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利用灰关联理论分析低碳能源的供需关系,通过构建GM(1,1)模型对中国低碳能源的供需形势进行分析和预测,并运用BP神经网络对低碳能源的需求量进行进一步的对比预测。研究表明,水电的生产量与消费量的关系最为密切,其次是核电,可再生能源的生产量与消费量的关系相对较弱;核电和水电的供需影响因子构建的GM(1,1)模型与可再生能源相比较为稳定,BP神经网络的预测值要略低于灰色系统的预测值;核电、水电、可再生能源的生产量和消费量都将呈现增长的趋势,核电的消费量要略高于其生产量,这种局面将在2025年得到扭转,水电的生产量和消费量将在未来一段时间稳定、持续增长,可再生能源的消费量将高于其生产量,并且随着时间的推进,这种差距会扩大。
The relationship between supply and demand of low-carbon energy is analyzed by using gray relational theory, the supply and demand of low-carbon energy in China are analyzed and predicted by constructing GM (1,1) model, and the demand of low-carbon energy by BP neural network is further compared prediction. The research shows that the production and consumption of hydropower are the most closely related, followed by nuclear power, and the relationship between production and consumption of renewable energy is relatively weak. The GM (1,1) model for the supply and demand factors of nuclear power and hydropower Compared with the renewable energy, the predicted value of BP neural network is slightly lower than the forecast value of gray system; the production and consumption of nuclear power, hydropower and renewable energy will all show an increasing trend, and the consumption of nuclear power should be slightly Higher than its production, this situation will be reversed in 2025, hydropower production and consumption will be stable and sustainable growth in the coming period, renewable energy consumption will be higher than its production capacity, and over time The gap will widen.