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A Quantification Index for Power Systems Transient Stability

Author

Listed:
  • Shengen Chen

    (Department of Electrical & Computer Engineering, University of Maine, Orono, ME 04469, USA)

  • Amamihe Onwuachumba

    (RLC Engineering LLC., Hallowell, ME 04347, USA)

  • Mohamad Musavi

    (Department of Electrical & Computer Engineering, University of Maine, Orono, ME 04469, USA)

  • Paul Lerley

    (RLC Engineering LLC., Hallowell, ME 04347, USA)

Abstract

In order to assess the reliability of power systems, transient stability simulations must be conducted in addition to steady state study. The transient stability component of reliability studies usually involves extensive simulations generating large amounts of data to be analyzed. Conventional stability analysis relies on a visual examination of selected simulation data plots to classify the severity of disturbances. This conventional examination, which aims to compare the simulations results to established performance criteria, is not comprehensive, is time consuming and prone to subjective interpretation. This paper presents a quantification method for power system performance evaluation. It applies a range of criteria such as rotor angle separation, loss of source, damping, and voltage sag directly to the simulation data files to achieve a more efficient and objective stability assessment. By using stability modules, the proposed method evaluates the performance of every fault location, numerically, by providing a local stability index, as well as an overall global stability index. The method also provides an evaluation of dispatches and their impacts on system stability. The IEEE 39-bus test system and the Northeast Interconnection Power System were used to show the results of this method. This method will free engineers from tedious, time-consuming and error-susceptible offline visual analysis and yield significantly quantified results.

Suggested Citation

  • Shengen Chen & Amamihe Onwuachumba & Mohamad Musavi & Paul Lerley, 2017. "A Quantification Index for Power Systems Transient Stability," Energies, MDPI, vol. 10(7), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:984-:d:104401
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    Cited by:

    1. Biyun Chen & Haoying Chen & Yiyi Zhang & Junhui Zhao & Emad Manla, 2019. "Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems," Energies, MDPI, vol. 12(6), pages 1-18, March.

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