AC and DC Transmission Line Expansion Planning Using Coronavirus Herd Immunity Optimizer

Mohamed M. Refaat, Shady H.E.Abdel Aleem, Yousry Atia, Ziad M. Ali, Mahmoud M. Sayed

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

5 Scopus citations

Abstract

In this paper, the coronavirus herd immunity optimizer (CHIO) was applied to solve the transmission line expansion planning (TEP) problem. CHIO was examined to solve AC and DC optimal power flow-based models, which are commonly used to formulate the TEP problem. Moreover, the impact of incorporating reactive power compensator allocation and TEP was extensively studied. A benchmark system (24 bus system) and two realistic Egyptian networks (500 kV and 66 kV networks) were used for the validation of the applied technique. The results demonstrated the superiority of the implemented technique compared to some meta-heuristic techniques reported in the literature. Therefore, CHIO is highly recommended for the TEP problem and expanse the methods toolbox. Integrating reactive sources with TEP further played an effective role in reducing the total investment cost and in enhancing system efficiency.

Original languageEnglish
Title of host publication22nd International Middle East Power Systems Conference, MEPCON 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages313-318
Number of pages6
ISBN (Electronic)9781665419987
DOIs
StatePublished - 2021
Event22nd International Middle East Power Systems Conference, MEPCON 2021 - Assiut, Egypt
Duration: 14 Dec 202116 Dec 2021

Publication series

Name22nd International Middle East Power Systems Conference, MEPCON 2021 - Proceedings

Conference

Conference22nd International Middle East Power Systems Conference, MEPCON 2021
Country/TerritoryEgypt
CityAssiut
Period14/12/2116/12/21

Keywords

  • AC and DC optimal power flow-based models
  • Coronavirus herd immunity optimizer
  • Reactive power compensator allocation
  • Transmission line expansion planning

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