Renewable Energy最新文献_第5页

A two-stage framework for quantifying the impact of operating parameters and optimizing power density and oxygen distribution quality of PEMFC 量化运行参数的影响以及优化 PEMFC 功率密度和氧气分布质量的两阶段框架

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-21 DOI: 10.1016/j.renene.2024.121430

Proton exchange membrane fuel cell (PEMFC) exhibits significant promise in generating power from hydrogen energy. Operating parameters exert a direct influence on both the power output and the uniformity of oxygen distribution within the PEMFC. Therefore, quantifying the impact of operating parameters and identifying the optimal operating conditions are pivotal to enhance the performance and extend the lifespan of the PEMFC. To this end, a two-stage framework leveraging interpretable machine learning and multi-objective optimization is proposed. In the first stage, an interpretable surrogate model for the PEMFC is established. The impacts of single parameter and pairwise parameters on the power output and the oxygen distribution quality are quantified. Moreover, the decision variables are selected for the second stage. In the second stage, the optimal operating parameters are determined via multi-objective optimization. The results from the first stage suggest that operating voltage and pressure have the highest cumulative contribution for both power density and oxygen distribution quality. The influence mechanism of one operating parameter on the relationship between another operating parameter and the research target is clearly quantified. The findings from the second stage indicate that power density increases by 32 %, 27.36 %, and 32.58 % for three optimized solutions, respectively, while the standard deviation of oxygen molar concentration in the selected operating condition is reduced by 29.66 %.

质子交换膜燃料电池（PEMFC）在利用氢能发电方面前景广阔。操作参数对功率输出和 PEMFC 内氧气分布的均匀性都有直接影响。因此，量化操作参数的影响和确定最佳操作条件对于提高 PEMFC 的性能和延长其使用寿命至关重要。为此，我们提出了一个利用可解释机器学习和多目标优化的两阶段框架。在第一阶段，建立了 PEMFC 的可解释代用模型。量化了单一参数和成对参数对功率输出和氧气分布质量的影响。此外，还为第二阶段选择了决策变量。在第二阶段，通过多目标优化确定最佳运行参数。第一阶段的结果表明，工作电压和压力对功率密度和氧气分布质量的累积贡献最大。明确量化了一个运行参数对另一个运行参数和研究目标之间关系的影响机制。第二阶段的研究结果表明，三种优化方案的功率密度分别提高了 32%、27.36% 和 32.58%，而选定运行条件下的氧摩尔浓度标准偏差降低了 29.66%。

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引用次数: 0

Objective representative flow field selection for tidal array layout design 潮汐阵列布局设计的客观代表性流场选择

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-20 DOI: 10.1016/j.renene.2024.121381

The representation of flow across influential spatiotemporal scales introduces a challenge when micro-siting tidal stream turbine arrays. Robust representative approximations could accelerate design optimisation, yet there is no consensus on what defines the most appropriate flow conditions. We summarise existing approaches to representative flow field selection for array optimisation and propose an objective-driven process. The method curates a subset of flow fields that best captures relevant dynamics, enabling the streamlined representation of tidal cycles. To demonstrate the method, we consider flow modelling data in the Inner Sound of the Pentland Firth, Scotland, UK. We examine the impact of flow field inputs to array design through comparative analyses using a heuristic array optimisation process. Results indicate notable sensitivity of the turbine layout to the flow conditions selected. For the case study presented, our method led to 4%–5% energy yield prediction improvements relative to use of simple time-interval based approaches and up to 2% improvement against using peak flow fields; these can be pivotal margins to secure feasibility by developers. We also find that using the data associated with a single monitored point across the array for flow field selection can lead to sub-optimal results, emphasising the need for accurate spatiotemporal representation.

在对潮汐流涡轮机阵列进行微观选址时，如何在有影响的时空尺度上表示水流是一项挑战。可靠的代表性近似值可以加速设计优化，但对于如何定义最合适的流场条件还没有达成共识。我们总结了用于阵列优化的代表性流场选择的现有方法，并提出了一种目标驱动流程。该方法能筛选出最能捕捉相关动态的流场子集，从而简化潮汐周期的表示。为了演示该方法，我们考虑了英国苏格兰彭特兰峡湾内湾的流量建模数据。我们使用启发式阵列优化流程，通过比较分析来研究流场输入对阵列设计的影响。结果表明，涡轮机布局对所选水流条件的敏感性很高。在案例研究中，我们的方法比使用简单的基于时间间隔的方法提高了 4%-5% 的发电量预测，比使用峰值流场提高了 2%；这些都是确保开发商可行性的关键因素。我们还发现，使用与整个阵列中单个监测点相关的数据进行流场选择可能会导致次优结果，这强调了精确时空表示的必要性。

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引用次数: 0

Exergy and thermoeconomic analysis of a novel polygeneration system based on gasification and power-to-x strategy 基于气化和电力转换战略的新型多联产系统的能效和热经济分析

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-20 DOI: 10.1016/j.renene.2024.121438

This study introduces a novel polygeneration system that integrates biomass gasification, anaerobic digestion, photovoltaic (PV) energy, and electrolysis to enhance system flexibility and efficiency. The system includes an allothermal gasification unit that processes lignocellulosic biomass sourced from a botanical garden. The gasifying agent, either steam or oxygen, is supplied by an alkaline electrolyzer, which operates under a Power-to-X strategy, utilizing surplus energy from a PV field. The resulting syngas and hydrogen are blended with biogas from an anaerobic digester, which treats municipal waste, to power a cogenerator. This cogenerator meets the electricity, heating, and cooling demands of a hospital, while the PV field powers the botanical garden. The systems components are modeled using various tools and integrated into the TRNSYS environment for dynamic simulation. An exergy analysis identifies the main sources of exergy destruction, while a thermo-economic analysis evaluates the energy, environmental, and economic impacts of a demonstration plant located in Bogotá’s Botanical Garden. Simulation results show that the system achieves an overall exergy efficiency of around 35 %, with a 96 % reduction in primary energy consumption compared to a reference system, avoiding nearly 6000 tons of CO₂ emissions annually. From an economic perspective, the system is profitable, with a payback period of 3.02 years and a Net Present Value of $15.23 million, almost double the capital cost. The gasification unit's exergy efficiency is significantly higher when using oxygen (0.50) compared to steam (0.25), underscoring the importance of integrating electrolysis for improved biomass conversion. The alkaline electrolyzer operates efficiently within its optimal range, with an energy efficiency close to 0.70 and an exergy efficiency around 0.60, effectively utilizing 25 % of the total PV production.

本研究介绍了一种新型多联产系统，该系统集成了生物质气化、厌氧消化、光伏（PV）能源和电解，以提高系统的灵活性和效率。该系统包括一个全热气化装置，用于处理来自植物园的木质纤维素生物质。气化剂（蒸汽或氧气）由一个碱性电解槽提供，该电解槽根据 "Power-to-X "战略运行，利用光伏发电场的剩余能源。产生的合成气和氢气与处理城市垃圾的厌氧发酵池产生的沼气混合，为热电联产机供电。这台热电联产机可以满足一家医院的电力、供暖和制冷需求，而光伏发电场则为植物园提供电力。系统组件使用各种工具建模，并集成到 TRNSYS 环境中进行动态模拟。放能分析确定了放能破坏的主要来源，而热经济分析则评估了位于波哥大植物园的示范电站对能源、环境和经济的影响。模拟结果表明，该系统的总体放能效率约为 35%，与参考系统相比，一次能源消耗量减少了 96%，每年可避免近 6000 吨二氧化碳排放。从经济角度看，该系统有利可图，投资回收期为 3.02 年，净现值为 1,523 万美元，几乎是资本成本的两倍。与蒸汽（0.25）相比，气化装置在使用氧气（0.50）时的放能效率要高得多，这突出了整合电解技术以提高生物质转化率的重要性。碱性电解槽在其最佳范围内高效运行，能量效率接近 0.70，放能效率约为 0.60，有效利用了光伏总产量的 25%。

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引用次数: 0

The heterogeneous impacts of climate finance on energy efficiency and renewable energy production in developing countries 气候融资对发展中国家能源效率和可再生能源生产的不同影响

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-20 DOI: 10.1016/j.renene.2024.121427

Climate finance (CF) is considered to be a key financial innovation to enhance energy efficiency (EE) and facilitate the pathway to energy transition (ET). However, the varied impacts of CF on EE and renewable energy production (REP) have been masked. Thus, this study examines the heterogeneous impacts of CF on EE and REP for 81 developing countries (DCs) for the period 2002–2019. The method of moments quantile regression (MMQR) approach is used to control for distributional and unobserved individual heterogeneity. We calculate EE using parametric stochastic frontier analysis (SFA). Also, the effects of CF on EE and REP are investigated subject to income heterogeneity and based on Copenhagen (COP15) and Paris (COP21) climate accords. The findings revealed that DCs with lower REP benefit the most from increased CF, and the positive effects break down for countries with the largest distributions of REP. Besides, CF positively contributes to EE across all quantiles of DCs. The results further imply that the impacts of CF are income-dependent, with positive effects on the EE and REP of middle-income economies and more pronounced after the COP15 and COP21 climate accords. Several policy implications are forwarded based on the findings.

气候融资（CF）被认为是提高能源效率（EE）和促进能源转型（ET）的关键金融创新。然而，气候融资对能源效率（EE）和可再生能源生产（REP）的不同影响却被掩盖了。因此，本研究考察了 2002-2019 年期间 81 个发展中国家（DCs）的金融创新对能源效率和可再生能源生产（REP）的不同影响。我们采用矩量回归法（MMQR）来控制分布和未观察到的个体异质性。我们使用参数随机前沿分析法（SFA）计算 EE。此外，我们还根据哥本哈根（COP15）和巴黎（COP21）气候协议，在收入异质性的条件下研究了CF对EE和REP的影响。研究结果表明，REP 较低的发展中国家从增加 CF 中获益最大，而对于 REP 分布最大的国家，其积极影响则被打破。此外，CF 对所有数量级的发展中国家的能源效率都有积极的促进作用。研究结果进一步表明，CF 的影响与收入有关，对中等收入经济体的 EE 和 REP 有积极影响，在 COP15 和 COP21 气候协议之后更为明显。根据研究结果，提出了若干政策影响。

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引用次数: 0

Exploring the path to promote energy revolution: Assessing the impact of new energy demonstration city construction on urban energy transition in China 探索推动能源革命的路径：新能源示范城市建设对中国城市能源转型的影响评估

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-20 DOI: 10.1016/j.renene.2024.121437

Cities serve as the epicenter of energy consumption, and urban energy transition (UET) is a pivotal prerequisite for achieving carbon peaking and neutrality goals. Leveraging the quasi-natural experiment of China's New Energy Demonstration City Construction (NEDCC), this paper evaluates its impact on UET based on balanced panel data spanning 272 cities from 2006 to 2022. Employing the difference-in-differences model, our estimates underscore NEDCC's facilitative role in promoting UET, a finding corroborated by a series of robustness tests. Mechanism examinations reveal that NEDCC advances UET by enhancing government strategic guidance, fostering green technological innovation, promoting industrial structural upgrading, and optimizing resource allocation efficiency. Furthermore, in cities with higher administrative tiers and more advanced digital finance, NEDCC exerts a more pronounced effect on UET. Conversely, cities endowed with richer resources and pursuing more ambitious economic growth targets exhibit weaker responses to NEDCC's UET-boosting influence. Additionally, NEDCC's demonstration effect surpasses its diffusion effect on neighboring cities, generating a positive spatial spillover that propels their energy transitions. This study offers a novel policy lens for advancing UET.

城市是能源消耗的中心，城市能源转型（UET）是实现碳峰值和碳中和目标的关键前提。本文利用中国新能源示范城市建设（NEDCC）这一准自然实验，基于 2006 年至 2022 年 272 个城市的平衡面板数据，评估了其对 UET 的影响。通过采用差分模型，我们的估计结果强调了 NEDCC 在促进 UET 方面的推动作用，一系列稳健性检验也证实了这一结论。机制检验显示，NEDCC 通过加强政府战略指导、促进绿色技术创新、推动产业结构升级和优化资源配置效率等方式推动 UET 的发展。此外，在行政层级较高、数字金融较为发达的城市，NEDCC 对 UET 的影响更为明显。相反，资源更丰富、追求更高的经济增长目标的城市，对 NEDCC 促进 UET 的影响反应较弱。此外，NEDCC 的示范效应超过了其对周边城市的扩散效应，产生了积极的空间溢出效应，推动了这些城市的能源转型。这项研究为推进 UET 提供了一个新颖的政策视角。

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引用次数: 0

Long-term performance analysis of a large-scale photoVoltaic plant in extreme desert conditions 极端沙漠条件下大型光伏电站的长期性能分析

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-20 DOI: 10.1016/j.renene.2024.121426

This study comprehensively evaluates the performance and operational challenges of a 9 MW grid-connected photovoltaic (PV) system in Timmimoun, southern Algeria, after eight years of operation. We identified a significant linear correlation (R² = 0.73) between increased ambient temperatures and decreased PV module efficiency, underscoring the need for effective thermal management strategies. The investigation also examines potential solutions, such as cooling mechanisms, optimization of panel orientation and tilt angles, and development of temperature-resistant materials. Adhering to the International Energy Agency IEC 61724 standard, our analysis reveals a yield factor of 5.04 h/day, a yield ratio of 7.04 h/day, a performance ratio of 73 %, and a capacity factor of 21 % in 2023. Over its operational lifespan, the system has generated 133.43 GW h of energy, mitigating 1.01 10⁵ tons of CO₂ emissions. This long-term study provides critical insights into the performance and reliability of PV systems in hot desert climates, offering valuable guidance for future large-scale solar installations and contributing to the transition towards a sustainable energy future.

本研究全面评估了阿尔及利亚南部 Timmimoun 9 兆瓦并网光伏（PV）系统在运行八年后的性能和运营挑战。我们发现，环境温度升高与光伏组件效率降低之间存在明显的线性相关关系（R2 = 0.73），这凸显了有效热管理策略的必要性。调查还研究了潜在的解决方案，如冷却机制、优化面板方向和倾斜角度以及开发耐温材料。根据国际能源机构 IEC 61724 标准，我们的分析表明，2023 年的产量系数为 5.04 小时/天，产量比率为 7.04 小时/天，性能比率为 73 %，容量系数为 21 %。在其运行寿命期间，该系统已产生 133.43 千兆瓦时的能量，减少了 1.01105 吨的二氧化碳排放量。这项长期研究提供了有关炎热沙漠气候下光伏系统性能和可靠性的重要见解，为未来大规模太阳能安装提供了宝贵的指导，并有助于向可持续能源的未来过渡。

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引用次数: 0

Energy-saving path planning navigation for solar-powered vehicles considering shadows 考虑阴影因素的太阳能汽车节能路径规划导航

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-19 DOI: 10.1016/j.renene.2024.121424

Globally, the adverse climate effects caused by greenhouse gas emissions are becoming increasingly apparent, and solutions to increase the use of eco-friendly transportation methods are urgently needed. Introducing solar-powered vehicles (SPVs), which are cars integrated with solar panels capable of generating power, presents a promising solution to reduce urban carbon footprints. However, the low adoption rate of SPVs implies that the benefits—such as environmental friendliness and ability to charge while driving—need to be more palpably experienced by consumers. To address this aspect, in this study, we aimed to develop a navigation system algorithm that guides users along routes that optimize energy consumption and solar energy production from the starting point to the destination. This was done with the objective of providing more tangible benefits from using SPVs. The study focused on the high-traffic urban center of Seoul, where determining solar power availability for a moving SPV is challenging, given the presence of shadows cast by roadside features such as buildings and trees. To achieve this, panoramic images from Google Street View were collected at 10 m intervals from all roads within the research area. From these images, sky and non-sky elements were separated. Subsequently, a hemispherical map was constructed and superimposed with the sun's path. The presence of shadows was determined by assessing whether the sun's path was obstructed by non-sky elements; if the path was unimpeded in the sky, no shadow was recorded. The shadow data obtained at each spot were efficiently stored in a database for quick retrieval and application based on specific locations and departure times. Using this shadow information, the navigation algorithm calculates power generation along a given route and considers the energy consumption of the SPV. Analysis led to the identification of an energy-saving route, which enabled the achievement of energy conservation and CO₂ reduction benefits. Furthermore, a comprehensive sensitivity analysis was conducted to examine the impact of four critical parameters—module efficiency, solar panel area, vehicle speed, and departure time—on route selection and net energy consumption. The energy-saving path planning algorithm enhances the economic feasibility of solar charging for SPVs during travel; thus, this study can contribute significantly to the widespread adoption of SPVs, which play a definitive role in reducing transportation's carbon footprint.

在全球范围内，温室气体排放对气候造成的不利影响日益明显，因此迫切需要增加使用生态友好型交通方式的解决方案。太阳能汽车（SPV）是一种集成了太阳能发电板的汽车，它的引入为减少城市碳足迹提供了一个前景广阔的解决方案。然而，SPV 的采用率较低，这意味着消费者需要更直观地感受到其优势，如环保性和驾驶时充电的能力。为了解决这方面的问题，在本研究中，我们旨在开发一种导航系统算法，引导用户沿着优化能源消耗和太阳能生产的路线从起点到达目的地。这样做的目的是为了让用户从使用 SPV 中获得更多实实在在的好处。这项研究的重点是首尔交通繁忙的市中心，由于路边有建筑物和树木等投下的阴影，因此确定移动 SPV 的太阳能可用性具有挑战性。为此，研究人员在研究区域内的所有道路上以 10 米的间隔收集了谷歌街景的全景图像。从这些图像中分离出天空和非天空元素。随后，绘制了半球地图，并与太阳轨迹叠加。阴影的存在是通过评估太阳的轨迹是否受到非天空元素的阻碍来确定的；如果天空中的轨迹畅通无阻，则不记录阴影。在每个地点获得的阴影数据都被有效地存储在数据库中，以便根据特定地点和出发时间进行快速检索和应用。利用这些阴影信息，导航算法可计算给定路线的发电量，并考虑 SPV 的能耗。通过分析，确定了一条节能路线，从而实现了节能和减少二氧化碳排放的效益。此外，还进行了全面的敏感性分析，以研究四个关键参数--模块效率、太阳能电池板面积、车辆速度和出发时间--对路线选择和净能耗的影响。节能路径规划算法提高了太阳能电池板在行驶过程中充电的经济可行性；因此，这项研究可为太阳能电池板的广泛应用做出重要贡献，而太阳能电池板在减少交通碳足迹方面发挥着决定性作用。

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引用次数: 0

Combination of integrated machine learning model frameworks and infrared spectroscopy towards fast and interpretable characterization of model pyrolysis oil 将综合机器学习模型框架与红外光谱技术相结合，对模型热解油进行快速、可解释的表征

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-19 DOI: 10.1016/j.renene.2024.121434

Model pyrolysis oil (bio-oil) is a promising bio-fuel with complex and unstable contents, making its fast characterization an essential demand in industrial production. This study proposed an integrated machine learning framework to predict elemental composition, low heating value, and unsaturated concentration from infrared spectra, achieving fast and interpretable characterization of bio-oil. In the integrated framework, a peak loading-based strategy was used to dimensionally reduce the spectral data. Bayesian optimized random forest (RF) and extreme gradient boosting (XGBoost) models were used to predict bio-oil properties from dimensionally reduced spectral data. Ensemble learning was used to combine RF and XGBoost models together for better predicting performance. Results showed that the proposed characterization method achieved an average accuracy of 99.53 %, a low RMSE value of 0.726, and an R² of 0.98. The Shapley value analysis revealed that the vibration of NH₂ stretch (1594 cm⁻¹), C-H stretch (2868 cm⁻¹), and C-N stretch in the aromatic ring (1229 cm⁻¹) have a significant contribution to the characterization results. The working mechanism of the proposed characterization method was interpreted by the internal relationship among spectral peak location/height, functional group species/amount, and the predicted characteristics. The results are hoped to serve quality control in production of bio-oil.

模型热解油（生物油）是一种前景广阔的生物燃料，其成分复杂且不稳定，因此对其进行快速表征是工业生产的基本要求。本研究提出了一种综合机器学习框架，可从红外光谱预测元素组成、低热值和不饱和浓度，从而实现快速、可解释的生物油表征。在集成框架中，采用了基于峰值加载的策略来降低光谱数据的维度。贝叶斯优化随机森林（RF）和极梯度提升（XGBoost）模型用于从降维的光谱数据中预测生物油特性。利用集合学习将 RF 和 XGBoost 模型结合在一起，以获得更好的预测性能。结果表明，所提出的表征方法的平均准确率达到 99.53%，RMSE 值低至 0.726，R2 为 0.98。Shapley 值分析表明，芳香环中的 NH2 伸展振动（1594 cm-1）、C-H 伸展振动（2868 cm-1）和 C-N 伸展振动（1229 cm-1）对表征结果有显著贡献。光谱峰位置/高度、官能团种类/数量和预测特征之间的内在关系解释了所提出的表征方法的工作机制。希望这些结果能用于生物油生产过程中的质量控制。

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引用次数: 0

Fast pyrolysis of paper sludge in a continuous stirred-tank reactor and liquid-liquid extraction of benzenoid aromatics from fast pyrolysis bio-liquid 在连续搅拌罐反应器中快速热解造纸污泥以及从快速热解生物液体中液-液萃取苯类芳烃

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-19 DOI: 10.1016/j.renene.2024.121429

Paper sludge is a solid waste in paper mills and is conventionally treated by, e.g., landfill, composting, and incineration. Paper sludge contains paper production fillers and lignocellulosic biomass, both of which can be recycled to recover circular minerals and produce bio-based fuels and chemicals by, e.g., thermochemical recycling technology namely fast pyrolysis, for circular bioeconomy. In this paper, three different paper sludge samples collected in The Netherlands and Spain were analyzed by thermogravimetric analysis, moisture analysis, ash analysis, CHNS elemental analysis, powder X-ray diffraction, and X-ray fluorescence spectrometry. Fast pyrolysis of paper sludge was carried out in a lab-scale continuous stirred tank reactor at 500 ± 10 °C with a paper sludge feeding rate of 1 kg h⁻¹. The recovery of circular minerals, which are mainly calcium carbonate, is 87.1 ± 2.2 % (on mineral basis). The yields of fast pyrolysis bio-liquid and biochar are 49.2 ± 6.7 wt% (on biomass basis, equivalent to 23.7 ± 2.2 wt% on paper sludge basis) and 23.8 ± 8.3 wt% (on biomass basis). Fast pyrolysis bio-liquid is a diluted aqueous containing various oxygenates (major, including alcohols, acids, benzenoid aromatics, aldehydes, ketones, ethers, and esters) and hydrocarbons. Liquid-liquid extraction of the fast pyrolysis bio-liquid using CH₃OH/H₂O and SO₂/H₂O was further performed to obtain an improved bio-liquid with relatively high concentration of the desired bio-based chemicals (namely benzenoid aromatics with the concentration of 53.1–65.9 area%). Both SO₂/H₂O and CH₃OH/H₂O show high liquid-liquid extraction efficiency to concentrate the benzenoid aromatics for 3.4–11.0 times. This work shows the fast pyrolysis followed by liquid-liquid extraction for the valorization of paper sludge, of which the former has been recently demonstrated on a pilot-scale unit in industry. However, the latter still needs to be further developed by, e.g., focusing on the extraction solvent and continuous liquid-liquid extraction process integrated to fast pyrolysis.

造纸污泥是造纸厂的固体废弃物，传统的处理方式包括填埋、堆肥和焚烧。造纸污泥中含有造纸填料和木质纤维素生物质，这两种物质都可以通过热化学回收技术（即快速热解）回收循环矿物并生产生物燃料和化学品，从而实现循环生物经济。本文通过热重分析、水分分析、灰分分析、CHNS 元素分析、粉末 X 射线衍射和 X 射线荧光光谱法分析了在荷兰和西班牙收集的三种不同的造纸污泥样本。造纸污泥的快速热解是在实验室规模的连续搅拌罐反应器中进行的，反应器温度为 500 ± 10 °C，造纸污泥进料速率为 1 kg h-1。循环矿物（主要是碳酸钙）的回收率为 87.1 ± 2.2 %（以矿物为基准）。快速热解生物液和生物炭的产量分别为 49.2 ± 6.7 wt%（按生物量计算，相当于 23.7 ± 2.2 wt%（按造纸污泥计算）和 23.8 ± 8.3 wt%（按生物量计算）。快速热解生物液是一种稀释的水液，含有各种含氧化合物（主要包括醇、酸、类苯芳烃、醛、酮、醚和酯）和碳氢化合物。使用 CH3OH/H2O 和 SO2/H2O 进一步对快速热解生物液进行液液萃取，以获得改进的生物液，其中所需生物基化学品的浓度相对较高（即苯类芳烃，浓度为 53.1-65.9 面积%）。SO2/H2O 和 CH3OH/H2O 均显示出较高的液-液萃取效率，可将类苯芳烃浓缩 3.4-11.0 倍。这项研究表明，快速热解后进行液液萃取可实现造纸污泥的资源化。然而，后者仍需进一步开发，例如，重点关注萃取溶剂和与快速热解相结合的连续液液萃取工艺。

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引用次数: 0

Experimental analysis and optimization of a concentrated thermo-photovoltaic collector with bi-facial receiver 带双面接收器的聚光光伏集热器的实验分析与优化

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2024-09-19 DOI: 10.1016/j.renene.2024.121401

In this study, a concentrated thermo-photovoltaic collector is examined experimentally and numerically, while it was geometrically optimized. The main objective is the collector's thermal performance evaluation and optical optimization for operation in Greece. Experiments were conducted in Athens, Greece, from July 10th to 17th, 2023, investigating the thermal operation of the collector in a temperature range of approximately 40–80 °C. The collector's slope was set to 12.3° for maximum solar irradiance utilization during the specified dates, considering south orientation. A numerical model was created using SolidWorks Flow Simulation and COMSOL Multiphysics, The model was validated with the experimental data, achieving mean deviation less than 6.5 % and a maximum deviation of 9.6 %. Various geometries were optically examined using Tonatiuh software. By applying a performance evaluation criterion, a new design is proposed and compared to the initial design across four different months, considering constant tilt angle. A maximum thermal efficiency of 49.19 % at the lower inlet temperature was found experimentally. The temperature of the PV cells was found to be highest where the solar rays are concentrated. Shape optimization revealed significant enhancements in optical efficiency, particularly at negative incident angles. The new geometry showed substantial improvement, with enhancements exceeding 20 % considering daily operation.

在这项研究中，对聚光光伏集热器进行了实验和数值研究，并对其进行了几何优化。主要目的是对集热器的热性能进行评估，并对其在希腊的运行进行光学优化。实验于 2023 年 7 月 10 日至 17 日在希腊雅典进行，研究了集热器在约 40-80 °C 温度范围内的热运行情况。集热器的斜率设定为 12.3°，以便在指定日期内最大限度地利用太阳辐照度，同时考虑到南向。使用 SolidWorks Flow Simulation 和 COMSOL Multiphysics 创建了一个数值模型，该模型与实验数据进行了验证，平均偏差小于 6.5%，最大偏差为 9.6%。使用 Tonatiuh 软件对各种几何形状进行了光学检测。通过应用性能评估标准，提出了一种新的设计方案，并在四个不同的月份与最初的设计方案进行了比较，同时考虑了恒定的倾斜角度。实验发现，在较低的入口温度下，最大热效率为 49.19%。在太阳光集中的地方，光伏电池的温度最高。形状优化显示光学效率显著提高，特别是在负入射角时。新的几何形状显示出显著的改进，考虑到日常运行，改进幅度超过 20%。

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