可再生能源
气候变化
环境科学
风力发电
电
气象学
市电
分位数
代表性浓度途径
气候模式
气候学
功率(物理)
计量经济学
地理
工程类
经济
地质学
物理
电气工程
生态学
生物
量子力学
作者
Yi Zhang,Chuntian Cheng,Tiantian Yang,Xiaoyu Jin,Zebin Jia,Jianjian Shen,Xinyu Wu
标识
DOI:10.1016/j.rser.2022.112480
摘要
Renewable energies such as hydro, wind, and solar power, are susceptible to the impacts of climate change. Energy Impact Assessment models under climate change are useful tools for understanding these impacts, but still face some challenges, such as the limited spatial resolution, the lack of utilization of the latest climate models, the inadequate analysis of uncertainties and extreme behaviors, and having not enough capability in simulating the coordinated operation of different power sources. To improve the situation, this study utilizes Random Forest Regression and its derivative Quantile Regression Forest to downscale the CMIP6 General Circulation Models for projecting the means and quantiles of the renewable energy resources for each individual power station under seven combined pathways of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Based on the projected results, a coordinated operation strategy is established to quantify the impacts of climate change on the regional hydro-wind-solar energy supply system. The assessment reveals: (1) changes of hydro-meteorological variables will present spatially and seasonal inhomogeneous; (2) at the end of the century, the projected increased level of electricity supply will be the highest under the SSP5-RCP8.5 and the increment will be 8.680 TWh; (3) the extreme lack electricity supply will occur under the SSP3-RCP7.0 for the period 2041–2060 and the twenty-year average value will be reduced by 16.83 TWh relative to the historical period reference period.
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