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<p>Rooftop solar panels with dual functions are a promising sustainable energy source given the world’s rapid urbanization, particularly in densely populated nations like India. Numerous studies have shown how well the System Advisory Model (SAM) performs when estimating the energy yield of bifacial solar photovoltaic (BSPV) systems. This study uses a popular photovoltaic design software to compare the output of a 3&#xa0;kW grid-connected BSPV system. The SAM simulation forecasts a production of 4864.5&#xa0;kWh, whereas the empirical data shows that the system’s yearly energy output is 4321.7&#xa0;kWh. The operational plant’s performance ratio is about 81.6%, which closely agrees with the 81.2% that SAM projected. Further, the relationship between various input parameters and power output of a BSPV generated from SAM simulation results was investigated using machine learning (ML) models. Among the ML models tested, the linear regression (LR) model delivered the best performance for a 3&#xa0;kW BSPV system in a specific location.</p>

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Performance Evaluation and Machine Learning Analysis of 3 kW Grid-Connected Bifacial Solar Photovoltaic Systems

  • 期刊论文

  • 发表日期：

    2025年2月24日

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  • Bojja. Shiva Kumar,
  • B. M. Kunar,
  • Ch. S. N. Murthy

摘要

Rooftop solar panels with dual functions are a promising sustainable energy source given the world’s rapid urbanization, particularly in densely populated nations like India. Numerous studies have shown how well the System Advisory Model (SAM) performs when estimating the energy yield of bifacial solar photovoltaic (BSPV) systems. This study uses a popular photovoltaic design software to compare the output of a 3 kW grid-connected BSPV system. The SAM simulation forecasts a production of 4864.5 kWh, whereas the empirical data shows that the system’s yearly energy output is 4321.7 kWh. The operational plant’s performance ratio is about 81.6%, which closely agrees with the 81.2% that SAM projected. Further, the relationship between various input parameters and power output of a BSPV generated from SAM simulation results was investigated using machine learning (ML) models. Among the ML models tested, the linear regression (LR) model delivered the best performance for a 3 kW BSPV system in a specific location.