1. 大连大学通信与网络重点实验室
2. 中国科学院大连化学物理研究所
纸质出版:2025
移动端阅览
蔡远航, 冯建新, 王艳青, 等. 基于NeuralProphet-LSTM模型的碳价预测研究[J]. 全球能源互联网, 2025,8(2):239-249.
蔡远航, 冯建新, 王艳青, 等. 基于NeuralProphet-LSTM模型的碳价预测研究[J]. 全球能源互联网, 2025,8(2):239-249. DOI: 10.19705/j.cnki.issn2096-5125.2025.02.011.
随着人类活动的不断扩展,温室气体的排放量也在持续增长,加剧了碳环境容量的稀缺程度,提高了对碳排放权进行定价的强烈需求。碳市场交易价格作为发挥碳市场功能的核心要素,关乎碳市场的稳定运行和碳减排效率。碳市场交易价格的准确预测对有效开展碳资产投资和寻求最低碳减排成本具有重要的意义。为此,提出一种基于NeuralProphet-LSTM(long short-term memory
长短期记忆)模型的新型碳价格预测方法:首先使用NeuralProphet对碳价序列进行趋势、季节性效应、事件和节假日效应以及自回归效应的模块分解并初步预测;之后使用其预测结果计算残差放入LSTM中进行更深层次的信息挖掘;最后将LSTM对残差的预测通过组件加法与NeuralProphet预测结果组合,完成碳价序列信息的融合。针对欧盟碳市场和中国湖北碳市场进行预测,结果显示该模型的预测性能超过了其他模型,展现出较高的应用价值。
田壁源,刘倩汝,戚红艳,徐海奇,刘琪,常喜强,张新燕.阶梯分时碳价下考虑能流-碳流耦合的综合能源园区优化调度[J].电力需求侧管理,2024(06).
叶健强,孙敦虎.碳交易条件下基于鲁棒优化的电源规划研究[J].发电技术,2024(03).
吴艳娟,靳鹏飞,刘长铖,王云亮.基于奖惩阶梯型碳价机制的能源枢纽低碳优化策略[J].电力工程技术,2024(03).
王守文,叶金根,徐丽洁,李国祥,袁莹超,朱兆彬.计及温控厌氧发酵和阶梯碳交易的农村综合能源低碳经济调度[J].电力系统保护与控制,2024(08).
韩浩博,刘晓峰,刘怀,凌静,季振亚,李峰.有限理性视角下发电商市场竞争动态行为分析[J].电力建设,2024(10).
王南,胡展硕,王丽霞,吕旭明,张延华.指数平滑法模型与ARIMA模型在行业碳排放趋势预测中的综合应用实践分析[J].数字技术与应用,2023(12).
陈旭东,鹿洪源,王涵.国外碳税最新进展及对我国的启示[J].国际税收,2022(02).
蓝虹,陈雅函.碳交易市场发展及其制度体系的构建[J].改革,2022(01).
张晶杰,王志轩,雷雨蔚.欧盟碳市场经验对中国碳市场建设的启示[J].价格理论与实践,2020(01).
吕靖烨,杜靖南,沙巴·拉苏尔.基于ARIMA模型的欧盟碳金融市场期货价格预测及启示[J].煤炭经济研究,2019(10).
姚奕,吕静,章成果.湖北碳市场价格形成机制及价格预测[J].统计与决策,2017(19).
何志昆,刘光斌,赵曦晶,王明昊.高斯过程回归方法综述[J].控制与决策,2013(08).
方匡南,吴见彬,朱建平,谢邦昌.随机森林方法研究综述[J].统计与信息论坛,2011(03).
Hanxiao Shi,Anlei Wei,Xiaozhen Xu,Yaqi Zhu,Hao Hu,Songjun Tang.A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China[J].Journal of Environmental Management,2024.
Jiang Nijun,Yu Xiaobing,Alam Manawwer.A hybrid carbon price prediction model based-combinational estimation strategies of quantile regression and long short-term memory[J].Journal of Cleaner Production,2023.
Zhou Feite,Huang Zhehao,Zhang Changhong.Carbon price forecasting based on CEEMDAN and LSTM[J].Applied Energy,2022.
Zhang Fang,Wen Nuan.Carbon price forecasting: a novel deep learning approach.[J].Environmental science and pollution research international,2022.
Wang Jujie,Cui Quan,Sun Xin.A novel framework for carbon price prediction using comprehensive feature screening, bidirectional gate recurrent unit and Gaussian process regression[J].Journal of Cleaner Production,2021.
Zhou Jianguo,Chen Dongfeng.Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm[J].Sustainability,2021.
Wei Sun,Chang Xu.Carbon price prediction based on modified wavelet least square support vector machine[J].Science of the Total Environment,2021.
Sheng Chunguang,Wang Guangyu,Geng Yude,Chen Lirong.The Correlation Analysis of Futures Pricing Mechanism in China’s Carbon Financial Market[J].Sustainability,2020.
Wei Sun,Zhaoqi Li.An ensemble‐driven long short‐term memory model based on mode decomposition for carbon price forecasting of all eight carbon trading pilots in China[J].Energy Science & Engineering,2020.
Yu Yong,Si Xiaosheng,Hu Changhua,Zhang Jianxun.A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures.[J].Neural computation,2019.
Lei Ji,Yingchao Zou,Kaijian He,Bangzhu Zhu.Carbon futures price forecasting based with ARIMA-CNN-LSTM model[J].Procedia Computer Science,2019.
Sean J. Taylor,Benjamin Letham.Forecasting at Scale[J].The American Statistician,2018.
Suk Joon Byun,Hangjun Cho.Forecasting carbon futures volatility using GARCH models with energy volatilities[J].Energy Economics,2013.
Leif E. Peterson.K-nearest neighbor.[J].Scholarpedia,2009.
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