Skip to main navigation Skip to search Skip to main content

Smart Meter Synthetic Data Generator development in python using FBProphet

  • P. Ezhilarasi*
  • , L. Ramesh
  • , Xiufeng Liu
  • , Jens Bo Holm-Nielsen
  • *Corresponding author for this work
  • Dr. M.G.R Educational and Research Institute
  • Aalborg University

Research output: Contribution to journalJournal articleResearchpeer-review

340 Downloads (Orbit)

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 languageEnglish
Article number100468
JournalSoftware Impacts
Volume15
ISSN2665-9638
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Smart meter
  • Data generator
  • Time-series
  • Synthetic data

Fingerprint

Dive into the research topics of 'Smart Meter Synthetic Data Generator development in python using FBProphet'. Together they form a unique fingerprint.

Cite this