Journal of Green Energy Research and Innovation
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Optimal Placement of Distributed Energy Resources to Reduce Losses, Improve Voltage Profile, and Convert it into a Self-healing Smart Grid

Document Type : Research article

Authors

Ali Kazemi 1
Ali Morsagh Dezfuli 2

1 Department of Electrical and Computer Engineering, Technical and Vocational University (TVU), Mazandaran, Iran.

2 Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran.

https://doi.org/10.61186/jgeri.1.1.16
Abstract
This study focuses on achieving a self-healing network with high reliability and minimal losses by discussing the optimal placement of distributed generation (DG) sources in the network using the particle swarm algorithm (PSO). Optimal placement not only reduces losses but also enhances the voltage profile and enhances system reliability. Consequently, the paper explores the concept of a self-healing smart grid. Smart grids possess a crucial attribute known as self-healing, designed to enhance the system’s dependability. The self-healing power grid can detect and rectify disruptions within its infrastructure with minimal or even absent human intervention. This study examines a standard IEEE 69-bus network and presents results demonstrating the network's safety, the prevention of blackouts, the reduction of losses, and the substantial enhancement of the voltage profile.

Graphical Abstract

Optimal Placement of Distributed Energy Resources to Reduce Losses, Improve Voltage Profile, and Convert it into a Self-healing Smart Grid

Highlights

 

  • Achieving a self-healing network with high reliability and minimal losses
  • Optimal placement of DGs in the network using the particle swarm algorithm
  • Enhancing the voltage profile and system reliability
  • Detecting and rectifying disruptions with minimal human intervention

Keywords

Smart Grid
Self-healing
Optimal location
Distributed energy resources

 

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, have been completely observed by the authors.

 

Credit Authorship Contribution Statement

Ali Kazemi: Conceptualization, Formal analysis, Investigation, Methodology, Roles/Writing - original draft, Writing - review & editing. Ali Morsagh Dezfuli: Conceptualization, Resources, Methodology, Roles/Writing - original draft, Writing - review & editing.

 

Bibliography

 Ali Kazemi received his B.Sc. and M.Sc. degrees in Electrical Engineering (Power Systems) from Islamic Azad University, Sari branch, Sari, Iran, in 2009 and 2015, respectively. His fields of interest include smart grids, distribution networks, renewable energies, and system operation. Currently he is working as an adjunct professor at Department of Electrical and Computer Engineering, Technical and Vocational University (TVU), Mazandaran, Iran.

 Ali Morsagh Dezfuli was born in Dezful, Iran in 1992. He received the B.Sc. degree from the Jundi-Shapur University of Technology of Dezful, Dezful, Iran in 2015, the M.Sc. degree from the Shahid Rajaee Teacher Training University of Tehran, Tehran, Iran in 2017 and he is a PhD candidate at Shahid Chamran University of Ahvaz, Ahvaz, Iran all in Power Electrical Engineering. His research interests are: Voltage and Frequency Control of Microgrid, Power Electronics, FACTs Devices and Power System Protection.

 

Citation

A. Kazemi, and A. Morsagh Dezfuli, " Optimal Placement of Distributed Energy Resources to Reduce Losses, Improve Voltage Profile, and Convert it into a Self-healing Smart Grid," Journal of Green Energy Research and Innovation, vol. 1, no. 1, pp. 16-33, 2024.

 
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Journal of Green Energy Research and Innovation
Volume 1, Issue 1
Winter 2024
Pages 16-33

  • Receive Date 04 December 2023
  • Revise Date 11 January 2024
  • Accept Date 23 January 2024
  • Publish Date 04 March 2024

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