Monitoring and managing transformative wind power generation through collaborative research

Special from DNV

DNV has announced two new collaborative research projects to maximise the power and integrity of offshore wind
DNV has announced two new collaborative research projects to maximise the power and integrity of offshore wind (photo: Simon Mockler)

With pressure growing from society to curtail carbon output and speed up the energy transition, industry research collaboration is now being seen as a viable solution to fast-track action for climate change and benefit all parties with greater efficiency, economic return, and a more holistic approach to business and environmental challenges.

To realise advances in the offshore wind industry, this will blend knowledge, experience, and skills from across the entire value chain. With a more cooperative and transparent approach, the aim is to ultimately drive forward investment in greener infrastructure and cleaner fuel. As global governments, industry leaders and influencers look ahead to COP26, achieving climate change as a lone entity is no longer sustainable.

DNV has recently announced a double dose of new research projects with academia, industry authorities and technology developers to improve the efficiency and effectiveness of offshore wind power generation.

Trusted data driven R&D
Working in partnership with the University of Bristol and Perceptual Robotics, an SME specialising in visual inspection of wind turbines using drones, DNV will develop an automated data processing procedure for the verification of detected wind turbine blade defects.

“With many inspections still being carried out manually, visual inspection of offshore wind turbines is expensive, labour intensive, and hazardous,” says Dr Elizabeth Traiger, a DNV Senior Researcher in the Future of Digital Assurance research program, Group Research and Development. “Automatic visual inspections can address these issues. The aim is to build trust and generate broader acceptance of automated data processing techniques across the industry and to inform future regulation.”

Unmanned autonomous and remote-controlled vehicles and drones are routinely used to conduct asset inspections in the hard to reach, extreme environments of offshore wind farms. These vehicles can collect rich and extensive data sets including high-definition video, images, geo-positioning, and sensor data, to provide integrity information about the installed structures without the need for personnel to travel to and access these dangerous locations. However, this is currently a semi-automated process with reliance on visual inspections by trained experts back onshore.

With an increasing number of installed wind turbines worldwide, including those in remote and harsh environments, the volume of inspection data is rapidly outpacing the capacity of skilled inspectors to competently review it. The initiative will address the need for fully automated processing of the data collected through machine learning algorithms and process automation.

Figure 1. Drone technology can be used as a fully autonomous blade inspection solution (photo: Perceptual Robotics)
Figure 1. Drone technology can be used as a fully autonomous blade inspection solution (photo: Perceptual Robotics)

The year-long project, which will run until April 2022, will investigate the automated verification, validation, and processing of inspection data, collected by autonomous drones, to improve inspection quality and performance. It is supported by an Innovate UK grant awarded through the Robotics for a safer world: extension competition. (Figure 1).

“This collaboration will develop and demonstrate an automated processing pipeline alongside a general framework. It should provide a stepping-stone to the growth of the automated inspection industry,” Dr Traiger adds.

As part of the project, experts in 3D computer vision and image processing from the University of Bristol’s Visual Information Lab, will create algorithms for automated localisation of inspection images and defects using SLAM and 3D tracking technology. Perceptual Robotics will perform drone inspections and create and trial AI-based models to detect defects in a commercial production environment. DNV will provide inspection expertise, verify data collected, validate the methodology and performance of the AI algorithms and provide guidance from its own and existing IEC recommend practices, regulations and industry networks.

Maximising the economic power of wind
DNV predicts that the installed capacity of floating wind would grow from 100 MW today to 250 GW in 2050, while the levelised cost of energy (LCoE) would fall to a global average of EUR 40 per MWh. This would open up deep water sites in many more countries and thereby “unlock the second phase of the energy transition”.[1] Figure 2 shows examples of floating wind turbine components.

Figure 2. Examples of floating wind turbine components (illustration: DNV)
Figure 2. Examples of floating wind turbine components (illustration: DNV)

An industry-first collaborative project, spanning the UK and US, will investigate the application of wake steering on floating offshore wind farm to assess whether this novel control strategy can have a positive impact on project costs.

As a strategic technology for turbine manufacturers, wind farm developers and operators, wake steering attempts to deflect each turbine’s wake away from downstream turbines, allowing increased overall power production and extending the life of the turbine through reduced fatigue damage (see Figure 3).

Figure 3. Schematic of the wake steering concept showing how, by yawing an upstream turbine, the wake impinging another turbine downstream can be deflected (illustration: Durham University, 2021)
Figure 3. Schematic of the wake steering concept showing how, by yawing an upstream turbine, the wake impinging another turbine downstream can be deflected (illustration: Durham University, 2021)

“There is growing interest in novel wind farm control strategies which can improve the operation of the wind farm as a whole, rather than controlling each wind turbine as if it was operating in isolation from its neighbours,” says Renzo Ruisi, Project Manager, Energy research program at DNV Group Research and Development.

“As the floating offshore wind sector develops, we need research to understand whether technology proven for onshore wind farms can also deliver good results in a more complex floating system.”

Funded by Innovate UK, and in cooperation with the US National Offshore Wind Research & Development Consortium (NOWRDC), the research, which began in June 2021 and is expected to be completed by March 2023, aims to highlight challenges and advantages of using wake steering in floating wind farms, ultimately aiming at reducing the LCoE in floating offshore wind.

Established in 2018, the National Offshore Wind Research and Development Consortium, is a not-for-profit public-private partnership focused on advancing offshore wind technology in the US through high impact research projects and cost-effective and responsible development to maximise economic benefits.

Funding for the Consortium comes from the US Department of Energy and the New York State Energy Research and Development Authority (NYSERDA), with each providing USD 20.5 million, as well as contributions from the Commonwealths of Virginia and Massachusetts and the States of Maryland and Maine, bringing total investment to approximately USD 47 million.

Figure 4: Marine Power Systems' floating platform WindSub (illustration: Marine Power Systems, 2021)
Figure 4: Marine Power Systems’ floating platform WindSub (illustration: Marine Power Systems, 2021)

Researchers from Marine Power Systems, one of the partners of the UK project team, will use their WindSub floating foundation design to simulate the effects of wake steering on a 15-MW turbine system. This platform is tensioned moored and provides a fundamentally more stable platform against which control forces can be applied, as it better resists twist compared to catenary moored platforms (illustrated in Figure 4).

In the UK, DNV, Durham University and Marine Power Systems will combine expertise on wind resource, wake modelling, wind farm control, floating platform design and economic modelling (Figure 5). While the project team in the US, led by the National Renewable Energy Laboratory (NREL), in partnership with Cornell University and Equinor, will focus on specific regions of North America with potential for offshore wind and will perform meteorological simulations and optimisation studies using wind farm control.

Figure 5. Wind speed contour plot during a time-domain simulation of the Lillgrund offshore wind farm, using DNV’s LongSim (illustration: DNV, 2021)
Figure 5. Wind speed contour plot during a time-domain simulation of the Lillgrund offshore wind farm, using DNV’s LongSim (illustration: DNV, 2021)

It is estimated that through use of this technology, an average-sized wind farm can create a gain in annual energy production above 1%, which is significant for the purpose of asset financing. A faster decrease of the LCoE for floating offshore wind technology would be desirable for the market to pick-up pace; as an example of the scale of the improvements to be made is Equinor’s Hywind Scotland, the world’s first floating offshore wind farm, which achieved a levelised cost of energy of GBP 180/MWh. [2] However, the typical LCoE of a fixed offshore wind farm in the UK is well below this at GBP 55/MWh.

Come together, right now
Like the burgeoning offshore wind sector, collaboration will also be needed in several other domains in 2021 such as increasing cost efficiency, greater standardisation, and improvements to data-driven decision-making. As the climate change agenda intensifies over the next three decades, united R&D will be at the heart of this drive to survive and thrive together in a cleaner and broader energy mix.

Dr Elizabeth Traiger, DNV Senior Researcher, Future of Digital Assurance research program, Group Research and Development
Dr Elizabeth Traiger, DNV Senior Researcher, Future of Digital Assurance research program, Group Research and Development

Dr Elizabeth Traiger has been working in the wind industry for 10 years. She currently is a Senior Researcher at DNV based in Oslo, Norway. Dr Traiger earned her doctorate in statistics at the University of Oxford and studied mathematics at the University of Kansas. She has worked on wind project development, operational assessments, due diligence, and grid integration projects throughout her career with companies worldwide. Her current research concerns advanced statistics, machine learning and predictive analytics on large data sets with a time series nature and deep learning issues in computer vision. Her passion is technology transfer, helping to increase the reliability of renewables in the energy mix.

Renzo Ruisi, DNV Researcher & Project Manager, Energy research program, Group Research and Development
Renzo Ruisi, DNV Researcher & Project Manager, Energy research program, Group Research and Development

Renzo Ruisi has a Master’s in Aerospace Engineering and has worked at DNV for the last seven years. His focus over the past 3 years has been on wind farm control and engineering wake modelling. His previous experience in the industry involves energy production and site conditions assessments, as well as CFD resource modelling for onshore sites in many industry markets. Ruisi has been involved in several EU-funded Horizon-2020 projects focused on wind farm control, CL-Windcon, TotalControl and Farmconners, and is now leading the CONFLOWS project, assessing the effects of wake steering on floating wind farms.