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Biomass and waste plastics chemical looping co-gasification for hydrogen-electricity-DME conservation and recycling based on machine learning

Author

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  • Tian, Wende
  • Zhang, Shuming
  • Wang, Shaochen
  • Liu, Bin
  • Cui, Zhe

Abstract

The reasonable utilization of organic solid waste can solve the problem of fossil energy shortage, but there are also challenges of high processing cost and difficulty. In this paper, a novel polygeneration system integrating biomass and waste plastic chemical looping co-gasification (BPCLG) for hydrogen production, power generation, and dimethyl ether (DME) synthesis is established and optimized by coupling process simulation and machine learning (ML) to achieve efficient utilization of organic solid waste. The artificial neural network (ANN) is employed to develop surrogate models for predicting the molar fractions of critical components in syngas and the system energy consumption. Then the non-dominated sorting genetic algorithm-II (NSGA-II) is utilized to optimize two objectives including the highest molar fraction of hydrogen in syngas and the lowest energy consumption. The optimized polygeneration system increased hydrogen production by 4.36 % and reduced energy consumption by 3.59 %. This work advances the resourceful utilization of organic solid waste while alleviating the energy crisis.

Suggested Citation

  • Tian, Wende & Zhang, Shuming & Wang, Shaochen & Liu, Bin & Cui, Zhe, 2025. "Biomass and waste plastics chemical looping co-gasification for hydrogen-electricity-DME conservation and recycling based on machine learning," Energy, Elsevier, vol. 318(C).
    • Handle: RePEc:eee:energy:v:318:y:2025:i:c:s0360544225005109
    DOI: 10.1016/j.energy.2025.134868
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    References listed on IDEAS

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    1. Chen, Xiangxiang & Sun, Zhuang & Kuo, Po-Chih & Aziz, Muhammad, 2026. "Zero direct carbon emission renewable natural gas production from municipal solid waste via chemical looping," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PE).
    2. Ma, Tengyu & Zhang, Xiantao & Xiao, Jiadong & Wang, Ruilin & Ruan, Chongyan & Wang, Hongsheng, 2026. "Systematic analysis of a fully renewable tri-generation system based on solar-biomass gasification and chemical looping processes," Energy, Elsevier, vol. 344(C).
    3. Abouzied, Amr S. & Farouk, Naeim & Shaban, Mohamed & Abed, Azher M. & Alhomayani, Fahad M. & Formanova, Shoira & Khan, Mohammad Nadeem & Alturise, Fahad & Alkhalaf, Salem & Albalawi, Hind, 2025. "Optimization of Ex/energy efficiencies in an integrated compressed air energy storage system (CAES) using machine learning algorithms: A multi-objective approach based on analysis of variance," Energy, Elsevier, vol. 322(C).

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