Voltage Risk Zoning and Multi-Resource Coordinated Optimization for Active Distribution Networks Under Feeder Disconnection Faults

Sustainable electricity systems require reliable power supply and the effective integration of distributed renewable energy. In active distribution networks, feeder disconnection can threaten both objectives by causing undervoltage during load transfer and creating overvoltage or reverse power flow risks under high photovoltaic (PV) generation. This paper proposes a post-fault coordination method integrating voltage risk zoning, resource direction screening, and restoration optimization. The method combines voltage and interface conditions, electrical distance changes, and resource sensitivities to identify and rank feasible regulation directions according to their benefits and costs. An outer procedure updates the risk zones and candidate set around a lexicographic mixed-integer linear optimization that prioritizes load restoration, constraint violation mitigation, and operating cost. Tests on a modified IEEE 33-bus system reduce candidate directions by 40% while preserving near-complete load restoration and modeled voltage and interface limit compliance, although operating cost, PV curtailment, and total computation time increase. A complementary study on the IEEE 123-node feeder with a fixed restored topology achieves the same percentage reduction in dispatch variables with essentially unchanged cost and a shorter dispatch solution time. The results inform sustainable distribution-network operation by quantifying trade-offs among service restoration, renewable-energy use, operating cost, and computational burden; screening benefits depend on the flexibility retained and the operating conditions.

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Publication Details

Journal
Sustainability
Published
2026-11-06
DOI
https://doi.org/10.3390/su182111333
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

Voltage Risk Zoning and Multi-Resource Coordinated Optimization for Active Distribution Networks Under Feeder Disconnection Faults

Jiangping Jing, Gaige Liang, Ling Hao, Fei Xu et al.
2 links
Sustainability
Optimal Power Flow Distribution
article

Voltage Risk Zoning and Multi-Resource Coordinated Optimization for Active Distribution Networks Under Feeder Disconnection Faults

Jiangping Jing, Gaige Liang, Ling Hao, Fei Xu, Ye Guo
article en

Abstract

Sustainable electricity systems require reliable power supply and the effective integration of distributed renewable energy. In active distribution networks, feeder disconnection can threaten both objectives by causing undervoltage during load transfer and creating overvoltage or reverse power flow risks under high photovoltaic (PV) generation. This paper proposes a post-fault coordination method integrating voltage risk zoning, resource direction screening, and restoration optimization. The method combines voltage and interface conditions, electrical distance changes, and resource sensitivities to identify and rank feasible regulation directions according to their benefits and costs. An outer procedure updates the risk zones and candidate set around a lexicographic mixed-integer linear optimization that prioritizes load restoration, constraint violation mitigation, and operating cost. Tests on a modified IEEE 33-bus system reduce candidate directions by 40% while preserving near-complete load restoration and modeled voltage and interface limit compliance, although operating cost, PV curtailment, and total computation time increase. A complementary study on the IEEE 123-node feeder with a fixed restored topology achieves the same percentage reduction in dispatch variables with essentially unchanged cost and a shorter dispatch solution time. The results inform sustainable distribution-network operation by quantifying trade-offs among service restoration, renewable-energy use, operating cost, and computational burden; screening benefits depend on the flexibility retained and the operating conditions.

SustainabilityVol. 18(21)
State Grid Jiangsu Electric Power (China) (CN), Tsinghua University (CN)
Industry, innovation and infrastructure, Affordable and clean energy
Openalex Percentile: Top 26%
Optimal Power Flow Distribution
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