Cable Connection Optimization for Heterogeneous Offshore Wind Farms via a Voronoi Diagram Based Adaptive Particle Swarm Optimization with Local Search

Yuanhang Qi, Peng Hou, Guisong Liu, Rongsen Jin, Zhile Yang, Guangya Yang and Zhaoyang Dong
Additional contact information
Yuanhang Qi: School of Computer Science, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China
Peng Hou: SEWPG European Innovation Center, 8000 Aarhus, Denmark
Guisong Liu: School of Computer Science, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China
Rongsen Jin: Department of Operation, University of Groningen, 9747 Groningen, The Netherlands
Zhile Yang: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Guangya Yang: Center of Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark, 2800 Lyngby, Denmark
Zhaoyang Dong: School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia

Energies, 2021, vol. 14, issue 3, 1-21

Abstract: Offshore wind energy, as one of the featured rich renewable energy sources, is getting more and more attention. The cable connection layout has a significant impact on the economic performance of offshore wind farms. To make better use of the wind resources of a given sea area, a new method for optimal construction of offshore wind farms with different types of wind turbines has emerged in recent years. In such a wind farm, the capacities of wind turbines are not identical which brings new challenges for the cable connection layout optimization. In this work, an optimization model named CCLOP is proposed for such wind farms. The model incorporates both the cable capital cost and the cost of power losses associated with the cables in its objective function. To get an optimized result, a Voronoi diagram based adaptive particle swarm optimization with local search is proposed and applied. The simulation results show that the proposed method can help find a solution that is 12.74% outperformed than a benchmark.

Keywords: offshore wind farm; multiple wind turbine types; cable connection layout; power losses; Voronoi diagram; adaptive particle swarm optimization; local search (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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