Real-Time Estimation Methods for the Frequency Support Function Based on a Virtual Wind Turbine

Bo-Hyun Woo, Ye-Chan Kim and Seung-Ho Song ()
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Bo-Hyun Woo: Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea
Ye-Chan Kim: Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea
Seung-Ho Song: Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea

Energies, 2025, vol. 18, issue 11, 1-16

Abstract: With the increasing penetration of renewable energy sources, reduced system inertia and weakened frequency regulation capability have emerged as critical issues in power systems. As a result, wind turbines are now required to provide frequency support functions. To enable accurate analysis of the operational characteristics of wind turbines equipped with such control functions, this study proposes a virtual wind turbine model that estimates the operating point of a wind turbine in real-time under the assumption that frequency support functions are not performed. The proposed model is based on a turbine state observer that estimates wind speed and the power coefficient, and subsequently estimates generator power, generator speed, and blade pitch angle across various operating modes. Simulations were conducted under conditions with fluctuating wind speed and grid frequency, including MPPT, speed control, and pitch control operating regions. The accuracy of the proposed estimation model was evaluated, and the results demonstrated low estimation errors for key variables such as generator speed, power output, pitch angle, and wind speed across all conditions. These results quantitatively validate the robustness and applicability of the proposed model.

Keywords: wind turbine power curves; baseline control; type 4B wind turbine; frequency support functions; droop control; pitch control; numerical analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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