Modeling and optimizing performance of bifacial PV systems with DC power optimizers

Bifacial photovoltaic (PV) systems represent advancement in solar energy harvesting, capable of capturing sunlight from both the front and rear surfaces of the modules, thereby promising significantly increased energy production compared to traditional monofacial systems. However, the performance of...

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Vydané v:Renewable energy Ročník 255; s. 123844
Hlavní autori: Abojela, Zuher R.Khalifa, Desa, Mohd Khairunaz Mat, Sabry, Ahmad H.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 15.12.2025
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ISSN:0960-1481
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Shrnutí:Bifacial photovoltaic (PV) systems represent advancement in solar energy harvesting, capable of capturing sunlight from both the front and rear surfaces of the modules, thereby promising significantly increased energy production compared to traditional monofacial systems. However, the performance of these systems in real-world applications can be affected by factors such as partial shading, module mismatch, and varying environmental conditions, potentially limiting their energy yield. To mitigate these challenges and further enhance the energy output of bifacial PV systems, the integration of DC power optimizers presents a promising solution. This study employed a combined experimental and modeling approach to rigorously evaluate the impact of DC power optimizers on the performance of various bifacial PV configurations. Experimental data, alongside daily energy production, were collected for systems with and without DC optimizers. A detailed simulation model, incorporating relevant electrical and thermal parameters, was developed and calibrated using the Pattern Search algorithm to accurately predict system behavior. The validated model estimated an annual energy yield of 3395.6 kWh for the system without optimizers and 4152.82 kWh for the system incorporating optimizers, demonstrating an approximate 22.3 % increase. The analysis further revealed that DC power optimizers contribute to reducing system losses, ultimately enhancing overall performance.
ISSN:0960-1481
DOI:10.1016/j.renene.2025.123844