A Data-Driven Method to Monitor Carbon Dioxide Emissions of Coal-Fired Power Plants
Author:
Zhou Shangli1, He Hengjing1, Zhang Leping1, Zhao Wei1, Wang Fei2ORCID
Affiliation:
1. Digital Grid Research Institute, China Southern Power Grid, Guangzhou 510663, China 2. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract
Reducing CO2 emissions from coal-fired power plants is an urgent global issue. Effective and precise monitoring of CO2 emissions is a prerequisite for optimizing electricity production processes and achieving such reductions. To obtain the high temporal resolution emissions status of power plants, a lot of research has been done. Currently, typical solutions are utilizing Continuous Emission Monitoring System (CEMS) to measure CO2 emissions. However, these methods are too expensive and complicated because they require the installation of a large number of devices and require periodic maintenance to obtain accurate measurements. According to this limitation, this paper attempts to provide a novel data-driven method using net power generation to achieve near-real-time monitoring. First, we study the key elements of CO2 emissions from coal-fired power plants (CFPPs) in depth and design a regression and physical variable model-based emission simulator. We then present Emission Estimation Network (EEN), a heterogeneous network-based deep learning model, to estimate CO2 emissions from CFPPs in near-real-time. We use artificial data generated by the simulator to train it and apply a few real-world datasets to complete the adaptation. The experimental results show that our proposal is a competitive approach that not only has accurate measurements but is also easy to implement.
Funder
Digital Grid Research Institute, China Southern Power Grid Guangdong Provincial Key Laboratory of Digital Grid Technology
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference64 articles.
1. Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.M. (2013). Climate Change 2013: The Physical Science Basis, Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press. 2. Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., and Gomis, M.I. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press. 3. EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012;Crippa;Earth Syst. Sci. Data,2019 4. A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide;Liu;Atmos. Chem. Phys.,2020 5. Yang, Z., Dou, X., Jiang, Y., Luo, P., Ding, Y., Zhang, B., and Tang, X. (2022). Tracking the CO2 Emissions of China’s Coal Production via Global Supply Chains. Energies, 15.
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