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

Wu, Y. (författare)
The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Japan
Xia, T. (författare)
The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Japan
Wang, Y. (författare)
China University of Petroleum (Beijing), Changping, Beijing, China
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Zhang, Haoran (författare)
Mälardalens universitet,Framtidens energi,The University of Tokyo, Japan
Feng, X. (författare)
Xi'an Jiaotong University, Shaanxi, China
Song, X. (författare)
Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China
Shibasaki, R. (författare)
The University of Tokyo, Kashiwa-shi, Chiba, Japan
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 (creator_code:org_t)
Elsevier Ltd, 2022
2022
Engelska.
Ingår i: Renewable energy. - : Elsevier Ltd. - 0960-1481 .- 1879-0682. ; 185, s. 302-320
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Nyckelord

Cable network
Meta-heuristic algorithms
Multi-type wind turbine
Offshore wind farm
Seabed terrain
Ant colony optimization
Cables
Electric utilities
Energy dissipation
Genetic algorithms
Heuristic algorithms
Linear programming
Offshore oil well production
Site selection
Wind turbines
Cable networks
Cable routing
Hybrid method
Layer model
Meta-heuristics algorithms
Obstacle-avoiding
Turbine layouts
Wind farm layout optimizations
Offshore wind farms
algorithm
methodology
network analysis
optimization
three-dimensional modeling
wind farm
wind turbine

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