Inertia damping identification method for grid type inverters based on RCOF

The current inertia testing method for inverters is complex and difficult to apply to grid-forming converter. This article proposes an inertia damping identification method for grid-forming converter based on the rate of change of frequency (RoCoF), analyzes the working mechanism of active power control for grid-forming converter, derives the relationship between active power of grid-forming converter and grid frequency slope disturbance, and provides the inertia and damping identification steps based on this relationship. Finally, the proposed method is validated in a 3.15MW grid type electrochemical energy storage unit and optimized using Kalman filtering, and the experimental results show that the maximum measurement error of the proposed method was only 1.6%, indicating its effectiveness and feasibility.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0553
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Inertia damping identification method for grid type inverters based on RCOF

Sheng Zhang, Zhijian Fang, Mengxing Wang
IET conference proceedings.
Power Systems and Renewable Energy
article

Inertia damping identification method for grid type inverters based on RCOF

Sheng Zhang, Zhijian Fang, Mengxing Wang
article en

Abstract

The current inertia testing method for inverters is complex and difficult to apply to grid-forming converter. This article proposes an inertia damping identification method for grid-forming converter based on the rate of change of frequency (RoCoF), analyzes the working mechanism of active power control for grid-forming converter, derives the relationship between active power of grid-forming converter and grid frequency slope disturbance, and provides the inertia and damping identification steps based on this relationship. Finally, the proposed method is validated in a 3.15MW grid type electrochemical energy storage unit and optimized using Kalman filtering, and the experimental results show that the maximum measurement error of the proposed method was only 1.6%, indicating its effectiveness and feasibility.

IET conference proceedings.Vol. 2024(33)
Ministry of Education of the People's Republic of China (CN), China University of Geosciences (CN), Shandong Institute of Automation (CN)
Affordable and clean energy
Openalex Percentile: Top 96%
Power Systems and Renewable Energy
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Inertia damping identification method for grid type inverters based on RCOF — Sheng Zhang, Zhijian Fang, et al. · IET conference proceedings. (2025) | TGRS Research Map | TGRS