A Solar-position-based Analytical Algorithm with Seasonal Atmospheric Correction for Forecasting Bifacial PV Energy Yield in the Fergana Valley

Accurate forecasting of photovoltaic energy generation is essential for preliminary system design, seasonal planning and reliable integration of solar power into electric-energy systems. This study proposes a solar-position-based analytical algorithm for estimating the seasonal and annual energy yield of a fixed-tilt bifacial photovoltaic system under the climatic conditions of Fergana city, Uzbekistan. The method combines solar-geometry calculations, monthly atmospheric correction factors, irradiance transposition onto an inclined surface, bifacial rear-side irradiance contribution and NOCT-based module-temperature correction within a unified hourly calculation framework. Monthly atmospheric coefficients were introduced to adapt theoretical clear-sky irradiation to the real seasonal radiation regime of the region. The algorithm was validated against PVsyst simulation results. The proposed method predicted an annual specific yield of 1860 kWh/kWp, while the PVsyst reference value was 1859 kWh/kWp, corresponding to an annual relative deviation of approximately 0.05%. Monthly deviations remained within 5.66%, and the mean absolute percentage error was 2.87%. The results also showed that summer thermal derating may reduce effective PV output by approximately 10–15%, whereas bifacial rear-side generation can increase annual yield by about 5–8%. The proposed algorithm provides a transparent and computationally efficient tool for preliminary photovoltaic energy-yield forecasting in regions with pronounced seasonal climatic variability.

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