FlexiWind: Modeling of virtual offshore wind farms for flexible operation and for load and performance optimization

At a glance

• At present, the primary goal of the control of wind farms is to maximize the yield over the lifespan of 20–25 years.
• A flexible, data-driven operating strategy could enable grid support, optimized turbine operation, and predictive maintenance.
• In the FlexiWind project, the project partners are employing a digital twin to develop precisely this kind of control system for a real wind farm.
• Fraunhofer IWES, the project coordinator, is responsible among other things for the development and validation of the digital twin.

The challenge

At present, wind farms are generally operated with the goal of optimizing the yield over the 20–25 year lifespan. Data-based, flexible control of individual turbines and the whole farm would offer a range of advantages. It has the potential to reduce the operating and maintenance costs along with the electricity production costs while making the same contribution to grid stability overall, thus rendering wind energy more competitive.

Among other factors, this is because the turbines could be controlled according to their load at the specific site. Wind turbines are subjected to highly variable loads within a wind farm. Said loads can only be considered in the design of the turbine in a standardized manner, as they depend heavily on the location of the turbine and the interactions among the turbines. A flexible control system considering these loads could not only extend the lifespan but also establish a predictive maintenance concept focusing on the condition of the components in the turbines. In addition, it enables grid-supporting operation and the provision of important grid services such as balancing power.

The solution

This is where the FlexiWind research project comes in. The project partners are researching the potential and influence of flexible control strategies on wind turbines and farms. The aim is to be able to respond to changing environmental conditions with the direct application of such strategies to wind farms and the associated dynamic adaptation of the wind farm’s operating state. This is to be implemented in a real-time capable simulation environment. The models will be validated with data from a real wind farm operated by one of the project partners and data from the RAVE research initiative. The final result will be a realistic assessment of the financial and technical potential of a flexible wind turbine and farm control system.

The added value

Fraunhofer IWES, the project coordinator, is responsible among other things for setting up a real-time capable simulation platform, the flow models of wind farms, and the modeling of the wind farm and wind turbine aeroelastics.