Frequency Support Capability Estimation for Renewable Energy Units under Dynamic Response Variations

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🔬研究者:Provides a novel power decoupling and parameter identification approach for estimating virtual inertia and primary frequency control coefficients from measured data.

🏢実務担当者:Grid operators and renewable plant owners can use this method to evaluate and optimize frequency support capability in low-inertia systems.

<title>Abstract</title> <p>High proportional integration of power-electronics-interfaced renewable energy generation has severely weakened the inertia and frequency regulation performance of modern power systems. Although virtual inertia control and primary frequency control strategies enable renewable generating units to provide active power support during frequency events, their actual output characteristics often deviate from design indexes due to resource constraints and control delays. Accurate online estimation of the available frequency support capacity from renewable energy stations based on measured data has become essential for maintaining secure operation in low-inertia grids. However, conventional assessment approaches neglect the transient dynamic response features of various renewable resources after disturbances and cannot effectively separate inertia-related power from primary frequency regulation power, leading to considerable errors in identified parameters. This paper first compares the dynamic frequency response mechanisms between synchronous generators and converter-based renewable generators. Then, an improved power decoupling approach is proposed to separate virtual inertia power from primary frequency control output, and a gradient-descent-based parameter identification scheme is presented to estimate the virtual inertia constant using the decoupled signal. Furthermore, a hardware-in-the-loop testing platform is established using a real-time digital simulator and synchronized measurement units to verify the proposed method under realistic working conditions. Validation results from both simulation cases and field measurements demonstrate that the proposed method can accurately identify the virtual inertia time constant and primary frequency control coefficient with high robustness. The estimated results can support optimal allocation of frequency regulation resources and reasonable tuning of control parameters for renewable energy stations.</p>

• Research Square https://doi.org/10.21203/rs.3.rs-9659377/v1first seen 2026-06-05 04:40:28 · last seen 2026-06-16 04:30:25