Development of a probabilistic short-term voltage quality assessment method with the weak point detection capability through the dynamic analyses

Onder Polat*, Omer Gul

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The proliferation of power electronics-based sources and equipment in low voltage to high voltage applications reshapes the dynamic behavior of power system networks, leading to certain voltage quality vulnerabilities for industrial customers and independent power producers. The root causes of most voltage quality problems are related to power system faults which may trigger voltage dips, voltage swells, and interruptions. In-depth stochastic modeling combined with advanced power system simulations and statistical validation is required to foresee the effects of these events on the network users. Therefore, a holistic method was proposed in this paper that utilizes reliability parameters in the context of the novel Monte Carlo-based fault creation approach. This method incorporates the input data from an extensive literature survey and real-life measurements. The probabilistic fault events are simulated in an environment where the protection system – dynamics interactions are considered. A modified IEEE test system was developed to introduce unconventional sources into the conventional test grid. A python script was developed to implement the algorithms into the power system analysis tool. Also, several voltage quality indices were introduced which are based on international standards. 30 Monte Carlo repetitions of a 5-year simulation period were performed (150 years Monte Carlo simulations), leading to a total number of 4410 fault cases for each network scenario. The results of the Monte-Carlo simulations were used to find the weak points of the network under five different operation and design scenarios with several statistical significance tests.

Original languageEnglish
Article number120003
JournalApplied Energy
Volume326
DOIs
Publication statusPublished - 15 Nov 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Battery storage
  • Interruptions
  • Inverter-based generation
  • Monte Carlo
  • Power quality
  • Power system dynamics
  • Power system protection
  • Reliability
  • Solar parks
  • STATCOM
  • Stochastic faults
  • Voltage dips (sag)
  • Voltage quality
  • Voltage swells
  • Wind parks

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