bibliography.bib

@techreport{Marion2013,
author = {Marion, William F and Dobos, Aron P},
institution = {National Renewable Energy Laboratory},
doi = {10.2172/1089596},
title = {{Rotation Angle for the Optimum Tracking of One-Axis Trackers}},
number = {NREL/TP-6A20-58891},
year = {2013},
url = {https://www.nrel.gov/docs/fy13osti/58891.pdf}
}
@misc{CypressCreekRenewables2019,
journal = {U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy},
number = {DE-FOA-0001840},
title = {{Capturing the full benefits of bifacial modules to achieve an LCOE of 3c/kWh through a regional optimization of the electrical architecture}},
url = {https://www.energy.gov/sites/prod/files/2019/02/f59/101337.pdf},
year = {2019}
}
@inproceedings{Mikofski_8547323,
abstract = {Accurate performance prediction of large PV systems with shading is challenging because computational complexity increases with system size. Solar Farmer is a new PV performance model with 3-D shading. Comparing predictions with measurements from the NIST PV test bed we observed a decrease in the annual difference of 17{\%} between module and submodule shading. By varying the resolution of shading from module to cell level, we also determined that 5 points persubmodule, resulting in a 0.5{\%} annual difference, was sufficient to accurately predict performance of shaded systems. Therefore, a balance of accuracy and computational expense was achieved allowing performance predictions of large PV systems with shade.},
author = {Mikofski, Mark A and Lynn, Matthew and Byrne, James and Hamer, Mike and Neubert, Anja and Newmiller, Jeff},
booktitle = {2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC {\&} 34th EU PVSEC)},
doi = {10.1109/PVSC.2018.8547323},
isbn = {978-1-5386-8529-7},
issn = {0160-8371},
keywords = {3D shading,Arrays,Computational modeling,Geometry,Inverters,Mathematical model,Meteorology,NIST,NIST PV test bed,PV performance model,PV systems,Solar Farmer,computational complexity,mismatch,performance,photovoltaic power systems,shaded systems,shading,solar cells,submodule mismatch calculation,submodule shading},
month = {jun},
pages = {3635--3639},
publisher = {IEEE},
title = {{Accurate Performance Predictions of Large PV Systems with Shading using Submodule Mismatch Calculation}},
url = {https://ieeexplore.ieee.org/document/8547323/},
year = {2018}
}
@techreport{Anderson2020,
abstract = {Closed-form equations of the true-tracking angle, backtracking angle, shaded fraction, and orientation angles of single-axis solar trackers installed on arbitrarily oriented slopes are derived. These slope-aware adjustments are necessary to successfully prevent row to row shading in arrays with nonzero cross-axis slope. A tracker rotation modeling procedure comprising these equations is provided.},
address = {Golden, CO},
author = {Anderson, Kevin and Mikofski, Mark A.},
institution = {National Renewable Energy Laboratory},
number = {NREL/TP--5K00--76626},
title = {{Slope-aware back-tracking for single-axis trackers}},
year = {2020},
url = {https://www.nrel.gov/docs/fy20osti/76626.pdf}
}
@misc{Moore,
author = {Moore, Jackson and Tse, Ian},
title = {{Solar Resource Compass}},
url = {https://src.dnvgl.com}
}
@inproceedings{Sengupta2018,
abstract = {The National Solar Radiation Database (NSRDB) provides gridded satellite-based data sets for the United States and other parts of North and South America using cloud properties retrieved from the Geostationary Operational Environmental (GOES) series of satellites. These cloud properties in combination with ancillary atmospheric parameters are used in the Physical Solar Model (PSM) to compute solar radiation. This paper seeks to 1) describe the changes made in the PSM for the recent update to the National Solar Radiation Database (NSRDB 1998-2016) and 2) examine the performance of this update by comparing it to high-quality ground-based measurements. We summarize the changes to the input data for the radiative transfer models as well as updates for the processing algorithms. We also analyze the performance and accuracy of the NSRDB across the United States. Additional details of the data set and model are described in (1), (2), (3), and (4).},
author = {Sengupta, Manajit and Lopez, Anthony and Habte, Aron and Xie, Yu},
booktitle = {35th European Photovoltaic Solar Energy Conference and Exhibition},
doi = {10.4229/35thEUPVSEC20182018-6DO.10.1},
isbn = {3-936338-50-7},
keywords = {Aerosol,MERRA-2,NSRDB,PSM},
pages = {1662 -- 1665},
title = {{Improving the accuracy of the National Solar Radiation Database (1998-2016)}},
url = {https://www.nrel.gov/docs/fy19osti/72410.pdf},
year = {2018}
}
@INPROCEEDINGS{Mikofski_9300381,
author = {Mikofski, Mark A. and Rainey, Patrick J.},
booktitle = {2020 47th IEEE Photovoltaic Specialists Conference (PVSC)},
title = {Tracker Terrain Losses},
year = {2020},
pages = {1859-1862},
doi = {10.1109/PVSC45281.2020.9300381},
url = {https://ieeexplore.ieee.org/document/9300381}
}
@INPROCEEDINGS{Mikofski_8980572,  
author = {Mikofski, Mark A. and Darawali, Renn and Hamer, Mike and Neubert, Anja and Newmiller, Jeff},
booktitle = {2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)},   
title = {Bifacial Performance Modeling in Large Arrays},   
year = {2019},  
pages = {1282-1287},  
doi = {10.1109/PVSC40753.2019.8980572},
url = {https://ieeexplore.ieee.org/document/8980572}
}
@INPROCEEDINGS{Anderson_9300438,  author={Anderson, Kevin},  booktitle={2020 47th IEEE Photovoltaic Specialists Conference (PVSC)},   title={Maximizing Yield with Improved Single-Axis Backtracking on Cross-Axis Slopes},   year={2020},  volume={},  number={},  pages={1466-1471}, url = {https://ieeexplore.ieee.org/document/9300438}, doi={10.1109/PVSC45281.2020.9300438}}