Time-Series Imputation Using Graph Neural Networks and Denoising Autoencoders-Reference-Cited by-同舟云学术

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Time-Series Imputation Using Graph Neural Networks and Denoising Autoencoders

Published:2023-06-11 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 50th Photovoltaic Specialists Conference (PVSC)
language:
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Author:

Wieser Raymond¹,Fan Yangxin¹,Yu Xuanji¹,Braid Jennifer²,Shaton Avishai³,Hoffman Adam⁴,Spurgeon Ben⁵,Gibbons Daniel⁶,Bruckman Laura S.¹,Wu Yinghui¹,French Roger H.¹

Affiliation:

1. Case Western Reserve University,SDLE Research Center,Cleveland,OH,USA

2. Sandia National Laboratories,Albuquerque,NM,USA

3. SolarEdge,Herzliya,Israel

4. Maxeon Solar Technologies,Singapore

5. Brookfield Renewable,Toronto,Ontario,Canada

6. Bay4 Energy,Tucson,AZ,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10359507/10359504/10359805.pdf?arnumber=10359805

Reference24 articles.

1. Data processing and quality verification for improved photovoltaic performance and reliability analytics

2. Five-year performance and reliability analysis of monocrystalline photovoltaic modules with different backsheet materials

3. Comparison of Degradation Rates of Individual Modules Held at Maximum Power

4. Best practices for photovoltaic performance loss rate calculations

5. Outdoor PV System Monitoring—Input Data Quality, Data Imputation and Filtering Approaches

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