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Strategic optimization framework considering unobservability in multi-voltage active distribution networks

  • Aeishwarya Baviskar*
  • , Firdous U. Nazir
  • , Anca D. Hansen
  • , Kaushik Das
  • , Bikash C. Pal
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
164 Downloads (Pure)

Abstract

An increase in the share of weather-dependent generation at low voltage levels necessitates incorporating the low-voltage network in optimizing a distribution network. Optimization in a multi-voltage network requires significant computation time and effort due to many nodes operating at different voltage levels. This research proposes a decomposition and strategic optimization method to reduce the computation requirements for such large multi-voltage distribution networks. The proposed algorithm reduces the space complexity and the computation time required for solving the optimization routines of these multi-voltage distribution networks. A virtual transformer model incorporates tap-changer as a continuous variable in the semidefinite programming power flow optimization model. The zero-duality gap condition for multiple virtual transformers is proven empirically. Compared to a centralized optimization using the same power flow model, the proposed framework reduced the computation time by 96%.

Original languageEnglish
Article number110127
Number of pages12
JournalInternational Journal of Electrical Power and Energy Systems
Volume161
Early online date12 Aug 2024
DOIs
Publication statusPublished - Oct 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Controllability
  • Distributed Renewable Generation
  • Multi-voltage Distribution Network
  • Observability
  • On-load tap changers
  • Reactive Power
  • Voltage-Violations

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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