Optimizing Bifacial Solar Modules for Enhanced Energy Capture on Cloudy DaysSource: Journal of Energy Resources Technology, Part A: Sustainable and Renewable Energy:;2025:;volume( 001 ):;issue: 004::page 41801-1Author:Lu, Jianqing
,
Xiao, Tingyi
,
Su, Xiao
,
Huang, Caiyuan
,
Jiang, Yipeng
,
Liu, Wenyang
,
Ao, Runchun
,
Zhang, Wei
,
He, Jianjun
DOI: 10.1115/1.4068052Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: To improve the utilization of solar irradiance by a bifacial photovoltaic (PV) flat single-axis tracking system under complex weather conditions, a dynamic optimization model for bifacial PV modules, a hybrid tracking algorithm was developed. Scattering coefficients are defined to differentiate weather conditions consistently so as to select different algorithms for tracking. The sun's position is tracked by using the visual sun trajectory model on sunny days, while the maximum sum of irradiance of bifacial modules is used as the tracking angle setting principle for high scattering weather. A month-long controlled field experiment was conducted at a PV plant in Ningxia. Data under typical cloudy and overcast conditions were selected to analyze and verify whether the proposed model can improve the power generation efficiency of the planar single-axis tracking system. The experiment results show that the tracking system using the all-weather dynamic optimization model for bifacial modules has an irradiance gain of 8.174% and 4.81%, and a daily power generation gain is 10.529% and 6.20%, respectively, under typical cloudy and overcast conditions. This demonstrates that the hybrid tracking model proposed in this article can improve the power generation of the bifacial flat single-axis tracking system under complex weather.
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contributor author | Lu, Jianqing | |
contributor author | Xiao, Tingyi | |
contributor author | Su, Xiao | |
contributor author | Huang, Caiyuan | |
contributor author | Jiang, Yipeng | |
contributor author | Liu, Wenyang | |
contributor author | Ao, Runchun | |
contributor author | Zhang, Wei | |
contributor author | He, Jianjun | |
date accessioned | 2025-08-20T09:28:30Z | |
date available | 2025-08-20T09:28:30Z | |
date copyright | 3/24/2025 12:00:00 AM | |
date issued | 2025 | |
identifier issn | 2997-0253 | |
identifier other | jerta-24-1196.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4308340 | |
description abstract | To improve the utilization of solar irradiance by a bifacial photovoltaic (PV) flat single-axis tracking system under complex weather conditions, a dynamic optimization model for bifacial PV modules, a hybrid tracking algorithm was developed. Scattering coefficients are defined to differentiate weather conditions consistently so as to select different algorithms for tracking. The sun's position is tracked by using the visual sun trajectory model on sunny days, while the maximum sum of irradiance of bifacial modules is used as the tracking angle setting principle for high scattering weather. A month-long controlled field experiment was conducted at a PV plant in Ningxia. Data under typical cloudy and overcast conditions were selected to analyze and verify whether the proposed model can improve the power generation efficiency of the planar single-axis tracking system. The experiment results show that the tracking system using the all-weather dynamic optimization model for bifacial modules has an irradiance gain of 8.174% and 4.81%, and a daily power generation gain is 10.529% and 6.20%, respectively, under typical cloudy and overcast conditions. This demonstrates that the hybrid tracking model proposed in this article can improve the power generation of the bifacial flat single-axis tracking system under complex weather. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Optimizing Bifacial Solar Modules for Enhanced Energy Capture on Cloudy Days | |
type | Journal Paper | |
journal volume | 1 | |
journal issue | 4 | |
journal title | Journal of Energy Resources Technology, Part A: Sustainable and Renewable Energy | |
identifier doi | 10.1115/1.4068052 | |
journal fristpage | 41801-1 | |
journal lastpage | 41801-8 | |
page | 8 | |
tree | Journal of Energy Resources Technology, Part A: Sustainable and Renewable Energy:;2025:;volume( 001 ):;issue: 004 | |
contenttype | Fulltext |