Webinar: Exploring Cluster Wakes and Their Impact on Wind Farm Annual Energy Production

Cluster wakes and their effect on a wind farm annual energy production: are current models capturing the magnitude of the effects observed in SCADA data?

Wind farm wakes (also known as cluster wakes) persisting over dozens of kilometres offshore has been reported by several authors in recent years. With the steady build-up of wind farms in the North Sea and US Eastern Seaboard, the impact of cluster wakes on wind farm annual energy production (AEP) increases over time. Wake effects over large distances / clusters is an increasingly emergent risk to LCoE. RWE’s press release in 2023 highlighted the risk of big cluster and far-field wakes and announced a collaborative effort with DNV to perform a deep dive into this effect.

To further investigate the status of cluster wakes modelling, DNV, jointly with RWE, conducted research on the subject, the latest results of which were presented to the wind industry at the WindEurope Technology Workshop in June 2024. This investigation focused on two wind farms in the North Sea, Amrumbank West (Germany) and Triton Knoll (UK), both affected by wakes from neighbouring wind farms between 5-30 km away.

As part of its ongoing efforts to develop and validate models and approaches to characterise turbine interaction losses (i.e. wakes and blockage), DNV had earlier retuned the engineering model it uses in bankable energy assessments. Higher-fidelity models,  such as computational fluid dynamics (CFD) and mesoscale models including a wind farm parametrisation, are also increasingly used in this context which present their own challenges when operating at scale. Also, machine learning models are starting to make an appearance.

But the questions remain: how good are these models at capturing the magnitude of turbine interaction losses, and in particular cluster effects, at far-field distances? And what magnitude of impact can we expect for current and future wind farms?

In this webinar, we will expand on the results presented at WindEurope, showing validation results using key model performance metrics and comparisons to real operational data, and aggregated turbine interaction losses from two CFD models, two engineering models, as well as WRF-WFP.

By attending you will find answers to the following questions:

• How far do offshore wind farm wakes persist?
• Are they an oddity, occurring only in very particular conditions, or are they the norm?
• Can we observe their effect in wind farm operational (SCADA) data at different distances?
• Are they well captured in models?
• And most importantly, what is their impact on a wind farm AEP?

You will see evidence supporting RWE’s claimed risks of big cluster and far-field wakes and that, while the retuning of DNV’s engineering model improves its ability to capture signals seen in SCADA data, capturing the fundamental physics possible in high-fidelity models is paramount. And finally, you will hear why we think that there is a risk that the turbine interaction losses derived with WRF, using the standard Fitch wind farm parameterisation, are excessive, when evaluating the losses with standard industry practice.

Presenter biographies:

Christiane Montavon

Christiane has been working with DNV since 2018 and has been modelling wind resource with Computational Fluid Dynamics (CFD) for 20+ years. Working in the Renewable Energy Analytics department, Christiane undertakes CFD analyses as part of the department’s pre- and post-construction services. In her role as CFD lead, she is also involved with research and development of DNV’s CFD service. Through her PhD, Christiane carried out pioneering research about the inclusion of atmospheric stability in wind resource assessment. She recently focused on modelling wind farm blockage and wakes, as well as CFD correction for remote sensing.

Christopher Rodaway

Christopher is Lead Scientist for Advanced Numerics at RWE. He is responsible for numerical modelling, research, development, and bringing advanced modelling techniques to a production level. Leveraging 12+ years experience, Christopher leads Computational Fluid Dynamics (CFD) capabilities for wind resource assessment  including high performance computing (HPC). He is heavily involved in research activities for turbine interaction (wakes and blockage), atmospheric and topographic effects utilising measured data and data science methods to drive improvements in model predictive power. He also led the Carbon Trust’s GloBE project that brought about industry consensus on the topic of the global blockage effect.