Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization
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...
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| Format: | Article |
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MDPI AG
2021-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/20/9746 |
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| author | Menova Yeghikian Abolfazl Ahmadi Reza Dashti Farbod Esmaeilion Alireza Mahmoudan Siamak Hoseinzadeh Davide Astiaso Garcia |
| author_facet | Menova Yeghikian Abolfazl Ahmadi Reza Dashti Farbod Esmaeilion Alireza Mahmoudan Siamak Hoseinzadeh Davide Astiaso Garcia |
| author_sort | Menova Yeghikian |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T06:44:04Z |
| format | Article |
| id | doaj.art-1cf707b3661f4419b7bb9750da9fb996 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T06:44:04Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-1cf707b3661f4419b7bb9750da9fb9962023-11-22T17:23:43ZengMDPI AGApplied Sciences2076-34172021-10-011120974610.3390/app11209746Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm OptimizationMenova Yeghikian0Abolfazl Ahmadi1Reza Dashti2Farbod Esmaeilion3Alireza Mahmoudan4Siamak Hoseinzadeh5Davide Astiaso Garcia6Department of Energy Systems Engineering, School of New Technologies, Iran University of Science and Technology, Tehran 13114-16846, IranDepartment of Energy Systems Engineering, School of New Technologies, Iran University of Science and Technology, Tehran 13114-16846, IranDepartment of Energy Systems Engineering, School of New Technologies, Iran University of Science and Technology, Tehran 13114-16846, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran 19967-15433, IranDepartment of Aerospace Engineering, K.N. Toosi University of Technology, Tehran 16765-3381, IranDepartment of Planning, Design, Technology of Architecture, Sapienza University of Rome, Via Flaminia 72, 00196 Rome, ItalyDepartment of Planning, Design, Technology of Architecture, Sapienza University of Rome, Via Flaminia 72, 00196 Rome, ItalyNowadays, 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.https://www.mdpi.com/2076-3417/11/20/9746wind farmoptimizationparticle swarm optimizationwind farm layout optimization |
| spellingShingle | Menova Yeghikian Abolfazl Ahmadi Reza Dashti Farbod Esmaeilion Alireza Mahmoudan Siamak Hoseinzadeh Davide Astiaso Garcia Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization Applied Sciences wind farm optimization particle swarm optimization wind farm layout optimization |
| title | Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization |
| title_full | Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization |
| title_fullStr | Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization |
| title_full_unstemmed | Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization |
| title_short | Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization |
| title_sort | wind farm layout optimization with different hub heights in manjil wind farm using particle swarm optimization |
| topic | wind farm optimization particle swarm optimization wind farm layout optimization |
| url | https://www.mdpi.com/2076-3417/11/20/9746 |
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