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Vulnerability Identification of High Proportion Distributed Photovoltaic Power Distribution Network Based on EGAT
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Yufei WANG, Xiaoning LÜ, Hai SHI, Yunfeng WEI
Journal of Power Supply | 2026, 24(5) : 219 - 228
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Journal of Power Supply | 2026, 24(5): 219-228
• Power Electronic Dominated Power Systems •
Vulnerability Identification of High Proportion Distributed Photovoltaic Power Distribution Network Based on EGAT
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Yufei WANG, Xiaoning LÜ, Hai SHI, Yunfeng WEI
Affiliations
  • State Grid Jibei Electric Power Co., Ltd., Zhangjiakou Power Supply Company, Zhangjiakou 075000, China
Published: 2026-05-30 doi: 10.13234/j.issn.2095-2805.2026.5.219
Outline
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To address the complexities in regulating and operating distribution grids with a high proportion of distributed photovoltaic (PV) systems, which challenges conventional methods in vulnerability identification, a novel methodology utilizing an edge-feature graph attention network (EGAT) is proposed for state estimation and further identification of vulnerabilities via over-limit indicators. Initially, busbars within the distribution network are conceptualized as nodes of a graph, with transmission lines serving as edges, thus forming a topological dataset grounded in their connectivity matrix. Subsequently, the power of each transmission line and the voltages at the connected busbars are consolidated into an edge feature matrix. The employment of EGAT layers facilitates targeted feature extraction and learning, where attention weights are attributed to each node and transmission line. In response to various operational scenarios of the PV distribution network, the EGAT model undergoes training with the integration of transfer learning techniques. Ultimately, by establishing indices for node vulnerability and line vulnerability, a thorough evaluation of the network’s vulnerability under different scenarios is achieved. Demonstrative case studies validate the effectiveness of this approach in recognizing vulnerabilities within distribution networks with substantial integration of distributed PV systems, accurately identifying vulnerable nodes and lines induced by fluctuations in PV output and topological modifications.

Distributed photovoltaic  /  distribution network  /  vulnerability identification  /  edge-feature graph attention network  /  node vulnerability index  /  line vulnerability index
王宇飞, 吕晓宁, 时海, 魏云峰. 基于EGAT的高比例分布式光伏配电网的脆弱性辨识. 电源学报, 2026 , 24 (5) : 219 -228 . DOI: 10.13234/j.issn.2095-2805.2026.5.219
Yufei WANG, Xiaoning LÜ, Hai SHI, Yunfeng WEI. Vulnerability Identification of High Proportion Distributed Photovoltaic Power Distribution Network Based on EGAT[J]. Journal of Power Supply, 2026 , 24 (5) : 219 -228 . DOI: 10.13234/j.issn.2095-2805.2026.5.219
  • 2023 Mass Innovation Project of State Grid Zhangjiakou Power Supply Company(520107230002)
Year 2026 volume 24 Issue 5
32
5
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.5.219
  • Receive Date:2024-01-18
  • Online Date:2026-10-29
  • Published:2026-05-30
Article Data
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History
  • Received:2024-01-18
  • Revised:2024-04-12
  • Accepted:2024-05-06
Funding
2023 Mass Innovation Project of State Grid Zhangjiakou Power Supply Company(520107230002)
Affiliations
    State Grid Jibei Electric Power Co., Ltd., Zhangjiakou Power Supply Company, Zhangjiakou 075000, China
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表12种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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