Synthetic Energy Data Generation Using Time Variant Generative Adversarial Network
نویسندگان
چکیده
Energy consumption data is being used for improving the energy efficiency and minimizing cost. However, obtaining has two major challenges: (i) collection very expensive, time-consuming, (ii) security privacy concern of users which can be revealed from actual data. In this research, we have addressed these challenges by using generative adversarial networks generating profile. We successfully generated synthetic similar to real On basis recent research conducted on TimeGAN, implemented a framework generation that could useful in analysis create business solutions. The real-world dataset, consisting year 2020 Australian states Victoria, New South Wales, Australia, Queensland Tasmania. results implementation evaluated various performance measures are showcased visualizations along with Principal Component Analysis (PCA) t-distributed stochastic neighbor embedding (TSNE) plots. Overall, experimental show Synthetic proposed possess characteristics dataset high comparison accuracy.
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ژورنال
عنوان ژورنال: Electronics
سال: 2022
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics11030355