| Peer-Reviewed

Dynamic Modelling and Simulation of Coal Pulverizer

Received: 17 August 2021    Accepted: 3 September 2021    Published: 15 September 2021
Views:       Downloads:
Abstract

The mathematical model and simulation of coal pulverizer has been presented in the paper using first principle mass and heat balance equations based on physical insight. The coal mass flow is modelled based on the mass balance model. The pulverized coal temperature is modelled by considering the coal and the pulverized coal as a lumped thermal mass. The multi variable non-linear model is simulated in Python environment and the parameters are obtained by using the moving horizon estimation. The archived data from an operating 660 MW coal fired boiler database are used to identify the parameters and to be compared with the model outputs. As the megawatt power output of thermal power generating plant is directly influenced by the coal being fired into the boiler, it is necessary to study the dynamic behaviour of the model as their poor dynamic performance causes a slow megawatt ramp up or ramp down rate and also causes shutdown of plant in some cases. In view of more and more penetration of renewable energy in the power grid, rapid and automatic flexible operation of coal fired boiler is necessary to accommodate injection of renewable power or withdrawal of renewable power as both remain connected directly or indirectly to the same power grid. Hence, fast response of the steam generating boiler is desired in a coal fired thermal power generating unit to generate the megawatt load as per the demand placed on the grid to maintain the power system frequency which calls for support of boiler steam flow, pressure and temperature to the steam turbine generator equipment. In order to achieve that, performance of combustion control of the boiler is one of the important factors which can be improved by modelling and implementing the predictive dynamic behaviour of coal pulverizer under varying coal feed rate in the boiler control system. The main focus of the work is to determine the pulverizer response under varying coal flow and coal characteristic condition with an objective of keeping minimum differential pressure across it based on a realistic mathematical model of pulverizer so that the boiler response can be improved under transient condition of megawatt load demand variation. The simulated model responses for various scenarios are also presented in this paper.

Published in International Journal of Mechanical Engineering and Applications (Volume 9, Issue 4)
DOI 10.11648/j.ijmea.20210904.11
Page(s) 58-71
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

DAE, NLP, NOx, HGI

References
[1] Piotr Niemczyk, Jan Dimon Bendtson, Anders Peter Ravn, Palle Anderson, Tom Sondergaard Pedersen,(2012), Derivation and validation of a coal mill model for control, Control Engineering Practice, 20, 519–530.
[2] P Pradeebha, N Pappa, D Vasanthi,(2013), Modeling and Control of Coal Mill, The International Federation of Automatic Control, 18-20.
[3] Xiufan Liang, Yiguo Li, Xiao Wu and Jiong Shen,(2018), Nonlinear Modeling and Inferential Multi-Model Predictive Control of a Pulverizing System in a Coal Fired Power Plant based on Moving Horizon Estimation, Energies
[4] Hwi-Beom Shin, Xin-lan Li, In-Young Jeong, Jong-Man Park, and Soonyoung Lee,(2009), Modeling and Parameter Identification of Coal Mill, Journal of Power Electronics, 700-706.
[5] Haseltine, E. L. and J. B. Rawlings (2005). Critical evaluation of extended kalman filtering and moving horizon estimation. Ind. Eng. Chem. Res. 44, 2451–2460.
[6] Agrawal, V.; Panigrahi, B. K.; Subbarao, P. M. V,.(2015), Review of control and fault diagnosis methods applied to coal mills. J. Process Control, 32, 138–153.
[7] Agrawal, V.; Panigrahi, B. K.; Subbarao, P. M. V. (2015), A unified thermo-mechanical model for coal mill operation. Control Eng. Pract. 44, 157–171.
[8] Gao, Y.; Zeng, D.; Liu, J.; Jian, Y. (2017), Optimization control of a pulverizing system on the basis of the estimation of the outlet coal powder flow of a coal mill. Control Eng. Pract., 63, 69–80.
[9] Wu, X; Shen, J; Li, Y; Lee, K. Y. (2014), Fuzzy modelling and stable model predictive tracking control of large scale power plants, J. Process Control, 24, 1609-1626.
[10] Garriga, J. L.; Soroush, M,. (2010), Model predictive control tuning methods: A review. Ind. Eng. Chem. Res, 49, 3505–3515.
[11] Zeng, D. L.; Hu, Y.; Gao, S.; Liu, J. Z.(2015), Modelling and control of pulverizing system considering coal moisture. Energy, 80, 55–63.
[12] Cortinovis A., Mercangoez M., and Mathur T., B (2013) Nonlinear coal mill modeling and its application to model predictive control. Control Engineering Practice, 21, 308–320.
[13] Lei, Y.; Yang, B.; Jiang, X.; Jia, F.; Li, N.; Nandi, A. K. (2020), Applications of machine learning to machine fault diagnosis: A review and roadmap. Mech. Syst. Signal Process, 138, 106587
[14] Yong Hu; Boyu Ping; Deliang Jeng; Yuguang Niu; Yaokui Gao; (2020), Modelling of coal mill system used for fault simulation, Energies, 13 (7), 1784.
[15] Bhatt, D.; Dadiala, V.; Barve, J. (2018), Industrial Coal Pulverizer Model Simulation and Parametric Investigation. IFAC Papers online, 51, 115–120.
Cite This Article
  • APA Style

    Sumanta Basu, Sushil Cherian. (2021). Dynamic Modelling and Simulation of Coal Pulverizer. International Journal of Mechanical Engineering and Applications, 9(4), 58-71. https://doi.org/10.11648/j.ijmea.20210904.11

    Copy | Download

    ACS Style

    Sumanta Basu; Sushil Cherian. Dynamic Modelling and Simulation of Coal Pulverizer. Int. J. Mech. Eng. Appl. 2021, 9(4), 58-71. doi: 10.11648/j.ijmea.20210904.11

    Copy | Download

    AMA Style

    Sumanta Basu, Sushil Cherian. Dynamic Modelling and Simulation of Coal Pulverizer. Int J Mech Eng Appl. 2021;9(4):58-71. doi: 10.11648/j.ijmea.20210904.11

    Copy | Download

  • @article{10.11648/j.ijmea.20210904.11,
      author = {Sumanta Basu and Sushil Cherian},
      title = {Dynamic Modelling and Simulation of Coal Pulverizer},
      journal = {International Journal of Mechanical Engineering and Applications},
      volume = {9},
      number = {4},
      pages = {58-71},
      doi = {10.11648/j.ijmea.20210904.11},
      url = {https://doi.org/10.11648/j.ijmea.20210904.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20210904.11},
      abstract = {The mathematical model and simulation of coal pulverizer has been presented in the paper using first principle mass and heat balance equations based on physical insight. The coal mass flow is modelled based on the mass balance model. The pulverized coal temperature is modelled by considering the coal and the pulverized coal as a lumped thermal mass. The multi variable non-linear model is simulated in Python environment and the parameters are obtained by using the moving horizon estimation. The archived data from an operating 660 MW coal fired boiler database are used to identify the parameters and to be compared with the model outputs. As the megawatt power output of thermal power generating plant is directly influenced by the coal being fired into the boiler, it is necessary to study the dynamic behaviour of the model as their poor dynamic performance causes a slow megawatt ramp up or ramp down rate and also causes shutdown of plant in some cases. In view of more and more penetration of renewable energy in the power grid, rapid and automatic flexible operation of coal fired boiler is necessary to accommodate injection of renewable power or withdrawal of renewable power as both remain connected directly or indirectly to the same power grid. Hence, fast response of the steam generating boiler is desired in a coal fired thermal power generating unit to generate the megawatt load as per the demand placed on the grid to maintain the power system frequency which calls for support of boiler steam flow, pressure and temperature to the steam turbine generator equipment. In order to achieve that, performance of combustion control of the boiler is one of the important factors which can be improved by modelling and implementing the predictive dynamic behaviour of coal pulverizer under varying coal feed rate in the boiler control system. The main focus of the work is to determine the pulverizer response under varying coal flow and coal characteristic condition with an objective of keeping minimum differential pressure across it based on a realistic mathematical model of pulverizer so that the boiler response can be improved under transient condition of megawatt load demand variation. The simulated model responses for various scenarios are also presented in this paper.},
     year = {2021}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Dynamic Modelling and Simulation of Coal Pulverizer
    AU  - Sumanta Basu
    AU  - Sushil Cherian
    Y1  - 2021/09/15
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijmea.20210904.11
    DO  - 10.11648/j.ijmea.20210904.11
    T2  - International Journal of Mechanical Engineering and Applications
    JF  - International Journal of Mechanical Engineering and Applications
    JO  - International Journal of Mechanical Engineering and Applications
    SP  - 58
    EP  - 71
    PB  - Science Publishing Group
    SN  - 2330-0248
    UR  - https://doi.org/10.11648/j.ijmea.20210904.11
    AB  - The mathematical model and simulation of coal pulverizer has been presented in the paper using first principle mass and heat balance equations based on physical insight. The coal mass flow is modelled based on the mass balance model. The pulverized coal temperature is modelled by considering the coal and the pulverized coal as a lumped thermal mass. The multi variable non-linear model is simulated in Python environment and the parameters are obtained by using the moving horizon estimation. The archived data from an operating 660 MW coal fired boiler database are used to identify the parameters and to be compared with the model outputs. As the megawatt power output of thermal power generating plant is directly influenced by the coal being fired into the boiler, it is necessary to study the dynamic behaviour of the model as their poor dynamic performance causes a slow megawatt ramp up or ramp down rate and also causes shutdown of plant in some cases. In view of more and more penetration of renewable energy in the power grid, rapid and automatic flexible operation of coal fired boiler is necessary to accommodate injection of renewable power or withdrawal of renewable power as both remain connected directly or indirectly to the same power grid. Hence, fast response of the steam generating boiler is desired in a coal fired thermal power generating unit to generate the megawatt load as per the demand placed on the grid to maintain the power system frequency which calls for support of boiler steam flow, pressure and temperature to the steam turbine generator equipment. In order to achieve that, performance of combustion control of the boiler is one of the important factors which can be improved by modelling and implementing the predictive dynamic behaviour of coal pulverizer under varying coal feed rate in the boiler control system. The main focus of the work is to determine the pulverizer response under varying coal flow and coal characteristic condition with an objective of keeping minimum differential pressure across it based on a realistic mathematical model of pulverizer so that the boiler response can be improved under transient condition of megawatt load demand variation. The simulated model responses for various scenarios are also presented in this paper.
    VL  - 9
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • Department of Electrical and I&C Engineering, L&T-MHI POWER Boilers Private Limited, Faridabad, India

  • Kalki Communication Technologies Pvt Ltd, Bangalore, India

  • Sections