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

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

Energy, 2025, vol. 318, issue C

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.

Keywords: Renewable energy; Solid waste recovery; Chemical looping co-gasification; Polygeneration system (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225005109
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s0360544225005109

DOI: 10.1016/j.energy.2025.134868

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().