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我们的计算流体动力学 (CFD) 服务可提供最准确的气流模拟。我们会根据您现场的地形和气象数据,创造风力条件,从而以最小误差预测风速。这样,我们便可识别哪里风速最高,哪里风速最低,并预测您的电能输出 — 为优化您现场的设计提供有价值的意见或信息。

我们的尖端 CFD 模型可捕捉尾流效应和复杂地形(如,林地),以达到最高准确性。除了绘制风速图以外,我们的模型还可预测:

  • 入流角
  • 气流分离
  • 风切乱流


我们的 CFD 服务已被独立认可为业内最准确的模型。这些模型已应用于各个大洲的数百个商用项目中。我们基于所有这些场地的数据不断验证我们的模型,因此您可以放心,我们能持续提供您所期望的准确性和可靠性。

Related information

Have a look at our leaflet and related services.

  Computational fluid dynamics flyer

Computational fluid dynamics flyer

Download the Computational fluid dynamics flyer for more information.

  Operational energy assessment of renewables

Operational energy assessment of renewables

The most accurate post-construction energy forecasts for renewable energy projects – based on actual operational data and advanced analytic techniques.


Pre-construction wind energy assessment

Validated pre-construction wind farm energy output predictions help you mitigate risk and build confidence in your project among prospective partners and customers.


Wind farm Resource measurements

Determine your wind farm site’s energy production potential and give investors the assurance of a highly credible resource measurement campaign.


Performance enhancement of renewables

Performance enhancement is how DNV supports your renewables plant in achieving optimal performance, with maximum efficiency and availability.



Our intuitive wind farm design tool, support service and training packages help you optimize your wind farm and maximize profits.


Virtual met data

Mesoscale weather modelling is an accurate and cost-effective data source for identifying and assessing potential wind farm locations.


An extensive validation of CFD flow modelling

DNV paper presented at DEWEK 2015, May 2015. DNV has produced the only validation of modern wind farm flow models known to DNV that you can trust. It is unique because it has statistical significance, meaning the industry can trust the results.


Modelling stability at microscale, both within and above the atmospheric boundary layer, substantially improves wind speed predictions

DNV paper presented at EWEA, November 2015.