State fusion evaluation and fusion compression method of multi-source sensors in power distribution Internet of things

2020 ◽  
Author(s):  
Juan Liu ◽  
Liping Lu ◽  
Dengfeng Ju ◽  
Yongyong Jia ◽  
Jianhua Qin ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Compression Method ◽  
State Fusion

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

scholarly journals Technoeconomic Assessment Based on Active Context-Knowledge Orchestration for Power Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yuanshuo Zheng ◽  
Shujuan Sun ◽  
Chenyang Li ◽  
Jingtang Luo ◽  
Jiuling Dong ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Economic Benefits ◽  
Assessment Model ◽  
Learning Technology ◽  
Assessment Framework ◽  
Technical Performance ◽  
System Requirements ◽  
Context Knowledge ◽  
Technology And Economy

Power Internet of Things (abbreviated as PIoT) is the information infrastructure to provide ubiquitous perception ability for smart grid (abbreviated as SG). To better deploy and utilize PIoT, its perception ability must be comprehensively assessed in terms of technical performance and economic benefits. However, at present, there is no assessment framework for PIoT due to the high diversity and heterogeneousness of SG scenarios. Additionally, there is information overlap between metrics in the assessment framework. The assessment model which could remove redundant information between metrics and simplify the assessment framework is an urgent demand to improve the effectiveness and timeliness of assessment. Consequently, first, aiming at the power system requirements of complex and diverse, a general assessment framework is put forward to assess the ability of PIoT in terms of technology and economy. Next, the requirement characteristics of power distribution scenario (abbreviated as PDS) are precisely analyzed with active context-knowledge orchestration technology. The general assessment framework is instantiated to build an instantiation assessment scheme in PDS. Moreover, an assessment model is established based on the instantiation assessment scheme to assess the efficiency of PIoT in Beijing. Finally, the assessment model is further refined with the machine learning technology to improve the efficiency of assessment. This refinement model achieves the extraction of 4-dimensional metrics from 23-dimensional metrics for assessment and finally improves assessment efficiency by 82.6%.

scholarly journals An Enhanced K-Means Clustering Algorithm for Pattern Discovery in Big Data Analysis of 3-Phase Electrical Quantities

2018 ◽  
Vol 7 (4.44) ◽  
pp. 8
Author(s):  
Dikpride Despa ◽  
Gigih Forda Nama
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Internet Of Things ◽  
Power Distribution ◽  
Distribution System ◽  
Clustering Algorithm ◽  
Measurement Data ◽  
Power Distribution System ◽  
Multiple Sensors ◽  
Industry Standard

The Unila Internet of Things Research Group (UIRG) was developed online monitoring of power distribution system based on Internet of Things (IoT) technology on Department of Electrical Engineering University of Lampung (Unila), has been running for several months, this system monitored electrical quantities of 3-phase main distribution panel of H-building. The measurement system involve multiple sensors such current sensors and voltage sensors, the measurement data stored in to database server and shown the information in a real-time through a web-based application.Main objective of this research was to capture, analyze, and identified the knowledge pattern of electrical quantities data measurements, using Cross-Industry Standard Process for Data Mining (CRISP-DM) data mining framework, for helping the stake holders to continuous improvement of the quality of electricity services, the initial research limited to total 770847 electrical quantities recorded data that save on database system, since 1 September - 31 October 2018, the dataset consist of 21 attribute electrical quantities such as; voltage, current, power factor values, energy consumption, frequency, on H building 3-Phase main panel control.Rapidminer as leading application on knowledge discovery application was used to analyze the big data, K-Mean cluster algorithm implemented to identify the data pattern, the result indicated that 3-Phase load was unbalanced, and Phase-0 was the most utilized phase, based on from total 5 cluster analysis result. 

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