Periodic Reporting for period 1 - Train2Wind (Training school on entrainment in offshore wind power)
Reporting period: 2020-02-01 to 2022-01-31
Train2Wind is a PhD and researcher training school analysing entrainment in offshore wind farms with computer models and experiments. Train2Wind aims to educate 19 fellows, 13 PhDs and 6 short-term fellows, to meet the expanding need for trained staff in the offshore wind industry and academia.
There is disagreement in the scientific community whether there is a limit to the possible installation density of very large offshore wind farm clusters. While the first results from the currently largest offshore farms do not point to a saturation of the exploitable potential, some quite widely published theoretical results from even larger wind farms point to an inherent limit to momentum transfer from the higher atmosphere. By its very nature, a wind turbine extracts energy from the wind, which for a single wind turbine is replenished from the wind field on the sides and above due to the ambient turbulence. However, offshore, the turbulence is lower, and wind farms are typically larger than onshore, therefore the wind can only be replenished from above in a process called entrainment. As even the largest wind farms and clusters to date had not yet come fully into this regime, research in entrainment has been very limited so far. To fully understand this process requires interdisciplinary knowledge on computer models, wind tunnels, remote sensing, Unmanned Aerial Systems (UAS), and a common field experiment.
The main research objectives for the entire project are to find answers to the questions below:
▪ How large is “infinite”, and is there a limit for installation / exploitation for “infinite” wind farms?
▪ How does the wind turbine atmospheric boundary layer (WTABL) develop?
▪ What factors influence that development?
▪ Can it be controlled?
▪ What is the influence of sea spray on the development?
▪ How does a network of heterogeneous European researchers collaborate and share information/data?
Additionally, Train2Wind has three main training objectives with early-stage researchers (ESRs) at the centre:
▪ to give the fellows the necessary skills to execute their particular research project successfully,
▪ to give them a broad background in wind energy, so that they are able to frame their own project in the larger picture,
▪ to give them transferable skills for further personal development, including the employment of better research practices and efficient communication/dissemination/exploitation of research.
There is disagreement in the scientific community whether there is a limit to the possible installation density of very large offshore wind farm clusters. While the first results from the currently largest offshore farms do not point to a saturation of the exploitable potential, some quite widely published theoretical results from even larger wind farms point to an inherent limit to momentum transfer from the higher atmosphere. By its very nature, a wind turbine extracts energy from the wind, which for a single wind turbine is replenished from the wind field on the sides and above due to the ambient turbulence. However, offshore, the turbulence is lower, and wind farms are typically larger than onshore, therefore the wind can only be replenished from above in a process called entrainment. As even the largest wind farms and clusters to date had not yet come fully into this regime, research in entrainment has been very limited so far. To fully understand this process requires interdisciplinary knowledge on computer models, wind tunnels, remote sensing, Unmanned Aerial Systems (UAS), and a common field experiment.
The main research objectives for the entire project are to find answers to the questions below:
▪ How large is “infinite”, and is there a limit for installation / exploitation for “infinite” wind farms?
▪ How does the wind turbine atmospheric boundary layer (WTABL) develop?
▪ What factors influence that development?
▪ Can it be controlled?
▪ What is the influence of sea spray on the development?
▪ How does a network of heterogeneous European researchers collaborate and share information/data?
Additionally, Train2Wind has three main training objectives with early-stage researchers (ESRs) at the centre:
▪ to give the fellows the necessary skills to execute their particular research project successfully,
▪ to give them a broad background in wind energy, so that they are able to frame their own project in the larger picture,
▪ to give them transferable skills for further personal development, including the employment of better research practices and efficient communication/dissemination/exploitation of research.
Train2Wind has hired all the PhDs (13 in total) and one short-term fellow. Both the recruitment and the training is inevitably influenced by COVID-19. Accordingly, the first and the second training schools have taken place online; see https://www.train2wind.eu/training-events for more details.
The ESR research activities and the main highlights so far can be listed as:
▪ Implementing vortex-based smearing correction into the coupled aeroelastic actuator line to improve blade loading and wake predictions
▪ Validation of aeroelastic actuator line method against blade resolved simulations and measurement data
▪ Investigation of the impact of the turbulent scales of the inflow on turbine wake recovery
▪ Evaluating wind farm parametrizations in mesoscale model for real and ideal situations
▪ Development of a new wind farm parameterisation in a mesoscale model
▪ Coupling of mesoscale and engineering wake models
▪ Wind speed variation mapped for offshore wind farms in northern European seas
▪ Decomposition of the coastal gradient effects from wind wakes caused by turbines for the coastal areas
▪ Further improvement for SAR wind retrieval workflow by introducing new filters to erase the anomalous pixels from scenes
▪ Investigation of turbulence structures around large offshore wind farms
▪ Analysis of momentum fluxes variation around wind farms using flight data
▪ Improving available analytical models for better wind farm performance and flow predictions
▪ Investigating the wind farm wakes and farm-to-farm interactions
▪ Investigating potential wake mitigation strategies
▪ Studying wind turbine wakes inside and after wind farms under controlled conditions
▪ Wind tunnel datasets for validation of numerical models
▪ Ultrasonic Anemometer CSAT3B interfacing with Raspberry Pi 4
▪ Ongoing 2D and 3D CFD study on down-wash generated by CRORs
▪ Development of python tool for post-processing of UAS measurements
▪ Calculation of heat fluxes in offshore wind farms from aircraft measurements
▪ Particle measurement system for use in off-shore environments
▪ Development of a mini-sized drying chamber for use with optical particle counters
▪ Preliminary testing of unmanned aerial vehicle aerosol particle measurements
▪ Development of five hole probe automated calibration system
▪ Application of multiple Reynolds number calibrations on the five hole probe for better accuracy of wind measurement
▪ Measuring wind using Multi-Copter
▪ Development of fast-response hygrometer
▪ Effect of modifying the TSR and tilt angle of upstream and downstream turbines on the overall power extraction
To observe the collaboration and knowledge/technology exchange supporting these technical activities, information scientist Train2Wind ESR has conducted 28 interviews with ITN members and completed two participant observations.
The ESR research activities and the main highlights so far can be listed as:
▪ Implementing vortex-based smearing correction into the coupled aeroelastic actuator line to improve blade loading and wake predictions
▪ Validation of aeroelastic actuator line method against blade resolved simulations and measurement data
▪ Investigation of the impact of the turbulent scales of the inflow on turbine wake recovery
▪ Evaluating wind farm parametrizations in mesoscale model for real and ideal situations
▪ Development of a new wind farm parameterisation in a mesoscale model
▪ Coupling of mesoscale and engineering wake models
▪ Wind speed variation mapped for offshore wind farms in northern European seas
▪ Decomposition of the coastal gradient effects from wind wakes caused by turbines for the coastal areas
▪ Further improvement for SAR wind retrieval workflow by introducing new filters to erase the anomalous pixels from scenes
▪ Investigation of turbulence structures around large offshore wind farms
▪ Analysis of momentum fluxes variation around wind farms using flight data
▪ Improving available analytical models for better wind farm performance and flow predictions
▪ Investigating the wind farm wakes and farm-to-farm interactions
▪ Investigating potential wake mitigation strategies
▪ Studying wind turbine wakes inside and after wind farms under controlled conditions
▪ Wind tunnel datasets for validation of numerical models
▪ Ultrasonic Anemometer CSAT3B interfacing with Raspberry Pi 4
▪ Ongoing 2D and 3D CFD study on down-wash generated by CRORs
▪ Development of python tool for post-processing of UAS measurements
▪ Calculation of heat fluxes in offshore wind farms from aircraft measurements
▪ Particle measurement system for use in off-shore environments
▪ Development of a mini-sized drying chamber for use with optical particle counters
▪ Preliminary testing of unmanned aerial vehicle aerosol particle measurements
▪ Development of five hole probe automated calibration system
▪ Application of multiple Reynolds number calibrations on the five hole probe for better accuracy of wind measurement
▪ Measuring wind using Multi-Copter
▪ Development of fast-response hygrometer
▪ Effect of modifying the TSR and tilt angle of upstream and downstream turbines on the overall power extraction
To observe the collaboration and knowledge/technology exchange supporting these technical activities, information scientist Train2Wind ESR has conducted 28 interviews with ITN members and completed two participant observations.
Up to now, there are no measurements of the boundary layer developing over a wind farm. Train2Wind addresses this with novel interdisciplinary measurement techniques, giving a complementary look at the effects happening in, around, behind, in front of, and especially above a large offshore wind farm. The current timeline for the campaign is set to be September 2022 and this new data will be used to improve the flow models used throughout the project, combined with the state of the art, open source V&V approaches provided by both academia and industry. The main project results expected until the end of the project are:
▪ Further improvements of individual flow models or experimental techniques (Software, Hardware)
▪ Knowledge of the entrainment process, large / “infinite” wind farm flow and mitigation measures (Knowledge, papers)
▪ Dataset of experimental campaign (Data)
▪ Knowledge of international research collaboration (Knowledge, papers)
▪ Recommendations on recovery zones / wind farm spacing (Report)
The impact of Train2Wind is two-fold: the cadre of trained fellows will transfer academic knowledge to industry, either through dissemination or through subsequent employment, and the datasets will be available for further wake model development. Using those improved models, a reduced uncertainty in the wind farm calculations translates directly into savings of financing cost, as the spread between the best estimate (“P50”) and the bank’s safety margin (“P90”) is getting smaller. This enables a low-cost no-regret route towards the EU target of 27% of renewables by 2030, as offshore wind power will be able to compete even without money transfers. Even more importantly, a positive answer to the central research question stating that there is a quite low limit to the large-scale exploitation of wind power would help Europe avoid tens of billions of euros in mis-allocated funds, as there could be “wind recovery zones” designated by Marine Spatial Planners. This would tie in with the H2020 Societal Challenge Energy, and would help to keep the current leading position of European companies in the offshore wind sector.
▪ Further improvements of individual flow models or experimental techniques (Software, Hardware)
▪ Knowledge of the entrainment process, large / “infinite” wind farm flow and mitigation measures (Knowledge, papers)
▪ Dataset of experimental campaign (Data)
▪ Knowledge of international research collaboration (Knowledge, papers)
▪ Recommendations on recovery zones / wind farm spacing (Report)
The impact of Train2Wind is two-fold: the cadre of trained fellows will transfer academic knowledge to industry, either through dissemination or through subsequent employment, and the datasets will be available for further wake model development. Using those improved models, a reduced uncertainty in the wind farm calculations translates directly into savings of financing cost, as the spread between the best estimate (“P50”) and the bank’s safety margin (“P90”) is getting smaller. This enables a low-cost no-regret route towards the EU target of 27% of renewables by 2030, as offshore wind power will be able to compete even without money transfers. Even more importantly, a positive answer to the central research question stating that there is a quite low limit to the large-scale exploitation of wind power would help Europe avoid tens of billions of euros in mis-allocated funds, as there could be “wind recovery zones” designated by Marine Spatial Planners. This would tie in with the H2020 Societal Challenge Energy, and would help to keep the current leading position of European companies in the offshore wind sector.