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- Shen, Jiong, et al. Show all 4 Authors
- Energy 2020 v.196 pp. 117070
- algorithms; carbon dioxide; flue gas; neural networks; temperature
- ... This paper develops an intelligent predictive controller (IPC) for a large-scale solvent-based post-combustion CO₂ capture (PCC) process. An artificial neural network (NN) model is trained to represent the dynamics of the PCC process based on an in-depth behavior investigation of the process under different operating conditions. The resulting NN model can portray the PCC characteristics very well ...
- Shen, Jiong, et al. Show all 5 Authors
- Applied energy 2020 v.257 pp. 113941
- carbon; carbon dioxide; dynamic models; flue gas; fossil fuels; greenhouse gas emissions; power plants; process control
- ... Solvent-based post-combustion CO₂ capture (PCC) appears to be the most effective choice to overcome the CO₂ emission issue of fossil fuel fired power plants. To make the PCC better suited for power plants, growing interest has been directed to the flexible operation of PCC in the past ten years. The flexible operation requires the PCC system to adapt to the strong flue gas flow rate change and to ...