A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network

Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronizati...

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Vydáno v:	Renewable energy Ročník 185; s. 302 - 320
Hlavní autoři:	Wu, Yan, Xia, Tianqi, Wang, Yufei, Zhang, Haoran, Feng, Xiao, Song, Xuan, Shibasaki, Ryosuke
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.02.2022
Témata:	algorithm algorithms Ant colony optimization Cable network Cable networks Cable routing Cables case studies Electric utilities energy Energy dissipation Genetic algorithms Heuristic algorithms Hybrid method landscapes Layer model Linear programming markets Meta-heuristic algorithms Meta-heuristics algorithms methodology Multi-type wind turbine network analysis Obstacle-avoiding Offshore oil well production Offshore wind farm Offshore wind farms optimization power generation Seabed terrain Site selection spatial data system optimization three-dimensional modeling Turbine layouts wind wind farm Wind farm layout optimizations wind farms wind turbine Wind turbines Cable network Meta-heuristic algorithms Offshore wind farm Seabed terrain Multi-type wind turbine
ISSN:	0960-1481, 1879-0682, 1879-0682
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Abstract	Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronization optimization of site selection of the offshore wind farm, three-dimensional wind turbine layout and three-dimensional cable network routing based on meta-heuristic algorithms and geographic information systems. Several practical issues, i.e., restricted areas, power generation, cable network and energy loss, are taken into consideration. A two-layer model is proposed. The outer layer model is for the site selection and the wind turbine layout optimization. The inner layer model is for the obstacle-avoiding cable routing optimization. In this stage, the seabed terrain is considered for the first time. The proposed integrated model is complex and non-convex. Thus, a hybrid method including an improved ant colony optimization combined with genetic algorithm, dual-simplex method and Kruskal algorithm is proposed to search the solution more efficiently. The initialization stage of the hybrid method is improved from random assignment to directional assignment. The directional solution is obtained by the widely used genetic algorithm. A case study based on a real offshore wind farm is established to prove the effectiveness of the proposed methodology. The results show an over one million dollars increase in annual benefit compared with conventional methods.
AbstractList	Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronization optimization of site selection of the offshore wind farm, three-dimensional wind turbine layout and three-dimensional cable network routing based on meta-heuristic algorithms and geographic information systems. Several practical issues, i.e., restricted areas, power generation, cable network and energy loss, are taken into consideration. A two-layer model is proposed. The outer layer model is for the site selection and the wind turbine layout optimization. The inner layer model is for the obstacle-avoiding cable routing optimization. In this stage, the seabed terrain is considered for the first time. The proposed integrated model is complex and non-convex. Thus, a hybrid method including an improved ant colony optimization combined with genetic algorithm, dual-simplex method and Kruskal algorithm is proposed to search the solution more efficiently. The initialization stage of the hybrid method is improved from random assignment to directional assignment. The directional solution is obtained by the widely used genetic algorithm. A case study based on a real offshore wind farm is established to prove the effectiveness of the proposed methodology. The results show an over one million dollars increase in annual benefit compared with conventional methods.
Author	Wang, Yufei Shibasaki, Ryosuke Feng, Xiao Song, Xuan Zhang, Haoran Wu, Yan Xia, Tianqi
Author_xml	– sequence: 1 givenname: Yan surname: Wu fullname: Wu, Yan organization: School of Chemical Engineering and Environment, China University of Petroleum (Beijing), 18 Fuxue Road, Changping, Beijing, 102249, China – sequence: 2 givenname: Tianqi surname: Xia fullname: Xia, Tianqi organization: Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan – sequence: 3 givenname: Yufei surname: Wang fullname: Wang, Yufei email: wangyufei@cup.edu.cn, yufei-wang@outlook.com organization: School of Chemical Engineering and Environment, China University of Petroleum (Beijing), 18 Fuxue Road, Changping, Beijing, 102249, China – sequence: 4 givenname: Haoran surname: Zhang fullname: Zhang, Haoran organization: Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan – sequence: 5 givenname: Xiao surname: Feng fullname: Feng, Xiao organization: School of Chemical Engineering and Technology, Xi'an Jiaotong University, 28 Xianning West Road, Xi'an, Shaanxi, 710049, China – sequence: 6 givenname: Xuan surname: Song fullname: Song, Xuan organization: SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China – sequence: 7 givenname: Ryosuke surname: Shibasaki fullname: Shibasaki, Ryosuke organization: Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan
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Snippet	Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing...
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SubjectTerms	algorithm algorithms Ant colony optimization Cable network Cable networks Cable routing Cables case studies Electric utilities energy Energy dissipation Genetic algorithms Heuristic algorithms Hybrid method landscapes Layer model Linear programming markets Meta-heuristic algorithms Meta-heuristics algorithms methodology Multi-type wind turbine network analysis Obstacle-avoiding Offshore oil well production Offshore wind farm Offshore wind farms optimization power generation Seabed terrain Site selection spatial data system optimization three-dimensional modeling Turbine layouts wind wind farm Wind farm layout optimizations wind farms wind turbine Wind turbines
Title	A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network
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