Improved coal combustion optimization model based on load balance and coal qualities
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DOI: 10.1016/j.energy.2017.05.068
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References listed on IDEAS
- Wei, Zhongbao & Li, Xiaolu & Xu, Lijun & Cheng, Yanting, 2013. "Comparative study of computational intelligence approaches for NOx reduction of coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 683-692.
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Cited by:
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- Lv, You & Lv, Xuguang & Fang, Fang & Yang, Tingting & Romero, Carlos E., 2020. "Adaptive selective catalytic reduction model development using typical operating data in coal-fired power plants," Energy, Elsevier, vol. 192(C).
- Yin, Junjie & Liu, Ming & Zhao, Yongliang & Wang, Chaoyang & Yan, Junjie, 2021. "Dynamic performance and control strategy modification for coal-fired power unit under coal quality variation," Energy, Elsevier, vol. 223(C).
- Chuanpeng Zhu & Pu Huang & Yiguo Li, 2022. "Closed-Loop Combustion Optimization Based on Dynamic and Adaptive Models with Application to a Coal-Fired Boiler," Energies, MDPI, vol. 15(14), pages 1-16, July.
- Zhu, Hengyi & Tan, Peng & He, Ziqian & Ma, Lun & Zhang, Cheng & Fang, Qingyan & Chen, Gang, 2023. "Revealing steam temperature characteristics for a double-reheat unit under coal calorific value variation," Energy, Elsevier, vol. 283(C).
- Mollo, Malebo & Kolesnikov, Andrei & Makgato, Seshibe, 2022. "Simultaneous reduction of NOx emission and SOx emission aided by improved efficiency of a Once-Through Benson Type Coal Boiler," Energy, Elsevier, vol. 248(C).
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- Tang, Zhenhao & Wang, Shikui & Chai, Xiangying & Cao, Shengxian & Ouyang, Tinghui & Li, Yang, 2022. "Auto-encoder-extreme learning machine model for boiler NOx emission concentration prediction," Energy, Elsevier, vol. 256(C).
- Bartnicki, Grzegorz & Klimczak, Marcin & Ziembicki, Piotr, 2023. "Evaluation of the effects of optimization of gas boiler burner control by means of an innovative method of Fuel Input Factor," Energy, Elsevier, vol. 263(PD).
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Keywords
NOx emissions; Optimization model; Coal qualities; Load balance; Coal-fired boiler;All these keywords.
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