A Power Quality Monitoring Data Management Scheme Based on Distributed Database

2013 ◽  
Vol 732-733 ◽  
pp. 1410-1414
Author(s):  
Qing Qing Zhang ◽  
Qing Yu Wang ◽  
Gao Feng Zhang ◽  
Yi Zhang ◽  
Lan Xu Wu
Keyword(s):  
Power Quality ◽  
Distributed Database ◽  
Database System ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Storage Space ◽  
Power Quality Monitoring ◽  
Management Scheme ◽  
Master Station ◽  
Distributed Database System

Currently the massive power quality monitoring data are stored in the centralized database of the monitoring master station, the problems such as large storage space; low query retrieval speed; low reliability and poor scalability will be caused. This paper proposes a data management scheme for massive power quality monitoring data based on the distributed database system. The monitoring data of different power quality indexes are stored in the distributed servers of the existing monitoring sub-stations; the server of monitoring master station is used for storing data characteristics value and data indexes, it is also used for unified management of distributed database system. The scheme takes full advantage of each servers storage space and network bandwidth, and saves the storage space and improves the access efficiency.

A New Distributed Mining Association Rules Algorithm in Distributed Database System

2010 ◽  
Vol 143-144 ◽  
pp. 658-662
Author(s):  
Shu Tao Gao
Keyword(s):  
Data Storage ◽  
Association Rules ◽  
Distributed Database ◽  
Database System ◽  
Storage Space ◽  
Round Trip ◽  
Frequent Item ◽  
Local Candidate ◽  
Distributed Database System ◽  
Frequent Item Sets

The traditional algorithms create the local candidate sets firstly, and then determine whether the local frequent item sets is the global frequent item sets by the traffic between the nodes. The most different between the proposed algorithm and the traditional algorithms is that it firstly generates all the local frequent item sets at each node and then communicates to the top point. At the top point, there are four cases to deal with all the local frequent item sets. For the fastest case, the determination could be made by the completion of round-trip communications. At the same time, all the operations of this algorithm are completed not by traditional data storage but by a new data storage in which the item is considered as the keyword. The method can save storage space, especially for sparse data. So the support can be calculated by the intersection of the transaction sets, which is much easier than by accessing to the database. Finally, the association rules in the distributed database are mined

scholarly journals Automatically detecting and correcting errors in power quality monitoring data

2017 ◽  
Author(s):  
Steven Blair ◽  
Campbell Booth ◽  
Gillian Williamson ◽  
Alexandros Poralis ◽  
Victoria Turnham
Keyword(s):  
Power Quality ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Power Quality Monitoring

Fault Location Method in Complex Power Network Based on Power Quality Monitoring Data

2013 ◽  
Vol 732-733 ◽  
pp. 1320-1327
Author(s):  
Jian Lan ◽  
Dong Xu Wang ◽  
Xue Zheng ◽  
Kai Pei Liu ◽  
Cai Xia Yang
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Fault Location ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Fault Line ◽  
Location Method ◽  
Voltage Dip ◽  
Power Quality Monitoring ◽  
Trained Neural Network

In this paper, a fault location method using power quality monitoring data is proposed. The fault location is divided into two classes including fault line recognition and fault distance calculation. Along the each power line in the target network some fictitious fault points are set and the fault voltage of each monitoring bus is calculated. The voltage dip calculation results and the fault line data are matched to form the learning samples and then train the designed fault line recognition BP artificial neural network. The trained neural network searches the fault line when actual fault occurs. After it finishes fault line searching the fault position is calculated using the function of voltage dip amplitude and fault position. The correctness and effectiveness of the proposed method is proved by the simulation results in standard IEEE-14 bus system.

scholarly journals Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

2022 ◽  
Vol 119 (1) ◽  
pp. 359-369
Author(s):  
Qiang Yu ◽  
Xiankai Chen ◽  
Xiaoyue Li ◽  
Chaoqun Zhou ◽  
Zhichao Li
Keyword(s):  
Power Quality ◽  
Quality Evaluation ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Power Quality Monitoring ◽  
Target Theory
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