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<p>The integration of biomass gasification with power-to-gas (PtG) technology offers a promising pathway for sustainable energy production by converting surplus renewable electricity into bio-synthetic natural gas (Bio-SNG) (in the graphical abstract, this process is shown). This review provides a comprehensive assessment of modelling approaches used to represent gasification, methanation, and electrolysis within PtG–biomass systems. Reported Bio-SNG production efficiencies range from 26% to 86.4% (LHV), with the highest values achieved in dual fluidised bed (DFB) gasifiers operated at 750–850&#xa0;°C. Methanation is predominantly modelled using equilibrium approaches, although hybrid kinetic–equilibrium frameworks yield more realistic predictions in multi-stage systems where heat removal and reaction kinetics affect CH₄ yield. The most prevalent layout in our review is Option B: electrolytic hydrogen is introduced after pre-methanation into the main methanation stage<b>,</b> and electrolytic oxygen supports gasification (often with O₂ storage). Despite these advances, limitations remain. Many models are not validated against pilot-scale or industrial data, reducing confidence in scalability. Dynamic operation under fluctuating renewable inputs is rarely addressed, although it is central to PtG viability. Inconsistent system boundaries and efficiency definitions complicate direct comparisons across studies. Open research needs include: (i) validated kinetic models of gasification and methanation, (ii) dynamic simulations that capture transient renewable electricity input, (iii) techno-economic assessments considering carbon pricing and declining electrolyser costs, and (iv) operational strategies for managing variable hydrogen supply. Addressing these gaps will be essential to advance PtG–biomass gasification systems from conceptual modelling to commercial deployment in decarbonised energy networks.</p> Graphical Abstract <p></p>

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A review on modelling of power-to-gas energy storage integrated with biomass gasification

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月22日

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  • Mohadeseh Naderi,
  • Anthony Reynolds,
  • Wayne Doherty

摘要

The integration of biomass gasification with power-to-gas (PtG) technology offers a promising pathway for sustainable energy production by converting surplus renewable electricity into bio-synthetic natural gas (Bio-SNG) (in the graphical abstract, this process is shown). This review provides a comprehensive assessment of modelling approaches used to represent gasification, methanation, and electrolysis within PtG–biomass systems. Reported Bio-SNG production efficiencies range from 26% to 86.4% (LHV), with the highest values achieved in dual fluidised bed (DFB) gasifiers operated at 750–850 °C. Methanation is predominantly modelled using equilibrium approaches, although hybrid kinetic–equilibrium frameworks yield more realistic predictions in multi-stage systems where heat removal and reaction kinetics affect CH₄ yield. The most prevalent layout in our review is Option B: electrolytic hydrogen is introduced after pre-methanation into the main methanation stage, and electrolytic oxygen supports gasification (often with O₂ storage). Despite these advances, limitations remain. Many models are not validated against pilot-scale or industrial data, reducing confidence in scalability. Dynamic operation under fluctuating renewable inputs is rarely addressed, although it is central to PtG viability. Inconsistent system boundaries and efficiency definitions complicate direct comparisons across studies. Open research needs include: (i) validated kinetic models of gasification and methanation, (ii) dynamic simulations that capture transient renewable electricity input, (iii) techno-economic assessments considering carbon pricing and declining electrolyser costs, and (iv) operational strategies for managing variable hydrogen supply. Addressing these gaps will be essential to advance PtG–biomass gasification systems from conceptual modelling to commercial deployment in decarbonised energy networks.

Graphical Abstract