Smart Meter Synthetic Data Generator development in python using FBProphet - P., Ezhilarasi; L., Ramesh; Liu, Xiufeng; Holm-Nielsen, Jens Bo (Software impacts, 2023)
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. •Smart meter becomes the most researched area in the energy sector due to its benefits for consumers and utilities.•The need for powerful algorithms in smart meter data analytics increases as data grows.•In smart meter data analytics, performance of algorithms is improved by testing them with real-time data.•To test the effectiveness of developed algorithms, a large amount of real-time data is required.•Obtaining smart meter data sets is difficult due to privacy and security policies in many countries.•Synthetic data are widely utilized to mitigate the above problem without compromising privacy and security issues.