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Optimal Allocation of FACTS Devices in Power Systems: A Multi-Objective Optimization Approach with Consideration of Wind Generation Integration

  • Ayman Awad*
  • , Salah Kamel
  • , Mohamed H. Hassan
  • , Francisco Jurado
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

The presence of FACTS devices in the modern power systems nowadays is obvious for its important contributions, however, it is essential to get the optimal allocation for the installed FACTS devices in a given system to acquire the best outcomes regarding the required objective of such installations. In this paper, the optimal allocation of various FACTS devices is investigated using a number of optimization algorithms in standard IEEE 30 bus system, taking in consideration the penetration of wind generators into the system. The objective function of the optimization is reducing the generation cost and power losses as a multi-objective function. Several optimization algorithms are involved in this optimization process, including traditional and recent optimization algorithms. The outcomes of these optimization algorithms are compared, deducting the most efficient algorithm for optimal allocation of FACTS devices regarding the other optimization algorithms.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350394528
DOIs
StatePublished - 2024
Externally publishedYes
Event2024 International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024 - Victoria, Seychelles
Duration: 1 Feb 2024 → 2 Feb 2024

Publication series

NameInternational Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024

Conference

Conference2024 International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024
Country/TerritorySeychelles
CityVictoria
Period1/02/24 → 2/02/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

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

  • FACTS
  • Generation costs
  • Optimization
  • Power losses

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Information Systems and Management
  • Health Informatics
  • Artificial Intelligence
  • Computer Science Applications

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