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Dynamic modeling of municipal solid waste incineration

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  • Magnanelli, Elisa
  • Tranås, Olaf Lehn
  • Carlsson, Per
  • Mosby, Jostein
  • Becidan, Michael

Abstract

In this work, a comprehensive dynamic model of a moving grate Waste-to-Energy plant is developed using MATLAB Simulink. The objective is to develop a reliable and flexible model which can reproduce the dynamic behavior of combustion chamber and boiler. For this purpose, an extensive number of process data is used both in model development and for validation. Contrary to previous works in literature, fluctuations in both waste properties and operational set points are taken into account. The validated model is then used to study the dynamic response of the plant to changes in important process parameters. As expected, the dynamic response of the plant is faster for changes in primary and secondary air than for changes in grate speed and waste flow. The steam production response is from 1 to 4 min slower than the flue gas oxygen concentration response. Moreover, the response time depends to a large extent on the properties of the waste; as an example, an increase in waste humidity from 25% to 35% results in a 21 min increase in the steam production response time. Such characterization of the dynamic response of the plant is fundamental to develop improved control strategies.

Suggested Citation

  • Magnanelli, Elisa & Tranås, Olaf Lehn & Carlsson, Per & Mosby, Jostein & Becidan, Michael, 2020. "Dynamic modeling of municipal solid waste incineration," Energy, Elsevier, vol. 209(C).
  • Handle: RePEc:eee:energy:v:209:y:2020:i:c:s0360544220315346
    DOI: 10.1016/j.energy.2020.118426
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    References listed on IDEAS

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    1. Malinauskaite, J. & Jouhara, H. & Czajczyńska, D. & Stanchev, P. & Katsou, E. & Rostkowski, P. & Thorne, R.J. & Colón, J. & Ponsá, S. & Al-Mansour, F. & Anguilano, L. & Krzyżyńska, R. & López, I.C. & , 2017. "Municipal solid waste management and waste-to-energy in the context of a circular economy and energy recycling in Europe," Energy, Elsevier, vol. 141(C), pages 2013-2044.
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    Cited by:

    1. Lianhong Chen & Chao Wang & Rigang Zhong & Jin Wang & Zheng Zhao, 2022. "Intelligent Modeling of the Incineration Process in Waste Incineration Power Plant Based on Deep Learning," Energies, MDPI, vol. 15(12), pages 1-12, June.
    2. Vasileiadou, Agapi & Zoras, Stamatis & Iordanidis, Andreas, 2021. "Biofuel potential of compost-like output from municipal solid waste: Multiple analyses of its seasonal variation and blends with lignite," Energy, Elsevier, vol. 236(C).
    3. Hatem Abushammala & Muhammad Adil Masood & Salma Taqi Ghulam & Jia Mao, 2023. "On the Conversion of Paper Waste and Rejects into High-Value Materials and Energy," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    4. Johan De Greef & Quynh N. Hoang & Raf Vandevelde & Wouter Meynendonckx & Zouhir Bouchaar & Giuseppe Granata & Mathias Verbeke & Mariya Ishteva & Tine Seljak & Jo Van Caneghem & Maarten Vanierschot, 2023. "Towards Waste-to-Energy-and-Materials Processes with Advanced Thermochemical Combustion Intelligence in the Circular Economy," Energies, MDPI, vol. 16(4), pages 1-19, February.
    5. Ding, Haixu & Tang, Jian & Qiao, Junfei, 2023. "Dynamic modeling of multi-input and multi-output controlled object for municipal solid waste incineration process," Applied Energy, Elsevier, vol. 339(C).
    6. Magnanelli, Elisa & Mosby, Jostein & Becidan, Michael, 2021. "Scenarios for carbon capture integration in a waste-to-energy plant," Energy, Elsevier, vol. 227(C).
    7. Natalia Vukovic & Evgenia Makogon, 2022. "Waste-to-Energy Generation: Complex Efficiency Analysis of Modern Technologies," Sustainability, MDPI, vol. 14(21), pages 1-18, October.

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