Strategic Placement and Sizing of Distributed Generation for Resilience Enhancement of Distribution Grids with Microgrid Formation

Dhiraj Pokhrel; Guodong Liu; Yang Chen; Hugh Medal

doi:10.1109/ACCESS.2025.3636007

Strategic Placement and Sizing of Distributed Generation for Resilience Enhancement of Distribution Grids with Microgrid Formation

Dhiraj Pokhrel
, Guodong Liu
, Yang Chen
, Hugh Medal

Grid Systems Architecture

Research output: Contribution to journal › Article › peer-review

Abstract

The rise in frequency and severity of extreme weather events highlights the need for resilient power distribution networks. Microgrids can help improve the resilience of distribution grids by providing continuous power supply using local distribution generation (DG) when the distribution grid fails. In this paper, we propose an approach for optimal placement and sizing of DG to form multiple microgrids throughout the distribution network by restoration actions such as switching operations in case of distribution grid outages caused by extreme weather events. Considering the randomness of damaged distribution lines, the DG placement and sizing problem is formulated as a two-stage stochastic mixed-integer program, with the first stage determining the placement and size of DG, and the second stage focusing on minimizing the amount of load shedding through network restoration and microgrid formations for each scenario. Due to the large number of scenarios, the sample average approximation (SAA) method is employed to solve the problem. The results of case studies on a modified IEEE 33 bus distribution grid demonstrate the effectiveness of the proposed DG placement and sizing strategy in improving the resilience of distribution grids by allowing the formation of multiple microgrids. In addition, the robustness and accuracy of the SAA method are validated through various case studies.

Original language	English
Journal	IEEE Access
DOIs	https://doi.org/10.1109/ACCESS.2025.3636007
State	Accepted/In press - 2025

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

Distributed generation planning
microgrid formation
resilience
sample average approximation
stochastic program

Access to Document

10.1109/ACCESS.2025.3636007

Cite this

@article{05b042965711420591747d8da9ebf52a,

title = "Strategic Placement and Sizing of Distributed Generation for Resilience Enhancement of Distribution Grids with Microgrid Formation",

abstract = "The rise in frequency and severity of extreme weather events highlights the need for resilient power distribution networks. Microgrids can help improve the resilience of distribution grids by providing continuous power supply using local distribution generation (DG) when the distribution grid fails. In this paper, we propose an approach for optimal placement and sizing of DG to form multiple microgrids throughout the distribution network by restoration actions such as switching operations in case of distribution grid outages caused by extreme weather events. Considering the randomness of damaged distribution lines, the DG placement and sizing problem is formulated as a two-stage stochastic mixed-integer program, with the first stage determining the placement and size of DG, and the second stage focusing on minimizing the amount of load shedding through network restoration and microgrid formations for each scenario. Due to the large number of scenarios, the sample average approximation (SAA) method is employed to solve the problem. The results of case studies on a modified IEEE 33 bus distribution grid demonstrate the effectiveness of the proposed DG placement and sizing strategy in improving the resilience of distribution grids by allowing the formation of multiple microgrids. In addition, the robustness and accuracy of the SAA method are validated through various case studies.",

keywords = "Distributed generation planning, microgrid formation, resilience, sample average approximation, stochastic program",

author = "Dhiraj Pokhrel and Guodong Liu and Yang Chen and Hugh Medal",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2025",

doi = "10.1109/ACCESS.2025.3636007",

language = "English",

journal = "IEEE Access",

issn = "2169-3536",

publisher = "Institute of Electrical and Electronics Engineers",

}

TY - JOUR

T1 - Strategic Placement and Sizing of Distributed Generation for Resilience Enhancement of Distribution Grids with Microgrid Formation

AU - Pokhrel, Dhiraj

AU - Liu, Guodong

AU - Chen, Yang

AU - Medal, Hugh

PY - 2025

Y1 - 2025

N2 - The rise in frequency and severity of extreme weather events highlights the need for resilient power distribution networks. Microgrids can help improve the resilience of distribution grids by providing continuous power supply using local distribution generation (DG) when the distribution grid fails. In this paper, we propose an approach for optimal placement and sizing of DG to form multiple microgrids throughout the distribution network by restoration actions such as switching operations in case of distribution grid outages caused by extreme weather events. Considering the randomness of damaged distribution lines, the DG placement and sizing problem is formulated as a two-stage stochastic mixed-integer program, with the first stage determining the placement and size of DG, and the second stage focusing on minimizing the amount of load shedding through network restoration and microgrid formations for each scenario. Due to the large number of scenarios, the sample average approximation (SAA) method is employed to solve the problem. The results of case studies on a modified IEEE 33 bus distribution grid demonstrate the effectiveness of the proposed DG placement and sizing strategy in improving the resilience of distribution grids by allowing the formation of multiple microgrids. In addition, the robustness and accuracy of the SAA method are validated through various case studies.

AB - The rise in frequency and severity of extreme weather events highlights the need for resilient power distribution networks. Microgrids can help improve the resilience of distribution grids by providing continuous power supply using local distribution generation (DG) when the distribution grid fails. In this paper, we propose an approach for optimal placement and sizing of DG to form multiple microgrids throughout the distribution network by restoration actions such as switching operations in case of distribution grid outages caused by extreme weather events. Considering the randomness of damaged distribution lines, the DG placement and sizing problem is formulated as a two-stage stochastic mixed-integer program, with the first stage determining the placement and size of DG, and the second stage focusing on minimizing the amount of load shedding through network restoration and microgrid formations for each scenario. Due to the large number of scenarios, the sample average approximation (SAA) method is employed to solve the problem. The results of case studies on a modified IEEE 33 bus distribution grid demonstrate the effectiveness of the proposed DG placement and sizing strategy in improving the resilience of distribution grids by allowing the formation of multiple microgrids. In addition, the robustness and accuracy of the SAA method are validated through various case studies.

KW - Distributed generation planning

KW - microgrid formation

KW - resilience

KW - sample average approximation

KW - stochastic program

UR - https://www.scopus.com/pages/publications/105022698249

U2 - 10.1109/ACCESS.2025.3636007

DO - 10.1109/ACCESS.2025.3636007

M3 - Article

AN - SCOPUS:105022698249

SN - 2169-3536

JO - IEEE Access

JF - IEEE Access

ER -

Strategic Placement and Sizing of Distributed Generation for Resilience Enhancement of Distribution Grids with Microgrid Formation

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this