Evaluating Grid Strength under Uncertain Renewable Generation

Manisha Maharjan, Almir Ekic, Mari Beedle, Jin Tan, Di Wu

Research output: Contribution to journalArticlepeer-review

3 Scopus Citations

Abstract

The increasing displacement of synchronous generators with renewable resources such as wind and solar via power electronic interfaces causes a reduction in short-circuit strength and weak grid issues. The variation and uncertainty of renewable energy increase challenges for identifying weak grid conditions. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses the probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce computational burden without compromising result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.

Original languageAmerican English
Article number108737
Number of pages9
JournalInternational Journal of Electrical Power and Energy Systems
Volume146
DOIs
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2022

NREL Publication Number

  • NREL/JA-5D00-84810

Keywords

  • Grid strength
  • Probabilistic collocation method
  • Renewable energy resources
  • Uncertainty analysis

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