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July 2, 2026Electric Power Systems Research0 citationsOpen Access

Dynamic similarity analysis for active distribution grid equivalents

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NMNICOLÁS MURILLOJSJoel SchindlerOAOnur Alican

Key Points

  • This research aims to develop methods to effectively reduce and assess dynamic similarities in distribution grids with inverter-based resources.
  • Proposed iterative network reduction techniques utilizing Kron reduction and optimization methods.
  • Validation of models based on time and frequency domain assessments.
  • Application of methodologies tested in a case study for real-world verification.
  • The reduced networks significantly enhance computational efficiency for large-scale system studies.
  • Dynamic similarity of aggregated models was confirmed, leading to improved power system planning.
  • Proven appropriateness of methodologies for real-world application and study results.

Abstract

The increasing share of inverter-based resources (IBRs) has reshaped distribution–transmission dynamics. Capturing their fast control interactions via electromagnetic transient (EMT) simulations are computationally demanding, necessitating effective aggregation and reduction methods for grid equivalents. This work proposes novel network reduction techniques and a sophisticated methodology to assess the dynamic similarity of grid equivalents. The aggregation techniques involve an iterative process employing Kron reduction and an optimisation-based approach. The validation of the dynamic similarity of the aggregated models is based on time and frequency domain. The resulting reduced networks enable the incorporation of the network system dynamics into large-scale system studies in a computationally efficient way. The proposed methodologies were tested in a case study and their appropriateness was verified. This has the potential to improve study results for appropriate power system planning and operation.

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Cite This Study

MURILLO et al. (2026) studied this question.

synapsesocial.com/papers/6a45ff3c9ed134303130fb43https://doi.org/10.1016/j.epsr.2026.113628
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