PDF(2770 KB)
Key Parameter Estimation Method for Frequency Modulation of Receiving- End Grid-Forming Converters Considering Damping Control
YAN Xiangwu, XU Yue, ZHANG Hui, QU Yue, LI Bohan, WANG Haoming, JIA Jiaoxin
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (4) : 1-15.
PDF(2770 KB)
PDF(2770 KB)
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 P-ω 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.
equivalent inertia time constant / damping coefficient / grid-forming converter / inertia / parameter estimation / flexible DC transmission
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As the penetration rate of wind turbines increases, the power system inertia level decreases year by year. At the same time, the frequency response has partition characteristics, and it is more flexible and accurate to evaluate the power system inertia in terms of region. Therefore, a dynamic partition inertia estimation method is presented based on one-dimensional squeeze and excitation residual neural network （1D-SE-ResNet）. Firstly, the trend and value approximation of frequency distance are computed, and the k-means clustering method is used to dynamically partition the system and the number of partitions is determined by the S-C metric. Then, the 1D-ResNet is improved by adding the squeeze and excitation module, which enables it to provide weights for each channel to enhance the network performance. The regional cluster centre node frequency and frequency change rate data under different inertia levels and load perturbations of the system are collected as one-dimensional feature inputs, and the regional effective inertia is the output, training the network to achieve regional inertia estimation. Finally, simulations are carried out on the IEEE 39-node and IEEE 118- node systems containing wind power. The results show that the trained 1D-SE-ResNet can achieve accurate evaluation of regional inertia based on dynamic partitioning. |
利益冲突声明（Conflict of Interests） 所有作者声明不存在利益冲突。
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