Abstract
The use of state estimation technique offers a means of estimating the effective wind speed based solely upon the measurements of the turbine. Such wind speed estimations are crucial for turbines to calculate the reserved power for ancillary services. Nonetheless, the system observability or the possibility of estimating the wind speed is influenced by various down-regulation strategies. Thus, this paper investigates the system observabilities of turbines in different down-regulating conditions via the use of the empirical observability Gramian. In addition, wind speed estimators are constructed for each control strategy using an extended Kalman filter approach. Subsequently, each estimation performance is evaluated from the assessments of the Gramians and high-fidelity turbine simulations. The results reveal that it is more difficult to reconstruct the wind estimate from measurements of the turbine operating in torque-based than rotor-speed-based down-regulation strategies.
Highlights
Down-regulation is essential for modern large wind turbines and is important in a wind farm
The knowledge of the wind speed is crucial to estimating the level of the power reserve for the wind turbine providing the ancillary services
An increasing number of studies used the concept of model-based state estimation for reconstructing the effective wind speed in normal operation (e.g. [4, 5])
Summary
Down-regulation is essential for modern large wind turbines and is important in a wind farm. Participation in ancillary services requires the turbine to maintain the proper power flow of the grid by providing the additional reserved power if needed. Such reserved power is calculated based on the difference between the instantaneous power generated by the turbine and the available power from the wind. Published under licence by IOP Publishing Ltd of some turbine components and noise reduction [9] Such various de-rating strategies inevitably influence the system observability. The system observabilities of turbines with various down-regulation control strategies are investigated via the use of the empirical observability Gramian, revealing under what de-rating strategies, the degree of estimating the wind speed is the worst.
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