Probabilistic Stability Evaluation Based on Confidence Interval in Distribution Systems with Inverter-Based Distributed Generations

Moonjeong Lee, Myungseok Yoon, Jintae Cho, Sungyun Choi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This study proposed a probabilistic methodology based on a confidence interval with the aim of overcoming the limitations of deterministic methods. A stability evaluation technique was required because the output variability of renewable energy can lead to instability of the distribution system. The proposed method can predict the possibility of violating stability in the future. It can also provide a theoretical basis for securing distribution system stability and improving operational efficiency by assessing the in-stability risk and worst-case scenarios. Because of steady-state analysis in the distribution system to which solar power is connected, the probability of violating the standard voltage during the daytime when PV fluctuations are severe was the highest. Moreover, as a result of a simulation of a three-phase short-circuit in the distribution system that is connected to the PV and WT, it was observed that it could violate the allowable capacity of the CB owing to the effects of the power demand pattern and output variability.

Original languageEnglish
Article number3806
JournalSustainability (Switzerland)
Volume14
Issue number7
DOIs
Publication statusPublished - 2022 Apr 1

Bibliographical note

Funding Information:
Funding: This research was supported in part by the KEPCO Research Institute under the project entitled by “A Research of Advanced Distribution Planning System for Mid-long term (R20DA16),” in part by the Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20204010600220), and in part by the Basic Research Program through the National Research Foundation of Korea (NRF) funded by the MSIT (No. 2020R1A4A1019405).

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • confidence interval
  • distributed generation
  • distribution systems
  • fault analysis
  • probabilistic stability evaluation
  • voltage stability

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Environmental Science (miscellaneous)
  • Geography, Planning and Development
  • Energy Engineering and Power Technology
  • Hardware and Architecture
  • Management, Monitoring, Policy and Law
  • Computer Networks and Communications
  • Renewable Energy, Sustainability and the Environment

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