Solar Energy最新文献_第5页

Experimental performance of a semi-transparent photovoltaic–thermoelectric hybrid collector for solar drying of indian gooseberry 印度醋栗太阳能干燥用半透明光电热电混合集热器的实验性能

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-26 DOI: 10.1016/j.solener.2025.114286

Priya Choubey , Harender Sinhmar , Sumit Tiwari

This study examines the drying and thermal performance of Indian gooseberry (Amla), which is one of the richest sources of Vitamin C, using a glass-to-glass photovoltaic–thermal thermoelectric cooling hybrid solar dryer (ST-PVT-TEC HSD). The drying kinetics obtained from this system were compared with those of a conventional open sun dryer (OSD). Among the drying models evaluated, the Midilli and Kucuk models provided the best fit for describing the drying process in ST-PVT-TEC HSD. The results indicated the corresponding equivalent thermal efficiency, and the total maximum electrical energy of the system was found to be 44.2 % and 49.6 W. Furthermore, the average equivalent thermal energy, exergy, and exergy efficiency of the system were determined as 337.74 W, 38.29 W, and 0.062. The average values of the sustainability index (SI), waste exergy ratio (WER), and improvement potential (IP) were calculated as 1.06, 0.93, and 34.70 W. Based on this study, the ST-PVT-TEC HSD demonstrated superior performance by significantly reducing the drying time and improving the quality of the product compared with the OSD. The optimal performance of the system was achieved at a mass flow rate of 0.024 kg/s. With CO₂ emissions of 44 kg CO₂ per year and a net CO₂ mitigation of 49.63 tons per year, the dryer’s energy payback period is 4 years, 2 months, demonstrating its cost-effectiveness and environmental friendliness.

本研究考察了印度醋栗（Amla）的干燥和热性能，这是维生素C最丰富的来源之一，使用玻璃对玻璃光伏-热热电冷却混合太阳能干燥器（ST-PVT-TEC HSD）。将该系统的干燥动力学与传统的开放式太阳干燥器（OSD）进行了比较。在评估的干燥模型中，Midilli和kuucuk模型最适合描述ST-PVT-TEC HSD的干燥过程。结果表明，该系统的等效热效率为44.2%，最大总电能为49.6 W。系统的平均等效热能、火用能和火用效率分别为337.74 W、38.29 W和0.062 W。可持续性指数（SI）、浪费能比（WER）和改善潜力（IP）的平均值分别为1.06、0.93和34.70 W。基于本研究，ST-PVT-TEC HSD与OSD相比，显著缩短了干燥时间，提高了产品质量，表现出优越的性能。在质量流量为0.024 kg/s时，系统性能达到最佳。每年的二氧化碳排放量为44千克，二氧化碳净排放量为49.63吨，烘干机的能源回收期为4年零2个月，证明了其成本效益和环境友好性。

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引用次数: 0

Effects of aperture configurations on heat losses in concentrated solar power systems: An experimental study for a semi-cylindrical cavity receiver 光圈结构对聚光太阳能系统热损失的影响：半圆柱形腔体接收器的实验研究

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-26 DOI: 10.1016/j.solener.2025.114278

Mohsen Nikbakht, Tahereh Yazdanipour, Kiyanoosh Razzaghi

This study presents a comprehensive experimental investigation into the convective heat losses of a semi-cylindrical cavity receiver, a geometry that holds considerable promise but has been inadequately explored in the context of parabolic trough concentrated solar power systems. The research systematically examines the impact of key operational and geometric parameters, including inclination angle, input heat flux, and—most critically—four distinct aperture configurations, namely Fully Open, Top, Bottom, and Center. The findings reveal a profound interdependence between aperture design and thermal performance. Specifically, increasing the inclination angle was found to expand the internal stagnant zone, thereby reducing convective loss and elevating surface temperatures; a shift from 0° to 90° resulted in dramatic convective loss reduction of up to 76 % for the Center configuration, under a constant surface heat flux of 440 W/m². The Center aperture configuration, characterized by sharp corners, was identified as the most effective for convective suppression due to a pronounced clogging effect that disrupts airflow stability. A novel dimensionless parameter,

ψ

, was also introduced to quantify the ratio of the stagnant zone to the convective zone, based on the underlying stagnant and convective zone hypotheses, providing unprecedented insight into the internal aerothermal dynamics. Furthermore, an empirical correlation was developed for the Nusselt number, correlating with more than 85 % of the data points while maintaining a deviation of less than ± 20 %. This was accomplished by incorporating a new characteristic length and a Grashof number within the range of 10⁴ to 3.4 × 10⁸.

本研究对半圆柱形腔接收器的对流热损失进行了全面的实验研究，半圆柱形腔接收器具有相当大的前景，但在抛物线槽聚光太阳能发电系统的背景下尚未得到充分的探索。该研究系统地检查了关键操作参数和几何参数的影响，包括倾角、输入热流密度，以及最关键的四种不同的孔径配置，即全开、顶部、底部和中心。研究结果揭示了孔径设计和热性能之间的深刻相互依存关系。增加倾角可以扩大内部滞流区，从而减少对流损失，提高地表温度；在440 W/m2的恒定表面热通量下，从0°到90°的转变导致中心配置的对流损失减少高达76%。中心孔径配置的特点是尖角，被认为是最有效的对流抑制，因为明显的堵塞效果会破坏气流稳定性。基于基本的滞流区和对流区假设，我们还引入了一个新的无量纲参数ψ来量化滞流区与对流区的比例，从而为内部空气热动力学提供了前所未有的见解。此外，为努塞尔数开发了经验相关性，与85%以上的数据点相关，同时保持小于±20%的偏差。这是通过结合一个新的特征长度和一个在104到3.4 × 108范围内的Grashof数来实现的。

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引用次数: 0

Performance enhancement of photovoltaic modules using burlap-based passive evaporative cooling: an experimental energy–exergy assessment 利用粗麻布为基础的被动蒸发冷却提高光伏组件的性能：一项实验性能量-消耗评估

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-25 DOI: 10.1016/j.solener.2025.114285

Hayder Altharwanee, Francisco Jurado, David Vera

His work experimentally investigates the thermal and electrical performance enhancement of photovoltaic (PV) modules using a burlap-based evaporative cooling technique. The tests were conducted over six consecutive days, from the 10th to the 16th of August, under hot and dry summer conditions. Several burlap configurations were evaluated on an identical PV module supplied with a steady water flow, while a second module operated simultaneously as a non-cooled reference.

The results revealed a notable improvement in PV performance due to the evaporative effect of the wetted burlap surface. The cooled modules exhibited a surface temperature reduction of up to 6

^{\circ}

C compared with the reference panel, resulting in an increase in electrical efficiency of approximately 2–4 %, depending on the burlap geometry and coverage area. Among the tested configurations, the hybrid arrangement (Case 3) achieved the most uniform cooling and the highest combined energy–exergy efficiency. Overall, the burlap-based cooling system offers a simple, sustainable, and low-cost solution for mitigating temperature rise and improving both efficiency and service life of PV modules in hot-climate applications.

他的工作是通过实验研究利用基于粗麻布的蒸发冷却技术来提高光伏（PV）模块的热电性能。试验于8月10日至16日在炎热干燥的夏季条件下连续6天进行。在提供稳定水流的相同光伏组件上评估了几种粗麻布配置，而另一个组件作为非冷却参考同时运行。结果表明，由于湿粗麻布表面的蒸发作用，PV性能得到了显着改善。与参考面板相比，经过冷却的组件表面温度降低了6°C，导致电效率提高了大约2 - 4%，具体取决于粗麻布的几何形状和覆盖面积。在测试的配置中，混合布置（案例3）实现了最均匀的冷却和最高的综合能能效率。总的来说，基于麻布的冷却系统提供了一种简单、可持续、低成本的解决方案，可以缓解温度上升，提高光伏组件在炎热气候应用中的效率和使用寿命。

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引用次数: 0

A greener approach for selecting organic PCM in solar thermal collectors using the MCDM framework 使用MCDM框架在太阳能集热器中选择有机PCM的更环保的方法

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-24 DOI: 10.1016/j.solener.2025.114283

Arumugam Ajithkumar, Poongavanam GaneshKumar

This article presents a comprehensive assessment of Multi-Criteria Decision-Making (MCDM) optimization methods for identifying sustainable, cost-effective phase change materials (PCMs) for solar thermal collectors. Comprising the 12 alternatives assessed, this study employs six distinct MCDM approaches, namely, GRA, WASPAS, PROMETHEE-II, PROMETHEE-I, COCOSO, and TODIM, to reduce the time consumption and identify the most suitable alternative. The effective selection of an optimum organic phase change material (PCM) is essential for enhancing thermal energy storage systems and remains stimulating owing to the enormous range of available materials with varying thermal, economic, and environmental characteristics. The optimization procedure accounts for multiple response parameters to assess thermal properties, ecological impacts, and economic aspects. The crucial qualities measured comprise latent heat of fusion, container compatibility, thermal conductivity (TC), specific heat capacity, density, price, global warming potential, ozone depletion potential, flammability, and toxicity. The comparative analysis reveals consistent and robust rankings across methodologies, founding a reliable decision-support tool for researchers and engineers. This combined assessment methodology augments PCM selection for various energy applications, contributing to sustainable and effective thermal management systems. Employing MCDM approaches, the grade values and weights determined by decision-makers are normalised into a unified metric for direct evaluation. Further, the results are validated by sensitivity analysis, Borda count, Copeland, and Spearman’s coefficient for their reliability and robustness. Whereas OM 49 is highlighted as the best choice among the alternatives suggested by MCDM approaches. MCDM suggestion is based on rankings, and the PROMETHEE-I analysis suggested the highest number of preferences.

本文提出了一个综合评估的多准则决策（MCDM）优化方法，以确定可持续的，具有成本效益的相变材料（pcm）用于太阳能集热器。本研究采用了GRA、WASPAS、promeee - ii、promeee - i、COCOSO和TODIM六种不同的MCDM方法，以减少时间消耗并确定最合适的替代方案。有效选择最佳有机相变材料（PCM）对于增强热能储存系统至关重要，并且由于具有不同热，经济和环境特性的大量可用材料仍然令人兴奋。优化过程考虑了多个响应参数，以评估热性能、生态影响和经济方面。测量的关键品质包括融合潜热、容器兼容性、导热系数（TC）、比热容、密度、价格、全球变暖潜势、臭氧消耗潜势、可燃性和毒性。对比分析揭示了跨方法的一致和强大的排名，为研究人员和工程师建立了可靠的决策支持工具。这种综合评估方法增加了各种能源应用的PCM选择，有助于可持续和有效的热管理系统。采用MCDM方法，决策者确定的等级值和权重归一化为统一的指标进行直接评价。此外，通过敏感性分析、Borda计数、Copeland和Spearman系数验证了结果的可靠性和稳健性。而om49被强调为MCDM方法建议的备选方案中的最佳选择。MCDM建议是基于排名的，promeee - i分析建议的偏好数量最多。

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引用次数: 0

Transferability of data-driven power estimate models from land to floating PV 数据驱动的电力估算模型从陆地到浮动光伏的可移植性

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-24 DOI: 10.1016/j.solener.2025.114259

Yiliao Zhou , Carlos D Rodríguez Gallegos , Tasmiat Rahman

Accurate power generation estimation is essential for the bankability and design optimization of solar photovoltaic (PV) systems, including emerging technologies such as floating PV (FPV)—but remains challenging. Research to date has largely focused on short-term forecasting. Long-term estimation, however, continues to depend on models like SAM and PVsyst, which systematically underestimate FPV yield by approximately 9 % because of coarse environmental representations. In contrast, estimation error for land-based PV (LPV) systems using these tools is typically limited to 1–5 %. To address this gap, we evaluate two machine learning models—XGBoost and Long Short-Term Memory (LSTM)—for high-resolution FPV power estimation and use XGBoost to assess transferability from LPV systems. We employ a 20-month tropical dataset with minute-level resolution, capturing environmental and power output data from co-located FPV and LPV systems. This fine granularity enables accurate modelling of rapid environmental dynamics. Both machine learning models outperform the pvlib baseline in FPV self-estimation, achieving a mean absolute error of approximately 30 W, a root mean square error of 83 W, and a coefficient of determination greater than 99 % for a 5.6 kW system. SHAP (SHapley Additive exPlanations) analysis highlights irradiance, temperature, and time as key influencing features. In the transferability analysis, an XGBoost model trained on only one month of LPV data achieved

R^{2} = 99.2 %

when estimating FPV output over the entire 20-month period. However, differences in surface albedo (rooftop vs. water) and longer LPV training durations each reduced transferability accuracy. These findings demonstrate the potential of data-driven approaches for reliable FPV performance estimation and introduce a scalable LPV-to-FPV transferability framework for emerging PV applications.

准确的发电量估算对于太阳能光伏系统的可融资性和设计优化至关重要，包括浮动光伏等新兴技术，但仍然具有挑战性。迄今为止的研究主要集中在短期预测上。然而，长期估计仍然依赖于SAM和PVsyst等模型，由于粗糙的环境表征，这些模型系统性地低估了FPV产量约9%。相比之下，使用这些工具的陆基PV （LPV）系统的估计误差通常限制在1 - 5%。为了解决这一差距，我们评估了两种机器学习模型——XGBoost和长短期记忆（LSTM）——用于高分辨率FPV功率估计，并使用XGBoost来评估LPV系统的可转移性。我们采用了20个月的热带数据集，具有分钟级分辨率，从位于同一位置的FPV和LPV系统中获取环境和电力输出数据。这种精细的粒度使快速环境动力学的精确建模成为可能。两种机器学习模型在FPV自我估计方面都优于pvlib基线，平均绝对误差约为30 W，均方根误差为83 W，对于5.6 kW的系统，确定系数大于99%。SHAP （SHapley加性解释）分析强调辐照度、温度和时间是主要的影响特征。在可转移性分析中，仅对一个月的LPV数据进行训练的XGBoost模型在估计整个20个月期间的FPV产量时达到了R2=99.2%。然而，表面反照率的差异（屋顶与水面）和较长的LPV训练时间都会降低可转移性的准确性。这些发现证明了数据驱动方法在可靠的FPV性能评估方面的潜力，并为新兴的PV应用引入了可扩展的lpv到FPV可转移性框架。

{"title":"Transferability of data-driven power estimate models from land to floating PV","authors":"Yiliao Zhou , Carlos D Rodríguez Gallegos , Tasmiat Rahman","doi":"10.1016/j.solener.2025.114259","DOIUrl":"10.1016/j.solener.2025.114259","url":null,"abstract":"<div><div>Accurate power generation estimation is essential for the bankability and design optimization of solar photovoltaic (PV) systems, including emerging technologies such as floating PV (FPV)—but remains challenging. Research to date has largely focused on short-term forecasting. Long-term estimation, however, continues to depend on models like SAM and PVsyst, which systematically underestimate FPV yield by approximately 9 % because of coarse environmental representations. In contrast, estimation error for land-based PV (LPV) systems using these tools is typically limited to 1–5 %. To address this gap, we evaluate two machine learning models—XGBoost and Long Short-Term Memory (LSTM)—for high-resolution FPV power estimation and use XGBoost to assess transferability from LPV systems. We employ a 20-month tropical dataset with minute-level resolution, capturing environmental and power output data from co-located FPV and LPV systems. This fine granularity enables accurate modelling of rapid environmental dynamics. Both machine learning models outperform the <span>pvlib</span> baseline in FPV self-estimation, achieving a mean absolute error of approximately 30 W, a root mean square error of 83 W, and a coefficient of determination greater than 99 % for a 5.6 kW system. SHAP (SHapley Additive exPlanations) analysis highlights irradiance, temperature, and time as key influencing features. In the transferability analysis, an XGBoost model trained on only one month of LPV data achieved <span><math><msup><mi>R</mi><mn>2</mn></msup><mo>=</mo><mn>99.2</mn><mspace></mspace><mi>%</mi></math></span> when estimating FPV output over the entire 20-month period. However, differences in surface albedo (rooftop vs. water) and longer LPV training durations each reduced transferability accuracy. These findings demonstrate the potential of data-driven approaches for reliable FPV performance estimation and introduce a scalable LPV-to-FPV transferability framework for emerging PV applications.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114259"},"PeriodicalIF":6.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Net metering interval impact on solar photovoltaic prosumer techno-economics in Finland 净计量间隔对芬兰太阳能光伏产消技术经济的影响

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-23 DOI: 10.1016/j.solener.2025.114230

Md Mofidul Bari Sakib, Altti Meriläinen, Vesa Ruuskanen, Antti Kosonen

Residential solar photovoltaic systems, supported by net metering policy, are increasingly adopted in Finland for cost savings and environmental benefits. European Union Regulation 2017/2195 provides a transition from the 1-hour to 15-minute imbalance settlement period, with even finer resolutions being possible in the future. This paper examines the effects of 15- and 5-minute net metering intervals on the energy dynamics and economic outcomes of residential solar photovoltaic installations in Finland. With measured data from two prosumer households over three years, changes in imported energy, self-consumption, self-sufficiency, and value of solar photovoltaic for capacities from 1–20 kWp are analyzed. Findings show that for the 15-minute interval with a 5 kWp solar PV system capacity, annual grid imports increase by up to 110 kWh, self-sufficiency decreases by up to 1.4 percentage points, and monetary value decreases by up to

€

11 for the capacities studied, with larger systems being less affected by the transition to a shorter metering interval. The 5-minute interval has a similar but slightly greater impact across all parameters. Moreover, Finland’s latest increase in value-added tax from 24 % to 25.5 % mitigates some financial losses of solar photovoltaic systems over shorter intervals. These findings offer insights for policymakers and prosumers navigating the evolving regulatory framework.

在净计量政策的支持下，芬兰越来越多地采用住宅太阳能光伏系统，以节省成本和环境效益。欧盟法规2017/2195规定了从1小时到15分钟的不平衡结算周期的过渡，未来可能会有更精细的解决方案。本文考察了15分钟和5分钟净计量间隔对芬兰住宅太阳能光伏装置的能源动态和经济结果的影响。本文利用两户产消户近三年的实测数据，分析了1-20 kWp的进口能源、自用能源、自给率和太阳能光伏发电价值的变化。研究结果表明，在5千瓦时太阳能光伏系统容量的15分钟间隔中，年度电网进口量增加了110千瓦时，自给率下降了1.4个百分点，所研究的容量的货币价值下降了11欧元，较大的系统受过渡到较短的计量间隔的影响较小。5分钟间隔对所有参数的影响类似，但略大一些。此外，芬兰最近将增值税从24%提高到25.5%，在较短的时间间隔内减轻了太阳能光伏系统的一些财务损失。这些发现为政策制定者和消费者在不断变化的监管框架中导航提供了见解。

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引用次数: 0

Stress evolution and degradation in zero-busbar silicon photovoltaic modules under thermal cycling: A finite element study 热循环下零母线硅光伏组件应力演化与退化：有限元研究

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-23 DOI: 10.1016/j.solener.2025.114206

Huiwen Liu , Selvakumar V. Nair , Hao Gu , Bo Yang , Jun Wu , Xinchun Yan , Ruirui Lv , Jingbing Dong , Yuanjie Yu , Tao Xu , Harry E. Ruda

Zero-busbar silicon-based photovoltaic modules are emerging as innovative designs in renewable energy systems, yet their thermo-mechanical reliability under operational stresses remains a critical concern. This study employs transient-state finite element analysis (FEA) to investigate stress evolution in silicon cells, solder joints, and glue joints during thermal cycling. Numerical simulations reveal that structural symmetry significantly influences stress concentrations, particularly at cell-to-cell interconnections. The analysis further demonstrates that glue pad properties exhibit minimal impact on overall stress distribution, while multi-cycle thermal loading highlights progressive hysteresis behaviour in solder joints, driven by accumulated plastic deformation. These findings highlight the importance of geometric optimisation and solder joint durability in enhancing the long-term reliability of zero-busbar photovoltaic modules. This work provides actionable insights for designing robust, high-efficiency systems capable of withstanding real-world thermal stresses.

零母线硅基光伏组件作为可再生能源系统的创新设计正在兴起，但其在运行应力下的热机械可靠性仍然是一个关键问题。本研究采用瞬态有限元分析（FEA）研究了硅电池、焊点和胶点在热循环过程中的应力演化。数值模拟表明，结构对称性显著影响应力集中，特别是在细胞与细胞之间的连接。分析进一步表明，胶垫性能对整体应力分布的影响最小，而多循环热加载突出了由累积塑性变形驱动的焊点的渐进滞后行为。这些发现强调了几何优化和焊点耐久性在提高零母线光伏组件的长期可靠性方面的重要性。这项工作为设计能够承受实际热应力的强大，高效的系统提供了可行的见解。

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引用次数: 0

A calculation method for indoor solar irradiance under tree shading 树荫下室内太阳辐照度的计算方法

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-22 DOI: 10.1016/j.solener.2025.114282

Zhechen Shen , Feng Qi , Tailong Zhang , Yukai Song , Yufei Zhou

Solar radiation is a critical source of heat gain in building interiors, and trees adjacent to windows significantly influence the solar radiation received indoors. While existing studies have primarily focused on the impact of nearby trees on wall temperatures and building energy loads, there is a notable lack of quantitative research on indoor surface solar irradiance under complex tree shading conditions. This gap hinders the scientific evaluation of trees’ effects on solar heat gain on indoor surfaces of adjacent buildings, thereby affecting the strategic greening of building surroundings from an energy-saving perspective. To address this, a calculation method for indoor surface incident solar irradiance under window-adjacent tree shading is proposed, based on experimental measurements and fisheye lens imaging. The method first calculates direct normal irradiance and horizontal diffuse irradiance using experimental data. It then evaluates the attenuation of diffuse irradiance by trees and other obstructions using fisheye images. Subsequently, fisheye images and 3D models are employed to compute view factors between measurement points and complex surfaces for reflected irradiance calculations. Finally, the proposed irradiance calculation model was validated through a case study. The comparison between the calculated and measured values showed a mean relative error of approximately 10 % and a root mean square error (RMSE) of 11.4 W/m², indicating the high accuracy of the model. This method provides a theoretical foundation for further investigating the mechanisms by which window-adjacent trees influence indoor surface incident solar irradiance.

太阳辐射是建筑物内部热量增加的一个重要来源，而靠近窗户的树木对室内接收的太阳辐射有显著影响。虽然现有的研究主要集中在附近树木对墙体温度和建筑能量负荷的影响，但对复杂树木遮荫条件下室内表面太阳辐照度的定量研究明显缺乏。这一差距阻碍了科学评价树木对相邻建筑室内表面太阳热增益的影响，从而从节能的角度影响建筑环境的战略性绿化。为了解决这一问题，提出了一种基于实验测量和鱼眼透镜成像的窗旁遮荫下室内表面入射太阳辐照度的计算方法。该方法首先利用实验数据计算直接法向辐照度和水平漫射辐照度。然后利用鱼眼图像评估树木和其他障碍物对漫射辐射的衰减。随后，利用鱼眼图像和三维模型计算测点与复杂表面之间的视点因子，计算反射辐照度。最后，通过实例验证了所提出的辐照度计算模型。计算值与实测值的平均相对误差约为10%，均方根误差（RMSE）为11.4 W/m2，表明模型具有较高的精度。该方法为进一步研究临窗树木对室内表面入射太阳辐照度的影响机制提供了理论基础。

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引用次数: 0

Drying kinetics, energy, exergy, and economic aspects of indirect solar dryer with phase change material 相变材料间接太阳能干燥机的干燥动力学、能量、火用和经济性

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-22 DOI: 10.1016/j.solener.2025.114287

S. Rajesh , S. Madhankumar , P.M. Arunkumar , T. Vignesh , S.D. Sekar

Efficient moisture removal is essential in food processing; yet conventional thermal drying methods are often energy-intensive and costly. Solar drying offers a sustainable alternative, particularly for rural and agricultural communities. This research investigates the drying kinetics, energy and exergy performance, and economic feasibility of two newly developed Indirect Solar Dryers (ISDs): a Passive Type (PTISD) and an Active Type (ATISD) − both integrated with a flat coil-embedded Phase Change Material (PCM) in the solar collector. The incorporation of paraffin wax as PCM with a flat-coil represents the key novelty of the system, enabling improved temperature and enhanced drying performance. Experiments conducted for drying Coccinia grandis showed that the ATISD operating at 0.055 kg/s achieved a mean collector outlet temperature of 39.28 °C with improved temperature uniformity and completed drying in 13 h with an average drying rate of 0.18 kg/h. In contrast, the PTISD, with an airflow rate of 0.026 kg/s, reached 40.15 °C and required 17 h with an average drying rate of 0.16 kg/h. The energy efficiency analysis revealed average values of 26.54 % for the PTISD and 28.12 % for the ATISD, whereas the exergy efficiencies were calculated as 26.55 % and 29.51 %, respectively. An economic evaluation, conducted utilizing life cycle savings and payback period approaches, indicated a payback period of 0.542 years for the PTISD and 0.327 years for the ATISD, based on a 20-year operational lifespan. Overall, the ATISD setup exhibited superior performance across all key parameters, highlighting the potential of ATISD for sustainable and energy-efficient agricultural practices, particularly in rural environments.

有效地去除水分在食品加工中是必不可少的；然而，传统的热干燥方法往往是能源密集型和昂贵的。太阳能干燥提供了一种可持续的替代方案，特别是对农村和农业社区而言。本研究研究了两种新开发的间接太阳能干燥器（isd）的干燥动力学，能量和火用性能以及经济可行性：被动型（PTISD）和主动型(ATISD) -两者都集成了太阳能集热器中的扁平线圈嵌入相变材料（PCM）。石蜡作为PCM与平面线圈的结合代表了该系统的关键新颖性，能够提高温度和增强干燥性能。实验结果表明，在0.055 kg/s的工作速度下，ATISD的平均集热器出口温度为39.28℃，温度均匀性得到改善，在13 h内完成干燥，平均干燥速率为0.18 kg/h。而PTISD在气流速率为0.026 kg/s时，干燥温度为40.15℃，干燥时间为17 h，平均干燥速率为0.16 kg/h。能源效率分析显示，PTISD的平均值为26.54%，ATISD的平均值为28.12%，而火用效率分别为26.55%和29.51%。利用生命周期节约和投资回收期方法进行的经济评估表明，在20年的使用寿命基础上，PTISD的投资回收期为0.542年，ATISD的投资回收期为0.327年。总体而言，ATISD设置在所有关键参数上都表现出色，突出了ATISD在可持续和节能农业实践方面的潜力，特别是在农村环境中。

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引用次数: 0

Machine learning based model predictive control of heliostat aiming strategy under cloud variation 云变化下基于机器学习的定日镜瞄准策略预测控制

IF 6 2区工程技术 Q2 ENERGY & FUELS

Solar Energy

Pub Date : 2025-12-22 DOI: 10.1016/j.solener.2025.114258

Jiayi Wu , Xingchao Wang , Chunjian Pan , Ni Liu , Weidong Wu

Solar power tower systems require optimal heliostat aiming strategies to maximize energy capture while ensuring receiver safety under dynamic environmental conditions. Conventional approaches relying on analytic optical models and heuristic methods are limited in computational efficiency and flexibility in handling design constraints for a large-scale heliostat field. This study applies machine learning techniques for developing a fast receiver flux prediction model that is designed for use in a model predictive control (MPC) framework to enhance operational efficiency and safety of the central receiver under cloud shading. A novel two-stage machine learning approach is proposed that uses a conditional variational autoencoder (CVAE) for efficient flux data compression, followed by an augmented neural network for rapid flux prediction (with peak flux errors of 2.91%) under varying DNI levels, sun positions, and cloud patterns. The MPC framework, based on the flux prediction model and with receiver thermal safety constraints enforced, facilitates real-time closed-loop optimization of aiming strategies under environmental variations. Performance assessments using simulated data generated by SolarPILOT for the Crescent Dunes solar power tower plant confirm the model’s robustness under various operational scenarios. The integrated MPC framework effectively balances power maximization and receiver safety constraints, and shows a significant performance improvement over static control methods, with a 10.8% higher power tracking accuracy, a 6.4% increase in power output, an allowable flux density (AFD) violation rate of only 0.91%, and a 22.3% enhancement in flux uniformity.

太阳能发电塔系统需要优化定日镜瞄准策略，以最大限度地获取能量，同时确保接收器在动态环境条件下的安全。基于解析光学模型和启发式方法的传统方法在处理大型定日镜视场设计约束的计算效率和灵活性方面受到限制。本研究应用机器学习技术开发了一个快速接收器通量预测模型，该模型设计用于模型预测控制（MPC）框架，以提高遮阳下中央接收器的运行效率和安全性。提出了一种新的两阶段机器学习方法，该方法使用条件变分自编码器（CVAE）进行有效的通量数据压缩，然后使用增强神经网络在不同DNI水平、太阳位置和云模式下进行快速通量预测（峰值通量误差为2.91%）。MPC框架基于通量预测模型，并强制执行接收机热安全约束，可实现环境变化下瞄准策略的实时闭环优化。利用SolarPILOT为新月沙丘太阳能塔式发电厂生成的模拟数据进行性能评估，证实了该模型在各种运行场景下的鲁棒性。集成的MPC框架有效地平衡了功率最大化和接收机安全约束，与静态控制方法相比，性能有显著提高，功率跟踪精度提高10.8%，功率输出提高6.4%，允许磁通密度（AFD）违规率仅为0.91%，磁通均匀性提高22.3%。

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