Unsupervised Hybrid Deep Generative Models for Photovoltaic Synthetic Data Generation

This paper contributes to the field of deep generative learning applied to solar photovoltaic (PV) synthetic data generation problems by exploring Deep Generative Model (DGM) that combines Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN), i.e., VAEGAN. We build upon knowledge...

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Bibliographic Details

Published in:	IEEE Power & Energy Society General Meeting pp. 1 - 5
Main Authors:	Rosa de Jesus, Dan A., Mandal, Paras, Senjyu, Tomonobu, Kamalasadan, Sukumar
Format:	Conference Proceeding
Language:	English
Published:	IEEE 26.07.2021
Subjects:	Data models Deep learning Feature extraction Generative adversarial networks Photovoltaic systems Privacy Solar Photovoltaic Synthetic Data Variational Autoen-coders
ISSN:	1944-9933
Online Access:	Get full text
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