Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm
To address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimiz...
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| Format: | Article |
| Language: | English |
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2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/11/2846 |
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| author | Xiaoshi Zhuang Honglue Wan Dongran Song Xinyu Fan Yuchen Wang Qian Huang Jian Yang |
| author_facet | Xiaoshi Zhuang Honglue Wan Dongran Song Xinyu Fan Yuchen Wang Qian Huang Jian Yang |
| author_sort | Xiaoshi Zhuang |
| collection | DOAJ |
| description | To address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimization objective. Therein, the synergistic effect between wind turbines and wave energy generators is taken into consideration to decouple the problem and establish a two-layer optimization framework. Secondly, the seagull optimization algorithm is enhanced by integrating three strategies: the nonlinear adjustment strategy for control factors, the Gaussian–Cauchy hybrid variational strategy, and the multiple swarm strategy, thereby improving the global search capability. Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. The results indicate that the optimized system achieves a LCOE of 0.6561 CNY/kWh, which is 0.29% lower than that achieved by traditional algorithms. The proposed method provides a reliable technical solution for the economic optimization of the co-generation system. |
| format | Article |
| id | doaj-art-482d4c8d651b46a68a6fd2987f011267 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-482d4c8d651b46a68a6fd2987f0112672025-08-20T03:46:38ZengMDPI AGEnergies1996-10732025-05-011811284610.3390/en18112846Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization AlgorithmXiaoshi Zhuang0Honglue Wan1Dongran Song2Xinyu Fan3Yuchen Wang4Qian Huang5Jian Yang6School of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaSchool of Automation, Central South University, Changsha 410083, ChinaTo address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimization objective. Therein, the synergistic effect between wind turbines and wave energy generators is taken into consideration to decouple the problem and establish a two-layer optimization framework. Secondly, the seagull optimization algorithm is enhanced by integrating three strategies: the nonlinear adjustment strategy for control factors, the Gaussian–Cauchy hybrid variational strategy, and the multiple swarm strategy, thereby improving the global search capability. Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. The results indicate that the optimized system achieves a LCOE of 0.6561 CNY/kWh, which is 0.29% lower than that achieved by traditional algorithms. The proposed method provides a reliable technical solution for the economic optimization of the co-generation system.https://www.mdpi.com/1996-1073/18/11/2846offshore wind and wave energy co-generationwhole-life-cycle costimproved seagull optimization algorithm |
| spellingShingle | Xiaoshi Zhuang Honglue Wan Dongran Song Xinyu Fan Yuchen Wang Qian Huang Jian Yang Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm Energies offshore wind and wave energy co-generation whole-life-cycle cost improved seagull optimization algorithm |
| title | Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm |
| title_full | Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm |
| title_fullStr | Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm |
| title_full_unstemmed | Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm |
| title_short | Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm |
| title_sort | optimization of offshore wind and wave energy co generation system based on improved seagull optimization algorithm |
| topic | offshore wind and wave energy co-generation whole-life-cycle cost improved seagull optimization algorithm |
| url | https://www.mdpi.com/1996-1073/18/11/2846 |
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