Long-distance wake losses could cause energy deficits to offshore wind mega-projects at a scale “much greater than expected”
Using validated, high-fidelity long-range wake loss modeling, ArcVera Renewables found in their new study that commonly used engineering wake models vastly underpredict energy losses due to external wakes. ArcVera calls for further critical research into long-distance wake losses of offshore wind plants.
October 03, 2022. By News Bureau
A recent study by ArcVera Renewables confirms the severe under-prediction of long-range wake losses by engineering wake loss models in common use and investigates long-range wake loss potential at the New York Bight offshore development sites. Velocity deficits, as high as 1 m/s or 10%, persist up to or greater than 100 km downwind of large offshore arrays, leading to long-range energy deficits much greater than expected by most subject matter experts in the industry. ArcVera’s methodology of utilizing the Weather Research and Forecasting (WRF) model, a firmly established high-fidelity numerical weather prediction model, is a core expertise of ArcVera Renewables. For the purpose of the long-distance wake study, the ArcVera WRF model uses Wind Farm Parameterization (WFP) to account for the effects of the wind turbines in the domain.
The New York Bight offshore lease areas represent 488,000 hectares of potential offshore wind development. The US Bureau of Ocean Energy Management (BOEM) auctioned the leases in February 2022, for a total value of $4.37 billion dollars.
The study analyzed two separate cases to estimate the external waking effect on lease area OCS-A 0538 by lease areas OCS-A 0539, OCS-A 0541, and OCS-A 0542. Case 1 parameterized the model using representative theoretical 15-MW wind turbines in the OCS-A 0541 and OCS-A 0542 lease areas. In Case 2, the model parameterization added an array, with the same theoretical wind turbine, to the OCS-A 0539 lease area. Locations of the lease areas can be seen in the BOEM map below in Figure 1.
Energy losses based on the WRF-WFP results were calculated and compared to two established engineering models: the Eddy Viscosity Deep Array Wake Model (EV DAWM) and ArcVera’s wind farm-atmosphere interaction (WFAI) model.
The results below show that conventional wake models produce much smaller wake losses than the more computationally advanced WRF-WFP model. In Case 1, external wake losses were measured at 13.0% compared to 0.5% at lease area OCS-A 0538 due to the neighboring arrays within lease areas OCS-A 0541 and OCS-A 0542 using WRF-WFP with EV DAWM external wake loss, and negligible losses with WFAI. In Case 2, external wake losses due to the arrays within OCS-A 0539, OCS-A 0541, and OCS-A 0542, were measured at 28.9% with WRF-WFP compared to 5.3% with EV DAWM and 0.2% with WFAI.
Table 1. Modeled long-range external wake losses at New York Bight Lease Area 0538 for the 16 selected days of primarily southwest wind direction, with separate results for wakes from Lease Area 0539 only, and from the combination of Lease Areas 0539, 0541, and 0542. Losses are expressed as the percent of gross energy.
The New York Bight offshore lease areas represent 488,000 hectares of potential offshore wind development. The US Bureau of Ocean Energy Management (BOEM) auctioned the leases in February 2022, for a total value of $4.37 billion dollars.
The study analyzed two separate cases to estimate the external waking effect on lease area OCS-A 0538 by lease areas OCS-A 0539, OCS-A 0541, and OCS-A 0542. Case 1 parameterized the model using representative theoretical 15-MW wind turbines in the OCS-A 0541 and OCS-A 0542 lease areas. In Case 2, the model parameterization added an array, with the same theoretical wind turbine, to the OCS-A 0539 lease area. Locations of the lease areas can be seen in the BOEM map below in Figure 1.
Energy losses based on the WRF-WFP results were calculated and compared to two established engineering models: the Eddy Viscosity Deep Array Wake Model (EV DAWM) and ArcVera’s wind farm-atmosphere interaction (WFAI) model.
The results below show that conventional wake models produce much smaller wake losses than the more computationally advanced WRF-WFP model. In Case 1, external wake losses were measured at 13.0% compared to 0.5% at lease area OCS-A 0538 due to the neighboring arrays within lease areas OCS-A 0541 and OCS-A 0542 using WRF-WFP with EV DAWM external wake loss, and negligible losses with WFAI. In Case 2, external wake losses due to the arrays within OCS-A 0539, OCS-A 0541, and OCS-A 0542, were measured at 28.9% with WRF-WFP compared to 5.3% with EV DAWM and 0.2% with WFAI.
Table 1. Modeled long-range external wake losses at New York Bight Lease Area 0538 for the 16 selected days of primarily southwest wind direction, with separate results for wakes from Lease Area 0539 only, and from the combination of Lease Areas 0539, 0541, and 0542. Losses are expressed as the percent of gross energy.
ArcVera’s leadership is focused on what the results mean for the future of forecasting wind energy production. “This new study provides an important cautionary lesson as the wind industry proceeds to ever-larger wind turbine models with greater farm density across the globe. WRF-WFP’s results here imply that wind energy resource assessments using only engineering wake or WFAI models may overpredict energy by a significant margin, pending further validation from in-depth additional research”, commented Greg Poulos, CEO of ArcVera Renewables.
Considering the large magnitude and length of wakes predicted by WRFWFP in the New York Bight lease areas, and lack of validating data for the large hypothetical wind turbines used in the simulations, ArcVera consulted with Professor Julie Lundquist’s research group at the University of Colorado to consider the uncertainty in these model predictions of large, long-range wakes. Several tests of sensitivity to model configuration parameters were run by ArcVera, and the results of these tests show that the original configuration actually produced the weakest wakes of all the configurations tested.
Further research is needed
Engineering models commonly used to estimate wakes have been validated for internal wakes and nearby external wakes but have not been validated regularly at such long distances and have not been validated at all for large nameplate (> 12 MW) and rotor diameter (> 200 m) wind turbines.
On the other hand, the WFP in WRF has been validated against SCADA recorded production for an onshore case by ArcVera and it was accurate with respect to long-distance wakes within 10% at a 5-km range (distance between wind farms being studied).
“In the onshore validation study that we conducted in Iowa, USA, wakes were found to travel over 40 km overland, in stable atmospheric conditions. Over the ocean, it is common for atmospheric stability to be enhanced, especially when warm air flow passes over colder underlying water. We also surmise that the very large turbines used in the study produce unusually strong wakes that cannot easily recover their lost momentum, especially under enhanced atmospheric stability conditions.”, commented Mark Stoelinga, who leads Atmospheric Science Innovation at ArcVera.
However, the WRF-WFP is a research tool that has been developed and validated against significantly smaller and less energetic turbines than those to be used in the New York Bight (15 MW, 240-m rotor diameter), and there may be additional adjustments to the WFP required considering the very large and distant external wakes it produced in these simulations.
Ultimately, the longer-term objective is to use operational wind speed measurements and production data of large, operational offshore wind plants near other large offshore wind plants. The preference would be to identify the effects of having the larger, +10 MW wind turbines would have on long-distance wakes. ArcVera welcomes the owners and operators of such large offshore wind facilities to collaborate with them to move the research forward and elevate the success of global offshore wind development.
- Mark Stoelinga, PhD - Lead, Atmospheric Science Innovation and Applications, ArcVera Renewables
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