LAPSE:2023.11987
Published Article
LAPSE:2023.11987
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, Chao Shi
February 28, 2023
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
deep-water semi-submersible production platform, new energy sources, Particle Swarm Optimization, reactive power optimization, Taguchi method
Suggested Citation
Cheng P, Xu Z, Li R, Shi C. A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources. (2023). LAPSE:2023.11987
Author Affiliations
Cheng P: College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China [ORCID]
Xu Z: College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Li R: 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
Shi C: Comac Beijing Civil Aircraft Center, Beijing 102209, China
Journal Name
Energies
Volume
15
Issue
13
First Page
4565
Year
2022
Publication Date
2022-06-22
ISSN
1996-1073
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Original Submission
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PII: en15134565, Publication Type: Journal Article
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