Renewable Energy最新文献_第5页

Insight into physicochemical properties and carbon-silicon interaction mechanisms of biochar during gasification 生物炭在气化过程中的物理化学性质和碳硅相互作用机制

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125289

Xuemei Fu , Beibei Yan , Jian Li , Zhi Wang , Xiaoqiang Cui , Guanyi Chen , Li'an Hou

Biomass gasification emerges as a potential technology for biochar production due to its carbon neutral property and independence to external energy sources. Compared to pyrolysis for producing biochar, the biomass gasification is more complex which contains pyrolysis, reduction, and oxidation stages. In this study, a series of experiment was performed to exactly control the heating rate and atmosphere in order to collect the biochars from different stages of gasification. With comprehensive characterizations, the evolution of biochar's physicochemical properties and the interaction between carbon and silicon during different stages of gasification were investigated. Biomass undergoes sequential dehydration, demethylation, decarboxylation, and secondary demethylation reactions. The graphitization of carbon begins during the pyrolysis stage, whereas the crystallization of silicon primarily occurs in the reduction and oxidation stages. The proportion of hydrogen bonding functional group rapidly declined during the oxidation stage, from 82.99 % to 14.32 %. A dense three-layer carbon-silicon-carbon structure forms. During the reduction and oxidation stages, a gradual occurrence of silicon-encapsulated carbon structures is found, and carbon is immobilized through the interactions with different types of siloxane. This work provides new insights into the preparation of biochar by gasification, which paves a way for the precise control and smart design of gasification process.

生物质气化由于其碳中性和不依赖外部能源的特性而成为一种潜在的生物炭生产技术。与热解生产生物炭相比，生物质气化更为复杂，包括热解、还原和氧化三个阶段。在本研究中，为了准确控制加热速率和气氛，进行了一系列实验，以收集不同气化阶段的生物炭。通过综合表征，研究了不同气化阶段生物炭理化性质的演变以及碳硅之间的相互作用。生物质经历连续的脱水、去甲基化、脱羧和二次去甲基化反应。碳的石墨化始于热解阶段，而硅的结晶主要发生在还原和氧化阶段。氢键官能团的比例在氧化阶段迅速下降，从82.99%下降到14.32%。形成致密的三层碳-硅-碳结构。在还原和氧化阶段，逐渐出现硅包覆碳结构，碳通过与不同类型硅氧烷的相互作用被固定。本研究为气化制备生物炭提供了新的见解，为气化过程的精确控制和智能设计铺平了道路。

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引用次数: 0

Design and proposal of a high-efficiency small wind turbine for distributed energy in low-wind regions 低风区分布式能源高效小型风力机的设计与方案

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125295

D. Mora-Herrera , G.L. Apan-Araujo , S.D. Flores-Cajica , Mou Pal

This research analyzes the design and performance of a small horizontal-axis wind turbine (HAWT) optimized for low-wind conditions in Amozoc, Puebla, Mexico. A wind resource assessment identified the Birnbaum-Saunders and Inverse Gaussian distributions as the best models for wind speed. Using QBlade software and Blade Element Momentum (BEM) theory, we analyzed six airfoils: NACA 4412, NACA 23012, Selig S1223, NREL S834, SG6042, and E216 to assess their lift-to-drag ratios (C_L/C_D). The E216 airfoil showed the highest aerodynamic efficiency, with a C_L/C_D ratio of 71.3 and a maximum lift coefficient (C_L) of 1.53 at the optimal angle of attack. To further improve performance, we optimized the chosen airfoil using a linear twist distribution. The final turbine design featured 1-m blades, a tip speed ratio (λ) of 5, and achieved a maximum power coefficient (C_P) of 0.44 with a power output of 16.5 W at an average wind speed of 2.42 m/s. The results suggest that airfoil optimization significantly enhances startup response and energy capture. These findings demonstrate the potential of small-scale wind turbines in low-wind rural areas, supporting distributed energy systems for applications like weather stations and micro-grids.

本研究分析了针对墨西哥普埃布拉州Amozoc低风条件优化的小型水平轴风力涡轮机（HAWT）的设计和性能。一项风力资源评估发现，Birnbaum-Saunders分布和逆高斯分布是风速的最佳模型。利用QBlade软件和叶片单元动量（BEM）理论，我们分析了六种翼型：NACA 4412、NACA 23012、Selig S1223、NREL S834、SG6042和E216，以评估它们的升阻比（CL/CD）。E216翼型表现出最高的气动效率，在最佳迎角下，CL/CD比为71.3，最大升力系数（CL）为1.53。为了进一步提高性能，我们使用线性扭转分布优化了选定的翼型。最终设计的涡轮叶片长度为1m，叶尖速比（λ）为5，最大功率系数（CP）为0.44，平均风速为2.42 m/s时输出功率为16.5 W。结果表明，翼型优化显著提高了启动响应和能量捕获。这些发现证明了小型风力涡轮机在低风力农村地区的潜力，支持分布式能源系统的应用，如气象站和微电网。

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引用次数: 0

Mitigating uncertainties: robust stochastic optimal operation of inter-regional hydro-wind-solar hybrid systems 减轻不确定性：区域间水能-风能-太阳能混合系统的鲁棒随机最优运行

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125230

He Li , Lewei Zhao , Zhikai Yang , Pan Liu , Bo Ming , Bojun Liu

The growing deployment of large-scale hydro-wind-solar hybrid systems at the basin scale calls for effective inter-regional coordination strategies. However, managing such systems under spatiotemporal renewable uncertainties poses significant challenges. This study proposes a robust stochastic optimization framework for inter-regional hydro-wind-solar hybrid system operations, integrating a multi-objective formulation, Markov-chain-based uncertainty representation, and stochastic dynamic programming with successive approximation to capture global uncertainties while reducing spatial complexity. Four operational schemes are designed for cross-comparison, including regional versus inter-regional and deterministic versus stochastic configurations. The framework is applied to the clean energy base of the upper Yellow River in China. The results indicate that inter-regional coordination consistently outperforms regional strategies, yielding additional power generation of 0.27 and 0.17 billion kWh under deterministic and stochastic conditions, respectively. Moreover, inter-regional operation exhibits enhanced robustness under stochastic optimization, as reflected by reduced variability in annual average generation, lower standard deviations of final reservoir water levels, and improved robustness indicators. These improvements arise from the mitigation of global uncertainties through coordinated operation, which further enhances downstream operational benefits by 2.0 %. Overall, the proposed framework provides a robust decision-making tool for optimizing inter-regional hydro-wind-solar hybrid systems under uncertainties.

在流域范围内越来越多地部署大型水电-风能-太阳能混合系统，需要有效的区域间协调战略。然而，在时空可再生不确定性下管理这样的系统带来了重大挑战。本研究提出了一种区域间水气-风能-太阳能混合系统运行的鲁棒随机优化框架，该框架集成了多目标公式、基于马尔可夫链的不确定性表示和随机动态规划与逐次逼近，以捕获全局不确定性，同时降低空间复杂性。设计了四种操作方案进行交叉比较，包括区域与区域间以及确定性与随机配置。将该框架应用于中国黄河上游清洁能源基地。结果表明，区域间协调优于区域策略，在确定性和随机条件下分别产生2.7亿千瓦时和1.7亿千瓦时的额外发电量。此外，在随机优化条件下，区域间调度的稳健性增强，表现为年平均发电量变异性减小，最终水库水位标准差降低，稳健性指标提高。这些改进源于通过协调作业减轻了全球不确定性，这进一步提高了下游运营效益2.0%。总体而言，所提出的框架为不确定条件下优化区域间水电-风能-太阳能混合系统提供了一个强大的决策工具。

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引用次数: 0

Seasonal storage of district heating surplus heat through borehole thermal energy storage: a global sensitivity analysis 井热蓄热季节性蓄热的全球敏感性分析

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125300

Ali Pour Ahmadiyan, Natasa Nord

Seasonal storage of surplus heat in district heating networks is an effective strategy for decarbonizing the heating sector and facilitating the integration of new neighborhoods into existing systems. In this paper, a borehole thermal energy storage system integrated with a district heating network, and a heat pump was investigated, supported by site-specific data from the Nyhavna case study in Trondheim, Norway. An efficient simulation framework was developed to capture both short-term thermal fluctuations and long-term interactions within the borehole field, as well as the coupling among system components under realistic operating conditions. A global sensitivity analysis was performed across design and operational variables through a system-level perspective. Seven variables were sampled using Latin hypercube method to generate 150 simulation cases. The high thermal conductivity of the studied site was found to significantly influence the interaction among variables and performance metrics. The maximum achieved borehole storage efficiency, and the heat pump coefficient of performance were 0.80 and 6.23, respectively. Maximum charging temperature, borehole spacing, and total borehole length were identified as the most influential variables on system performance, while heat pump characteristics predominantly affected the discharging phase. Across all configurations, the total system energy demand ranged from 352 to 665 GWh, with peak electricity and district heating demands spanned 2.2–9.2 MW and 9.9–42.2 MW, respectively. These results highlighted how coordinated sizing of the borehole field and heat pump, together with effective waste heat utilization, can moderate peak loads and total energy requirements under realistic design constraints.

在区域供热网络中季节性储存余热是使供热部门脱碳和促进新社区融入现有系统的有效策略。本文以挪威特隆赫姆尼哈夫纳案例研究的现场数据为依据，研究了一个集成了区域供热网络和热泵的钻孔热能储存系统。开发了一个有效的模拟框架，以捕获井内短期热波动和长期相互作用，以及实际操作条件下系统组件之间的耦合。通过系统级视角对设计和操作变量进行全局敏感性分析。采用拉丁超立方体方法对7个变量进行采样，生成150个模拟案例。研究发现，研究地点的高导热性显著影响变量和性能指标之间的相互作用。最大井内储能效率和热泵性能系数分别为0.80和6.23。最大充注温度、钻孔间距和钻孔总长度是影响系统性能的最大变量，而热泵特性主要影响放电阶段。在所有配置中，系统总能源需求范围为352至665吉瓦时，峰值电力和区域供热需求分别为2.2-9.2兆瓦和9.9-42.2兆瓦。这些结果强调了如何协调钻孔场和热泵的规模，以及有效的余热利用，可以在现实设计约束下调节峰值负荷和总能源需求。

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引用次数: 0

Rattan-based Janus evaporator decorated with dense arrays for efficient light harvesting and broad-spectrum solar absorption 以藤条为基础的Janus蒸发器装饰有密集阵列，用于高效的光收集和广谱太阳能吸收

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125288

Shaocong Wang, Haocheng Xu, Feiyu Tian, Yanan She, Xinwu Xu

Solar-driven interfacial evaporation is an effective solution to alleviate the global freshwater crisis. In this work, hydrophilic biomass-derived rattan was used as the substrate, with Ti₂O₃ and carbon nanoparticles spray-coated onto its surface without employing complex carbonization processes. Owing to the difference in hydrophilicity between these two photothermal materials, a synergistic effect led to the formation of microcone array structures on the rattan surface. This array structure prolongs the residence time of light, enhancing light harvesting while increasing the evaporation area. The hybrid coating combines the pronounced light absorption of Ti₂O₃ and carbon. This synergy enables broad-spectrum light absorption, reaching up to 95.97 %. Subsequently, a layer of polydimethylsiloxane (PDMS) was coated, and the hydrophobicity imparted by PDMS combined with the hydrophilicity of the rattan substrate formed a Janus structure. Under one-sun illumination, the Janus evaporator exhibited excellent freshwater output (2.39 kg m⁻² h⁻¹) and a photothermal conversion efficiency of 93.42 %. It achieved over 99 % purification efficiency for heavy metal ions, organic dyes, and saline solutions. Importantly, it demonstrated high stability in evaporation and salt resistance in real seawater. This low-cost and environmentally friendly evaporator offers novel insights for efficient light harvesting, demonstrating high application value and great potential in practical seawater desalination.

太阳能驱动的界面蒸发是缓解全球淡水危机的有效解决方案。在本研究中，采用亲水性生物质来源的藤条作为基材，在其表面喷涂Ti2O3和碳纳米颗粒，而无需采用复杂的碳化工艺。由于两种光热材料的亲水性不同，协同效应导致藤表面形成微锥阵列结构。这种阵列结构延长了光的停留时间，在增加蒸发面积的同时增强了光的收集。混合涂层结合了Ti2O3和碳的明显光吸收。这种协同作用使广谱光吸收达到95.97%。然后，涂覆一层聚二甲基硅氧烷（PDMS）， PDMS赋予的疏水性与藤底物的亲水性结合形成Janus结构。在单太阳光照下，Janus蒸发器表现出优异的淡水输出（2.39 kg m−2 h−1）和93.42%的光热转换效率。对重金属离子、有机染料、生理盐水的净化效率达到99%以上。重要的是，它在实际海水中表现出很高的蒸发稳定性和耐盐性。这种低成本、环保的蒸发器为高效光收集提供了新的见解，在实际海水淡化中显示出很高的应用价值和巨大的潜力。

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引用次数: 0

EPformer: Unlocking day-ahead electricity price forecasting accuracy using the time–frequency domain feature learning strategy considering renewable energy EPformer：利用考虑可再生能源的时频域特征学习策略解锁日前电价预测准确性

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125296

Hang Fan , Weican Liu , Zuhan Zhang , Wencai Run , Yunjie Duan , Dunnan Liu

Accurate day-ahead price forecasting is critical for power market participants in the electricity market. However, the increasing penetration of renewable energy introduces greater complexity and intermittency into electricity price patterns, making accurate day-ahead forecasting a significant challenge. To this end, we propose a novel framework for day-ahead electricity price forecasting, EPformer. Specifically, the proposed framework begins with a two-stage data preprocessing module. Then, the proposed framework adopts an encoder–decoder architecture. It first employs Bidirectional Long Short-Term Memory (BiLSTM) as the temporal encoder to capture sequential dependencies and utilizes Temporal Convolutional Networks (TCN) as the feature encoder to extract data features, respectively. The learned representations and additional data features are then fused and fed into the decoder to generate the final prediction. In addition, the proposed framework is trained using a customized loss function that integrates time–frequency domain features. This strategy replaces the conventional MSELoss training paradigm, which enables the model to effectively capture peak and valley features in electricity price, while also mitigating the inherent autocorrelation in the label sequences under the direct forecasting (DF) paradigm. Finally, we conduct a comprehensive evaluation and validation of the proposed model on two electricity price datasets from Shanxi in China.

准确的日前电价预测对电力市场参与者来说至关重要。然而，可再生能源的日益普及给电价模式带来了更大的复杂性和间歇性，使准确的日前预测成为一项重大挑战。为此，我们提出了一种新的日前电价预测框架——EPformer。具体来说，该框架从一个两阶段的数据预处理模块开始。然后，该框架采用编码器-解码器结构。首先利用双向长短期记忆（BiLSTM）作为时序编码器捕获序列依赖关系，利用时序卷积网络（TCN）作为特征编码器分别提取数据特征。然后将学习到的表示和额外的数据特征融合并馈送到解码器中以生成最终的预测。此外，所提出的框架使用集成时频域特征的自定义损失函数进行训练。该策略取代了传统的MSELoss训练范式，使模型能够有效地捕获电价的峰谷特征，同时也减轻了直接预测（DF）范式下标签序列固有的自相关性。最后，我们在中国山西省的两个电价数据集上对所提出的模型进行了综合评估和验证。

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引用次数: 0

Development of hybrid DNN-iPOA model for predicting diesel engine performance and emission for biodiesel optimization 基于混合DNN-iPOA模型的柴油机性能与排放预测及生物柴油优化研究

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125247

Veeresh M. Kodekal, C.R. Rajashekhar

This paper proposes a new method as a hybrid deep learning-based framework, the Deep Neural Network- Improved Pelican Optimization Algorithm (DNN-iPOA) framework, to improve the prediction of the engine performance and emission of biodiesel-fueled diesel engines. The model uses a 201 experimental data set having five important input variables (density, kinematic viscosity, cetane number, flash point and net calorific value) to predict six important output parameters: Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC), Carbon Monoxide (CO), Nitrogen Oxides (NO_X), Unburned Hydrocarbons (HC) and smoke opacity. Current performance of the proposed DNN-iPOA model is remarkable, with Mean Absolute Error (MAE) = 0.0064, Mean Squared Error (MSE) = 0.0001, Root Mean Squared Error (RMSE) = 0.008, Normalized MSE (NMSE) = 0.0035, Coefficient of Determination (R²) = 0.9965, and Adjusted R² = 0.9964. The proposed DNN-iPOA model showed significant performance, reducing the prediction error of MAE by about 2.8 % in smoke emissions. It also increased the accuracy of R² by up to 65.4 % in key parameters such as smoke emissions when compared to conventional models such as Recurrent Neural Network (RNN), Feedforward Neural Network (FNN), Convolutional Neural Network (CNN), and Long Short Term Memory (LSTM). These findings validate the better accuracy, generalization, and robustness of the model; hence, a valid model in the maximization of biodiesel utilization and minimization of diesel engine emissions.

本文提出了一种基于混合深度学习框架的新方法——深度神经网络-改进鹈鹕优化算法（DNN-iPOA）框架，以改进生物柴油发动机的发动机性能和排放预测。该模型使用具有五个重要输入变量（密度、运动粘度、十六烷值、闪点和净热值）的2011年实验数据集来预测六个重要输出参数：制动热效率（BTE）、制动比油耗（BSFC）、一氧化碳（CO）、氮氧化物（NOX）、未燃烧碳氢化合物（HC）和烟雾不透明度。目前提出的DNN-iPOA模型性能显著，平均绝对误差(MAE) = 0.0064，均方误差(MSE) = 0.0001，均方根误差(RMSE) = 0.008，归一化误差(NMSE) = 0.0035，决定系数(R2) = 0.9965，调整后的R2 = 0.9964。提出的DNN-iPOA模型表现出显著的性能，将MAE在烟雾排放中的预测误差降低了约2.8%。与循环神经网络（RNN）、前馈神经网络（FNN）、卷积神经网络（CNN）和长短期记忆（LSTM）等传统模型相比，它还将R2在烟雾排放等关键参数上的准确性提高了65.4%。这些发现验证了模型更好的准确性、泛化性和鲁棒性；因此，一个有效的模型在最大限度地利用生物柴油和最小的柴油发动机排放。

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引用次数: 0

Optimal operation of hydropower systems with environmental constraints on reservoir management 水库管理环境约束下水电系统优化运行

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125258

Linn Emelie Schäffer , Tor Haakon Bakken , Arild Helseth , Magnus Korpås

Hydropower is a low-carbon energy technology with a unique capability to provide flexibility and long-term energy storage, thus being a key contributor to cost-effective and reliable decarbonisation of power systems. To ensure sustainable operation, environmental regulations are normally imposed on the plants. Some of these regulations can be difficult to model in existing scheduling tools based on optimisation because of their non-convex and logical characteristics. This study contributes to the existing literature by assessing the operational impacts of two types of complex environmental reservoir constraints, with the aim to identify the operational implications as well as the economic impacts of including these constraints in medium-term hydropower scheduling. The results show that optimal reservoir management may change considerably due to these types of constraints. An important finding is that improved planning can reduce the economic loss associated with the environmental regulation, nevertheless, it is shown that the improvements depend on the power price and the characteristics of the hydropower system.

水电是一种低碳能源技术，具有独特的灵活性和长期储能能力，因此是电力系统经济可靠脱碳的关键因素。为确保可持续运作，工厂通常会实施环境法规。其中一些规则很难在现有的基于优化的调度工具中建模，因为它们具有非凸性和逻辑特性。本研究通过评估两类复杂的水库环境约束的运行影响来补充现有文献，旨在确定将这些约束纳入中期水电调度的运行影响和经济影响。结果表明，由于这些类型的约束，最优油藏管理可能会发生很大的变化。一个重要的发现是，改进规划可以减少与环境监管相关的经济损失，然而，研究表明，改进取决于电价和水电系统的特点。

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引用次数: 0

Techno-economic analysis of solar-powered electric float glass kiln 太阳能电动浮法玻璃窑技术经济分析

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125293

Benjun Cheng , Weibin Xu , Hao Feng , Sheng Yang , Xiaocheng Liang

Glass is extensively used in aerospace,precision instruments, and various other fields, where it plays an irreplaceable role. Currently most furnaces producing float glass burn fossil fuels or use electrodes for heating, and most of the electrodes source their electrical energy from coal combustion, which not only increases carbon emissions, but also increases the cost of glass production. Exploring and applying renewable energy sources can solve the energy and the emission problems faced by glass kilns. In this paper, a novel system was proposed for powering an electric float glass melting kiln using solar power generation, and then was simulated and analyzed using Aspen Plus process simulation software to integrate the energy flows while meeting the requirements of the glass production process. The performance metrics of a traditional float glass melting kiln (TFGK) and a solar-powered electrical fused float glass melting kiln (SEFGK) are presented in the form of simulation results. A comparative analysis of SEFGK and TFGK reveals a 30.5 % reduction in production costs, a 36.5 % reduction in low-carbon production costs, an improvement in energy efficiency by 25 %, an increase in the probability of positive net present value (NPV) by 2.1 %, and a reduction in carbon emissions by 1373.75 kg/t_glass. The implementation of SEFGK has been demonstrated to result in a reduction in greenhouse gas emissions, energy consumption and production costs. As technology advances, this study offers a framework for the prospective integration of renewable energy in electric float glass melting kilns.

玻璃广泛应用于航空航天、精密仪器等各个领域，发挥着不可替代的作用。目前，生产浮法玻璃的窑炉大多燃烧化石燃料或使用电极加热，而大多数电极的电能来自煤炭燃烧，这不仅增加了碳排放，也增加了玻璃生产成本。开发和应用可再生能源可以解决玻璃窑面临的能源和排放问题。本文提出了一种利用太阳能发电为电动浮法玻璃熔窑供电的新型系统，并利用Aspen Plus工艺仿真软件进行了仿真分析，在满足玻璃生产工艺要求的前提下，实现了能量流的集成。以仿真结果的形式给出了传统浮法玻璃熔窑（TFGK）和太阳能电熔浮法玻璃熔窑（SEFGK）的性能指标。SEFGK和TFGK的对比分析显示，生产成本降低30.5%，低碳生产成本降低36.5%，能源效率提高25%，净现值（NPV）正概率增加2.1%，碳排放量减少1373.75千克/吨玻璃。SEFGK的实施已被证明可以减少温室气体排放、能源消耗和生产成本。随着技术的进步，本研究为可再生能源在电动浮法玻璃熔窑的整合提供了一个框架。

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引用次数: 0

Reduction behavior and multiphase reaction mechanism of antimony oxide using representative biomass 代表性生物质还原氧化锑的行为及多相反应机理

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.renene.2026.125290

Renjie Tan , Jia Yang , Dachun Liu , Baozhong Ma , Zhaofeng Cui , Honglei Tan , Hongwei Yang , Bin Yang , Xiangfeng Kong

The traditional reduction smelting process for antimony oxide relies on coal-based reductants, which not only cause severe environmental pollution but also exhibit low reduction efficiency. This study systematically investigates the use of biomass as a reducing agent for antimony oxide reduction and elucidates its underlying reaction mechanism. In this study, five representative biomass types were first characterized, and their pyrolysis behavior was evaluated. Subsequently, the effects of biomass, biochar, and biomass pyrolysis gas on the reduction of antimony oxide were examined separately. Finally, the mechanism of antimony oxide reduction by biomass was revealed. The results indicate that pine sawdust exhibits the best reduction performance due to its high volatile content (71.47%), low ash content (0.96%), and well-developed porous structure. Additionally, at 1073 K with a reaction time of approximately 15 min, a high direct yield of antimony can be achieved. The synergistic interaction between gaseous reducing agents from biomass pyrolysis and biochar establishes a gas-liquid-solid three-phase reaction system, significantly enhancing the reduction process. This study clarifies the multiphase synergistic mechanism of antimony oxide reduction by biomass, providing theoretical insights to support the advancement of green and low-carbon metallurgical technologies.

传统的氧化锑还原冶炼工艺依赖于煤基还原剂，不仅环境污染严重，而且还原效率低。本研究系统地研究了利用生物质作为还原剂还原氧化锑，并阐明了其潜在的反应机理。本研究首先对5种具有代表性的生物质类型进行了表征，并对其热解行为进行了评价。随后，分别考察了生物质、生物炭和生物质热解气对氧化锑还原的影响。最后，揭示了生物质还原氧化锑的机理。结果表明，松木木屑具有挥发分高（71.47%）、灰分低（0.96%）、孔隙结构发达等特点，还原效果最佳。此外，在1073 K下，反应时间约为15分钟，可以实现高的锑的直接收率。生物质热解产生的气态还原剂与生物炭之间的协同作用建立了气-液-固三相反应体系，显著增强了还原过程。本研究阐明了生物质还原氧化锑的多相协同机理，为支持绿色低碳冶金技术的发展提供了理论见解。

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引用次数: 0