CMIP6–PVsyst Assessment across Three Climatic Zones of Cameroon

Historical meteorological data were obtained from internationally recognized climate databases for the baseline period. Climate data for this study were obtained from two primary sources: • Baseline Climate Data (2001–2020): Sourced from the NASA POWER database, providing a historical benchmark of regional performance (hourly records of Global Horizontal Irradiance (GHI), ambient temperature, relative humidity, and wind speed) [29], [37]. • Future Climate-Adjusted Data (2031–2060): Generated by applying CORDEX-Africa-derived monthly deltas to the baseline data to simulate projected climate-induced changes. These high-resolution projections offer improved representation of regional processes compared to coarse Global Climate Models (GCMs) [38], [36]. Figures use both traditional and projected data to demonstrate how the two variables interact continuously during system operation. It reveals that effective global irradiance is the principal driver of photovoltaic electricity generation, whereas PV array temperature constitutes the dominant source of thermal performance losses. However, the simultaneous increase in module operating temperature reduces the open-circuit voltage and conversion efficiency, partially offsetting the gains associated with higher irradiance. By extracting the key metrics from these summaries, the net impact on productivity can be quantified.本研究基准期的历史气象数据取自国际公认的气候数据库，本次研究所用气候数据主要来自两个来源： • 基准期气候数据（2001–2020年）：源自NASA POWER数据库，提供区域性能的历史基准数据集，包含全球水平辐照度（Global Horizontal Irradiance, GHI）、环境温度、相对湿度与风速的逐小时记录[29, 37]。 • 未来气候修正数据（2031–2060年）：通过将CORDEX-Africa衍生的月度偏差增量应用于基准期数据，以模拟预估的气候变化。相较于低分辨率全球气候模型（Global Climate Models, GCMs），此类高分辨率投影能够更精准地表征区域气候过程[38, 36]。 本研究的图表结合了历史基准与未来预估气候数据，用以展示系统运行过程中两类变量的持续交互机制。研究结果表明，有效全球辐照度是光伏发电量的核心驱动因子，而光伏阵列温度则是热性能损耗的主要来源。然而，光伏组件运行温度的同步升高会降低开路电压与光电转换效率，部分抵消了更高辐照度带来的发电量增益。通过提取上述分析中的关键指标，即可量化其对系统产能的净影响。