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Application of an offshore wind farm layout optimization methodology at Middelgrunden wind farm

机译:海上风电场布局优化方法在Middelgrunden风电场中的应用

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摘要

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.
机译:本文探讨了风电场布局评估功能和布局优化框架在丹麦Middelgrunden风电场中的应用。这项工作采用了一种评估工具,以估算Middelgrunden风电场现有布局的成本,能源生产和能源的平均成本;将这些与风电场报告的成本和能源生产进行比较。从这里开始,使用遗传算法和粒子群优化技术设计了新的布局。这项研究发现,与现有布局相比,这两种算法都能够以降低的平均能源成本来标识布局,同时仍要考虑该站点遇到的特定条件和约束。降低平均能源成本,例如,这可以在项目的整个生命周期中节省大量资金,从而突出显示了在风电场布局设计中包括新的先进方法的重要性。

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