FENGBO-WIND - Farming the ENvironment into the Grid: Big data in Offshore Wind
Lead Research Organisation:
Imperial College London
Department Name: Aeronautics
Abstract
The proposed project will develop an integrated computational simulation approach capable of handling the complex interactions between the local atmosphere, the coastal ocean and sedimentary environment, farm aerodynamics, turbine response and grid integration in offshore wind farms. This will target a substantial reduction in the cost of energy in offshore wind by exploiting: high-fidelity optimization of array design and operation, tailored to a specific site and able to deal with realistic marine atmospheric boundary layer conditions, in particular the very slow dissipation of rotor wakes; combined with big-data analysis of very-large-scale simulations of the whole system under extreme conditions, to minimize integrity risks without overly conservative safety factors. Both situations will be investigated within the context of the development of offshore farms off the Chinese coast, which brings particular challenges regarding coastal characteristics (e.g. high sediment concentrations) and extreme events (in particular typhoons).
To achieve this we propose a multiscale approach to wind farm design and network integration that considers, first, a more accurate characterisation of extreme events (and active mitigation strategies) in the analysis through highly-resolved computer simulation; second, new optimization techniques for the design and operation of wind farms that allow for sustained power extraction using relevant knowledge of both the marine atmosphere and individual turbine (aeroservoelastic) dynamics; and third, robust grid design and operation strategies that accommodate wind resource variability and maximise the sustainability of energy generation. FENGBO-WIND will carry out the most ambitious computer simulations to date on farm dynamics and farm/environment interaction, to build physics-based predictive capabilities on farm output and investigate long-term interactions between farms and their local environment.
An interdisciplinary consortium of experts, including Earth/environmental scientists, civil and electrical engineers, and fluid dynamicists, have been assembled to tackle this challenging computational problem. The team will have access to (1) the world's largest supercomputer (Sunway TaihuLight) to carry out full system simulations of energy output and farm state for specific environmental scenarios, (2) operational data from existing wind farms off the Chinese coast as well as conditions at a target site through a partnership with a local grid company, and (3) performance data for a state-of-the-art wind turbine design from the leading Chinese manufacturer. The results will be benchmarked against state-of-the-art industrial design tools and protocols for grid integration for offshore wind farms.
To achieve this we propose a multiscale approach to wind farm design and network integration that considers, first, a more accurate characterisation of extreme events (and active mitigation strategies) in the analysis through highly-resolved computer simulation; second, new optimization techniques for the design and operation of wind farms that allow for sustained power extraction using relevant knowledge of both the marine atmosphere and individual turbine (aeroservoelastic) dynamics; and third, robust grid design and operation strategies that accommodate wind resource variability and maximise the sustainability of energy generation. FENGBO-WIND will carry out the most ambitious computer simulations to date on farm dynamics and farm/environment interaction, to build physics-based predictive capabilities on farm output and investigate long-term interactions between farms and their local environment.
An interdisciplinary consortium of experts, including Earth/environmental scientists, civil and electrical engineers, and fluid dynamicists, have been assembled to tackle this challenging computational problem. The team will have access to (1) the world's largest supercomputer (Sunway TaihuLight) to carry out full system simulations of energy output and farm state for specific environmental scenarios, (2) operational data from existing wind farms off the Chinese coast as well as conditions at a target site through a partnership with a local grid company, and (3) performance data for a state-of-the-art wind turbine design from the leading Chinese manufacturer. The results will be benchmarked against state-of-the-art industrial design tools and protocols for grid integration for offshore wind farms.
Planned Impact
Offshore wind farms tap into an abundant source of renewable energy and can be scaled up in size (both farm size and number). Their location at sea does not place additional pressures on the use of land, although their environmental impacts at local and regional scales needs to be carefully assessed. They will undoubtedly play a very important role in the decarbonization of the energy mix required to avoid global warming, yet they are still relative expensive compared to other sources of energy.
The research in this project targets directly the reduction in the cost of offshore wind energy by developing the design tools and knowledge required to build and operate more efficient wind farms. This will have a direct economic impact by making wind energy more competitive, while increasing energy independence will benefit local economies. It will further have a societal impact by facilitating the expansion of a clean source of energy in an environmentally sympathetic manner, and in doing so it will expand our knowledge regarding the interactions between the wind farm and its local environment.
The FENGBO-WIND project will specifically target these issues in the context of the further development of offshore wind energy in China. It will produce the most detailed predictions to date of the future interactions between large farms and the local marine environment in coastal areas, with the high sediment concentrations that are characteristic of the East China Sea, while also constructing high-resolution simulations of the impact of typhoons on wind farms. The high-resolution simulations will be further used to build new performance forecasting strategies. The combination of this will provide new knowledge and tools to the local wind operators, while assessing the potential long-term impact on the local environment. It will also contribute to the formation of a more skilled workforce in both research skills and application to wind energy.
To maximize its impact, the project has been designed in close collaboration with energy operators, wind manufactures, policy institutes and marine research centres in China, as well with expert wind consultancies in the UK. This will ensure the relevance of the studies from the point of view of the Chinese wind energy industry, as well as of the conservation of the marine environment. While the solutions may focus on particular case studies, the methods will as much as possible address the more general problem, and many solutions will be applicable elsewhere. To facilitate this, all the software tools developed in the project are and will remain open source and will be developed using the highest best-practice standards in software development. This will stimulate the wider adoption of the new solution methods, both for further development by the research community and for application to specific site studies by wind farm design offices.
The research in this project targets directly the reduction in the cost of offshore wind energy by developing the design tools and knowledge required to build and operate more efficient wind farms. This will have a direct economic impact by making wind energy more competitive, while increasing energy independence will benefit local economies. It will further have a societal impact by facilitating the expansion of a clean source of energy in an environmentally sympathetic manner, and in doing so it will expand our knowledge regarding the interactions between the wind farm and its local environment.
The FENGBO-WIND project will specifically target these issues in the context of the further development of offshore wind energy in China. It will produce the most detailed predictions to date of the future interactions between large farms and the local marine environment in coastal areas, with the high sediment concentrations that are characteristic of the East China Sea, while also constructing high-resolution simulations of the impact of typhoons on wind farms. The high-resolution simulations will be further used to build new performance forecasting strategies. The combination of this will provide new knowledge and tools to the local wind operators, while assessing the potential long-term impact on the local environment. It will also contribute to the formation of a more skilled workforce in both research skills and application to wind energy.
To maximize its impact, the project has been designed in close collaboration with energy operators, wind manufactures, policy institutes and marine research centres in China, as well with expert wind consultancies in the UK. This will ensure the relevance of the studies from the point of view of the Chinese wind energy industry, as well as of the conservation of the marine environment. While the solutions may focus on particular case studies, the methods will as much as possible address the more general problem, and many solutions will be applicable elsewhere. To facilitate this, all the software tools developed in the project are and will remain open source and will be developed using the highest best-practice standards in software development. This will stimulate the wider adoption of the new solution methods, both for further development by the research community and for application to specific site studies by wind farm design offices.
Publications
Artola M
(2021)
Generalized Kelvin-Voigt Damping for Geometrically Nonlinear Beams
in AIAA Journal
Bartholomew P
(2020)
Xcompact3D: An open-source framework for solving turbulence problems on a Cartesian mesh
in SoftwareX
Burton Tony L.
(2021)
Wind Energy Handbook
Chen K
(2021)
Wake-effect aware optimal online control of wind farms: An explicit solution
in IET Renewable Power Generation
Clare M
(2021)
Hydro-morphodynamics 2D modelling using a discontinuous Galerkin discretisation
in Computers & Geosciences
Clare M
(2022)
Assessing erosion and flood risk in the coastal zone through the application of multilevel Monte Carlo methods
in Coastal Engineering
Clare M
(2022)
Calibration, inversion and sensitivity analysis for hydro-morphodynamic models through the application of adjoint methods
in Computers & Geosciences
Clare M
(2022)
Multilevel multifidelity Monte Carlo methods for assessing uncertainty in coastal flooding
in Natural Hazards and Earth System Sciences
Description | We have developed a suite of computational tools to simulate and predict the flow fields of wind-farms with an emphasis on offshore. We have built the methodological framework to carry out these high-resolution computational simulations at both wind turbine blade and farm level, optimization of the blade geometry and farm layout, and optimization of operations. The common thread has been the development of state-of-the-art computational tools for design and analysis in offshore wind. For design optimization we have used computationally-efficient methods for evaluation of design derivatives on large models of blades or farms. Candidate farm layouts have been explored using highly resolved simulations obtained in one of the world's largest supercomputers. The large amounts of data obtained from those simulations have been then used to inform machine learning strategies that identify the optimal operation of the farm for varying wind conditions. As a result, we have a suite of analysis methods to support the development of next-generation large-scale offshore wind farms. |
Exploitation Route | These findings can be used by Academia or other researchers. All our aerodynamic tools are available as open source. |
Sectors | Energy |
URL | https://www.ukchn-core.com/project/fengbo-wind/ |
Description | Collaboration with the Technical University of Munich |
Organisation | Technical University of Munich |
Country | Germany |
Sector | Academic/University |
PI Contribution | Essential code-to-code verification exercise for simulation of wind farms. |
Collaborator Contribution | Essential code-to-code verification exercise for simulation of wind farms. |
Impact | Joint publication in the upcoming Torque conference (https://www.torque2020.org/), the leading European conference in wind energy. |
Start Year | 2019 |
Title | SU2: The open-source CFD software |
Description | SU2 is one of the leading open-source fluid dynamic solvers for aerospace applications. Most of the fluid-structure interaction capabilities have been developed at Imperial, including adjoints for design, and the architecture for simultaneus aerodynamic shape and structural topology optimization. Our contributions started to appear in the official distribution from version 4 of the software and have grown to include also new parallelization strategies, preconditioners for unsteady low-Mach solutions and sparse linear algebra libraries. |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | SU2 has a very large user base, with over 100k downloads as of January 2017. Users include aircraft companies, start-up, and students from all over the world. Our contribution expands the range of available simulation and it is currently being tested at Boeing to support wind design. |
URL | https://su2code.github.io/ |