Wind farm layout optimization using genetic algorithm with different hub height wind turbines
► Introducing wind farm layout optimization with different hub height wind turbines. ► Considering both maximum power output and minimum cost/power as objective functions. ► Using both nested and real code genetic algorithms. ► Using both single and multi-objective optimizations. Layout optimization...
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| Published in | Energy conversion and management Vol. 70; pp. 56 - 65 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.06.2013
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0196-8904 1879-2227 |
| DOI | 10.1016/j.enconman.2013.02.007 |
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| Abstract | ► Introducing wind farm layout optimization with different hub height wind turbines. ► Considering both maximum power output and minimum cost/power as objective functions. ► Using both nested and real code genetic algorithms. ► Using both single and multi-objective optimizations.
Layout optimization is one of the methods to increase wind farm’s utilization rate and power output. Previous researches have revealed that different hub height wind turbines may increase wind farm’s power output. However, few researches focus on optimizing a wind farm’s layout in a two-dimensional area using different hub height wind turbines. In this paper, the authors first investigate the effect of using different hub height wind turbines in a small wind farm on power output. Three different wind conditions are analyzed using nested genetic algorithm, where the results show that power output of the wind farm using different hub height wind turbines will be increased even when the total numbers of wind turbines are same. Different cost models are also taken into account in the analysis, and results show that different hub height wind turbines can also improve cost per unit power of a wind farm. At last, a large wind farm with commercial wind turbines is analyzed to further examine the benefits of using different hub height wind turbines in more realistic conditions. |
|---|---|
| AbstractList | Layout optimization is one of the methods to increase wind farm’s utilization rate and power output. Previous researches have revealed that different hub height wind turbines may increase wind farm’s power output. However, few researches focus on optimizing a wind farm’s layout in a two-dimensional area using different hub height wind turbines. In this paper, the authors first investigate the effect of using different hub height wind turbines in a small wind farm on power output. Three different wind conditions are analyzed using nested genetic algorithm, where the results show that power output of the wind farm using different hub height wind turbines will be increased even when the total numbers of wind turbines are same. Different cost models are also taken into account in the analysis, and results show that different hub height wind turbines can also improve cost per unit power of a wind farm. At last, a large wind farm with commercial wind turbines is analyzed to further examine the benefits of using different hub height wind turbines in more realistic conditions. Layout optimization is one of the methods to increase wind farmas utilization rate and power output. Previous researches have revealed that different hub height wind turbines may increase wind farmas power output. However, few researches focus on optimizing a wind farmas layout in a two-dimensional area using different hub height wind turbines. In this paper, the authors first investigate the effect of using different hub height wind turbines in a small wind farm on power output. Three different wind conditions are analyzed using nested genetic algorithm, where the results show that power output of the wind farm using different hub height wind turbines will be increased even when the total numbers of wind turbines are same. Different cost models are also taken into account in the analysis, and results show that different hub height wind turbines can also improve cost per unit power of a wind farm. At last, a large wind farm with commercial wind turbines is analyzed to further examine the benefits of using different hub height wind turbines in more realistic conditions. ► Introducing wind farm layout optimization with different hub height wind turbines. ► Considering both maximum power output and minimum cost/power as objective functions. ► Using both nested and real code genetic algorithms. ► Using both single and multi-objective optimizations. Layout optimization is one of the methods to increase wind farm’s utilization rate and power output. Previous researches have revealed that different hub height wind turbines may increase wind farm’s power output. However, few researches focus on optimizing a wind farm’s layout in a two-dimensional area using different hub height wind turbines. In this paper, the authors first investigate the effect of using different hub height wind turbines in a small wind farm on power output. Three different wind conditions are analyzed using nested genetic algorithm, where the results show that power output of the wind farm using different hub height wind turbines will be increased even when the total numbers of wind turbines are same. Different cost models are also taken into account in the analysis, and results show that different hub height wind turbines can also improve cost per unit power of a wind farm. At last, a large wind farm with commercial wind turbines is analyzed to further examine the benefits of using different hub height wind turbines in more realistic conditions. |
| Author | Li, Hua Jin, Kai Chen, Ying Song, Qing |
| Author_xml | – sequence: 1 givenname: Ying surname: Chen fullname: Chen, Ying – sequence: 2 givenname: Hua surname: Li fullname: Li, Hua email: hua.li@tamuk.edu – sequence: 3 givenname: Kai surname: Jin fullname: Jin, Kai – sequence: 4 givenname: Qing surname: Song fullname: Song, Qing |
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| Snippet | ► Introducing wind farm layout optimization with different hub height wind turbines. ► Considering both maximum power output and minimum cost/power as... Layout optimization is one of the methods to increase wind farm's utilization rate and power output. Previous researches have revealed that different hub... Layout optimization is one of the methods to increase wind farmas utilization rate and power output. Previous researches have revealed that different hub... Layout optimization is one of the methods to increase wind farm’s utilization rate and power output. Previous researches have revealed that different hub... |
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| SubjectTerms | algorithms Applied sciences commercial farms Cost analysis Energy Exact sciences and technology Genetic algorithm Genetic algorithms Layout Natural energy Optimization Two dimensional Utilization wind Wind energy Wind farm Wind power Wind power generation Wind turbines |
| Title | Wind farm layout optimization using genetic algorithm with different hub height wind turbines |
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