen’s University of Belfast, Belfast BT9 5AH, UK)

Abstract

Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED) problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE), particle swarm optimization (PSO) and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems.

Suggested Citation

  • Qun Niu & Zhuo Zhou & Hong-Yun Zhang & Jing Deng, 2012. "An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects," Energies, MDPI, vol. 5(9), pages 1-19, September.
  • Handle: RePEc:gam:jeners:v:5:y:2012:i:9:p:3655-3673:d:20172
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    References listed on IDEAS

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    1. Alsumait, J.S. & Sykulski, J.K. & Al-Othman, A.K., 2010. "A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems," Applied Energy, Elsevier, vol. 87(5), pages 1773-1781, May.
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    Cited by:

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    2. Wei-Tzer Huang & Kai-Chao Yao & Ming-Ku Chen & Feng-Ying Wang & Cang-Hui Zhu & Yung-Ruei Chang & Yih-Der Lee & Yuan-Hsiang Ho, 2018. "Derivation and Application of a New Transmission Loss Formula for Power System Economic Dispatch," Energies, MDPI, vol. 11(2), pages 1-19, February.
    3. Ly Huu Pham & Minh Quan Duong & Van-Duc Phan & Thang Trung Nguyen & Hoang-Nam Nguyen, 2019. "A High-Performance Stochastic Fractal Search Algorithm for Optimal Generation Dispatch Problem," Energies, MDPI, vol. 12(9), pages 1-25, May.
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