Evaluating Recursive Blind Forecast Against API and Baseline: A Puerto Rican Case Study on Solar Irradiance for Normal and Extreme Weather-Reference-Cited by-同舟云学术

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Evaluating Recursive Blind Forecast Against API and Baseline: A Puerto Rican Case Study on Solar Irradiance for Normal and Extreme Weather

Published:2023-10-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Energy Conversion Congress and Exposition (ECCE)
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Author:

Sundararajan Aditya¹,Olama Mohammed²,Ferrari Maximiliano¹,Ollis Ben³,Massol Arturo⁴,Liu Guodong¹,Chen Yang⁵

Affiliation:

1. Oak Ridge National Laboratory,EEID,Oak Ridge,TN,USA

2. Oak Ridge National Laboratory,CSED,Oak Ridge,TN,USA

3. Oak Ridge National Laboratory,NSSD,Oak Ridge,TN,USA

4. University of Puerto Rico Mayaguez,Department of Biology,Mayaguez,PR,USA

5. North Carolina Agricultural and Technical State University,Department of Industrial & Systems Engineering,Greensboro,NC,USA

Funder

Office of Energy Efficiency and Renewable Energy

Battelle

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10361838/10361943/10362867.pdf?arnumber=10362867

Reference18 articles.

1. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria

2. Regression and Generalized Additive Model to Enhance the Performance of Photovoltaic Power Ensemble Predictors

3. Global Solar Radiation Forecasting Based on Hybrid Model with Combinations of Meteorological Parameters: Morocco Case Study

4. Solar Radiation Prediction Using Different Machine Learning Algorithms and Implications for Extreme Climate Events

5. Deep Learning Approaches for Long-Term Global Horizontal Irradiance Forecasting for Microgrids Planning

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