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Co-processing of petcoke and producer gas obtained from RDF gasification in a white cement plant: A techno-economic analysis

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  • Sharma, Prateek
  • Sheth, Pratik N.
  • Mohapatra, B.N.

Abstract

White cement production, unlike grey cement, depends entirely on ashless conventional fuels (oil, petcoke) to meet its thermal energy requirement. The primary barrier to utilizing any solid alternative fuel in white cement is the impact on whiteness due to ash content. The study is focused on establishing producer gas from refuse-derived fuel (RDF) gasification as an alternative fuel in clinker production in an Indian white cement plant with a 15% thermal substitution rate (TSR). A stoichiometric calciner model has been developed to predict calciner outlet parameters considering co-firing of petcoke and producer gas, where producer gas has a high heating value (HHV) of 3.95 MJ/Nm3 and gas yield of 2.36 Nm3/kg RDF. The model predicted the decrease in calciner outlet temperature by 2.6% at 15% TSR with 8.49% CO2 mitigation potential by replacing conventional fuel. It is concluded that RDF gasification is viable for white cement plants considering an IRR of 13.57% and discounted payback period of six years and two months for a 10-year gasifier operation. The study will facilitate the utilization of the RDF in white cement plants, reducing their manufacturing cost and dependence on fossil fuels.

Suggested Citation

  • Sharma, Prateek & Sheth, Pratik N. & Mohapatra, B.N., 2023. "Co-processing of petcoke and producer gas obtained from RDF gasification in a white cement plant: A techno-economic analysis," Energy, Elsevier, vol. 265(C).
    • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222031346
    DOI: 10.1016/j.energy.2022.126248
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    References listed on IDEAS

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    1. Silva, Isabelly P. & Lima, Rafael M.A. & Silva, Gabriel F. & Ruzene, Denise S. & Silva, Daniel P., 2019. "Thermodynamic equilibrium model based on stoichiometric method for biomass gasification: A review of model modifications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
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    3. Gan, Zhaowang & Guo, Qiang & Liu, Taishan & Ding, Guangchao & Li, Songgeng, 2025. "Optimization of sludge-derived fuel formulation based on co-combustion behaviors and artificial neural network modeling, with economic assessment," Energy, Elsevier, vol. 334(C).

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