A post-fault island partitioning method for distribution networks considering overall frequency security and spatial nodal RoCoF constraints

For distribution networks with distributed generators, post-fault island partitioning can restore local power supply, whereas limited island inertia and frequency support may cause frequency security violations during load restoration. To address the limitations of conventional methods in simultaneously capturing the center-of-inertia frequency response and the spatial heterogeneity of nodal rate of change of frequency (RoCoF), this paper proposes a post-fault island partitioning method considering overall frequency security and spatial nodal RoCoF constraints. An island-level frequency response model is first established, in which the center-of-inertia RoCoF, frequency nadir, and quasi-steady-state frequency deviation are embedded into the stepwise load restoration process. A spatial nodal RoCoF model is then developed to identify local dynamic security risks that may be overlooked by center-of-inertia frequency indicators. Furthermore, nodal RoCoF checking is incorporated into the feasibility assessment of load restoration, and load blocks associated with RoCoF violations are adjusted to determine load block energization, partial load restoration, and final island partitioning results. Case studies on the IEEE 33-bus and IEEE 69-bus systems show that a restoration scheme satisfying center-of-inertia frequency constraints may still experience local nodal RoCoF violations. The proposed method can eliminate such local violations by adjusting selected load blocks, thereby improving the dynamic security of post-fault island partitioning schemes.

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Publication Details

Journal
Electric Power Systems Research
Published
2026-09-19
DOI
https://doi.org/10.1016/j.epsr.2026.114225
Primary Topic
Power System Optimization and Stability
Type
article
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A post-fault island partitioning method for distribution networks considering overall frequency security and spatial nodal RoCoF constraints

Jidong Chen, Zhipeng Yuan, Feng Lu, Haiyan Wang
Electric Power Systems Research
Power System Optimization and Stability
article

A post-fault island partitioning method for distribution networks considering overall frequency security and spatial nodal RoCoF constraints

Jidong Chen, Zhipeng Yuan, Feng Lu, Haiyan Wang
article en

Abstract

For distribution networks with distributed generators, post-fault island partitioning can restore local power supply, whereas limited island inertia and frequency support may cause frequency security violations during load restoration. To address the limitations of conventional methods in simultaneously capturing the center-of-inertia frequency response and the spatial heterogeneity of nodal rate of change of frequency (RoCoF), this paper proposes a post-fault island partitioning method considering overall frequency security and spatial nodal RoCoF constraints. An island-level frequency response model is first established, in which the center-of-inertia RoCoF, frequency nadir, and quasi-steady-state frequency deviation are embedded into the stepwise load restoration process. A spatial nodal RoCoF model is then developed to identify local dynamic security risks that may be overlooked by center-of-inertia frequency indicators. Furthermore, nodal RoCoF checking is incorporated into the feasibility assessment of load restoration, and load blocks associated with RoCoF violations are adjusted to determine load block energization, partial load restoration, and final island partitioning results. Case studies on the IEEE 33-bus and IEEE 69-bus systems show that a restoration scheme satisfying center-of-inertia frequency constraints may still experience local nodal RoCoF violations. The proposed method can eliminate such local violations by adjusting selected load blocks, thereby improving the dynamic security of post-fault island partitioning schemes.

Electric Power Systems ResearchVol. 265
Xi'an University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 20%
Power System Optimization and Stability
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