Smart Meter Synthetic Data Generator development in python using FBProphet[Formula presented]

P. Ezhilarasi; L. Ramesh; Xiufeng Liu; Jens Bo Holm-Nielsen

doi:10.1016/j.simpa.2023.100468

Smart Meter Synthetic Data Generator development in python using FBProphet[Formula presented]

P. Ezhilarasi^*, L. Ramesh, Xiufeng Liu, Jens Bo Holm-Nielsen

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Data-science is a key component of modern science since it fuels AI, ML and data analytics, etc. As the electrical grid has been modernized into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm's workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. In this paper, using the prophet library, we code and develop a prediction-based Synthetic Data Generator GUI, which generate the synthetic data sets.

Original language	English
Article number	100468
Journal	Software Impacts
Volume	15
ISSN	2665-9638
DOIs	https://doi.org/10.1016/j.simpa.2023.100468
Publication status	Published - Mar 2023

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Keywords

Data generator
Smart meter
Synthetic data
Time-series

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10.1016/j.simpa.2023.100468Licence: CC BY 4.0

Open Access articleFinal published version, 1.35 MBLicence: CC BY 4.0

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title = "Smart Meter Synthetic Data Generator development in python using FBProphet[Formula presented]",

abstract = "Data-science is a key component of modern science since it fuels AI, ML and data analytics, etc. As the electrical grid has been modernized into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm's workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. In this paper, using the prophet library, we code and develop a prediction-based Synthetic Data Generator GUI, which generate the synthetic data sets.",

keywords = "Data generator, Smart meter, Synthetic data, Time-series",

author = "P. Ezhilarasi and L. Ramesh and Xiufeng Liu and Holm-Nielsen, {Jens Bo}",

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doi = "10.1016/j.simpa.2023.100468",

language = "English",

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AU - Ezhilarasi, P.

AU - Ramesh, L.

AU - Liu, Xiufeng

AU - Holm-Nielsen, Jens Bo

PY - 2023/3

Y1 - 2023/3

N2 - Data-science is a key component of modern science since it fuels AI, ML and data analytics, etc. As the electrical grid has been modernized into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm's workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. In this paper, using the prophet library, we code and develop a prediction-based Synthetic Data Generator GUI, which generate the synthetic data sets.

AB - Data-science is a key component of modern science since it fuels AI, ML and data analytics, etc. As the electrical grid has been modernized into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm's workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. In this paper, using the prophet library, we code and develop a prediction-based Synthetic Data Generator GUI, which generate the synthetic data sets.

KW - Data generator

KW - Smart meter

KW - Synthetic data

KW - Time-series

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DO - 10.1016/j.simpa.2023.100468

M3 - Journal article

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SN - 2665-9638

VL - 15

JO - Software Impacts

JF - Software Impacts

M1 - 100468

ER -

Smart Meter Synthetic Data Generator development in python using FBProphet[Formula presented]

Abstract

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Keywords

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