Nowadays, optimizing wind farm configurations is one of the biggest concerns for energy communities. The ongoing investigations have so far helped increasing power generation and reducing corresponding costs. The primary objective of this study is to optimize a wind farm layout in Manjil, Iran. The optimization procedure aims to find the optimal arrangement of this wind farm and the best values for the hubs of its wind turbines. By considering wind regimes and geographic data of the considered area, and using the Jensen’s method, the wind turbine wake effect of the proposed configuration is simulated. The objective function in the optimization problem is set in such a way to find the optimal arrangement of the wind turbines as well as electricity generation costs, based on the Mossetti cost function, by implementing the particle swarm optimization (PSO) algorithm. The results reveal that optimizing the given wind farm leads to a 10.75% increase in power generation capacity and a 9.42% reduction in its corresponding cost.

Wind farm layout optimization with different hub heights in manjil wind farm using particle swarm optimization / Yeghikian, M.; Ahmadi, A.; Dashti, R.; Esmaeilion, F.; Mahmoudan, A.; Hoseinzadeh, S.; Astiaso Garcia, D.. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 11:20(2021), p. 9746. [10.3390/app11209746]

Wind farm layout optimization with different hub heights in manjil wind farm using particle swarm optimization

Hoseinzadeh S.;Astiaso Garcia D.
2021

Abstract

Nowadays, optimizing wind farm configurations is one of the biggest concerns for energy communities. The ongoing investigations have so far helped increasing power generation and reducing corresponding costs. The primary objective of this study is to optimize a wind farm layout in Manjil, Iran. The optimization procedure aims to find the optimal arrangement of this wind farm and the best values for the hubs of its wind turbines. By considering wind regimes and geographic data of the considered area, and using the Jensen’s method, the wind turbine wake effect of the proposed configuration is simulated. The objective function in the optimization problem is set in such a way to find the optimal arrangement of the wind turbines as well as electricity generation costs, based on the Mossetti cost function, by implementing the particle swarm optimization (PSO) algorithm. The results reveal that optimizing the given wind farm leads to a 10.75% increase in power generation capacity and a 9.42% reduction in its corresponding cost.
2021
optimization; particle swarm optimization; wind farm; wind farm layout optimization
01 Pubblicazione su rivista::01a Articolo in rivista
Wind farm layout optimization with different hub heights in manjil wind farm using particle swarm optimization / Yeghikian, M.; Ahmadi, A.; Dashti, R.; Esmaeilion, F.; Mahmoudan, A.; Hoseinzadeh, S.; Astiaso Garcia, D.. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 11:20(2021), p. 9746. [10.3390/app11209746]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1583103
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