
Slide

Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Khosrojerdi, F.; Gagnon, S.; Valverde, R.
Full Shading for Photovoltaic Systems Operating under Snow Conditions Article d'actes
Dans: 2021 9th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2021, p. 82–87, Institute of Electrical and Electronics Engineers Inc., 2021, ISBN: 978-0-7381-4535-8.
Résumé | Liens | BibTeX | Étiquettes: Computer software, Condition, Energy consumer, Energy forecasting, Photovoltaic cells, Photovoltaic planning, Photovoltaic shading, Photovoltaic systems, Photovoltaics, Snow, Snow-covered module, Solar energy, Solar power generation, Solar power plants, USC
@inproceedings{khosrojerdi_full_2021,
title = {Full Shading for Photovoltaic Systems Operating under Snow Conditions},
author = {F. Khosrojerdi and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116021648&doi=10.1109%2fSEGE52446.2021.9534991&partnerID=40&md5=3a4487157a809d03ae5c46c10499f865},
doi = {10.1109/SEGE52446.2021.9534991},
isbn = {978-0-7381-4535-8},
year = {2021},
date = {2021-01-01},
booktitle = {2021 9th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2021},
pages = {82–87},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Photovoltaic (PV) installers and non-technical solar energy consumers use PV planning software for the system design and simulation. End-users rely on the designed system and power estimations provided by these tools. However, most planning software products fail to consider shading conditions. This problem affects energy forecasting for solar power plants located in cold climates. In this paper, we define the status of full shading for a snow-covered panel and the minimum depth of snow creating it. Using a case study, we design the project by the most reliable planning software, System Advisor Model (SAM). We show that the simulation overestimates power generations for snowy months. To identify shading conditions and the correlated performance reductions, we compare the SAM results with the measured data collected onsite. As a result, the minimum depth of snow that can create full shading and zero production is detected. Moreover, comparing the measured data with the simulated power helps us to define a rule-base system providing PV performance reduction factors. It assists solar sector practitioners to plan a PV project accurately, especially for the locations where snowfall is an important environmental factor for several months. © 2021 IEEE.},
keywords = {Computer software, Condition, Energy consumer, Energy forecasting, Photovoltaic cells, Photovoltaic planning, Photovoltaic shading, Photovoltaic systems, Photovoltaics, Snow, Snow-covered module, Solar energy, Solar power generation, Solar power plants, USC},
pubstate = {published},
tppubtype = {inproceedings}
}
Photovoltaic (PV) installers and non-technical solar energy consumers use PV planning software for the system design and simulation. End-users rely on the designed system and power estimations provided by these tools. However, most planning software products fail to consider shading conditions. This problem affects energy forecasting for solar power plants located in cold climates. In this paper, we define the status of full shading for a snow-covered panel and the minimum depth of snow creating it. Using a case study, we design the project by the most reliable planning software, System Advisor Model (SAM). We show that the simulation overestimates power generations for snowy months. To identify shading conditions and the correlated performance reductions, we compare the SAM results with the measured data collected onsite. As a result, the minimum depth of snow that can create full shading and zero production is detected. Moreover, comparing the measured data with the simulated power helps us to define a rule-base system providing PV performance reduction factors. It assists solar sector practitioners to plan a PV project accurately, especially for the locations where snowfall is an important environmental factor for several months. © 2021 IEEE.