Both onshore and offshore wind turbines are placed and operated in wind farms to reduce the necessary infrastructure and related costs. In a wind farm, it is inevitable that wake interactions take place due to the relative proximity between machines. Wind turbines in the wake of another turbine experience a wind field with a lower average wind speed and higher turbulence intensity, causing a decrease in the available energy, while increasing mechanical loads.
Wake interactions and their effect on power production and fatigue loading are usually taken into account during wind farm planning, design and commissioning, for example by fine-tuning turbine placements and controller settings. Commercial wind farms are typically operated to control loads, power production and lifetime at an individual turbine level. Thus, each turbine is controlled independently based on locally available measurements to optimize its own performance.
However, there is still much unleveraged potential at a wind farm level, in particular for large-scale onshore and offshore farms, with regard to overall operational optimization by taking into account all available data across the farm as well as farm-level interactions between turbines.
Several strategies have already been proposed to optimize the overall power output of a wind farm. These are mainly open-loop strategies, whose potential for success is extremely dependent on the accuracy of the model used for its design.
CL-Windcon will take farm-level controls from the current non-existing or basic static approach to dynamic open and closed-loop control strategies. Dynamic closed-loop wind farm control will be capable of dealing with both time-varying inflow conditions and model mismatch/uncertainties, thereby removing important technological barriers.
In particular, the project will use a cooperative wind farm and wind turbine closed-loop control paradigm which treats the entire wind farm as a comprehensive real-time optimization problem. This approach will combine measurement data and more precise dynamic flow field models, and will incorporate a balance between energy production, loads, lifetime and O&M costs, aimed at minimizing lifetime LCoE. CL-Windcon’s ambition is not only to modify the way wind farms are operated nowadays, but also how they will be designed in the coming future.
The main control enabling technologies developed within the project will be:
· Axial induction control, in which some of the turbines upstream within a farm will lower their energy capture thereby increasing the wind velocity and reducing the turbulence downstream.
· Wake redirection, in which some of the turbines within a wind farm will redirect their wakes to reduce the wake effects on other turbines further downstream.
· Supporting wind farm control technologies for further load mitigation.