Chen, Zhe

Hou, Peng

Hu, Weihao

Soltani, Mohsen

With the increasing size of wind farm, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of the wind turbines’ (WT) locations will influence the capital investment and contribute to the wake losses which incur the reduction of energy production. As a consequence, the optimized placement of the wind turbines may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using Levelized Production Cost (LPC) as the objective function. The optimization procedure is performed by Particle Swarm Optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective to find the optimized layout, which minimizes the LPC. The optimization procedure is applicable for optimized placement of wind turbines within wind farms and extendible for different wind conditions and capacity of wind farms

VBN (Videnbasen)  Aalborg Universitets forskningsportal

Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm using Particle Swarm Optimization Algorithm

Peng Hou

Weihao Hu

Mohsen Soltani

Zhe Chen

Crossref

IEEE Transactions on Sustainable Energy

Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm Using Particle Swarm Optimization Algorithm

http://vbn.aau.dk/files/210245124/Optimized_Placement_of_Wind_Turbines_in_Large_Scale_Offshore_Wind_Farm.pdf

Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm using Particle Swarm Optimization Algorithm

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VBN (Videnbasen) Aalborg Universitets forskningsportal

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