ERC - Johan Meyers
Active Wind Farms: Optimization and Control of Atmospheric Energy Extraction in Gigawatt Wind Farms
With the recognition that wind energy will become an important contributor to the world’s energy portfolio, wind farms are expected to cover increasingly large surface areas. Currently, several wind farms with a total capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and meteorology. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case.
The major ambition of the ERC grant ActiveWindFarms is to employ optimal control techniques to control the interaction between large wind farms and the atmospheric boundary layer. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. Hence, wind-farms may not only be designed to optimally react to the turbulent atmosphere, but can be employed to actively control the conditions in the atmosphere with the objective to increase power output and reduce costs. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented.
To this end, ActiveWindFarms focuses on the development of optimal control techniques that are combined with time-resolved three-dimensional turbulent-flow simulations of wind-farm ABL interaction, and multi-scale turbine models. Simulations are performed on supercomputing platforms. Next to that, one task of the project concentrates on experimental wind-tunnel validation of optimal turbine placement and turbine-control strategies resulting from simulations.