Lightning risk estimation and preventive control method for power distribution networks referring to the indeterminacy of wind power and photovoltaic

Xu, Yang; Tong, Chong Wen; Xiang, Min; Wang, Tao; Xu, Jing; Zheng, Jianhua

doi:10.1016/j.epsr.2022.108896

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Numerous electrical discharge protection measures, such as lightning rod installations, have been implemented, improving insulation levels. However, the ESI caused by electrical discharges is significant according to operational experience [27]. They contribute significantly to both temporary and permanent interruptions [28].…”

Section: Energy Supply Interruptions: Electrical Dischargesmentioning

confidence: 99%

Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges

Santos,

Faria,

Lopes

et al. 2023

Energies

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Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to power utilities and consumer units: financial losses, damage to power distribution reliability, power quality deterioration, etc. Most studies in the specialized literature concerning faults in power distribution systems present methodologies for detecting, classifying, and locating faults after their occurrence. In contrast, the main aim of this study is to prevent faults by estimating the city regions whose power grid is most vulnerable to them. In this sense, this work incorporates a geographical-space study via a spatial data analysis using the local variable electrical discharge density that can increase fault risks. A geographically weighted spatial analysis is applied to data aggregated by regions to produce thematic maps with the city regions whose feeders are more vulnerable to failures. The spatial data analysis is implemented in QGIS and R programming environments. It is applied to the real data of faults in distribution power grid transformers and electrical discharges in a medium-sized city with approximately 200,000 inhabitants. In this study, we highlight a moderate positive correlation between electrical discharge density and the percentage of faults in transformers by regions in the central and western areas of the city under study.

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Section: Energy Supply Interruptions: Electrical Dischargesmentioning

confidence: 99%

Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges

Santos,

Faria,

Lopes

et al. 2023

Energies

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“…The power grid stability situation knowledge map uses the graph model to describe the relationship between power grid stability situation knowledge and power grid physical equipment and realizes the direct expression of power grid stability situation knowledge [10][11][12][13][14][15]. The power grid stability situation knowledge graph can be divided into a system-level knowledge graph and a device-level knowledge graph according to the dispatcher's concern level, which realizes the hierarchical knowledge of the power grid stability situation and helps dispatchers intuitively understand the power grid stability situation information [16][17][18][19]30].…”

Section: Analysis Of Knowledge Graph Construction Technologymentioning

confidence: 99%

“…In addition, the existing text data of the distribution network presents the characteristics of multiple types and small volumes, which makes it difficult to effectively support the training of the conventional deep learning model [7][8][9][10][11][12]. Therefore, it is urgent to extract and refine the multi-source heterogeneous distribution network text data into knowledge with the help of intelligent technology and organize this knowledge into structured and visual representation forms.…”

Section: Introductionmentioning

confidence: 99%

Research on distribution network fault processing technology based on knowledge of graph

Li,

Zhao,

Zhuang

et al. 2023

PLoS ONE

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Safety and reliability are the basis of the development of a distribution network. To analyze the risk transmission process in the distribution network and ensure the safe and reliable operation of the power system, this paper intends to use the knowledge graph method to realize the risk analysis of the distribution network information system. Firstly, the knowledge graph method is used to extract and integrate the risk knowledge of the multi-dimensional information collected by the distribution network. Secondly, the knowledge graph model of distribution network risk analysis is constructed, and the multi-dimensional distribution network fault handling and knowledge graph construction oriented to the feeder and platform area are designed. The distribution line parameters of the low-voltage distribution network model, neutral point grounding mode, and different fault types are analyzed, and the non-planned island is searched based on the knowledge graph adjacency matrix. Finally, combined with the simulation experiment, it is verified that the proposed method can effectively depict the information risk process of the distribution network. The structure of this paper starts from the multi-node complex distribution network, combined with a knowledge graph and deep learning method, which can solve the distribution network fault more quickly.

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Active Distribution Grid Risk Prevention and Control Method Based on Biological Immune Mechanism

Zhao,

Ma,

Yue

et al. 2024

Lecture Notes in Electrical Engineering

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Lightning risk estimation and preventive control method for power distribution networks referring to the indeterminacy of wind power and photovoltaic

Cited by 5 publications

References 7 publications

Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges

Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges

Research on distribution network fault processing technology based on knowledge of graph

Active Distribution Grid Risk Prevention and Control Method Based on Biological Immune Mechanism

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