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Abstract：
Chongqing, as the last ecological barrier of the Upper Yangtze River, is constrained to achieve \"dual carbon\" goals due to imbalanced energy structure. Based on selecting the energy structure influencing factors through Copula function and Granger causality, a multi-dimensional dynamic support vector machine model (SSA-MFD-SVR-ARIMA) by adopting sparrow algorithm was constructed to predict the proportion of Chongqing\'s energy structure from 2021 to 2030 under the drive of green finance development, and an optimization path was obtained. The novel findings confirm that (1) the correlated contribution rate of Green Finance to optimizing Chongqing\'s Energy Structure is 10.8 %; (2) under the sustained growth rate of Green Finance at 4.5 %, the proportion of coal consumption will reach 40.03 % by 2030, and non-fossil energy consumption will account for 27 %. It confirms that Chongqing can achieve the Energy Development Plan assigned by the Central Government in 2025. The research proposes a four-dimensional optimized pathway from a financial perspective that includes green equity investments, digital finance for energy, financing environmental rights and interests, and developing an industry fund. Furthermore, our put forward the safeguard strategies for financing, innovation, linkage, and protection mechanisms of this pathway optimization.
摘要：
重庆,作为长江上游的最后一道生态屏障,由于能源结构不平衡，限制了实现“双碳”目标。在通过Copula函数和Granger因果关系选择能量结构影响因素的基础上,构建了基于Sparrow算法的多维动态支持向量机模型(SSA-MFD-SVR-ARIMA),对绿色金融发展驱动下2021-2030年重庆市能源结构占比进行了预测,并获得了优化路径。新的研究结果证实，(1)绿色金融对优化重庆能源结构的相关贡献率为10.8%；(2)在绿色金融4.5%的持续增长下，到2030年，煤炭消费比重将达到40.03%，非化石能源消费占比将达到27%。这证实了重庆在2025年能够实现中央下达的《能源发展规划》。该研究从财务角度提出了包括绿色股权投资在内的四维优化路径，能源数字金融，为环境权益融资，发展产业基金。此外，我们提出了融资保障策略，创新,联动,以及该途径优化的保护机制。
