The Online Identification Of Lines' Parameters Based On Synchronized Phasor Measurement

The transmission line is one major part in the electrical system and getting the exact transmission lines' parameters is very important. The traditional method of calculating the lines' parameters is using the precise physics calculation. Although this method can figure out the parameters, its practicability is poor for it does not take the effects of nature conditions such as climate and geography into regarding. The emergence of the PMU based on GPS makes the synchronized phasor measurement technology become possible. The method of online identification of lines' parameters based on synchronized phasor measurement is presented in this paper. It figures out the lines' parameters by the real-time voltage and current phasor of the two ends in the equivalent lumped parameter model. Using the relationship between this model and the distributed parameter model, we can transform these results into the distributed one. Considering the dissymmetry of the line load in the three-phase transmission lines when running, this paper transforms the voltage and current phasor using symmetric components method and solves out it by the sequence parameter method. When it comes to the transmission lines with mutual inductance, this paper presents a method of solving the real-time measurement of the transmission line using increment theory. It can not only eliminate the effects of the traditional power failure measurement to the zero-sequence parameter, but also avoid the complicated connection manner. Considering the nature factors' effect to the field measurement parameters will result in many problems such as how to protect the inaccurate calculation of settings, this paper analyzes the effects such as climate environment and geography to the transmission line and finds a new way to establish the relationship between the lines' parameter and the nature factors. Finally, this paper simulates the presented method in Matlab environment including modeling and programming. The results show us that this method has many advantages such as veracity, real time performance and fastness. Comparing to the traditional method that needs more time and energy, it is more economical.