Mitigating Blackout Risk in Power Electronics Penetrated Power Systems through Metrics-Driven Inverter-Based Generator Placement

This paper investigates the strategic placement of inverter-based generators (IBGs) in power electronics penetrated (PE-penetrated) power systems, aiming to mitigate power blackout risk. Two metrics, namely distance of load to IBGs (DL2IBG) and Gini coefficient (GI), are employed to guide this placement strategy. DL2IBG assesses how concentrated the distribution of IBGs is in the network, while GI evaluates the uniformity of power generation among different IBGs. By setting the network configuration based on these metrics, the relationship between the metrics and the blackout risk evaluated through cascading failure simulation is examined. The simulation results on the IEEE 118-bus system emphasize the crucial role of determining GI across various DL2IBG in mitigating blackout risks, particularly as the penetration levels of IBGs vary. This research offers valuable and practical insights into optimizing the placement of IBGs to enhance the resilience of PE-penetrated power systems.

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Publication Details

Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11044005
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Mitigating Blackout Risk in Power Electronics Penetrated Power Systems through Metrics-Driven Inverter-Based Generator Placement

Chi K. Tse, Dong Liu, Biwei Li, Shuo Li
Microgrid Control and Optimization
article

Mitigating Blackout Risk in Power Electronics Penetrated Power Systems through Metrics-Driven Inverter-Based Generator Placement

Chi K. Tse, Dong Liu, Biwei Li, Shuo Li
article en

Abstract

This paper investigates the strategic placement of inverter-based generators (IBGs) in power electronics penetrated (PE-penetrated) power systems, aiming to mitigate power blackout risk. Two metrics, namely distance of load to IBGs (DL2IBG) and Gini coefficient (GI), are employed to guide this placement strategy. DL2IBG assesses how concentrated the distribution of IBGs is in the network, while GI evaluates the uniformity of power generation among different IBGs. By setting the network configuration based on these metrics, the relationship between the metrics and the blackout risk evaluated through cascading failure simulation is examined. The simulation results on the IEEE 118-bus system emphasize the crucial role of determining GI across various DL2IBG in mitigating blackout risks, particularly as the penetration levels of IBGs vary. This research offers valuable and practical insights into optimizing the placement of IBGs to enhance the resilience of PE-penetrated power systems.

Tianjin University (CN), City University of Hong Kong (HK)
Affordable and clean energy
Openalex Percentile: Top 83%
Microgrid Control and Optimization
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