Strategic SDN-Based Microgrid Formation for Managing Communication Failures in Distribution System Restoration

Grid modernization has increased the reliance of power networks on cyber networks within distribution systems (DSs), heightening their vulnerability to disasters. Communication network failures significantly impede DS load recovery by diminishing observation and control. Prior research has largely ignored the need for integrated recovery of DS power and cyber networks' centralized control. Indeed, communication network restoration is critical for speedy load recovery through DS automation based microgrid formation. This paper exploits the data routing capabilities of software-defined networking (SDN) to enhance centralized control recovery in DS communication networks, incorporating it into a comprehensive DS restoration model. This model, tailored to the control requirements of load restoration, strategically allocates limited communication resources to re-establish connections between the operation center and terminal devices. Subsequently, DS automation is employed to orchestrate DS microgrid formation for power resupply. Additionally, we introduce a cyclic algorithm designed to optimize the load recovery via a multi-step, cooperative process. The efficacy of the proposed method is demonstrated on IEEE 33-node and IEEE 123-node test feeders.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Power Systems
Published
2024-11-13
DOI
https://doi.org/10.1109/tpwrs.2024.3497306
Citations
6
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
1.97
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strategic SDN-Based Microgrid Formation for Managing Communication Failures in Distribution System Restoration

Zhaohong Bie, Mohammad Shahidehpour, Jian Zhong, Chen Chen
6 citations
IEEE Transactions on Power Systems
Smart Grid Security and Resilience
1.97
article

Strategic SDN-Based Microgrid Formation for Managing Communication Failures in Distribution System Restoration

Zhaohong Bie, Mohammad Shahidehpour, Jian Zhong, Chen Chen
article en
6 citations

Abstract

Grid modernization has increased the reliance of power networks on cyber networks within distribution systems (DSs), heightening their vulnerability to disasters. Communication network failures significantly impede DS load recovery by diminishing observation and control. Prior research has largely ignored the need for integrated recovery of DS power and cyber networks' centralized control. Indeed, communication network restoration is critical for speedy load recovery through DS automation based microgrid formation. This paper exploits the data routing capabilities of software-defined networking (SDN) to enhance centralized control recovery in DS communication networks, incorporating it into a comprehensive DS restoration model. This model, tailored to the control requirements of load restoration, strategically allocates limited communication resources to re-establish connections between the operation center and terminal devices. Subsequently, DS automation is employed to orchestrate DS microgrid formation for power resupply. Additionally, we introduce a cyclic algorithm designed to optimize the load recovery via a multi-step, cooperative process. The efficacy of the proposed method is demonstrated on IEEE 33-node and IEEE 123-node test feeders.

IEEE Transactions on Power SystemsVol. 40(3)
Illinois Institute of Technology (US), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 13%
Smart Grid Security and Resilience
1.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.