Speaker
Description
Energy transition is one of the great challenges for engineers in the next decades. Caused by its energy density wind turbines will be one of the major energy sources of the future. Tasks of the energy transition will not only be the pure energy production, but also the ensuring of energy supply for industrial and private consumer at any time. For economic reasons lossy energy storage through mechanical and chemical conversion will not overcome the overall problem. A possible approach will be to enhance energy producers and consumers to be more adaptive with respect to the available energy. In the case of wind turbines, this is primarily a challenge for the control of the system.
In cooperation with the wind turbine developer W2E Wind to Energy and the Institute of Automatic Control of the RWTH Aachen University in numerous projects the possibilities of Model Predictive Control are investigated since 2014. The central idea of using Model Predictive Control is to overcome the problem of contrary objectives, such as power output, structural integrity and grid support. While first studies are based on pure simulation studies using coupled multibody-simulations, the research has been focussed on field testing since 2019. From 2020 to 2024 five field tests on a 3 MW wind turbine located near Rostock (Germany) have been carried out.
As the dynamic behaviour of wind turbines can be represented in an appropriate way by coupled multibody-simulation a three-level-testing procedure has been developed for applying the Model Predictive Control to a real prototype. In the first stage the control algorithms are tested against the coupled multibody simulation building a Software-in-the-Loop-simulation. In the second stage the control algorithms are brought to the same programmable logic controller as used on the real wind turbine. The final level has been the field testing on the real wind turbine.
While the first field tests in 2020 and 2022 can be understood as a proof of concept, the field tests carried out in 2023 and 2024 showed that Model Predictive Control and ML-assisted MPC is able to control current wind turbines ensuring the structural integrity under arbitrary wind conditions. The current presentation will give hints on developing a safe testing procedure for Model Predictive Control on real wind turbines. Furthermore also aspects of field tests will be provided to the community that not worked as expected.
