An adaptive two-factor robust recursive least squares based online assessment method for power system inertia
ID：52
Submission ID：57 View Protection：ATTENDEE
Updated Time：2025-10-11 22:34:51 Hits：65
Poster Presentation
Start Time：2025-11-09 09:04 （Asia/Shanghai）
Duration：1min
Session：[P] Poster presentation » [P1] 1.Renewable energy system
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Abstract
Under virtual inertia control, the output of wind farms presents fast time-varying characteristics, resulting in dynamic changes in power system inertia, and quantitative assessment of inertia becomes more difficult. Aiming at the difficulty of existing methods to stabilize and quickly assess its equivalent time-varying inertia, this paper proposes a power system inertia estimation method based on the virtual inertia control of wind power. First, the theoretical expression for the system equivalent inertia when containing wind power virtual inertia is derived; using the node power and frequency data measured by PMU, combined with the detrended fluctuation analysis (DFA), the moment of large perturbation is determined and the observation data are extracted. Subsequently, the controlled autoregressive (CAR) model and adaptive two-factor robust recursive least squares (ADF-RLS) algorithm are adopted to realize the estimation of the equivalent inertia of the whole network. The simulation results verify the accuracy and robustness of the method in recognizing the time-varying characteristics of inertia in new energy systems.
Keywords
Virtual inertia control, wind farm time-varying inertia, power system equivalent inertia, detrended fluctuation analysis (DFA), adaptive two-factor robust recursive least squares (ADF-RLS)
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