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

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.
- Aalborg University Library (AUB) Aalborg Universitet Research Portal Denmark
- Aalborg University Library (AUB) Denmark
- Aalborg University Library (AUB) Denmark
- Aalborg University Denmark
- Aalborg University Denmark
Optimized placement, Particle Swarm Optimization (PSO), Wake effect, Energy yields, Wake model, Levelized Production Cost (LPC)
Optimized placement, Particle Swarm Optimization (PSO), Wake effect, Energy yields, Wake model, Levelized Production Cost (LPC)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).139 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
