Energy Loss Mechanisms in Photovoltaic Systems: Assessment and Mitigation Approaches

Engineering notes

Engineering notes will be added by the Power for Solar editorial team.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

Energy is one of the most critical inputs for the socio-economic development and sustainable prosperity of humanity. Historically, fossil fuels like coal, oil, and natural gas formed the backbone of the global energy supply. However, their limited reserves and environmental impacts have raised serious sustainability concerns. According to the International Energy Agency, fossil resources still met approximately 81% of the global primary energy demand in 2019. This dependence drives greenhouse gas emissions, the climate crisis, environmental degradation, and import reliance. Consequently, countries are increasingly turning to renewable sources to ensure energy security and reduce carbon footprints. Solar energy stands out for its high potential, modularity, ease of technological integration, and zero emissions. Photovoltaic (PV) systems, converting solar radiation directly into electricity, are widely adopted. However, PV systems face various losses in real-world conditions, generally classified as PV array capture losses and system losses. Irradiance irregularities, temperature increases, and module mismatches cause capture losses, while cable resistance, inverter inefficiencies, and transformer losses represent system losses. Dust accumulation, partial shading, and environmental factors also directly impact efficiency. Therefore, the accurate prediction and early detection of these losses are critical for investors and operators. Recently, artificial intelligence and machine learning approaches have been increasingly applied to model these complex losses and predict faults. Unlike traditional analytical methods, data-driven algorithms provide more flexible and precise solutions under non-linear dynamic field conditions. This study analyzes energy losses in PV systems, discusses current academic and industrial solutions, and presents future projections for research and sectoral applications.

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