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An Improved Multi-objective Bare-Bones PSO for Optimal Design of Solar Dish Stirling Engine Systems

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Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration (ICSEE 2017, LSMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 763))

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Abstract

An improved bare-bones multi-objective particle swarm optimization, namely IMOBBPSO is proposed to optimize the solar-dish Stirling engine systems. A new simple strategy for updating particle’s velocity is developed based on the conventional bare-bones PSO, aiming to enhance the diversity of the solutions and accelerate the convergence rate. In order to test the effectiveness of IMOBBPSO, four benchmarks are used. Compared with the non-dominated sorting genetic algorithm-II (NSGAII) and multi-objective particle swarm optimization algorithm (MOPSO), it is revealed that IMOBBPSO can quickly converge to the true Pareto front and efficiently solve practical problems. IMOBBPSO is then used to solve the design of the solar-dish Stirling engine. It is shown that IMOBBPSO obtains the best optimization results than NSGAII and MOPSO. It further achieves significant improvements 25.6102% to 29.2926% in terms of the output power and entropy generation rate when it is compared with existing results in the literature.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (61273040).

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Authors and Affiliations

  1. Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200071, China

    Qun Niu, Ziyuan Sun & Dandan Hua

Authors
  1. Qun Niu
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  2. Ziyuan Sun
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  3. Dandan Hua
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Corresponding author

Correspondence to Qun Niu .

Editor information

Editors and Affiliations

  1. Queen’s University Belfast, Belfast, United Kingdom

    Kang Li

  2. Nanjing Automation Research Institute, Nanjing, China

    Yusheng Xue

  3. Harbin Institute of Technology, Harbin, China

    Shumei Cui

  4. Shanghai University, Shanghai, China

    Qun Niu

  5. Queen’s University Belfast, Belfast, United Kingdom

    Zhile Yang

  6. Cranfield University, Bedford, United Kingdom

    Patrick Luk

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© 2017 Springer Nature Singapore Pte Ltd.

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Niu, Q., Sun, Z., Hua, D. (2017). An Improved Multi-objective Bare-Bones PSO for Optimal Design of Solar Dish Stirling Engine Systems. In: Li, K., Xue, Y., Cui, S., Niu, Q., Yang, Z., Luk, P. (eds) Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 763. Springer, Singapore. https://doi.org/10.1007/978-981-10-6364-0_17

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  • DOI: https://doi.org/10.1007/978-981-10-6364-0_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6363-3

  • Online ISBN: 978-981-10-6364-0

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