Solar Energy最新文献_第4页

Energy efficiency optimization of CdTe photovoltaic glass based on PAM/SA hydrogel 基于PAM/SA水凝胶的CdTe光伏玻璃能效优化

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-11 DOI: 10.1016/j.solener.2025.114211

Mincheng Lu , Qiaodong Xu , Bianyiran Xie , Jiaqi Zhang , Xiaobin Fu , Mingjun Ji , Jian Yang , Feiliang Wang

The operational efficiency of Cadmium Telluride (CdTe) photovoltaic (PV) glass, a promising material for building-integrated photovoltaics (BIPV), is significantly degraded by temperature elevation, posing a challenge for maximising energy generation in zero-carbon buildings. To address this, this study introduces a novel evaporative cooling approach using a Polyacrylamide/Sodium Alginate (PAM/SA) modified hydrogel. Three hydrogel formulations (PAM/SA-I, II, III) were synthesised and characterised, and their mechanism for regulating the operating temperature of CdTe photovoltaic glass was analysed. The influencing factors of the power generation efficiency of CdTe photovoltaic glass and the cooling capability of the PAM/SA hydrogel are studied. A multiphysics model was established to simulate the thermal and electrical performance of the CdTe PV glass-hydrogel system, with findings validated through laboratory experiments and full-scale field testing. The results demonstrate that the optimal hydrogel formulation (PAM/SA-I) at a 7 mm thickness can reduce the PV glass surface temperature by up to 15.8 °C, leading to an increase in power generation of more than 5 %. The novelty of this work lies in developing a scalable, high-transparency hydrogel cooling module that passively and effectively regulates PV operating temperature. This provides a new, practical approach to enhancing BIPV efficiency, directly supporting the development of energy-positive buildings by increasing renewable energy yield without active energy consumption.

碲化镉（CdTe）光伏（PV）玻璃是一种很有前途的建筑集成光伏（BIPV）材料，其运行效率随着温度升高而显著降低，这对零碳建筑中最大限度地提高能源产量提出了挑战。为了解决这一问题，本研究采用聚丙烯酰胺/海藻酸钠（PAM/SA）改性水凝胶，提出了一种新的蒸发冷却方法。合成并表征了三种水凝胶配方（PAM/SA-I、II、III），并分析了它们调节CdTe光伏玻璃工作温度的机理。研究了影响CdTe光伏玻璃发电效率的因素和PAM/SA水凝胶的冷却性能。建立了一个多物理场模型来模拟CdTe光伏玻璃水凝胶体系的热学和电学性能，并通过实验室实验和全尺寸现场测试验证了研究结果。结果表明，7 mm厚度的最佳水凝胶配方（PAM/SA-I）可使PV玻璃表面温度降低15.8℃，发电量提高5%以上。这项工作的新颖之处在于开发了一种可扩展的、高透明度的水凝胶冷却模块，该模块可以被动有效地调节PV的工作温度。这为提高BIPV效率提供了一种新的、实用的方法，通过增加可再生能源产量而不消耗主动能源，直接支持节能建筑的发展。

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引用次数: 0

An interpretable multi-site information selection and fusion method for short-term photovoltaic forecasting 光伏短期预测的可解释多站点信息选择与融合方法

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-10 DOI: 10.1016/j.solener.2025.114240

Yunxiao Chen , Chaojing Lin , Pengzhao Wang , Xueqin Tian , Shaoli Zeng , Hui Li , Jinfu Liu , Daren Yu

Accurate short-term photovoltaic forecasting is of great significance for power system dispatch. To address the harm of insufficient or redundant input information to model accuracy in traditional methods, this paper proposes an interpretable multi-site information selection and fusion method. Firstly, through interpretable correlation analysis and information gain analysis, this paper studies contribution of the feature sequences under different time delays of each site to improving the forecasting accuracy. Based on the analysis of five indicators, the optimal length of each feature sequence is determined. Thirteen machine learning models are used for short-term PV forecasting, with the selected feature sequences as model inputs. The best-performing model achieves the MAE of 0.44786 MW, RMSE of 0.91715 MW, NMAE of 0.00976, NRMSE of 0.01873 and R² of 0.99348. Compared with the baseline method, it achieves a 41.75 % reduction in MAE/NMAE, a 30.54 % reduction in RMSE/NRMSE and a 0.71 % improvement of R². Meanwhile, the traditional forecasting method with single-site information sequences as inputs and the traditional forecasting methods with unfiltered multi-site information sequences are used as comparison groups. Through T-test, the significant superiority of the proposed method in model accuracy compared to two traditional methods is verified.

准确的光伏短期预测对电力系统调度具有重要意义。针对传统方法中输入信息不足或冗余对模型精度的影响，提出了一种可解释的多位点信息选择与融合方法。首先，通过可解释相关分析和信息增益分析，研究各站点不同时延下特征序列对提高预测精度的贡献；通过对五个指标的分析，确定了每个特征序列的最优长度。13个机器学习模型用于短期PV预测，选择的特征序列作为模型输入。最佳模型的MAE为0.44786 MW， RMSE为0.91715 MW， NMAE为0.00976，NRMSE为0.01873，R2为0.99348。与基线方法相比，MAE/NMAE降低41.75%，RMSE/NRMSE降低30.54%，R2提高0.71%。同时，将传统的单点信息序列预测方法作为输入，与传统的未过滤多点信息序列预测方法作为对照组。通过t检验，验证了该方法与两种传统方法相比在模型精度上的显著优势。

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引用次数: 0

Advancements in hybrid photovoltaic thermal (PV/T) systems multi objective optimization strategies and emerging Frontiers 光伏热混合系统多目标优化策略及新领域研究进展

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-10 DOI: 10.1016/j.solener.2025.114179

Sheng Huang , Shijie Sun , Shuli Liu , Shihan Deng , Zhihao Wang

Photovoltaic/thermal (PV/T) technology enables the simultaneous conversion of solar energy into both electrical and thermal energy, representing a key research focus in the field of renewable energy applications. However, the underlying mechanism of electrical-thermal synergistic optimization and demand matching remains unclear, which significantly hinders its practical application and deployment. This paper establishes an analytical framework from the dual dimensions of “energy flow hierarchy” and “application scenarios”, conducting a systematic review of existing PV/T studies. It elucidates the mechanisms of action and applicable scenarios of various key technologies from three perspectives: electrical performance enhancement, thermal performance improvement, and electrical-thermal synergy. Furthermore, this paper identifies that current PV/T technologies still confront challenges in cost, stability, and environmental adaptability during practical application. Accordingly, future research directions are put forward from perspectives including material development, structural optimization, and artificial intelligence. The proposed analytical framework affords researchers a systematic approach to evaluating and developing next-generation PV/T technologies.

光伏/热（PV/T）技术能够将太阳能同时转化为电能和热能，是可再生能源应用领域的一个重要研究热点。然而，电-热协同优化和需求匹配的潜在机制尚不清楚，这极大地阻碍了其实际应用和部署。本文从“能量流层次”和“应用场景”两个维度构建了分析框架，对现有PV/T研究进行了系统回顾。从电学性能增强、热学性能改善和电热协同三个方面阐述了各种关键技术的作用机理和应用场景。此外，本文认为当前PV/T技术在实际应用中仍面临成本、稳定性和环境适应性方面的挑战。据此，从材料发展、结构优化、人工智能等方面提出了未来的研究方向。提出的分析框架为研究人员提供了评估和开发下一代光伏/T技术的系统方法。

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引用次数: 0

Performance enhancement of TiO2/CZTSSe solar cells via bandgap grading and tungsten back contact 通过带隙分级和钨背接触增强TiO2/CZTSSe太阳能电池的性能

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-10 DOI: 10.1016/j.solener.2025.114201

Nadia Mahsar , Beddiaf Zaidi , Lakhdar Dehimi , Fortunato Pezzimenti

The wxAMPS-1D (Analysis of Microelectronic and Photonic Structures) software was employed to analyse the effect of bandgap grading in CZTS_xSe_1-x (Copper Zinc Tin Sulphur Selenium) absorber layer, by using titanium dioxide TiO₂ as the buffer layer in thin-film solar cells. The study is focused on the role of the bandgap engineering in influencing the overall efficiency of the cell. Also, it investigates an appropriate back contact material selection based on the metal work function (MWF) value. The variation in the gap depends on the ratio S/(Se + S). A notable enhancement in the solar cell performance has been observed, achieving an efficiency of 23.17 % in the graded band device configuration with tungsten (W) as back contact, compared to the 13.26 % efficiency attained for the single-layer absorber. The efficiency improvement is mainly attributed to the bandgap grading in the absorber, which enhances the internal electric field, and to the improved back contact, which better facilitates carrier collection. These results highlight the potential of our approach to advance the performance of kesterite-based solar cells.

采用wxAMPS-1D （Analysis of Microelectronic and Photonic Structures）软件，以二氧化钛TiO2作为薄膜太阳能电池的缓冲层，分析了CZTSxSe1-x （Copper Zinc Tin硫硒）吸收层中带隙分级的影响。研究的重点是带隙工程在影响电池整体效率中的作用。此外，本文还研究了基于金属功函数（MWF）值的适当背触点材料选择。间隙的变化取决于比值S/(Se + S)。太阳能电池的性能得到了显著的提高，与单层吸收器的13.26%的效率相比，以钨(W)为背接触的梯度带器件配置的效率达到了23.17%。效率的提高主要归功于吸收器的带隙分级，增强了内部电场，以及改进的背接触，更好地促进了载流子的收集。这些结果突出了我们的方法在提高kesterite基太阳能电池性能方面的潜力。

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引用次数: 0

Improved probabilistic forecasting for solar photovoltaic generation via CVAE with continuous-discrete mixture distributions 基于连续离散混合分布的CVAE改进的太阳能光伏发电概率预测

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-10 DOI: 10.1016/j.solener.2025.114209

Hongyuan Yang , Bozhen Jiang , Yidi Wang , Qin Wang , Hua Geng

Accurate probabilistic forecasting (PF) of solar photovoltaic (PV) generation is essential to ensure the efficient and stable operation of modern power systems. Recently, conditional variational autoencoder (CVAE)-based PF methods have addressed the quantile crossing problem in quantile-based PF methods. However, CVAE-based PF methods often produce errors and conservative results due to the neglect of physical constraints and the continuous-discrete mixture distribution characteristics of PV generation. To address these problems, this paper presents an improved CVAE-based PF method (ICPFM). The proposed ICPFM leverages the strengths of CVAEs while incorporating the continuous-discrete mixture distribution characteristics inherent in PV generation, thereby enabling more accurate learning and inference of its probability distributions. The ICPFM for PV generation PF in this work involves several key steps. First, the Bernoulli distribution is adopted for the latent variables, which forces the model to perform only a limited number of samples, thus accurately capturing the discrete distribution characteristics of PV generation. Furthermore, the forms of the reconstruction loss and Kullback-Leibler divergence loss functions are derived for the CVAE-based PF model training. Secondly, based on the central limit theorem, an enhanced inference strategy is proposed to more fully explore the continuous distribution characteristics of PV generation during certain periods. Finally, a time-segmented sampling strategy is introduced to better capture uncertainty during daytime periods while adhering to physical laws during nighttime periods. Empirical evaluations conducted on publicly available datasets from Denmark demonstrate that the proposed ICPFM provides accurate and reliable probabilistic distribution forecasts.

准确的太阳能光伏发电概率预测是保证现代电力系统高效稳定运行的关键。近年来，基于条件变分自编码器（CVAE）的滤波方法解决了基于分位数的滤波方法中的分位数交叉问题。然而，由于忽略了物理约束和PV发电的连续离散混合分布特性，基于cvae的PF方法往往产生误差和保守的结果。针对这些问题，本文提出了一种改进的基于cvee的PF方法（ICPFM）。所提出的ICPFM利用了cvae的优势，同时结合了PV发电固有的连续离散混合分布特征，从而能够更准确地学习和推断其概率分布。在本研究中，光伏发电的ICPFM包括几个关键步骤。首先，潜变量采用伯努利分布，这使得模型只能执行有限数量的样本，从而准确地捕捉了光伏发电的离散分布特征。在此基础上，推导了基于cvae的PF模型训练的重构损失和Kullback-Leibler散度损失函数的形式。其次，在中心极限定理的基础上，提出了一种增强推理策略，以更充分地探索光伏发电在特定时段的连续分布特征。最后，介绍了一种时间分段采样策略，以便在白天更好地捕获不确定性，同时在夜间遵循物理定律。对来自丹麦的公开数据集进行的实证评估表明，所提出的ICPFM提供了准确可靠的概率分布预测。

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引用次数: 0

Influence of rooftop photovoltaic on campus thermal and humid environment and optimization of building configurations 屋顶光伏对校园热湿环境的影响及建筑构型优化

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-09 DOI: 10.1016/j.solener.2025.114235

Lei Zhao, Xiaosong Cheng, Jing Wu, Hongqiang Ma, Shunze Wang, Jiajun Wang

In this paper, a multi-factor coupled model is established to simulate the effect of ambient parameters and building configurations on the outdoor thermal-humidity environment under rooftop photovoltaic (PV). Unlike traditional urban microclimate models, this model combines interactions between irregular objects and solar radiation, the heat absorption by rooftop PV modules, and the transpiration process of plants. This is to better match the outdoor real environment under rooftop photovoltaic applications. The model is proven to be reliable by the experimental test. The Universal Thermal Climate Index (UTCI) is used as index to evaluate the outdoor thermal-humidity environment for different building distribution patterns with or without rooftop PV in campus at different times. The results show that the average UTCI of the traditional campus scenario without rooftop PV is significantly higher than that of the new campus scenario with rooftop PV. The maximum UTCI standard deviation of new scenario with rooftop PV is 65.04 % lower than that of the traditional scenario. Which means the thermal comfort uniformity of new campus scenario is significantly better than that of the traditional campus. Moreover, the staggered building layout in campus has the lowest UTCI standard deviation variation. It is recommended to lower the building height to improve outdoor human comfort in summer when the space between buildings is 20 m. The results can provide a reference for the design of future campus.

本文建立了多因素耦合模型，模拟了环境参数和建筑形态对屋顶光伏下室外热湿环境的影响。与传统的城市微气候模型不同，该模型结合了不规则物体与太阳辐射、屋顶光伏组件的吸热以及植物的蒸腾过程之间的相互作用。这是为了更好地匹配屋顶光伏应用下的室外真实环境。通过实验验证了该模型的可靠性。以通用热气候指数（Universal Thermal Climate Index， UTCI）为指标，对校园内不同建筑分布模式下不同时段的室外热湿环境进行了评价。结果表明：无屋顶光伏的传统校园场景的平均UTCI显著高于有屋顶光伏的新校园场景。屋顶光伏新方案的最大UTCI标准差比传统方案低65.04%。这意味着新校园场景的热舒适均匀性明显优于传统校园。校园内错开建筑布局的UTCI标准差变化最小。夏季建筑间距为20m时，建议降低建筑高度，提高室外人体舒适度。研究结果可为未来校园的设计提供参考。

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引用次数: 0

Investigation of fatigue crack propagation in photovoltaic modules under dynamic cyclic loading 动态循环载荷作用下光伏组件疲劳裂纹扩展研究

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-09 DOI: 10.1016/j.solener.2025.114217

Qinghe Fang , Bowen Jiao , Dong Yu , Chunhui Liu , Pengfei Liu

Microcracks in silicon cells induced by environmental loads would significantly degrade the long-term power output and reliability of photovoltaic (PV) modules. Previous studies concern the development of microcracks under static loads but limited attention have been paid to the fatigue crack propagation under dynamic cyclic loading. In this study, a three-dimensional numerical model based on the extended finite element method (XFEM) and Paris’ law was built to investigate the crack propagation in silicon cells under cyclic loading. The numerical model was validated against published experimental data to ensure its accuracy. An optimized mounting location was obtained to minimize the crack area in silicon cells. With the optimized mounting location, the fatigue crack behavior in silicon cell with different initial microcracks under dynamic cyclic loads with different amplitude, frequency, and waveforms were studied. It is found that the load amplitude significantly influences the propagation of crack. The crack in silicon cells increase progressively with the increase of loading cycles. The waveform of cyclic loading plays a key role in determining the final state of fatigue cracks. Unidirectional pressure cycling poses a greater fatigue risk than bidirectional pressure cycling. These findings would be helpful for the design and maintenance of PV systems.

环境载荷引起的硅电池微裂纹会显著降低光伏组件的长期输出功率和可靠性。以往的研究多关注静载荷作用下微裂纹的发展，而对动态循环载荷作用下疲劳裂纹的扩展研究较少。本文基于扩展有限元法（XFEM）和Paris定律建立了三维数值模型，研究了循环载荷作用下硅电池的裂纹扩展。用已发表的实验数据对数值模型进行了验证，以保证模型的准确性。优化了硅电池的安装位置，使硅电池的裂纹面积最小。在优化安装位置的基础上，研究了具有不同初始微裂纹的硅电池在不同振幅、频率和波形的动态循环载荷作用下的疲劳裂纹行为。结果表明，载荷幅值对裂纹扩展有显著影响。随着加载次数的增加，硅电池的裂纹逐渐增大。循环加载波形对确定疲劳裂纹的最终状态起着关键作用。单向压力循环比双向压力循环具有更大的疲劳风险。这些发现将有助于光伏系统的设计和维护。

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引用次数: 0

Fuel-Driven one-pot microwave-combustion engineering of Z-scheme Cu-Al-CuAl nanophotocatalyst for solar-powered decontamination of textile effluents Z-scheme Cu-Al-CuAl纳米光催化剂在纺织废水太阳能净化中的单锅微波燃烧工程

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-08 DOI: 10.1016/j.solener.2025.114192

Mehran Alizadeh , Mohammad Haghighi , Maryam Shabani

This study presents a novel Z-scheme hierarchical Cu-Al-CuAl nanophotocatalyst synthesized through a microwave-assisted combustion approach. The effects of different fuels including citric acid, sorbitol, glycine, and urea, along with heating approaches, on structural and photocatalytic performance were systematically explored. The Cu-Al-CuAl (MCCA) sample, derived using citric acid, exhibited a distinctive cheese-like architecture with uniformly distributed surface particles (∼15.6 nm), a specific surface area of 33 m²/g, pore volume of 0.087 cm³/g, and mean pore size of 10.5 nm. UV–vis and PL analyses confirmed the formation of a Z-scheme CuO/CuAl₂O₄ heterojunction with a narrow band gap of 1.82 eV, enabling efficient solar light utilization and reduced charge recombination. Under simulated solar irradiation, the Cu-Al-CuAl (MCCA) nanophotocatalyst achieved 92.1 % degradation of Congo red and 86.7 % of Eosin Y, with an apparent rate constant (k_app) of 0.0185 1/min, which was up to 11.5 times higher than that of other samples. The material retained over 80 % of its activity after four consecutive cycles, indicating excellent reusability. Radical trapping tests revealed that superoxide radicals (·O₂^-) and photogenerated holes (h⁺) were the main reactive agents in degradation mechanism. This work demonstrates a rapid and energy-efficient route for fabricating high-performance Cu-Al-CuAl photocatalyst for solar-driven wastewater treatment.

本研究提出了一种新型的Z-scheme分层Cu-Al-CuAl纳米光催化剂，通过微波辅助燃烧方法合成。系统探讨了柠檬酸、山梨醇、甘氨酸和尿素等不同燃料以及加热方式对结构和光催化性能的影响。用柠檬酸衍生的Cu-Al-CuAl （MCCA）样品具有独特的奶酪状结构，表面颗粒均匀分布（~ 15.6 nm），比表面积为33 m2/g，孔体积为0.087 cm3/g，平均孔径为10.5 nm。UV-vis和PL分析证实了Z-scheme CuO/CuAl2O4异质结的形成，其窄带隙为1.82 eV，能够有效利用太阳能光并减少电荷复合。在模拟太阳照射下，Cu-Al-CuAl （MCCA）纳米光催化剂对刚果红的降解率为92.1%，对伊红Y的降解率为86.7%，表观速率常数（kapp）为0.0185 1/min，是其他样品的11.5倍。经过连续四个循环后，该材料保留了80%以上的活性，表明了良好的可重复使用性。自由基捕获试验表明，超氧自由基（·O2-）和光生空穴（h+）是降解机理的主要反应因子。这项工作展示了一种快速和节能的路线，用于制造高性能的Cu-Al-CuAl光催化剂，用于太阳能驱动的废水处理。

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引用次数: 0

Enhanced photocatalytic and piezoelectric properties in SbNO/blue phosphorene heterostructures SbNO/蓝磷烯异质结构的光催化和压电性能增强

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-08 DOI: 10.1016/j.solener.2025.114226

Wen-Yi Li , Yong-Xue Du , Meng Zhou , Jia-He Lin , Tian Zhang

Relying on diverse assembly modes and controllability, two-dimensional (2D) materials can be constructed into heterostructures with excellent physical and chemical properties, demonstrating their potential as next-generation photocatalysts. In this work, we design a novel monolayer SbNO and construct its heterostructures with blue phosphorene. First-principles calculations demonstrate that monolayer SbNO exhibits excellent mechanical, dynamical, and thermal stabilities, and displays a considerable HSE06 band gap of approximately 2.86 eV. However, its band-edge alignment does not fulfill the necessary position requirements for overall water splitting, even when biaxial strain is applied. Subsequently, we systematically explore the SbNO/blue phosphorene heterostructures with various stacking sequences, and reveal the influences of the stacking orders on their electronic, optical, photocatalytic, and piezoelectric properties. All heterostructures exhibit Z-scheme band alignments, which promotes the spatial separation of photogenerated carriers. Compared to most 2D materials, these heterostructures exhibit stronger visible-light absorption, larger carrier mobilities, and super-high solar-to-hydrogen (STH) efficiencies (>45 %). We confirm that the application of an external electric field and the significant out-of-plane piezoelectric effect both contribute to enhancing the photocatalytic activity of these heterostructures. Our findings not only demonstrate the potential of SbNO/blue phosphorene as highly efficient photocatalysts, but also provide new design principles for advanced 2D water-splitting materials.

基于不同的组装方式和可控性，二维（2D）材料可以构建具有优异物理和化学性能的异质结构，显示出其作为下一代光催化剂的潜力。在这项工作中，我们设计了一种新的单层SbNO，并以蓝色磷烯构建了它的异质结构。第一性原理计算表明，单层SbNO具有优异的力学、动力学和热稳定性，并显示出约2.86 eV的可观的HSE06带隙。然而，即使施加双轴应变，其带边对准也不能满足整体水劈裂的必要位置要求。随后，我们系统地研究了不同堆叠顺序的SbNO/蓝磷烯异质结构，揭示了堆叠顺序对其电子、光学、光催化和压电性能的影响。所有异质结构均呈现z型带对准，这促进了光生载流子的空间分离。与大多数2D材料相比，这些异质结构具有更强的可见光吸收，更大的载流子迁移率和超高的太阳能制氢效率（> 45%）。我们证实了外电场的应用和显著的面外压电效应都有助于提高这些异质结构的光催化活性。我们的研究结果不仅证明了SbNO/蓝磷烯作为高效光催化剂的潜力，而且为先进的二维水分解材料的设计提供了新的原则。

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引用次数: 0

Inverse design of selective multilayer emitters for thermophotovoltaic systems via Bayesian optimization 基于贝叶斯优化的热光伏系统选择性多层发射体反设计

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-08 DOI: 10.1016/j.solener.2025.114210

Yiğithan Mehmet Köse, Hakan Ertürk

Inverse design of the emitter for a thermophotovoltaic system is introduced. For this, the spectral emittance yielding the ideal performance is identified by considering the efficiency and power output through a parametric analysis. 1-D multilayer structures stand out among several alternative conceptual designs due to their ease of fabrication to achieve selective emission. The inverse problem is then formulated as identifying the design parameters that define the multilayer emitter that matches the ideal emission behavior. Such an inverse problem is highly nonlinear and yields a non-convex topology in the parameter domain necessitating the use of computationally expensive global search algorithms to achieve an optimal solution. Bayesian optimization relies on machine learning, utilizing a trained surrogate model to search the global extremum throughout the topology with a limited number of function evaluations. This study introduces a novel systematic approach for material selection based on a preliminary analysis that investigates the classical models of optical properties to achieve the ideal spectral emission behavior. Three multilayer structures, dielectric-dielectric, metal-dielectric, and metal-metal emitters, are considered and their performances are compared. Because of its ability to suppress sub-bandgap emission, the metal-metal emitter exhibited superior performance. The tunability of doped silicon is then utilized to match the desired material property identified. Targeting an emittance profile that represents an optimal combination of the two performance metrics, an estimated efficiency of 17.5 % and a power density of 4.88 kW/m² are achieved for a 1100 K emitter.

介绍了热光伏系统发射极的反设计。为此，通过参数分析，通过考虑效率和功率输出来确定产生理想性能的光谱发射度。1-D多层结构因其易于制造以实现选择性发射而在几种替代概念设计中脱颖而出。然后将反问题表述为确定定义符合理想发射行为的多层发射极的设计参数。这样的反问题是高度非线性的，在参数域产生非凸拓扑，需要使用计算昂贵的全局搜索算法来实现最优解。贝叶斯优化依赖于机器学习，利用经过训练的代理模型在整个拓扑中搜索全局极值，并进行有限数量的函数求值。本研究在对经典光学特性模型进行初步分析的基础上，提出了一种新的系统的材料选择方法，以实现理想的光谱发射行为。考虑了三种多层结构：介电-介电、金属-介电和金属-金属发射体，并对其性能进行了比较。由于具有抑制亚带隙发射的能力，金属-金属发射极具有优异的性能。然后利用掺杂硅的可调性来匹配所确定的所需材料特性。以两种性能指标的最佳组合为目标，在1100k的发射器上实现了17.5%的效率和4.88 kW/m2的功率密度。

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引用次数: 0