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

Energies

Guangya Yang¹  Rongsen Jin²  Peng Hou³  Yuanhang Qi⁴  Guisong Liu⁴  Zhaoyang Dong⁵  Zhile Yang⁶ 

[1] Center of Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark, 2800 Lyngby, Denmark;Department of Operation, University of Groningen, 9747 Groningen, The Netherlands;SEWPG European Innovation Center, 8000 Aarhus, Denmark;School of Computer Science, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China;School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2052, Australia;Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;

关键词: offshore wind farm;    multiple wind turbine types;    cable connection layout;    power losses;    Voronoi diagram;    adaptive particle swarm optimization;   

DOI  :  10.3390/en14030644

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown