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Chernobyl Disaster Optimizer-Based Optimal Integration of Hybrid Photovoltaic Systems and Network Reconfiguration for Reliable and Quality Power Supply to Nuclear Research Reactors

  • Sobha Rani Penubarthi
  • , Radha Rani Korrapati
  • , Varaprasad Janamala
  • , Chaitanya Nimmagadda
  • , Arigela Satya Veerendra*
  • , Srividya Ravindrakumar
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In view of the complexity and importance of nuclear research reactor (NRR) installations, it is imperative to uphold high standards of reliability and quality in the electricity being supplied to them. In this paper, the performance of low-voltage (LV) distribution feeders integrated with NRRs is improved in terms of reduced distribution loss, improved voltage profile, and reduced greenhouse gas (GHG) emissions by determining the optimal location and size of photovoltaic (PV) systems. In the second stage, the power quality of the feeder is optimized by reducing the total harmonic distortion (THD) by optimally allocating D-STATCOM units. In the third and fourth stages, the reliability and resilience aspects of the feeder are optimized using optimal network reconfiguration (ONR) and by integrating an energy storage system (ESS). To solve the non-linear complex optimization problems at all these stages, an efficient meta-heuristic Chernobyl disaster optimizer (CDO) is proposed. Simulations are performed on a modified IEEE 33-bus feeder considering the non-linear characteristics of NRRs, variability of the feeder loading profile, and PV variability. The study reveals that the proposed methodology can significantly improve the service requirements of NRRs for attaining sustainable research activities.

Original languageEnglish
Pages (from-to)1268-1285
Number of pages18
JournalModelling
Volume5
Issue number3
DOIs
Publication statusPublished - 09-2024

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

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Engineering (miscellaneous)
  • Mathematics (miscellaneous)
  • Modelling and Simulation

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