Optimal Design of Bifacial Floating Photovoltaic System With Different Installation Azimuths

Bhang, Byeong Gwan; Hyun, Jin Hee; Ahn, Seong-Hyeon; Choi, Jinho; Kim, Gyu Gwang; Ahn, Hyungkeun

doi:10.1109/access.2022.3233100

Cited by 9 publications

(4 citation statements)

References 24 publications

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“…A predictive equation that changes according to the module inclination, azimuth, and declination angle is given in (7) [19]. S module is the incident solar irradiance (S incident ) calculated as the…”

Section: A Prediction Of Front Irradiance According To the Movement O...mentioning

confidence: 99%

“…The view factor, which calculates the degree of radiation reaching one surface to another, is given in (8) [19].…”

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

“…In (11), VF stands for view factor and Alb represents the albedo of the ground surface [19]. The measured albedo at the location where the experiment took place yielded a value of 0.08.…”

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

“…The results showed a MAPE of 5.05% and a RMSE of 9.26. The output of a bifacial PV module is the sum of the outputs from the front and rear sides, as shown in the following equation: The solar irradiance on the rear side, which considers both direct solar irradiance due to the view factor and the part determined by the Alb of the rear side where the PV module is installed, is represented in the following equation [19]:…”

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

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Optimal Inclination and Azimuth Angles of a Photovoltaic Module With Load Patterns for Improved Power System Stability

Choi,

Ahn

et al. 2024

IEEE J. Photovoltaics

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Globally, large-scale photovoltaic (PV) systems are being installed to achieve maximum power generation efficiency. However, this often results in severe power fluctuations, impacting the stability of the power system. To enhance the power system stability, it is crucial to effectively distribute the times of maximum power output. This can be achieved by making changes to the inclination angle and azimuth of PV modules at power plants. The modeling results indicate a prediction error of 3.65% relative to the actual measurements. To assess system stability based on each installation method, new concepts called demand gradient (DG) and demand gradient average (DGA) were introduced and analyzed using the load pattern in Metropolitan Seoul. The electricity usage was categorized into four divisions: residential (dwelling), public, service, and manufacturing. The analysis revealed that optimal inclination angles for the dwelling, public, service, and manufacturing sectors were 60°, 30°, 30°, and 15°, respectively. As for installation azimuths, the optimal values were 0°, 80°, 160°, and 230°, respectively. When both the inclination angle and azimuth were varied simultaneously, their optimal installation methods included inclination angles of 60°, 60°, 35°, and 50°, and azimuths of 330°, 210°, 230°, and 190°for the dwelling, public, service, and manufacturing sectors, respectively. Among the various scenarios, the most significant improvement in grid stability was observed in the existing south-facing installation of DGA in the dwelling sector, demonstrating a remarkable 77% reduction from 0.1 to 0.057.

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Section: A Prediction Of Front Irradiance According To the Movement O...mentioning

confidence: 99%

“…The view factor, which calculates the degree of radiation reaching one surface to another, is given in (8) [19].…”

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

“…In (11), VF stands for view factor and Alb represents the albedo of the ground surface [19]. The measured albedo at the location where the experiment took place yielded a value of 0.08.…”

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

Section: B Prediction Of the Output Of Bifacial Pv Modulementioning

confidence: 99%

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