Status Evaluation of Power Secondary Equipment Based on Big Data of Monitoring

Duan, Xiangxi; Long, Cheng; Feng, Shilin; Luo, Rongsen; Gao, Yiwen; Sun, Yongchao

doi:10.1109/isgt-asia.2019.8880945

Cited by 4 publications

(1 citation statement)

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“…As a new computing model framework, cloud computing is more suitable for processing massive online monitoring data of distribution equipment [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

State Evaluation Method of Distribution Equipment Based on Health Index in Big Data Environment

Xue¹,

Li²,

Wang³

et al. 2022

Mathematical Problems in Engineering

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Aiming at the problems of time-consuming and low accuracy in the existing state evaluation methods of distribution equipment, a state evaluation method of distribution equipment based on health index in big data environment is proposed. Firstly, in order to optimize the time-consuming of big data analysis on large-scale and distributed clusters, a distribution equipment condition monitoring data platform in big data environment is designed, and a hive based relational online analysis method (ROLAP) is proposed. Secondly, the health index (HI) is introduced as the evaluation index to evaluate the health status of distribution equipment. According to the different influence degree of different fault factors on the equipment status, a comprehensive multifactor fault rate correction model is obtained, and the method based on success flow is used to solve the model to improve the accuracy of state evaluation. Finally, experiments show that when the data volume of distribution equipment is 60 GB, the time of the proposed method is only 30.0 s, which is far lower than 73.6 s and 82.5 s of the comparison method. The evaluation accuracy of the proposed method is 95.1%, while the evaluation accuracy of the comparison method is only 82.4% and 73.1%, respectively. Therefore, the proposed method can effectively improve the efficiency of distribution equipment condition evaluation.

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“…As a new computing model framework, cloud computing is more suitable for processing massive online monitoring data of distribution equipment [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

State Evaluation Method of Distribution Equipment Based on Health Index in Big Data Environment

Xue¹,

Li²,

Wang³

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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Control Networks and Smart Grid Teleprotection: Key Aspects, Technologies, Protocols, and Case-Studies

et al. 2020

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The appeal for more reliable, efficient and resilient power grids has become indispensable with the recent technological development and ever-increasing demand for electrical energy. These goals might be achieved by introducing sensors and actuators in the power grid, with the purpose of enabling a smart control of the power network. All power devices must be connected using a reliable communication network, which should be able to operate even when the power grid fails. Currently, several communication technologies have been applied for supporting this new application scenario. This paper aims for reviewing both academic and market use cases for technologies applied to the mission-critical, control networks and Smart Grid applications, such as teleprotection, self-healing, communication with control centers and field devices, among others. More specifically, the key aspects, potential technologies, main protocols and use cases of operating data networks in energy transmission, power distribution and smart grid environments, including circuit and packet switching technologies, are discussed into details. Furthermore, resilience and the main telecommunications technologies used in power grids, as well, the correlation among them, are exploited in practical point of view. The article provides a broad discussion on the best telecommunication options to build the emerging intelligent energy distribution systems, covering control networks, teleprotection, and smart grid applications.

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