Abstract

Due to the growing penetration of renewables, Wind Turbines (WT) are becoming increasingly crucial for grid balancing services, such as Frequency Containment Reserve (FCR). This study proposes an adaptive operational strategy that optimally accommodates the power reserve and controls the active power based on grid frequency uncertainties and stochastic wind variations. The proposed approach includes an end-to-end solution, considering fixed and percentage reserve methods, from estimating an appropriate reserve margin to the real-time computation of generator torque and pitch control setpoints in response to grid frequency variations. A real-time look-up table is incorporated to actively adjust the reserve and adapt the deloading rotor speed-power curve based on a short-term estimation of the grid frequency using a deep-learning technique. Applying the proposed strategy improves WTs’ FCR contribution by at least 3.3 times reserve in MW. Moreover, adaptive fuzzy-PI pitch-torque controllers are suggested to enhance the WT dynamic response and ensure smooth provision of FCR. Simulation results of a 5 MW-NREL offshore model show the improvement of the fuzzy-PI in power reference tracking, rotor speed regulation, and average studied mechanical load parameters in the range of 2.14–11.69%, 11.1%, and 8.81%, respectively, for an average of 250 kW reserve, confirming an overall improvement.

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