Abstract

Microgrid systems can experience prolonged outages, load shed, and also can affect the resilience of Microgrid, when there are unexpected contingencies due to human error or natural disasters. Integrating Battery Energy Storage (BES) is necessary to increase the resilience of the Microgrid system by recovery the load because it can act as an additional generator and can return the power supply to the load directly in the event of a contingency. Integration BES needs an optimal location and capacity determination plan. In this paper, by using the Hybrid Multi-Objective Particle Swarm Optimization (H-MOPSO) method which is a combination of Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA II) methods determine optimal BES placement. The objective function used in this research is to maximize annual benefits costs and minimize Load shedding under contingency conditions. This paper also uses Linear Distribution Factor (LODF) to calculate the security constraint of the Microgrid system, which will be used to manage the line limit.

Original languageEnglish
Title of host publicationICPEA 2021 - 2021 IEEE International Conference in Power Engineering Application
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages62-67
Number of pages6
ISBN (Electronic)9781728185460
DOIs
Publication statusPublished - 8 Mar 2021
Event2021 IEEE International Conference in Power Engineering Application, ICPEA 2021 - Virtual, Online, Malaysia
Duration: 8 Mar 20219 Mar 2021

Publication series

NameICPEA 2021 - 2021 IEEE International Conference in Power Engineering Application

Conference

Conference2021 IEEE International Conference in Power Engineering Application, ICPEA 2021
Country/TerritoryMalaysia
CityVirtual, Online
Period8/03/219/03/21

Keywords

  • Battery Energy Storage
  • Contingency
  • H-MOPSO
  • LODF
  • Resiliency

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