Modeling and processing big data of power transmission grid substation using Neo4j

A Perçuku, D Minkovska, L Stoyanova - Procedia Computer Science, 2017 - Elsevier
Procedia Computer Science, 2017Elsevier
Data sizes in power transmission grid have increased rapidly, which results in challenges.
These data are large in volume; they are generated fast and in different format, and come
from various sources such as electrical substations. Traditional relational databases are
inadequate in terms of response time and have impact on performance when applied to very
large data sets, and also make this database difficult to evolve according to business needs.
To address this shortcoming, the Big Data implementations are leveraging new technologies …
Abstract
Data sizes in power transmission grid have increased rapidly, which results in challenges. These data are large in volume; they are generated fast and in different format, and come from various sources such as electrical substations. Traditional relational databases are inadequate in terms of response time and have impact on performance when applied to very large data sets, and also make this database difficult to evolve according to business needs. To address this shortcoming, the Big Data implementations are leveraging new technologies such as NoSQL data stores. This research paper aims and tries to improve this process by modeling and processing those data using Neo4j database, and presents modeling and processing the data of power transmission grid substation which has two power transformers, and then adding a new power transformer to simulate the evolving feature of Neo4j database according to the business needs.
Elsevier
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