Grid-forming converter-based generation (CBG) with the advantage of self-organization can be widely used. Accurate estimation of grid-forming CBG inertia will become a reliable basis for the safe and stable operation of power systems in the future. In this paper, a method for estimating the inertia of grid-forming CBG based on small disturbance response is proposed. Based on the time scale analysis of each control link in the detailed model of grid-forming CBG, the inertia response model under electromechanical time scale is constructed. By analyzing the electromechanical oscillation response characteristics of the grid-forming CBG under small perturbations, the analytical expression of its inertia is derived, which can effectively avoid the risk of evaluating meaninglessness. The dominant oscillation modes are extracted by the oscillation mode decomposition technique, which improves the application of the estimation method in large-scale multi-machine systems. The proposed method is verified by simulation of the IEEE 4-machine power system, and the results show that the proposed method is effectiveness.

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Data-Driven Inertia Estimation of Grid-Forming Converter-Based Generation in Power System

  • Bo Wang,
  • Xinbo Zhou,
  • ZhenYi Wang,
  • Qingyu Wang

摘要

Grid-forming converter-based generation (CBG) with the advantage of self-organization can be widely used. Accurate estimation of grid-forming CBG inertia will become a reliable basis for the safe and stable operation of power systems in the future. In this paper, a method for estimating the inertia of grid-forming CBG based on small disturbance response is proposed. Based on the time scale analysis of each control link in the detailed model of grid-forming CBG, the inertia response model under electromechanical time scale is constructed. By analyzing the electromechanical oscillation response characteristics of the grid-forming CBG under small perturbations, the analytical expression of its inertia is derived, which can effectively avoid the risk of evaluating meaninglessness. The dominant oscillation modes are extracted by the oscillation mode decomposition technique, which improves the application of the estimation method in large-scale multi-machine systems. The proposed method is verified by simulation of the IEEE 4-machine power system, and the results show that the proposed method is effectiveness.