• Corpus ID: 239616485

Generating Multivariate Load States Using a Conditional Variational Autoencoder

@article{Wang2021GeneratingML,
  title={Generating Multivariate Load States Using a Conditional Variational Autoencoder},
  author={Chenguang Wang and Ensieh Sharifnia and Zhi Gao and Simon Tindemans and Peter Palensky},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.11435}
}
For planning of power systems and for the calibration of operational tools, it is essential to analyse system performance in a large range of representative scenarios. When the available historical data is limited, generative models are a promising solution, but modelling high-dimensional dependencies is challenging. In this paper, a multivariate load state generating model on the basis of a conditional variational autoencoder (CVAE) neural network is proposed. Going beyond common CVAE… 

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