Transient Islanding Constrained Resilient Planning of Distribution System to Achieve Secure MG Formation

Power distribution system is vulnerable to natural disasters, when natural disasters occur, its resilience can be improved by formation of MGs. However, unsafe unplanned islands may trigger cascade shedding of DGs, leading to the failure of forming MG. Therefore, a new resilient investment planning method for distribution systems is proposed in this paper, which not only considers the static safe operation constraints before and after random accidents, but also incorporates the transient island safety constraints. The problem is formulated as a two-stage stochastic programming model with transient constraints. Since the problem cannot be solved directly, a simulation-assisted artificial intelligence method is proposed, in which frequency response simulation under stochastic interrupt of distribution system is built, and an extreme learning machine-based method is used to extract the relationship between the interrupted line power and the lowest frequency of the formed MG. Then it is embedded into the optimization problem. The proposed model and method are verified by a 37-node distribution system to demonstrate its superiority.

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Publication Details

Published
2025-02-15
DOI
https://doi.org/10.1109/cpeee64598.2025.10987307
Primary Topic
Smart Grid and Power Systems
Type
article
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article

Transient Islanding Constrained Resilient Planning of Distribution System to Achieve Secure MG Formation

Xiaobo Dou, Zongqiang Qi, Yi Zhang
Smart Grid and Power Systems
article

Transient Islanding Constrained Resilient Planning of Distribution System to Achieve Secure MG Formation

Xiaobo Dou, Zongqiang Qi, Yi Zhang
article en

Abstract

Power distribution system is vulnerable to natural disasters, when natural disasters occur, its resilience can be improved by formation of MGs. However, unsafe unplanned islands may trigger cascade shedding of DGs, leading to the failure of forming MG. Therefore, a new resilient investment planning method for distribution systems is proposed in this paper, which not only considers the static safe operation constraints before and after random accidents, but also incorporates the transient island safety constraints. The problem is formulated as a two-stage stochastic programming model with transient constraints. Since the problem cannot be solved directly, a simulation-assisted artificial intelligence method is proposed, in which frequency response simulation under stochastic interrupt of distribution system is built, and an extreme learning machine-based method is used to extract the relationship between the interrupted line power and the lowest frequency of the formed MG. Then it is embedded into the optimization problem. The proposed model and method are verified by a 37-node distribution system to demonstrate its superiority.

Southeast University (CN)
Climate action
Openalex Percentile: Top 92%
Smart Grid and Power Systems
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