Performance analysis of an integrated biomass-to-energy system based on gasification and pyrolysis

Li, Tongyu; Wang, Jinjun; Chen, Heng; Li, Wenchao; Pan, Peiyuan; Wu, Lining; Xu, Gang; Chen, Honggang

doi:10.1016/j.enconman.2023.117085

Cited by 33 publications

(8 citation statements)

References 52 publications

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“…Performance Analysis of Biomass-To-Energy System Based on Gasification and Pyrolysis [17] The pyrolysis of woody biomass generates bio-oil and accompanying gas that is mixed with gasification-produced syngas to increase its heating value, thereby increasing power generation.…”

Section: Performance Analysis and Improvement Reference Methodology O...mentioning

confidence: 99%

“…Tongyu Li et al, 2023 [17] a novel integrated biomass-to-energy system based on gasification and pyrolysis for efficient and sustainable energy production which is shown in Figure 8. The system combines the advantages of gasification and pyrolysis to convert different types of biomasses into electrical energy and hydrogen energy, respectively.…”

Section: Performance Analysis Of Biomass-to-energy System Based On Ga...mentioning

confidence: 99%

“…Meanwhile, the coupled system has low CO 2 , SO 2 , and NO x emissions and thus many advantages in terms of environmental performance. [17].…”

Section: Performance Analysis Of Biomass-to-energy System Based On Ga...mentioning

confidence: 99%

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Thermodynamic Analysis and Performance Improvement in Biomass Power Plant: A Comprehensive Review

Roni,

Abedin,

Islam

et al. 2024

AJMME

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Biomass power plants play a crucial role in the sustainable energy sector by converting organic materials such as agricultural residues, forest biomass, and dedicated energy crops into electricity and heat. Biomass power plants represent a viable and renewable energy solution that can contribute to transitioning to a low-carbon economy. Their ability to convert organic materials into electricity and heat, coupled with proper management of feedstocks and emissions, can provide a sustainable alternative to fossil fuel-based power generation. Biomass has appeared as one of the most encouraging renewable energy sources for the replacement of fossil fuels. An extensive study about the prospective of biomass to produce renewable energy in the world has been exhibited in this article. The biomass-driven combined heat and power plant demonstrates 67% and 12% efficiency improvement compared to the stand-alone biomass power plant. BFP-CCS performs best at the H2O/Mn2O3 mass ratio of 1.6, the H2O/O2 molar ratio of 2.8, the O2/biomass mass ratio of 0.22, and the fuel utilization factor of 0.65. The exergo-economic and exergo-environmental factors obtained are 51.5% and 0.0288% respectively at the favorable operating conditions. The round-trip efficiency of the process using R1233zd was 8.77%, which was slightly lower than that of the process using R245fa (8.84%). The net power output of the final CLC integrated configuration and conventional power plants are 492.19 kW and 273.12 kW respectively. A lot of energy can be recovered without low-temperature corrosion problems, and 7% of the total input energy can be saved. The maximum obtainable exergy efficiency was 42.03%, which was related to MSW (Municipal Solid Waste). The primary aim of this review is to furnish a thorough understanding of the thermodynamic complexities and potential improvements within biomass power plants. Through a critical analysis of current research and emerging technologies, this review aims to establish the groundwork for more effective and sustainable energy production from biomass, playing a crucial role in shaping a cleaner and more environmentally friendly future.

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Section: Performance Analysis and Improvement Reference Methodology O...mentioning

confidence: 99%

Section: Performance Analysis Of Biomass-to-energy System Based On Ga...mentioning

confidence: 99%

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Thermodynamic Analysis and Performance Improvement in Biomass Power Plant: A Comprehensive Review

Roni,

Abedin,

Islam

et al. 2024

AJMME

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“…1 As the only carbon-based renewable energy, biomass energy (bioenergy) is considered a potential alternative to fossil fuels due to its abundance, diverse utilization paths, and capacity to provide a consistent and reliable energy supply. 2 Bioenergy with carbon capture and storage (BECCS) can achieve negative carbon emissions, contributing to future carbon neutrality goals. 3 Biomass gasification shows promise as a route to convert biogenic wastes into high-value-added syngas, which can be further utilized as fuel or chemicals for power generation, heating supply, hydrogen production, Fischer−Tropsch synthesis, and more.…”

Section: Introductionmentioning

confidence: 99%

“…Renewable energy has garnered significant attention as an effective solution to the increasing global energy demand and substantial greenhouse gas emissions . As the only carbon-based renewable energy, biomass energy (bioenergy) is considered a potential alternative to fossil fuels due to its abundance, diverse utilization paths, and capacity to provide a consistent and reliable energy supply . Bioenergy with carbon capture and storage (BECCS) can achieve negative carbon emissions, contributing to future carbon neutrality goals .…”

Section: Introductionmentioning

confidence: 99%

Disentangled Representation Aided Physics-Informed Neural Network for Predicting Syngas Compositions of Biomass Gasification

Ren,

Wu,

Weng

et al. 2024

Energy Fuels

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Machine learning (ML) has been extensively studied and applied in the biomass gasification field currently. However, insufficient experimental data tends to cause a mismatch between the ML model and physical mechanism, particularly for the feedstocks that do not appear in the training data set, becoming a significant challenge in creating credible ML models for biomass gasification. Therefore, this study proposes a disentangled representation-aided physics-informed neural network method, briefly called DR-PINN, to predict biomass gasification syngas components. First, the DR-PINN extracts the latent variables to represent the feedstock properties through disentangled representation learning and generates synthetic samples in the gasificationrelated latent variable space to cover a full range of feedstock types. Then, DR-PINN employs inequality constraints to embed a priori monotonic relationships into the model training loss function. Finally, experimental and synthetic samples are simultaneously considered in the model training process to realize the synergy and complementarity of actual data information and existing physical knowledge using an evolutionary algorithm. As a result, DR-PINN shows good prediction performance (the feedstocks within the training data set: R 2 ≈ 0.96, root-mean-square error (RMSE) ≈ 1.7; the feedstocks outside the training data set: R 2 ≈ 0.81, RMSE ≈ 3). Moreover, even with the feedstocks outside the training data set, the DR-PINN model can strictly abide by the prior physical monotonic relationships, with the physical consistency degree equal to 1. Overall, the proposed DR-PINN demonstrates superior generalization and interpretability compared to other methods, such as RF, GBR, SVM, ANN, and PINN.

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Enhancing syngas production and hydrogen content in syngas from catalytic slow pyrolysis of biomass in a pilot scale fixed bed reactor

Alam,

Sarkar,

Chanda

et al. 2024

Biomass Conv. Bioref.

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Performance analysis of an integrated biomass-to-energy system based on gasification and pyrolysis

Cited by 33 publications

References 52 publications

Thermodynamic Analysis and Performance Improvement in Biomass Power Plant: A Comprehensive Review

Thermodynamic Analysis and Performance Improvement in Biomass Power Plant: A Comprehensive Review

Disentangled Representation Aided Physics-Informed Neural Network for Predicting Syngas Compositions of Biomass Gasification

Enhancing syngas production and hydrogen content in syngas from catalytic slow pyrolysis of biomass in a pilot scale fixed bed reactor

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