Towards An Improved Understanding of PV System Degradation Behavior and Robust Estimation of PLR |
Ange Dominique Yao1,2, William C. Oltjen1,2, Manjunath Matam3, Hubert Seigneur3, Laura Bruckman1,2, Roger H. French1,2, Kristopher O. Davis3,4,5, Mengjie Li3,4 1SDLE Research Center, Case Western Reserve University (CWRU), Cleveland, OH, United States /2Department of Materials Science and Engineering, CWRU, Cleveland, OH, United States /3Florida Solar Energy Center (FSEC), University of Central Florida (UCF), Cocoa, FL, United States /4Resilient, Intelligent and Sustainable Energy Systems (RISES) Cluster, UCF, Orlando, FL, United States /5Department of Materials Science and Engineering, Orlando, FL, United States |
The surge in photovoltaic (PV) data availability marks a pivotal juncture in the study of solar energy, particularly as the world grapples with climate change challenges. Harnessing this PV data, this study conducts a comprehensive time series analysis of PV systems across diverse climate zones, focusing on Florida and Ohio. Datasets from multiple sources are thus subjected to rigorous quality assessment and filtering processes and advanced techniques like XbX Regression, and Facebook Prophet are employed to model time series data in order to calculate the PV Performance Loss Rates (PLRs). A comparative analysis between these methods and the rewsulting PLR values across these zones will then be conducted to understand the degradation behaviors of PV systems. |