Coordinated Control of Dynamic Zoning and Load Shedding for Enhancing Fault Recovery of High-Penetration Renewable Distribution Network

With the increasing penetration of distributed renewable energy, distribution networks face severe operational challenges during grid faults, where rapid power restoration and system stability are crucial. Traditional fault restoration strategies often rely on static dynamic zoning or simple power balancing, neglecting the critical electrical interactions among nodes. To address these limitations, this paper innovatively proposes a hierarchical coordinated control framework for distribution network fault recovery, combining dynamic zoning and coordinated load shedding. The core novelty of this research lies in integrating the node electrical correlation degree into the load grading process to assist in coordinating dynamic network dynamic zoning. By comprehensively evaluating real-time power flow, the regulation capabilities of distributed resources, and intra-region electrical correlations, the proposed framework adaptively optimizes both the zoning structure and the load shedding sequence. Simulation results demonstrate that, compared with conventional static or uncoordinated methods, the proposed approach significantly minimizes load loss while improving grid recovery efficiency and voltage stability. Ultimately, this coordinated control strategy effectively enhances the resilience and operational safety of high-penetration renewable distribution networks, providing robust support for distribution network operations under a high proportion of renewable energy integration.

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Publication Details

Journal
Electronics
Published
2026-06-09
DOI
https://doi.org/10.3390/electronics15122542
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

Coordinated Control of Dynamic Zoning and Load Shedding for Enhancing Fault Recovery of High-Penetration Renewable Distribution Network

Yudun Li, Maozeng Lu, Wenliang Yin, Kuan Li
Electronics
Optimal Power Flow Distribution
article

Coordinated Control of Dynamic Zoning and Load Shedding for Enhancing Fault Recovery of High-Penetration Renewable Distribution Network

Yudun Li, Maozeng Lu, Wenliang Yin, Kuan Li
article en

Abstract

With the increasing penetration of distributed renewable energy, distribution networks face severe operational challenges during grid faults, where rapid power restoration and system stability are crucial. Traditional fault restoration strategies often rely on static dynamic zoning or simple power balancing, neglecting the critical electrical interactions among nodes. To address these limitations, this paper innovatively proposes a hierarchical coordinated control framework for distribution network fault recovery, combining dynamic zoning and coordinated load shedding. The core novelty of this research lies in integrating the node electrical correlation degree into the load grading process to assist in coordinating dynamic network dynamic zoning. By comprehensively evaluating real-time power flow, the regulation capabilities of distributed resources, and intra-region electrical correlations, the proposed framework adaptively optimizes both the zoning structure and the load shedding sequence. Simulation results demonstrate that, compared with conventional static or uncoordinated methods, the proposed approach significantly minimizes load loss while improving grid recovery efficiency and voltage stability. Ultimately, this coordinated control strategy effectively enhances the resilience and operational safety of high-penetration renewable distribution networks, providing robust support for distribution network operations under a high proportion of renewable energy integration.

ElectronicsVol. 15(12)
Shandong University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 11%
Optimal Power Flow Distribution
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Coordinated Control of Dynamic Zoning and Load Shedding for Enhancing Fault Recovery of High-Penetration Renewable Distribution Network — Yudun Li, Maozeng Lu, et al. · Electronics (2026) | TGRS Research Map | TGRS