Published April 30, 2023 | Version v1
Journal article Open

Improving the efficiency of mode automation using synchrophasor measurements to identify stability disturbance

Creators

  • 1. Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev
  • 2. Kazakhstan Electricity Grid Operating Company (KEGOC)

Description

The paper presents new approaches and principles for identifying the conditions of stability disturbance based on detecting dangerous disturbances in the early stages using information about changes in regime parameters and their Rate of Change. As a mode parameter, the mutual voltage angle between the controlled 500 kV substation and its Rate of Change was selected in the study. It is suggested to take the values of the mentioned parameters from the Wide Area Measurements System (WAMS). The relevance of the research is due to the need to improve the efficiency and eliminate the drawbacks of existing revealing devices of regime automatics, which will reduce the number of accidents due to disturbances of the power system stability. The proposed principle of predicting stability violation is based on using the provision of Lyapunov’s stability theory, according to which the assessment of stability is carried out by the total system energy consisting of kinetic and potential. In contrast to the existing principles of detecting stability violation, where the exit from the stability area is determined by the main parameter (potential energy), the prediction principle allows evaluating stability by its rate of change (kinetic energy), which provides the early detection of stability disturbance.

Calculations were performed on modeling power surges in the North-South interconnection of the Kazakhstan Unified Energy System in the «DigSILENT Power Factory» software on the model, which was verified by real perturbations in the power system according to the WAMS data. The calculations confirmed the effectiveness of the proposed principles and the possibility of using WAMS data for detecting emergency power surges on transit power networks in the initial stage

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References

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