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Correlated power time series of individual wind turbines: A data driven model approach
Wind farms can be regarded as complex systems that are, on the one hand, coupled to the nonlinear, stochastic characteristics of weather and, on the other hand, strongly influenced by supervisory control mechanisms. One crucial problem in this context today is the predictability of wind energy as an intermittent renewable resource with additional non-stationary nature. In this context, we analyze the power time series measured in an offshore wind farm for a total period of one year with a time resolution of 10 min. Applying detrended fluctuation analysis, we characterize the autocorrelation of power time series and find a Hurst exponent in the persistent regime with crossover behavior. To enrich the modeling perspective of complex large wind energy systems, we develop a stochastic reduced-form model of power time series. The observed transitions between two dominating power generation phases are reflected by a bistable deterministic component, while correlated stochastic fluctuations account for the identified persistence. The model succeeds to qualitatively reproduce several empirical characteristics such as the autocorrelation function and the bimodal probability density function. © 2020 Author(s).
Pressure-based lift estimation and its application to feedforward load control employing trailing-edge flaps
This experimental load control study presents results of an active trailing-edge flap feedforward controller for wind turbine applications. The controller input is derived from pressure-based lift estimation methods that rely either on a quasi-steady method, based on a three-hole probe, or on an unsteady method that is based on three selected surface pressure ports. Furthermore, a standard feedback controller, based on force balance measurements, is compared to the feedforward control. A Clark-Y airfoil is employed for the wing that is equipped with a trailing-edge flap of chordwise extension. Inflow disturbances are created by a two-dimensional active grid. The Reynolds number is Re=290 000, and reduced frequencies of k=0.07 up to k=0.32 are analyzed. Within the first part of the paper, the lift estimation methods are compared. The surface-pressure-based method shows generally more accurate results, whereas the three-hole probe estimate overpredicts the lift amplitudes with increasing frequencies. Nonetheless, employing the latter as input to the feedforward controller is more promising as a beneficial phase lead is introduced by this method. A successful load alleviation was achieved up to reduced frequencies of k=0.192.