人民黄河

流域水风光一体化开发是践行低碳、绿色发展理念的重要举措。然而，当前气候变化加剧，导致清洁能源波动性增大、未来发电潜力不确定性升高、一体化基地的生态环境效益难以准确预估，给流域清洁能源高效利用和生态保护造成诸多挑战。为此，以黄河上游茨哈峡水风光一体化基地为研究对象，运用分位数映射法、CNN-LSTM-Attention深度学习预测模型和改进的风光电理论出力计算方法，筛选研究区适用的高精度未来气候模式数据，预测一体化基地规划运行期(2035—2065年)的水风光电逐日平均出力及其多时间尺度互补性，预估一体化基地的生态环境效益。研究结果发现：1)2035—2065年，预测水电、风电、光伏年均发电量分别为101.30亿、11.87亿、437.85亿kW·h。4种SSP情景下，茨哈峡水电站日均入库流量分别增加0.97、1.74、1.25、1.99 m³/s,水电日均理论出力平均上升2.23 MW,风电、光伏日均理论出力平均下降0.29、0.80 MW。2)水风、水光、风光、水风光组合的年发电量相关系数分别为-0.22、0.18、-0.10、-0.03,水风组合的年际互补性更强，年内冬季互补性显著。3)水风光电年均可替代551.02亿kW·h燃煤发电，减碳0.48亿t/a,风光发电替代燃煤发电可实现节水1.08亿m³/a。此外，预计一体化基地下垫面的潜在蒸散发量年均减少284.56 mm,生态系统净初级生产力(NPP)年均增加97.04 gC/m²。

Integrated hydro-wind-photovoltaic development in river basins represents a crucial initiative for implementing low-carbon and green development principles. However, intensified climate change currently leads to increased volatility in renewable energy outputs, heightened uncertainty regarding future power generation potential, and challenges in accurately predicting the eco-environmental benefits of integrated energy bases. These factors pose significant obstacles to the efficient utilization of basin clean energy resources and ecological conservation. Therefore, the Cihaxia integrated water-wind-photovoltaic base in the upper reaches of the Yellow River was taken as the research object. The quantile mapping method, CNN-LSTM-Attention deep learning prediction model and improved theoretical output calculation method of water-wind-photovoltaic were used to screen high-precision future climate model data applicable to the study area. The daily average output of water-wind-photovoltaic power and its multi-time scale complementarity during the planned operation period of the integrated base(2035-2065) were predicted, and the ecological and environmental benefits of the integrated base were estimated. The key findings are: a) From 2035 to 2065, the predicted average annual power generation is 10.13 billion kW·h for hydropower, 1.187 billion kW·h for wind power, and 43.785 billion kW·h for photovoltaic power. Under four SSP scenarios, the average daily inflow to the Cihaxia Hydropower Station is increased by 0.97, 1.74, 1.25, and 1.99 m³/s respectively. The average daily theoretical hydropower output is increased by an average of 2.23 MW, while wind and photovoltaic outputs experience slight average decreases of 0.29 MW and 0.80 MW respectively. b) The annual power generation correlation coefficients are-0.22 for hydro-wind, 0.18 for hydro-photovoltaic,-0.10 for wind-photovoltaic and-0.03 for hydro-wind-photovoltaic combined. The hydro-wind combination exhibits stronger inter-annual complementarity, with the strongest intra-annual complementarity occurring during winter. c) The annual power generation from the integrated base can potentially replace 55.102 billion kW·h of coal-fired power, reducing carbon emissions by 48 million tonnes per year. Furthermore, replacing coal power with wind and photovoltaic generation saves approximately 108 million m³ of water annually. Additionally, the base is projected to reduce the average annual potential evapotranspiration of the underlying surface by 284.56 mm and increase the average annual Net Primary Productivity(NPP) of the ecosystem by 97.04 gC/m².