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Development of lower heating value prediction models and estimation of energy recovery potential of municipal solid waste and RDF incineration

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  • Kumar, Atul
  • Samadder, Sukha Ranjan

Abstract

Due to heterogeneity in municipal solid waste (MSW) characteristics and composition, the already available heating value estimation methods cannot be accurately applied for the cities of developing countries. In this study, both linear and non-linear approaches have been used for the development of lower heating value (LHV) prediction models. The models have been developed based on the physical composition, proximate analysis, and ultimate analysis of both mixed MSW and combustible components (food waste, yard waste, plastic, paper & cardboard, textile & rubber) separately. In total, six multiple linear regression (MLR) models and six artificial neural network (ANN) models have been developed. All of them can be used for the timely decision making as per the availability of data and requirements with a sufficient level of accuracy. The physical composition based LHV prediction models (both MLR and ANN) showed highest prediction performance. The models developed using combustible components showed slightly better prediction capabilities than mixed MSW based models. Further, in this study, an appropriate refuse-derived fuel (RDF) mix has been determined based on the ease of recovery of the individual waste components from the mixed MSW stream. Finally, the energy recovery potential from mass-burn incineration and RDF incineration has been evaluated. The energy recovery potential of proposed RDF (combination of plastic, paper & cardboard, textile & rubber and yard waste) and mixed MSW was found to be 1310 kWh/tonne and 837 kWh/tonne of dry weight respectively.

Suggested Citation

  • Kumar, Atul & Samadder, Sukha Ranjan, 2023. "Development of lower heating value prediction models and estimation of energy recovery potential of municipal solid waste and RDF incineration," Energy, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:energy:v:274:y:2023:i:c:s0360544223006679
    DOI: 10.1016/j.energy.2023.127273
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    References listed on IDEAS

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    1. Dastjerdi, B. & Strezov, V. & Kumar, R. & Behnia, M., 2019. "An evaluation of the potential of waste to energy technologies for residual solid waste in New South Wales, Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    2. Khan, Imran & Kabir, Zobaidul, 2020. "Waste-to-energy generation technologies and the developing economies: A multi-criteria analysis for sustainability assessment," Renewable Energy, Elsevier, vol. 150(C), pages 320-333.
    3. Lopes, E.J. & Okamura, L.A. & Maruyama, S.A. & Yamamoto, C.I., 2018. "Evaluation of energy gain from the segregation of organic materials from municipal solid waste in gasification processes," Renewable Energy, Elsevier, vol. 116(PA), pages 623-629.
    4. Wang, Dan & Tang, Yu-Ting & He, Jun & Yang, Fei & Robinson, Darren, 2021. "Generalized models to predict the lower heating value (LHV) of municipal solid waste (MSW)," Energy, Elsevier, vol. 216(C).
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    Cited by:

    1. Bae, Jisu & Lee, Suyoung & Kim, Kyuyeon & Kang, Jun-gu & Jeon, Taewan, 2024. "Reassessment of lower heating value calculations for municipal solid waste incineration facilities in South Korea," Energy, Elsevier, vol. 293(C).
    2. Lidia Lombardi & Marco J. Castaldi, 2024. "Energy Recovery from Residual Municipal Solid Waste: State of the Art and Perspectives within the Challenge to Climate Change," Energies, MDPI, vol. 17(2), pages 1-18, January.

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