Optimum Allocation and Sizing of Storages with Multi-Objective Grey Wolf Optimizer

Gunnur Yesilyurt*, Cenk Andic, Esra Aydin, Belgin Turkay

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study employs the Multi-Objective Grey Wolf Optimizer (MOGWO) to optimize the allocating and sizing of ESS in a modified IEEE 123 Bus Test System integrated with PV systems. The simulation was conducted on MATLAB and the load flow analysis were conducted using OpenDSS through COM interface. The analysis assesses both the operational and placement optimizations of ESSs, demonstrating significant improvements in reducing power loss and voltage deviations while ensuring economic viability. The inclusion of ESSs reduced overand under-voltage events by more than 50%, from 866 in the PVonly scenario to 409 with ESSs, and overall voltage deviation decreased from 7.108 p.u. to 6.809 p.u. The results indicate that optimized ESS deployment can lead to a more stable and efficient power grid, reinforcing the value of MOGWO in complex system optimization.

Original languageEnglish
Title of host publication8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331531492
DOIs
Publication statusPublished - 2024
Event8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 - Malatya, Turkey
Duration: 21 Sept 202422 Sept 2024

Publication series

Name8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

Conference

Conference8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024
Country/TerritoryTurkey
CityMalatya
Period21/09/2422/09/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • energy storage systems
  • multi-objective grey wolf optimizer
  • optimization
  • renewable energy

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