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Abstract
This article explores the application of a wind farm layout evaluation function and layout optimization framework to Middelgrunden wind farm in Denmark. This work applies an evaluation tool to estimate the cost, energy production, and the levelized cost of energy for the existing layout at Middelgrunden wind farm; comparing these against the cost and energy production reported by the wind farm. From here, new layouts have then been designed using both genetic algorithms and particle swarm optimization. This study has found that both algorithms are capable of identifying layouts with reduced levelized cost of energy compared to the existing layout while still considering the specific conditions and constraints experienced by this site. Reductions in levelized cost of energy, such as this can result in very significant savings over the lifetime of the project thereby highlighting the importance of including new advanced methods to wind farm layout design.
Original language | English |
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Pages (from-to) | 287–297 |
Number of pages | 11 |
Journal | Ocean Engineering |
Volume | 139 |
Early online date | 9 May 2017 |
DOIs | |
Publication status | Published - 15 Jul 2017 |
Keywords
- offshore wind farm
- layout optimization
- genetic algorithm
- particle swarm optimization
- Middelgrunden wind farm
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Dive into the research topics of 'Application of an offshore wind farm layout optimization methodology at Middelgrunden wind farm'. Together they form a unique fingerprint.Projects
- 1 Finished
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Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE)
Incecik, A. (Principal Investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/10/11 → 31/03/22
Project: Research - Studentship