A Data-Driven Method to Monitor Carbon Dioxide Emissions of Coal-Fired Power Plants
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- Huiru Zhao & Guo Huang & Ning Yan, 2018. "Forecasting Energy-Related CO 2 Emissions Employing a Novel SSA-LSSVM Model: Considering Structural Factors in China," Energies, MDPI, vol. 11(4), pages 1-21, March.
- Akpan, P.U. & Fuls, W.F., 2021. "Cycling of coal fired power plants: A generic CO2 emissions factor model for predicting CO2 emissions," Energy, Elsevier, vol. 214(C).
- Jeon, Eui-Chan & Myeong, Soojeong & Sa, Jae-Whan & Kim, Jinsu & Jeong, Jae-Hak, 2010. "Greenhouse gas emission factor development for coal-fired power plants in Korea," Applied Energy, Elsevier, vol. 87(1), pages 205-210, January.
- Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014.
"Carbon emission coefficient measurement of the coal-to-power energy chain in China,"
Applied Energy, Elsevier, vol. 114(C), pages 290-300.
- Zhi-Shuang Zhu & Hua Liao & Huai-Shu Cao & Lu Wang & Yi-Ming Wei & Jinyue Yan, 2012. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," CEEP-BIT Working Papers 38, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
- Shiwei Yu & Yi-Ming Wei & Haixiang Guo & Liping Ding, 2012. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," CEEP-BIT Working Papers 39, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
- Wierzbowski, Michal & Lyzwa, Wojciech & Musial, Izabela, 2016. "MILP model for long-term energy mix planning with consideration of power system reserves," Applied Energy, Elsevier, vol. 169(C), pages 93-111.
- Zheqi Yang & Xuming Dou & Yuqing Jiang & Pengfei Luo & Yu Ding & Baosheng Zhang & Xu Tang, 2022. "Tracking the CO 2 Emissions of China’s Coal Production via Global Supply Chains," Energies, MDPI, vol. 15(16), pages 1-10, August.
- Wang, Ning & Ren, Yixin & Zhu, Tao & Meng, Fanxin & Wen, Zongguo & Liu, Gengyuan, 2018. "Life cycle carbon emission modelling of coal-fired power: Chinese case," Energy, Elsevier, vol. 162(C), pages 841-852.
- Gutiérrez-Martín, F. & Da Silva-Álvarez, R.A. & Montoro-Pintado, P., 2013. "Effects of wind intermittency on reduction of CO2 emissions: The case of the Spanish power system," Energy, Elsevier, vol. 61(C), pages 108-117.
- Huafang Huang & Xiaomao Wu & Xianfu Cheng, 2021. "The Prediction of Carbon Emission Information in Yangtze River Economic Zone by Deep Learning," Land, MDPI, vol. 10(12), pages 1-23, December.
- Nam, KiJeon & Hwangbo, Soonho & Yoo, ChangKyoo, 2020. "A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
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Keywords
CO 2 ; emission; coal-fired power plant; deep learning; data-driven;All these keywords.
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