Abstract Studies for high voltage power networks generally ignore line resistance with the assumption of being far less than line reactance. However, this treatment could cause certain errors in analysing low-voltage distributed networks, causing the assumption to no longer be applicable. Such errors could be significant considering the impact of load carrying and ambient conditions, such as online resistance or temperature due to electro-thermal coupling (ETC). Then, it becomes an open question to accurately capture the system state of distribution networks due to changed line parameters. Integrating new style energy sources, such as renewable power generation, energy storage applications, and adjustable power load, will promote the deployment of measurement devices at distribution networks. With the assumption of sufficient accumulated data offered by online monitoring terminals, this study proposes a nonlinear regression method—Levenberg-Marquardt—to identify the parameters of the line. However, since it is difficult to access practical data, this study employs the electro-thermal coupling power flow (ETCPF) to simulate line operation and take the results as monitoring data for case studies. The identification results under various data volumes and error levels demonstrate the reliability and accuracy of the proposed approach.
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