ArcVera Renewables’ Post

Deepwater divers who monitor and maintain underwater transmission lines and cables for #offshorewind turbines face hazards such as subfreezing temperatures, low visibility, jellyfish and sharks. A new project at The #UniversityofTexas at #Dallas' Wind Energy Center, known as UTD Wind, is designed to make the divers' jobs safer through the development of remote-monitoring technology for offshore wind farms. The project, which began in March, expands UTD Wind research into a new area focusing on safety. Researchers will develop digital twins, or virtual models, to simulate #windturbines, and #algorithms to extract information about failures from simulation data. "We're focusing on something very important: safety. In every industry, you want zero accidents," said Dr. Mario Rotea, professor of mechanical engineering in the Erik Jonsson School of Engineering and Computer Science and principal investigator. "We're working to develop technology to reduce human exposure to hazardous conditions in the ocean environment." Working with Rotea are co-principal investigators Dr. Todd Griffith, professor of mechanical engineering, and Dr. Jie Zhang, associate professor of mechanical engineering. The UTD researchers are working with collaborators from NEC Laboratories America and Texas A&M University. There are two types of offshore wind turbines: fixed platform and floating platform. Fixed platform turbines are built closer to the coast in more shallow water, while floating platform turbines can be miles from the coast, with cables and mooring lines connected to a seabed more than 100 feet below sea level. The power transmission lines connect to a transmission center, which transfers power to the #electricalgrid. The water can be as deep as 200 feet. Fixed and floating wind turbine platforms pose risks to personnel and vessels that are not seen at wind power projects on land, Rotea said. "If we can use technology to provide early warnings and prevent a diver from having to inspect an underwater cable, that would be excellent," said Rotea, who is also the director of UTD Wind. The researchers' goal is to place sensors in accessible locations to detect damage and transmit early alarms about any problems. The technology will provide information about the conditions and improve safety for offshore wind energy personnel if they need to intervene, Rotea said. In 2023, wind energy represented nearly 29% of energy generation in Texas, which has more wind turbines—15,300—than any state in the country, according to the state comptroller's office.

Available now (open access): Assessing some statistical and physical modelling uncertainties of extreme responses for monopile-based offshore wind turbines, using metocean contours As a part of the WAS-XL project, in collaboration with Erin Bachynski-Polić and Sverre K. Haver, we present the results of a comparative study that evaluates some statistical and physical load modelling uncertainties, when estimating long-term extreme responses for large-diameter offshore wind turbines. - How do different probabilistic models of metocean parameters affect the contours and extreme responses? - How does seed variability impact extreme values compared to the choice of probabilistic models? - What is the relative importance using state-of-the-art load models versus common approaches in estimating extremes, compared to statistical uncertainties? Explore more here: https://lnkd.in/dC_U9TBZ #OffshoreWindTurbines #RenewableEnergy

Hydrogen production analysis carried out on North Sea wind turbines. By Edward Laity H2SEA and the Delft University of Technology have carried out a structural assessment on offshore hydrogen wind turbine generators (WTG) in the North Sea. The project assessed monopile-based support structures for the offshore WTGs’ to see whether it was structurally feasible to perform hydrogen production. The research aimed to define the differences in support structure geometry and assess the changes in the design of methodology of an offshore wind turbine support structure, such as a decentralised hydrogen production platform. For future developments, a 15MW reference turbine was selected for a water depth of 45m in the North Sea. To understand the platform mass, dimensions, and rotational inertia were selected, listed and the optimised platform layout and mass estimations were made by the Dutch university and H2SEA. The design of the platform support beams, gravitational loads, and extreme wind gust loads were also considered, whilst the selection of the support structure concept was performed using a multi-criteria analysis. For fatigue assessment, an analytical fully dynamical model was constructed in Maple, which was then simulated by the equations of motions, including airy wave force, rotor damping, topside and platform mass and rotational inertia, embedded length, and homogeneous soil stiffness. The maple model simulated the dynamic behaviour of both structures and determined the first and second natural frequency and present displacements. A fatigue damage calculation including 500 combinations of wave height and period will be performed for a 25-year lifetime. https://lnkd.in/dVzd_9sf

This quick read offers valuable insights into the potential of AI in the renewable energy industry and how Machine Learning can provide fast and reliable turbine interaction modeling for the biggest wind farms.

This quick read offers valuable insights into the potential of AI in the renewable energy industry and how Machine Learning can provide fast and reliable turbine interaction modeling for the biggest wind farms.

Thrilled to share a milestone in our journey towards advancing wind energy technologies. Our latest paper, “Developing a digital twin framework for wind tunnel testing: validation of turbulent inflow and airfoil load applications,” represents a step forward in our collective understanding of wind turbine efficiency in the face of atmospheric turbulence. In this work, we've explored the integration of digital twin technology with wind tunnel testing to better simulate and understand the turbulent inflows impacting wind turbines. Our approach, focusing on the Taylor micro-scale within RANS simulations, has shown promising alignment with real-world data, a small but significant step towards improving the accuracy of wind turbine testing. The validation of our models against physical experiments, especially in replicating airfoil load dynamics, offers a glimpse into the potential of digital twins in enhancing renewable energy technologies. I look forward to the discussions and developments this research might spark in our ongoing quest for sustainable energy solutions. Special thanks to my mentors: Caroline Braud, Ingrid Neunaber, and Emmnuel Guilmineau. #WindEnergy #windenergysciencejournal #EAWE #RenewableEnergy #DigitalTwin #cnrs #ntnu #centrale_nantes #anr #MOMENTA

See our recently published Tidal Turbine Benchmark CFD Simulation. Cape Horn Engineering participated in The Tidal Turbine Benchmarking Project, conducted and funded by the UK’s EPSRC1 and Supergen ORE Hub2. The main objective of this benchmark study is to mitigate climate change by accelerating the development of tidal technolo- gies and harnessing the untapped potential of Offshore Renewable Energy. To achieve this goal, the benchmark study aims to reduce conservatism in the design of tidal turbines by addressing the modelling uncertainty and by validating engineering methods with good-quality experimental data. The project was an excellent opportunity for Cape Horn Engineering to participate in a blind validation study to demonstrate our specialist technologies and capabilities to assist companies in exploring less carbon-intensive and more sustainable energy systems. According to the paper presented by the organisers of the benchmark to the European Wave and Tidal Energy Conference 2023, ”The solutions of CHE-BR-uRANS were found to be very effective with a significantly lower cell count compared to other methods, whilst returning some of the most accurate solutions”. All simulations were performed with the code STAR-CCM+ from Siemens Digital Industries. For more details, see our case study:  https://lnkd.in/etkH2K2N #navalarchitecture #navalarchitect #designengineering #marineengineering #design #optimization #cfd #computationalfluiddynamics #engineering #optimisation #optimization #efficiency #renewableenergy #renewables #renewablesindustry #tidalenergy #tidal #performanceoptimization

We are pleased to inform you that we have lots of new published contents online: Enjoy reading through the newest article.   This week we have the following article online:   1. Field-data-based validation of an aero-servo-elastic solver for high-fidelity large-eddy simulations of industrial wind turbines 2. Nonlinear vibration characteristics of virtual mass systems for wind turbine blade fatigue testing 3. Towards real-time optimal control of wind farms using large-eddy simulations 4. Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 1: Large-eddy-simulation study 5. Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 2: Analytical modelling 6. Drivers for optimum sizing of wind turbines for offshore wind farms 7. Sensitivity of cross-sectional compliance to manufacturing tolerances for wind turbine blades 8. Active trailing edge flap system fault detection via machine learning 9. Influence of rotor blade flexibility on the near-wake behavior of the NREL 5 MW wind turbine Here the corresponding links to read the full article: 1.   https://lnkd.in/gHRrbecQ 2.  https://lnkd.in/gBPdrQgH 3.  https://lnkd.in/gzXYWwdf 4.   https://lnkd.in/giEW6GeE 5.  https://lnkd.in/gSBQYHpU 6.   https://lnkd.in/gmEJaGa3 7.  https://lnkd.in/gAQkAWMG 8.  https://lnkd.in/gq_t7gN4   9.   https://lnkd.in/gw55-5Ww A big thanks to all the authors and reviewers for their great effort and support. For more information, and to submit your new manuscript, visit us at the WES Journal website: https://lnkd.in/dfDVqGv7 #windenergy #windenergyresearch #research #journal #windenergysciencejournal #futurewind #papers #publications #wind #EAWE #sustainableenergy #renewableenergy #openaccessjournal #impactfactor

We are pleased to inform that we have new published contents online: Enjoy reading through the latest articles:   1. Experimental validation of a short-term damping estimation method for wind turbines in nonstationary operating conditions 2. OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures 3. Control co-design optimization of floating offshore wind turbines with tuned liquid multi-column dampers Here the corresponding links to read the full article: 1. https://lnkd.in/gREzpdJm 2. https://lnkd.in/gSW2rbfn   3. https://lnkd.in/gcPdbg7W A big thanks to all the authors and reviewers for their great effort and support. For more information, and to submit your new manuscript, visit us at the WES Journal website: https://lnkd.in/dfDVqGv7 #windenergy #windenergyresearch #research #journal #windenergysciencejournal #futurewind #papers #publications #wind #EAWE #sustainableenergy #renewableenergy #openaccessjournal #impactfactor