Data-Driven Modeling and Analysis for Solar Generation Considering the Post-Snow Day Meteorology Factors-Reference-Cited by-同舟云学术

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Data-Driven Modeling and Analysis for Solar Generation Considering the Post-Snow Day Meteorology Factors

Published:2023-10-15 Issue: Volume: Page:
ISSN:
Container-title:2023 North American Power Symposium (NAPS)
language:
Short-container-title:

Author:

Stenstadvolden Owen¹,Stenstadvolden Anders¹,Zhao Long¹,Kapourchali Mohammad Heidari²,Kapourchali Masoumeh Heidari³

Affiliation:

1. South Dakota School of Mines and Technology,Department of Electrical Engineering and Computer Science,Rapid City,USA

2. University of Alaska Anchorage,Department of Electrical Engineering,Anchorage,USA

3. University of Alaska Anchorage,Department of Computer Science and Engineering,Anchorage,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10318157/10318530/10318647.pdf?arnumber=10318647

Reference20 articles.

1. Snow Loss Modeling for Roof Mounted Photovoltaic Systems: Improving the Marion Snow Loss Model

2. Using On-site Ambient Temperature and Performance Ratio to Identify Days when Snow Cover Affects PV Plant Production

3. Snow Loss Prediction for Photovoltaic Farms Using Computational Intelligence Techniques

4. Systematic Analysis and Computational Intelligence Based Modeling of Photovoltaic Power Generation in Snow Conditions

5. Data-Driven Science and Engineering

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