全球能源互联网2025，Vol.8Issue(2)：239-249,11.DOI:10.19705/j.cnki.issn2096-5125.2025.02.011
基于NeuralProphet-LSTM模型的碳价预测研究
Research on Carbon Price Prediction Based on NeuralProphet-LSTM Model
摘要
Abstract
With the expanding of humanity's activities,the continuous escalation in greenhouse gas emissions has exacerbated the scarcity of carbon environmental capacity,thereby intensifying the demand for precise carbon emission rights pricing.The transaction price in the carbon market,as a pivotal element driving the functionality of the carbon market,is crucial for the stable operation of the carbon market and the efficiency of carbon emission reductions.Accurate forecasting of carbon market transaction prices is of paramount importance for the effective investment in carbon assets and the pursuit of the lowest carbon emission reduction costs.Consequently,this paper proposes a novel carbon price forecasting method based on the NeuralProphet-LSTM(long short-term memory)model.Initially,the NeuralProphet model is utilized to decompose the carbon price series into trends,seasonal effects,event and holiday effects,and autoregressive effects for preliminary forecasting.The forecast results are then used to calculate the residuals,which are inputted into the LSTM for deeper information mining.Finally,the LSTM's prediction of the residuals is combined with the NeuralProphet forecast results through component addition,completing the integration of carbon price series information.Forecasts for the EU carbon market and China's Hubei carbon market demonstrate that this model's forecasting performance surpasses other models,showing high application value.关键词
碳价预测/人工智能/混合模型/NeuralProphet/LSTMKey words
carbon price prediction/artificial intelligence/hybrid model/NeuralProphet/LSTM分类
信息技术与安全科学引用本文复制引用
蔡远航,冯建新,王艳青,李婉君,丁元明,胡越..基于NeuralProphet-LSTM模型的碳价预测研究[J].全球能源互联网,2025,8(2):239-249,11.基金项目
大连大学学科交叉项目(DLUXK-2023-ZD-001).Interdisciplinary project of Dalian University(DLUXK-2023-ZD-001). （DLUXK-2023-ZD-001）
