Efficient power monitoring with dynamic power curve
Stochastic methods provide a broad range of analysis for an environment characterized by an incoming turbulence. In collaboration with ForWind at the university of Oldenburg, Fraunhofer IWES promotes these methods, e.g. CTRW wind field model, continuous time random walk model as well as the dynamic power curve for power monitoring. A main method is the analyses of noise profiles. Different sources of noise and deterministic dynamics can be separated in a signal. This process can be applied on all kinds of data, which are influenced by deterministic and random parts.
The dynamic power curve is a quick and cost effective method to monitor the power output of wind turbines and whole wind farms. The software is based on stochastic examination method, which enables the user to determine a turbine´s power curve in only a few days by using hub anemometer and power output data. The generated data provide an overview of the wind turbine functionality for manufacturers, operators, service companies and public utilities. Deviating behavior of same type turbines is reliably detected, so that improvements of turbines and wind farms result in a reduction of yield losses.