Towards application of machine learning algorithms for prediction temperature distribution within CFB boiler based on specified operating conditions
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2021.121538
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Smrekar, J. & Assadi, M. & Fast, M. & Kuštrin, I. & De, S., 2009. "Development of artificial neural network model for a coal-fired boiler using real plant data," Energy, Elsevier, vol. 34(2), pages 144-152.
- Adamczyk, Wojciech P. & Myöhänen, Kari & Hartge, Ernst-Ulrich & Ritvanen, Jouni & Klimanek, Adam & Hyppänen, Timo & Białecki, Ryszard A., 2018. "Generation of data sets for semi-empirical models of circulated fluidized bed boilers using hybrid Euler-Lagrange technique," Energy, Elsevier, vol. 143(C), pages 219-240.
- Ma, Yunpeng & Niu, Peifeng & Yan, Shanshan & Li, Guoqiang, 2018. "A modified online sequential extreme learning machine for building circulation fluidized bed boiler's NOx emission model," Applied Mathematics and Computation, Elsevier, vol. 334(C), pages 214-226.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Izabella Maj, 2022. "Significance and Challenges of Poultry Litter and Cattle Manure as Sustainable Fuels: A Review," Energies, MDPI, vol. 15(23), pages 1-17, November.
- Zima, Wiesław & Taler, Jan & Grądziel, Sławomir & Trojan, Marcin & Cebula, Artur & Ocłoń, Paweł & Dzierwa, Piotr & Taler, Dawid & Rerak, Monika & Majdak, Marek & Korzeń, Anna & Skrzyniowska, Dorota, 2022. "Thermal calculations of a natural circulation power boiler operating under a wide range of loads," Energy, Elsevier, vol. 261(PB).
- Sungur, Bilal & Basar, Cem & Kaleli, Alirıza, 2023. "Multi-objective optimisation of the emission parameters and efficiency of pellet stove at different supply airflow positions based on machine learning approach," Energy, Elsevier, vol. 278(PA).
- Yan, Peiliang & Fan, Weijun & Zhang, Rongchun, 2023. "Predicting the NOx emissions of low heat value gas rich-quench-lean combustor via three integrated learning algorithms with Bayesian optimization," Energy, Elsevier, vol. 273(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Fredrik Skaug Fadnes & Reyhaneh Banihabib & Mohsen Assadi, 2023. "Using Artificial Neural Networks to Gather Intelligence on a Fully Operational Heat Pump System in an Existing Building Cluster," Energies, MDPI, vol. 16(9), pages 1-33, May.
- Liukkonen, M. & Heikkinen, M. & Hiltunen, T. & Hälikkä, E. & Kuivalainen, R. & Hiltunen, Y., 2011. "Artificial neural networks for analysis of process states in fluidized bed combustion," Energy, Elsevier, vol. 36(1), pages 339-347.
- Xuemin Liu & Hairui Yang & Junfu Lyu, 2020. "Optimization of Fluidization State of a Circulating Fluidized Bed Boiler for Economical Operation," Energies, MDPI, vol. 13(2), pages 1-20, January.
- Nikpey, H. & Assadi, M. & Breuhaus, P., 2013. "Development of an optimized artificial neural network model for combined heat and power micro gas turbines," Applied Energy, Elsevier, vol. 108(C), pages 137-148.
- Rostek, Kornel & Morytko, Łukasz & Jankowska, Anna, 2015. "Early detection and prediction of leaks in fluidized-bed boilers using artificial neural networks," Energy, Elsevier, vol. 89(C), pages 914-923.
- Vo, Nguyen Dat & Oh, Dong Hoon & Kang, Jun-Ho & Oh, Min & Lee, Chang-Ha, 2020. "Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas," Applied Energy, Elsevier, vol. 273(C).
- Mousapour, Ashkan & Hajipour, Alireza & Rashidi, Mohammad Mehdi & Freidoonimehr, Navid, 2016. "Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction," Energy, Elsevier, vol. 94(C), pages 100-109.
- Kljajić, Miroslav & Gvozdenac, Dušan & Vukmirović, Srdjan, 2012. "Use of Neural Networks for modeling and predicting boiler's operating performance," Energy, Elsevier, vol. 45(1), pages 304-311.
- Navarkar, Abhishek & Hasti, Veeraraghava Raju & Deneke, Elihu & Gore, Jay P., 2020. "A data-driven model for thermodynamic properties of a steam generator under cycling operation," Energy, Elsevier, vol. 211(C).
- Zhu, Yukun & Yu, Cong & Fan, Wei & Yu, Haiquan & Jin, Wei & Chen, Shuo & Liu, Xia, 2023. "A novel NOx emission prediction model for multimodal operational utility boilers considering local features and prior knowledge," Energy, Elsevier, vol. 280(C).
- Jiang, Xiaolong & Liu, Pei & Li, Zheng, 2014. "Gross error isolability for operational data in power plants," Energy, Elsevier, vol. 74(C), pages 918-927.
- Shi, Yan & Zhong, Wenqi & Chen, Xi & Yu, A.B. & Li, Jie, 2019. "Combustion optimization of ultra supercritical boiler based on artificial intelligence," Energy, Elsevier, vol. 170(C), pages 804-817.
- Rashidi, M.M. & Ali, M. & Freidoonimehr, N. & Nazari, F., 2013. "Parametric analysis and optimization of entropy generation in unsteady MHD flow over a stretching rotating disk using artificial neural network and particle swarm optimization algorithm," Energy, Elsevier, vol. 55(C), pages 497-510.
- Peng, Gongzhuang & Wang, Hongwei & Song, Xiao & Zhang, Heming, 2017. "Intelligent management of coal stockpiles using improved grey spontaneous combustion forecasting models," Energy, Elsevier, vol. 132(C), pages 269-279.
- Yuansheng, Huang & Mengshu, Shi, 2021. "What are the environmental advantages of circulating fluidized bed technology? ——A case study in China," Energy, Elsevier, vol. 220(C).
- Lv, You & Hong, Feng & Yang, Tingting & Fang, Fang & Liu, Jizhen, 2017. "A dynamic model for the bed temperature prediction of circulating fluidized bed boilers based on least squares support vector machine with real operational data," Energy, Elsevier, vol. 124(C), pages 284-294.
- Zhou, Taotao & Tang, Peng & Ye, Taohong, 2023. "Machine learning based heat release rate indicator of premixed methane/air flame under wide range of equivalence ratio," Energy, Elsevier, vol. 263(PE).
- Lv, You & Liu, Jizhen & Yang, Tingting & Zeng, Deliang, 2013. "A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 319-329.
- Yunpeng Ma & Chenheng Xu & Hua Wang & Ran Wang & Shilin Liu & Xiaoying Gu, 2022. "Model NOx, SO 2 Emissions Concentration and Thermal Efficiency of CFBB Based on a Hyper-Parameter Self-Optimized Broad Learning System," Energies, MDPI, vol. 15(20), pages 1-19, October.
- Alobaid, Falah & Peters, Jens & Amro, Rami & Epple, Bernd, 2020. "Dynamic process simulation for Polish lignite combustion in a 1MWth circulating fluidized bed during load changes," Applied Energy, Elsevier, vol. 278(C).
More about this item
Keywords
Prediction; Machine learning; CFB; Erosion; Boiler malfunction; Deep learning algorithms;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221017862. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.