Research on Informatization Construction of Digital Substation in Smart Grid

Guo, You Guang; Yuan, Hui; Zhuang, Yan; Xu, Jie; Zhang, Yintie

doi:10.1088/1755-1315/632/4/042089

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…The final algorithm model consists of three modules: multi-level knowledge mapping module, state detection module, and fault diagnosis module. And the algorithm model is shown in the figure below [5][6]. Firstly, the online data of each piece of equipment is obtained, and the state is judged by the historical data of the weapon and equipment in normal operation.…”

Section: Substation Equipment Operation Fault Diagnosis Model Constru...mentioning

confidence: 99%

Research on Knowledge Graph-based Fault Diagnosis Method for Substation Equipment Operation

Zhang

Huang²,

Li³

et al. 2023

J. Phys.: Conf. Ser.

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The current image processing-based fault diagnosis method for substation equipment operation realizes fault diagnosis by monitoring the thermal status of the equipment, which leads to low diagnostic accuracy due to the lack of analysis of alarm signals. In this regard, the research of substation equipment operation fault diagnosis method based on knowledge mapping is proposed. A fault diagnosis model is established by building a behavior map of substation accident-like alarm signals, analyzing the alarm behavior as well as the causes of faults, and predicting the posterior probability of faults. In the experiment, the diagnosis accuracy of the proposed method is verified. The analysis of the experimental results shows that the fault diagnosis model constructed by the proposed method has good diagnostic performance and high diagnostic accuracy.

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Section: Substation Equipment Operation Fault Diagnosis Model Constru...mentioning

confidence: 99%

Research on Knowledge Graph-based Fault Diagnosis Method for Substation Equipment Operation

Zhang

Huang²,

Li³

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…Guo et al. [1] elaborated on the specific architecture and networking of intelligent substations, proposed the current problems in intelligent substations, and put forward a new system integration architecture design concept for the development trend of intelligent and integrated substation equipment. Zhang et al.…”

Section: Related Workmentioning

confidence: 99%

“…In the past few years, many studies have focused on intelligence substation. Guo et al [1] elaborated on the specific architecture and networking of intelligent substations, proposed the cur-rent problems in intelligent substations, and put forward a new system integration architecture design concept for the development trend of intelligent and integrated substation equipment. Zhang et al [2] introduced the four modules of the upgraded intelligent distribution station monitoring system and then elaborated on the development of the intelligent distribution station inspection control system.…”

Section: Related Workmentioning

confidence: 99%

Deep learning‐based substation remote construction management and AI automatic violation detection system

Yan

et al. 2022

IET Generation Trans & Dist

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Workplace video surveillance and timely response to operational violations are critical to avoid operator injuries at power construction sites. Here, a system that combines remote substation construction management and artificial intelligence object detection techniques to intellectualize the power construction management process and identify violations during construction in real time is proposed. To improve the detection accuracy, a data augmentation method, including three operations: (1) object segmentation and background fusion; (2) partial erasing; and (3) other basic transformations, is also proposed. Six variants of the You Only Look Once (YOLO) model are trained as detectors for comparative experiments on a dataset collected at the practical construction site. The experimental results show that the detection precision and recall of the YOLOv5‐s model are 0.852 and 0.922, with high accuracy and low miss rate, which meet the requirements of robustness and accuracy in detecting realistic power construction violations.

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“…This type of information fusion is increasingly used to diagnose defects in capacitive substation equipment [ 23 , 24 ]. However, the data acquisition of both detection methods is independent, the hardware integration of the acquisition system is low, and with the maturity of big data technology, the digitalization and visualization of the grid system are becoming significant directions of development in the industry [ 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection

Chen,

Zhu,

Meng

et al. 2023

Sensors

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Capacitive equipment refers to its insulation design using the principle of capacitance of electrical equipment, mainly by a variety of different capacitive components in series. Most of the equipment in the substation is capacitive equipment. Once an insulation failure occurs, it will lead to extremely serious consequences. Monitoring grid overvoltage and insulation degradation of capacitive equipment is an effective means to ensure the stable operation of the power system. Therefore, in order to enhance the health management of capacitive equipment, including transformers, bushings, and current transformers, and to mitigate the risk of severe failures, it is imperative to conduct broad-spectrum frequency-domain online monitoring of overvoltages, dielectric losses, and partial discharge. However, the current monitoring work requires the utilization of multiple detection apparatuses. Aiming at the disadvantage that the existing inspection is not well integrated and requires a combination of multiple devices. This paper proposes a smart grid overvoltage identification system that utilizes partial discharge (PD) signals in correlation with dielectric loss detection. The system achieves synchronous detection of dielectric loss and high-frequency partial discharge by synchronously and in real-time acquiring four current signals from the power grid, enhancing the integration level of the hardware system.

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Research on Informatization Construction of Digital Substation in Smart Grid

Cited by 7 publications

References 6 publications

Research on Knowledge Graph-based Fault Diagnosis Method for Substation Equipment Operation

Research on Knowledge Graph-based Fault Diagnosis Method for Substation Equipment Operation

Deep learning‐based substation remote construction management and AI automatic violation detection system

A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection

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