Wind turbine aeroelasticity
Large off-shore wind turbines present new challenges to their design, from their extreme strength requirements on their foundations to the very high speed of the wing tips. We are mainly concerned with the computational methods for the assessment of aeroelastic effects on rotors and turbines with very long (over 100m) flexible composite blades, in the integration of active load control mechanisms that improve performance and increase fatigue life. We seek innovative numerical solutions and modelling strategies to address challenging engineering problems, such as the efficient stabilization of floating wind turbines or physics-based description of dynamic loads in a wind farm environment. This links our developments in computational physics at the most fundamental level to real applications where our technologies can prove their worth.
Sponsors of our research in this area include EPSRC, the European Commission, the National Research Foundation, Singapore, and the Spanish National Centre for Renewable Energy (CENER).
HPCWE (High-Performance Computing in Wind Energy)
At almost every stage in wind energy exploitation ranging from wind turbine design, wind resource assessment to wind farm layout and operations, the application of HPC is a must. The goal of HPCWE is to address the key open challenges in applying HPC on wind energy, including efficient use of HPC resources in wind turbine simulations, accurate integration of meso- and micro-scale simulations, and optimization. We are members of a 13-partner consortium representing top academic institutes, HPC centres and industries in Europe and Brazil. The consortium will develop novel algorithms, implement them in state-of-the-art codes and test the new software in academic and industrial cases.
CONFLEX (Control of Flexible Structures and Fluid-Structure Interactions)
ConFlex is a new EC Marie Curie training network on advanced methods for control of structures and fluid-structure interactions, involving 10 universities and several affiliated institutions. For more details of the projects, please go to the CONFLEX website.
FENGBO-WIND (Farming the ENvironment into the Grid: Big data in Offshore Wind)
This project is developing a computational simulation approach capable of handling the complex interactions between the local atmosphere, farm aerodynamics, and turbine response 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. Those will be investigated within the context of the development of offshore farms off the Chinese coast, which brings particular challenges regarding coastal characteristics and extreme events (in particular typhoons). More information at Imperial's Energy Future Lab FENGBO-WIND webpage.
MAXFARM (MAXimizing wind Farm Aerodynamic Resource via advanced Modelling)
This project aims to investigate the non-stationary aerodynamic field in offshore wind farms using numerical methods, wind tunnel tests, and satellite imagery. It is one of the EPSRC Supergen Wind Grand Challenges, where we are part of a consortium of leading UK research centres in wind energy. Imperial's efforts are mostly in investigating how the improved knowledge of the farm aerodynamics cascades into better estimations of the loading on the wind turbines and identifying control strategies to improve performance.
Aeroelasticity of deformable wind-turbine airfoils in stalled conditions (2010-2017)
Main investigator: Alvaro Gonzalez
In this project we developed aeroelastic analysis process for deformable aerofoils or blade sections, including attached and separated flow and dynamic stall phenomena. We sought in particular computationally-efficient solutions to assist in trade-off studies on airfoil design and trailing-edge actuation and demonstrated them against canonical test cases from the literature in dynamic stall as well recently-available experimental data on wind turbine airfoils. The project was a collaboration with CENER.
Model-based aeroservoelastic design and load alleviation of large wind turbines (2010-14)
Main investigator: Bing Feng Ng (link to PhD thesis)
This project developed an aeroservoelastic modelling approach for dynamic load alleviation in large wind turbines with trailing-edge aerodynamic surfaces. Time-domain aerodynamics are given by a linearised three-dimensional unsteady vortex-lattice method that allows better characterisation of aeroelastic responses under attached flow conditions and the direct modelling of lifting surfaces. The resulting unsteady aerodynamics is written in a state-space formulation suitable for model reductions and controller design, which does not rely on empirical corrections commonly found in Blade Element Momentum methods. Structural modules of the tower, potentially on a moving base, and the rotating blades are modelled using geometrically non-linear composite beams, which are linearised around reference conditions that have undergone arbitrarily-large structural displacements. This provided higher-fidelity efficient numerical models for linear robust controller design (LQG and Hinf), to achieve load alleviation in larger and more flexible wind turbines. The land-based NREL 5MW reference wind turbine is chosen to demonstrate the unified aeroservoelastic analysis framework.
Multiscale Analysis of Slender Composite Wings (2009-2014)
Main investigators: Julian Dizy (link to PhD thesis)
This project aimed at bridging the gap between the detailed information of geometric and material properties required for stress analyses on advanced composite blades and the low-order description required for the estimation of dynamic loads under actual operating conditions. It developed methods for homogenisation of periodic slender composite structures and demonstrated impressive gains in numerical efficiency against full 3-D simulations of the full structure.