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Machine learning-based model for prediction of power consumption in smart grid
Joint Authors
Tiwari, Shamik
Jain, Anurag
Yadav, Kusum
Ramadan, Rabi
Source
The International Arab Journal of Information Technology
Issue
Vol. 19, Issue 3 (31 May. 2022), pp.323-329, 7 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2022-05-31
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
An electric grid consists of transformers, generation centers, communication links, control stations, and distributors.
Collectively these components help in moving power from one electricity station to commercial and domestic consumers.
Traditional grid stations can’t predict the dynamic need of consumers’ electricity.
Furthermore, these traditional grids are not sufficiently strong and adaptable.
This is the driving force for the transition towards a smart grid.
A modern smart grid is a self-healing, long-lasting electrical system that can adapt to changing client needs.
Machine learning has aided in grid stability calculation in the face of dynamically shifting consumer demands.
By avoiding a breakdown, the smart grid has been transformed into a reliable smart grid.
The authors of this study used a variety of machine learning-based algorithms to estimate grid stability to avoid a breakdown situation.
An open-access dataset lying on Kaggle repository has been used for experimental work.
Experiments are conducted in a simulation environment generated through Python.
Using the Bagging classifier algorithm, the suggested model has attained an accuracy level of 97.9% while predicting the load.
A precise prediction of power demand will aid in the avoidance of grid failure, hence improving grid stability and robustness.
American Psychological Association (APA)
Tiwari, Shamik& Jain, Anurag& Yadav, Kusum& Ramadan, Rabi. 2022. Machine learning-based model for prediction of power consumption in smart grid. The International Arab Journal of Information Technology،Vol. 19, no. 3, pp.323-329.
https://search.emarefa.net/detail/BIM-1437348
Modern Language Association (MLA)
Tiwari, Shamik…[et al.]. Machine learning-based model for prediction of power consumption in smart grid. The International Arab Journal of Information Technology Vol. 19, no. 3 (May. 2022), pp.323-329.
https://search.emarefa.net/detail/BIM-1437348
American Medical Association (AMA)
Tiwari, Shamik& Jain, Anurag& Yadav, Kusum& Ramadan, Rabi. Machine learning-based model for prediction of power consumption in smart grid. The International Arab Journal of Information Technology. 2022. Vol. 19, no. 3, pp.323-329.
https://search.emarefa.net/detail/BIM-1437348
Data Type
Journal Articles
Language
English
Record ID
BIM-1437348