考虑电价碳价不确定性的燃煤发电基准电价优化模型.
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- Zhejiang Electric Power, 2023, v. 42, n. 5, p. 59, doi. 10.19585/j.zjdl.202305007
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- Article
Works matching Carbon price
Results: 2480
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Impact of Carbon Prices on Wholesale Electricity Prices and Carbon Pass-Through Rates in the Australian National Electricity Market.
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- Energy Journal, 2015, v. 36, n. 3, p. 137, doi. 10.5547/01956574.36.3.pwil
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Carbon prices forecasting based on sliding time window and improved support vector regression: Carbon prices forecasting based on sliding time window...: S. Jia et al.
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- Computing, 2025, v. 107, n. 2, p. 1, doi. 10.1007/s00607-024-01404-9
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4
融合新闻影响力衰减的碳价格多元分解集成预测.
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- Journal of Henan University of Science & Technology, Natural Science, 2024, v. 45, n. 1, p. 51, doi. 10.15926/j.cnki.issn1672-6871.2024.01.007
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5
中国试点碳市场交易价格的影响因素及驱动路径.
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- Journal of Hefei University of Technology (Social Sciences), 2025, v. 39, n. 1, p. 96
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6
考虑电-碳价格耦合的低碳需求响应研究.
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- Integrated Intelligent Energy, 2024, v. 46, n. 10, p. 56, doi. 10.3969/j.issn.2097-0706.2024.10.008
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7
Fluctuations and Forecasting of Carbon Price Based on A Hybrid Ensemble Learning GARCH-LSTM-Based Approach: A Case of Five Carbon Trading Markets in China.
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- Sustainability (2071-1050), 2024, v. 16, n. 4, p. 1588, doi. 10.3390/su16041588
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8
Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots.
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- Sustainability (2071-1050), 2020, v. 12, n. 14, p. 5581, doi. 10.3390/su12145581
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9
碳排放权价格波动 对制造业上市公司价值的影响研究.
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- China Forestry Economy, 2023, n. 5, p. 84, doi. 10.13691/j.cnki.cn23-1539/f.2023.05.012
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10
基于ARMA-GARCH 簇模型的碳配额价格 波动特征研究.
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- China Forestry Economy, 2023, n. 2, p. 100, doi. 10.13691/j.cnki.cn23-1539/f.2023.02.017
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- Article
11
二次分解策略的深度学习碳交易价格预测.
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- Science Technology & Engineering, 2024, v. 24, n. 18, p. 7928, doi. 10.12404/j.issn.1671-1815.2306264
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12
基于 VAR 和 ARIMA-LSTM 模型的碳排放权交易价格影响因素分析及预测.
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- Journal of Hubei Minzu University (Natural Science Edition), 2025, v. 43, n. 2, p. 280, doi. 10.13501/j.cnki.42-1908/п.2025.06.012
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13
中国碳市场交易价格的共同趋势特征研究.
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- Issues of Forestry Economics, 2020, v. 40, n. 3, p. 270, doi. 10.16832/j.enki.1005-9709.20190243
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- Article
14
基于阶梯碳价和自适应分时电价的电动汽车有序充电.
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- Electric Power Automation Equipment / Dianli Zidonghua Shebei, 2024, v. 44, n. 2, p. 64, doi. 10.16081/j.epae.202304012
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15
Empirical analysis of the relationship between carbon trading price and stock price of high carbon emitting firms based on VAR model — evidence from Chinese listed companies.
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- Environmental Science & Pollution Research, 2024, v. 31, n. 1, p. 1146, doi. 10.1007/s11356-023-30906-w
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- Article
16
基于 TTBIGRUA 的碳价预测研究.
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- Journal of Nanjing University of Information Science & Technology (Natural Science Edition) / Nanjing Xinxi Gongcheng Daxue Xuebao (ziran kexue ban), 2025, v. 17, n. 4, p. 467, doi. 10.13878/j.cnki.jnuist.20241023002
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17
Climate change, carbon prices and insurance systems.
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- International Journal of Sustainable Development & World Ecology, 2010, v. 17, n. 2, p. 95, doi. 10.1080/13504500903541806
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18
Cointegration analysis of fundamental drivers affecting carbon price dynamics in the EU ETS.
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- AIMS Environmental Science, 2025, v. 12, n. 1, p. 1, doi. 10.3934/environsci.2025008
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19
TFR: A Temporal Feature‐Refined Multi‐Stage Carbon Price Forecasting.
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- Energy Science & Engineering, 2025, v. 13, n. 2, p. 611, doi. 10.1002/ese3.2015
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- Article
20
A carbon price ensemble prediction model based on secondary decomposition strategies and bidirectional long short‐term memory neural network by an improved particle swarm optimization.
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- Energy Science & Engineering, 2024, v. 12, n. 6, p. 2568, doi. 10.1002/ese3.1769
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- Article
21
Forecasting carbon price using signal processing technology and extreme gradient boosting optimized by the whale optimization algorithm.
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- Energy Science & Engineering, 2024, v. 12, n. 3, p. 810, doi. 10.1002/ese3.1655
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- Article
22
A novel interpretable model ensemble multivariate fast iterative filtering and temporal fusion transform for carbon price forecasting.
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- Energy Science & Engineering, 2023, v. 11, n. 3, p. 1148, doi. 10.1002/ese3.1380
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- Article
23
Forecasting carbon dioxide emission price using a novel mode decomposition machine learning hybrid model of CEEMDAN‐LSTM.
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- Energy Science & Engineering, 2023, v. 11, n. 1, p. 79, doi. 10.1002/ese3.1304
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- Article
24
Fossil Fuel Subsidy Inventories vs. Net Carbon Prices.
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- Energy Journal, 2024, v. 45, n. 4, p. 1, doi. 10.5547/01956574.45.4.jboh
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25
Fossil Fuel Subsidy Inventories vs. Net Carbon Prices.
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- Energy Journal, 2024, v. 45, n. 4, p. 59, doi. 10.1177/01956574241277304
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- Article
26
An Estimation of Market-Based Carbon-Emission Prices Using Comparative Analogy: A Korean Case.
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- Energy Journal, 2019, v. 40, p. 259, doi. 10.5547/01956574.40.SI1.smoo
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27
Carbon Price instead of Support Schemes: Wind Power Investments by the Electricity Market.
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- Energy Journal, 2016, v. 37, n. 4, p. 109, doi. 10.5547/01956574.37.4.mpet
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28
KARBON FİYATLARININ SİMETRİK VE ASİMETRİK NEDENSELLİK TESTİ İLE ANALİZİ.
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- International Journal of Management Economics & Business / Uluslararası Yönetim İktisat ve İşletme Dergisi, 2020, v. 16, n. 4, p. 989, doi. 10.17130/ijmeb.792394
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29
Carbon Price Point and Interval-Valued Prediction Based on a Novel Hybrid Model.
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- Energies (19961073), 2025, v. 18, n. 5, p. 1054, doi. 10.3390/en18051054
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30
Carbon Price Forecasting Using Optimized Sliding Window Empirical Wavelet Transform and Gated Recurrent Unit Network to Mitigate Data Leakage.
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- Energies (19961073), 2024, v. 17, n. 17, p. 4358, doi. 10.3390/en17174358
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31
Application of Dynamic Weight Mixture Model Based on Dual Sliding Windows in Carbon Price Forecasting.
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- Energies (19961073), 2024, v. 17, n. 15, p. 3662, doi. 10.3390/en17153662
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32
Short-Term Natural Gas and Carbon Price Forecasting Using Artificial Neural Networks.
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- Energies (19961073), 2023, v. 16, n. 18, p. 6643, doi. 10.3390/en16186643
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33
A Multi-Strategy Integration Prediction Model for Carbon Price.
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- Energies (19961073), 2023, v. 16, n. 12, p. 4613, doi. 10.3390/en16124613
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34
Prediction of Regional Carbon Price in China Based on Secondary Decomposition and Nonlinear Error Correction.
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- Energies (19961073), 2023, v. 16, n. 11, p. 4444, doi. 10.3390/en16114444
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- Article
35
The Effect of Carbon Price Volatility on Firm Green Transitions: Evidence from Chinese Manufacturing Listed Firms.
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- Energies (19961073), 2022, v. 15, n. 20, p. 7456, doi. 10.3390/en15207456
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36
Forecasting Regional Carbon Prices in China Based on Secondary Decomposition and a Hybrid Kernel-Based Extreme Learning Machine.
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- Energies (19961073), 2022, v. 15, n. 10, p. N.PAG, doi. 10.3390/en15103562
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- Article
37
A VaR-Based Methodology for Assessing Carbon Price Risk across European Union Economic Sectors.
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- Energies (19961073), 2021, v. 14, n. 24, p. 8424, doi. 10.3390/en14248424
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- Article
38
A Carbon Price Prediction Model Based on the Secondary Decomposition Algorithm and Influencing Factors.
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- Energies (19961073), 2021, v. 14, n. 5, p. 1328, doi. 10.3390/en14051328
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- Article
39
Carbon Price Forecasting Based on Multi-Resolution Singular Value Decomposition and Extreme Learning Machine Optimized by the Moth–Flame Optimization Algorithm Considering Energy and Economic Factors.
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- Energies (19961073), 2019, v. 12, n. 22, p. 4283, doi. 10.3390/en12224283
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40
Modeling Latent Carbon Emission Prices for Japan: Theory and Practice.
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- Energies (19961073), 2019, v. 12, n. 21, p. 4222, doi. 10.3390/en12214222
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- Article
41
Forecasting the Carbon Price Using Extreme-Point Symmetric Mode Decomposition and Extreme Learning Machine Optimized by the Grey Wolf Optimizer Algorithm.
- Published in:
- Energies (19961073), 2019, v. 12, n. 5, p. 950, doi. 10.3390/en12050950
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- Article
42
Analysis and Forecasting of the Carbon Price in China's Regional Carbon Markets Based on Fast Ensemble Empirical Mode Decomposition, Phase Space Reconstruction, and an Improved Extreme Learning Machine.
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- Energies (19961073), 2019, v. 12, n. 2, p. 277, doi. 10.3390/en12020277
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- Publication type:
- Article
43
Multi-Step-Ahead Carbon Price Forecasting Based on Variational Mode Decomposition and Fast Multi-Output Relevance Vector Regression Optimized by the Multi-Objective Whale Optimization Algorithm.
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- Energies (19961073), 2019, v. 12, n. 1, p. 147, doi. 10.3390/en12010147
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- Article
44
Predicting the Carbon Price Sequence in the Shenzhen Emissions Exchange Using a Multiscale Ensemble Forecasting Model Based on Ensemble Empirical Mode Decomposition.
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- Energies (19961073), 2018, v. 11, n. 7, p. 1907, doi. 10.3390/en11071907
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45
The Integration of Carbon Price Between European and Chinese Markets: What are the Implications?
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- International Journal of Environmental Research, 2021, v. 15, n. 4, p. 667, doi. 10.1007/s41742-021-00342-0
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- Article
46
The Impact of Carbon Emissions Trading Scheme on Corporate Financial Performance: Based on the Moderating Effect of Carbon Prices.
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- IAENG International Journal of Applied Mathematics, 2023, v. 53, n. 4, p. 1162
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- Article
47
Carbon sink price prediction based on radial basis kernel function support vector machine regression model.
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- International Journal of Low Carbon Technologies, 2022, v. 17, p. 1075, doi. 10.1093/ijlct/ctac088
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- Article
48
Research on carbon price in emissions trading scheme: a bibliometric analysis.
- Published in:
- Natural Hazards, 2019, v. 99, n. 3, p. 1381, doi. 10.1007/s11069-018-3433-6
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- Article
49
Multisource Data-Driven Carbon Price Composite Forecasting Model: Based on Feature Selection and Multiscale Prediction Strategy.
- Published in:
- Strategic Planning for Energy & the Environment, 2024, v. 43, n. 4, p. 791, doi. 10.13052/spee1048-5236.4342
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- Article
50
Prediction uncertainty and volatility for carbon price using an adaptive lower and upper bound estimation model.
- Published in:
- Environmental Progress & Sustainable Energy, 2023, v. 42, n. 4, p. 1, doi. 10.1002/ep.14216
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- Article