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A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources

Author

Listed:
  • Peng Cheng

    (College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China)

  • Zhiyu Xu

    (College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China)

  • Ruiye Li

    (College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
    Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China)

  • Chao Shi

    (Comac Beijing Civil Aircraft Center, Beijing 102209, China)

Abstract

In order to realize the sustainable development of energy, the combination of new energy power generation technology and the traditional offshore platform has excellent research prospects. The access to new energy sources can provide a powerful supplement to the power grid of the offshore platform, but will also create new challenges for the planning, operation, and control of the power grid of the platform; hence, it is very important to optimize the reactive power of the offshore platform with new study, a mathematical model was first built for the reactive power optimization of offshore platform power systems with new energy sources, and the Taguchi method was then used to optimize the parameters and population of particle swarm optimization, thereby addressing a defect in particle swarm optimization, namely, that it can easily fall into local optimal solutions. Finally, the algorithm proposed in this paper was applied to solve the reactive power optimization problem of the offshore platform power system with new energy sources. The experimental results show that the proposed algorithm has stronger optimization ability, reduces the system active power loss to the greatest extent, and improves the voltage quality. These results provide theoretical support for the practical application and optimization of the deep-water semi-submersible production platform integrated with new energy sources.

Suggested Citation

  • Peng Cheng & Zhiyu Xu & Ruiye Li & Chao Shi, 2022. "A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources," Energies, MDPI, vol. 15(13), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4565-:d:845281
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    References listed on IDEAS

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