A reliable determination of the loads requires a relatively high measurement effort and is therefore carried out only on individual plants. For most installations there is no data available on their loads history. To overcome this problem, Nicolai Cosack develops and evaluates methods for "Fatigue Load Monitoring with Standard Wind Turbine Signals". On the basis of standard signals of a Multibrid M5000 like energy yield, rotational speed, pitch angle and tower head vibrations methods are being developed that allow to deduce the loads status via regression analysis and neural networks. The data will be validated using different types of turbines. For this extremely cost efficient method a broad range of applications is conceivable. Those could be a site specific optimisation of operation and yield as well as precautionary operation and maintenance strategies.
In her research on „Online Load Monitoring of Wind Turbines for Advanced Control and Optimized Operation", Ursula Smolka connects load monitoring and control. Innovative control methods like individual pitch demand extremely reliable loads measurements of e.g. bending of blades and tower in real-time. Robust industrial sensors are chosen and tested. Methods for measurement and analysis are developed that allow a continuous monitoring of load measurements with error compensation. A further application aims at the use of the loads data for a reduction of loads with simultaneous yield optimisation.

New control strategies place higher demands on the pitch mechanism. To address the issues involved, Stefan Baehr works on "Dynamics & Design of Pitch Systems Employing Different Control Concepts". He validates models of electrical and hydraulic systems, the control algorithms and sensor systems by using hardware-on-the-loop simulation and field tests.
At present, a number of uncertainties are tied to the dimensioning of pitch systems. Those should be reduced employing conventional control strategies as well as individual pitch control. In addition, the effects of load reducing control concepts on the components and the profitability of the wind energy plant shall be analysed. This work is conducted in close cooperation with the industry.

Those projects are complemented by the research of David Schlipf who follows with "Model Predictive Control of Wind Turbines with LiDAR Wind Measurements" a completely different approach. Present approaches adapt to changing conditions only after their effects on the turbine, such as the change of rotational speed of the rotor and load changes, are measured. This delay in the adaptation to environmental conditions results in both, reduced yields and increased loads on the components. Using LiDAR, the changing environmental conditions shall be factored in at the moment they arrive at the plant with minimal use of the control system. LiDAR technology is still fairly expensive and not completely reliable, but extremely promising with respect to the expected advantages. Thus the technology shall be improved and control strategies shall be developed and tested numerically and experimentally.