Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization

被引：15

作者：

Yeghikian, Menova ^{[1
]}

Ahmadi, Abolfazl ^{[1
]}

Dashti, Reza ^{[1
]}

Esmaeilion, Farbod ^{[2
]}

Mahmoudan, Alireza ^{[3
]}

Hoseinzadeh, Siamak ^{[4
]}

Garcia, Davide Astiaso ^{[4
]}

机构：

[1] Iran Univ Sci & Technol, Sch New Technol, Dept Energy Syst Engn, Tehran 1311416846, Iran

[2] KN Toosi Univ Technol, Dept Mech Engn, Tehran 1996715433, Iran

[3] KN Toosi Univ Technol, Dept Aerosp Engn, Tehran 167653381, Iran

[4] Sapienza Univ Rome, Dept Planning Design Technol Architecture, Via Flaminia 72, I-00196 Rome, Italy

来源：

APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 20期

关键词：

wind farm; optimization; particle swarm optimization; wind farm layout optimization; GENETIC ALGORITHM; FLUID-FLOW; DESIGN; ENERGY; POWER; HEAT; ENHANCEMENT; EFFICIENCY; SYSTEM;

D O I：

10.3390/app11209746

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

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.</p>

引用

页数：19

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