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

Peng Cheng, Zhiyu Xu, Ruiye Li and Chao Shi
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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
Chao Shi: Comac Beijing Civil Aircraft Center, Beijing 102209, China

Energies, 2022, vol. 15, issue 13, 1-16

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.

Keywords: particle swarm optimization; Taguchi method; new energy sources; deep-water semi-submersible production platform; reactive power optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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