Key Parameter Estimation Method for Frequency Modulation of Receiving- End Grid-Forming Converters Considering Damping Control

[Objective] Driven by the “dual carbon” goals， the installed capacity of new energy sources has grown rapidly， and the system inertia characteristics are evolving from physical inertia to virtual inertia. New energy units adopt multiple control strategies， and their strong nonlinearity of dynamic responses and time-varying parameter characteristics significantly increase the difficulty in evaluating equivalent inertia and damping parameters. Therefore， this paper proposes a coordinated estimation method for inertia and damping of receiving-end grid-forming converters considering damping control. [Methods] Firstly， the influence of key frequency modulation parameters on various frequency dynamic response indicators is analyzed. Then， a coordinated estimation method based on least squares method and genetic algorithm for sliding fitting of inertia and damping of grid-forming converters at the receiving end is proposed. Considering the difficulty in verifying the effectiveness of estimation results， a dual-model comparative verification method based on <i>P</i>-<i>ω</i> admittance method is proposed. Finally， the key parameters of frequency modulation of the grid-connected converter at the receiving end of the PV system under different working conditions are estimated， and the accuracy of the estimated results is intuitively verified， which provides an important basis for the overall estimation and safety and stability analysis of the system. [Results] Simulation estimation and verification methods show that the proposed estimation method can complete the estimation of key frequency modulation parameters of receiving-end grid-forming converters with high accuracy， and the estimation method is efficient and feasible. [Conclusions] This paper studies the estimation of inertia and damping parameters of grid-forming converters， and proposes a parameter estimation method and verification scheme. Case studies show that the proposed method can quickly estimate key parameters after disturbances with small errors， providing a basis for the estimation of key frequency modulation parameters and security and stability analysis of the entire system.