Abstract：The high penetration of distributed photovoltaic (PV) systems into distribution networks has transformed the operational modes and fault characteristics of the networks. To meet the requirements of distribution network protection, there is an urgent need to explore an equivalent impedance identification method for distribution network operation modes. In calculating the system equivalent impedance, traditional identification methods ignore the impact of PV power sources, leading to significant errors in the identification results. In response, this paper proposes a system equivalent impedance identification method that accounts for the influence of PV power sources, aiming to improve the identification accuracy of the system equivalent impedance in distribution networks. Firstly, this paper establishes a three-node equivalent model of the distribution network system, analyzes in detail the phasor relationship at the distribution network busbars, and draws the corresponding phasor diagram. Based on the phasor triangular relationship reflected by the phasor diagram, the analytical expression of the system equivalent impedance is derived using the diameter of the circumscribed circle of the triangle, the sine theorem, and the power angle variation. The influence of the power flow direction of the PV power source on the structure of the phasor diagram is thoroughly analyzed, and a system equivalent impedance identification model considering the impact of the PV power flow direction is established. Meanwhile, this paper proposes a data processing method based on weighted parameter correction of the equivalent model. By eliminating noise data points and correcting measurement parameters, the accuracy of the final system equivalent impedance identification results is improved. In addition, based on the actual topological structure and engineering parameters of a 10 kV distribution network in southern China, a hardware-in-the-loop (HIL) simulation model is built in RTDS to verify the proposed system impedance identification method. The verified scenarios include different PV access capacities (0.1~5.0 MV·A), load side fluctuation ranges (±5%~±50%), load side disturbance frequencies (10~5 000 Hz), and the tracking capability for sudden changes in system equivalent impedance. Comparisons are made with traditional identification algorithms such as the least squares (LS) identification method, the statistical relationship identification method, etc. Under the condition of reasonable power fluctuations in the distribution network, the maximum identification error of the proposed method is less than 10%, the average identification error is less than 5%, and it has a strong tracking capability for sudden changes in system equivalent impedance. Compared with traditional identification methods, the identification accuracy is significantly improved, and the identification error rate is only about 1/4 of that of traditional algorithms. The research results show that the proposed identification method fully considers the impact of PV power integration on the equivalent impedance identification of distribution network systems, ensuring accurate identification of the system-side equivalent impedance when PV is connected to the distribution network. At the same time, it reduces the adverse impact of defects and noise points in the measured data on the identification results. The proposed algorithm has high identification accuracy, strong parameter tracking capability, and strong adaptability to different operating conditions.
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2026, Vol. 41 
