Load forecasting for smart grid using non-linear model in Hadoop distributed file system

The conventional electrical grid structure is evolving in recent years, enhancing with new technology. The new structure of power system ‘Smart grid’ is trying to get solution for the problems in conventional grid. In a smart grid environment, every end user is connected with the market. The control...

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Veröffentlicht in:	Cluster computing Jg. 22; H. Suppl 6; S. 13533 - 13545
Hauptverfasser:	Arun Jees, S., Gomathi, Venugopal
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.11.2019 Springer Nature B.V
Schlagworte:	Algorithms Artificial intelligence Big Data Classification Clustering Communications systems Complexity Computer Communication Networks Computer Science Decision trees Electric power grids Electric power systems Electrical loads Electricity Energy industry Forecasting Machine learning Neural networks New technology Operating Systems Processor Architectures Regression analysis Smart grid Support vector machines Time series Variables k-means clustering Forecasting model Support vector machine Hadoop framework
ISSN:	1386-7857, 1573-7543
Online-Zugang:	Volltext
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