Pub Date : 2025-12-22DOI: 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.
{"title":"Machine learning based model predictive control of heliostat aiming strategy under cloud variation","authors":"Jiayi Wu , Xingchao Wang , Chunjian Pan , Ni Liu , Weidong Wu","doi":"10.1016/j.solener.2025.114258","DOIUrl":"10.1016/j.solener.2025.114258","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114258"},"PeriodicalIF":6.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837666","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}
Pub Date : 2025-12-22DOI: 10.1016/j.solener.2025.114232
Junce Wang , Tingting Huang
Rapid urbanization across China, particularly in high-density metropolitan regions, has intensified the urban heat island (UHI) effect, leading to rising cooling energy demand, increased peak electricity loads, and deteriorating indoor thermal comfort. These challenges are especially pronounced in China’s hot-humid and hot-summer–warm-winter climate zones, where strong solar radiation and high ambient humidity exacerbate thermal stress on building envelopes. In this context, passive envelope-level cooling strategies that reduce solar heat gain without additional energy consumption are urgently needed. This study comparatively evaluates the solar-induced thermal response of three reflective coating technologies—diffuse highly reflective (DHR), general reflective (GR), and retro-reflective (RR)—to assess their effectiveness in reducing surface temperatures, improving indoor thermal comfort, and mitigating urban heat accumulation relevant to Chinese cities. Simplified cubic building models (900 × 900 × 900 mm) coated with each material were tested under controlled outdoor conditions, with high-resolution monitoring of solar irradiance, surface temperature, indoor air temperature, mean radiant temperature (MRT), operative temperature (OT), and shortwave and longwave radiative fluxes. Optical characterization using spectrometer analysis showed that the DHR coating achieved the highest solar reflectance (82 %) with an emissivity of 0.90, followed by RR (76 %, ε = 0.88), while GR exhibited substantially lower reflectance (33 %, ε = 0.86). Both DHR and RR coatings maintained strong reflectance across visible (400–700 nm) and near-infrared (700–2500 nm) wavelengths, directly contributing to superior thermal performance. Experimental results indicated that DHR and RR coatings reduced external surface temperatures by 9–11 °C, indoor air temperatures by 8–10 °C, and MRT/OT values by 7–8 °C relative to GR coatings. Heat-transfer modeling further confirmed that conductive heat flux through the envelope was reduced by more than 25 % under peak solar conditions. Orientation-specific analysis revealed that RR coatings were particularly effective on east- and west-facing façades due to their enhanced performance at low solar incidence angles, a condition common in high-rise Chinese urban environments. Overall, the findings demonstrate that reflective coatings optimized through combined reflectance and emissivity properties can substantially enhance passive cooling performance. Retro-reflective coatings, in particular, emerge as a promising, visually adaptable, and durable solution for reducing cooling energy demand and alleviating UHI effects in China’s rapidly urbanizing cities, supporting national goals for energy efficiency and low-carbon urban development.
{"title":"Urban Heat Island Mitigation and Indoor Comfort: A Cost-Effectiveness Analysis of Green Building Solutions for China’s Cities","authors":"Junce Wang , Tingting Huang","doi":"10.1016/j.solener.2025.114232","DOIUrl":"10.1016/j.solener.2025.114232","url":null,"abstract":"<div><div>Rapid urbanization across China, particularly in high-density metropolitan regions, has intensified the urban heat island (UHI) effect, leading to rising cooling energy demand, increased peak electricity loads, and deteriorating indoor thermal comfort. These challenges are especially pronounced in China’s hot-humid and hot-summer–warm-winter climate zones, where strong solar radiation and high ambient humidity exacerbate thermal stress on building envelopes. In this context, passive envelope-level cooling strategies that reduce solar heat gain without additional energy consumption are urgently needed. This study comparatively evaluates the solar-induced thermal response of three reflective coating technologies—diffuse highly reflective (DHR), general reflective (GR), and <em>retro</em>-reflective (RR)—to assess their effectiveness in reducing surface temperatures, improving indoor thermal comfort, and mitigating urban heat accumulation relevant to Chinese cities. Simplified cubic building models (900 × 900 × 900 mm) coated with each material were tested under controlled outdoor conditions, with high-resolution monitoring of solar irradiance, surface temperature, indoor air temperature, mean radiant temperature (MRT), operative temperature (OT), and shortwave and longwave radiative fluxes. Optical characterization using spectrometer analysis showed that the DHR coating achieved the highest solar reflectance (82 %) with an emissivity of 0.90, followed by RR (76 %, ε = 0.88), while GR exhibited substantially lower reflectance (33 %, ε = 0.86). Both DHR and RR coatings maintained strong reflectance across visible (400–700 nm) and near-infrared (700–2500 nm) wavelengths, directly contributing to superior thermal performance. Experimental results indicated that DHR and RR coatings reduced external surface temperatures by 9–11 °C, indoor air temperatures by 8–10 °C, and MRT/OT values by 7–8 °C relative to GR coatings. Heat-transfer modeling further confirmed that conductive heat flux through the envelope was reduced by more than 25 % under peak solar conditions. Orientation-specific analysis revealed that RR coatings were particularly effective on east- and west-facing façades due to their enhanced performance at low solar incidence angles, a condition common in high-rise Chinese urban environments. Overall, the findings demonstrate that reflective coatings optimized through combined reflectance and emissivity properties can substantially enhance passive cooling performance. Retro-reflective coatings, in particular, emerge as a promising, visually adaptable, and durable solution for reducing cooling energy demand and alleviating UHI effects in China’s rapidly urbanizing cities, supporting national goals for energy efficiency and low-carbon urban development.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114232"},"PeriodicalIF":6.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837686","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}
Pub Date : 2025-12-22DOI: 10.1016/j.solener.2025.114276
Yu-Hung Hsiao , Lan-Sheng Yang , Shih-Han Huang , Hou-Chin Cha , Wen-Ting Li , Sheng-Long Jeng , Yu-Chiang Chao , Yu-Ching Huang
Perovskite solar cells (PSCs) have emerged as strong contenders for next-generation photovoltaic applications, owing to their exceptional optoelectronic characteristics and adjustable bandgaps. Despite these advantages, a notable discrepancy persists between the theoretical and experimentally achieved open-circuit voltage (Voc), largely attributed to interfacial energy misalignment and non-radiative recombination processes. In this work, we propose the introduction of chiral organic compounds into the perovskite precursor solution as a means to tailor the electronic structure and interfacial behavior of the absorber layer. Our systematic study reveals that the integration of chiral ligands not only promotes improved crystallinity of the perovskite films but also modulates lattice microstrain, as evidenced by X-ray diffraction (XRD) and microstrain analysis. Electrochemical impedance spectroscopy (EIS) results further indicate a reduction in charge transport resistance and interfacial recombination, confirming a more favorable electronic interface between the perovskite and charge transport layers. Importantly, the non-radiative voltage loss is significantly mitigated, decreasing from 354 mV in the control to 304 mV with chiral additive incorporation, thereby yielding an average Voc of 1.16 V. This study underscores the effectiveness of chiral molecular engineering in tuning film quality and interface properties. It also demonstrates a scalable strategy for enhancing PSC device efficiency, offering a promising pathway to close the Voc gap and advance perovskite-based photovoltaics toward greater performance and long-term operational stability.
{"title":"Chiral ligand-assisted interface modulation for reduced voltage loss in perovskite solar cells","authors":"Yu-Hung Hsiao , Lan-Sheng Yang , Shih-Han Huang , Hou-Chin Cha , Wen-Ting Li , Sheng-Long Jeng , Yu-Chiang Chao , Yu-Ching Huang","doi":"10.1016/j.solener.2025.114276","DOIUrl":"10.1016/j.solener.2025.114276","url":null,"abstract":"<div><div>Perovskite solar cells (PSCs) have emerged as strong contenders for next-generation photovoltaic applications, owing to their exceptional optoelectronic characteristics and adjustable bandgaps. Despite these advantages, a notable discrepancy persists between the theoretical and experimentally achieved open-circuit voltage (Voc), largely attributed to interfacial energy misalignment and non-radiative recombination processes. In this work, we propose the introduction of chiral organic compounds into the perovskite precursor solution as a means to tailor the electronic structure and interfacial behavior of the absorber layer. Our systematic study reveals that the integration of chiral ligands not only promotes improved crystallinity of the perovskite films but also modulates lattice microstrain, as evidenced by X-ray diffraction (XRD) and microstrain analysis. Electrochemical impedance spectroscopy (EIS) results further indicate a reduction in charge transport resistance and interfacial recombination, confirming a more favorable electronic interface between the perovskite and charge transport layers. Importantly, the non-radiative voltage loss is significantly mitigated, decreasing from 354 mV in the control to 304 mV with chiral additive incorporation, thereby yielding an average Voc of 1.16 V. This study underscores the effectiveness of chiral molecular engineering in tuning film quality and interface properties. It also demonstrates a scalable strategy for enhancing PSC device efficiency, offering a promising pathway to close the Voc gap and advance perovskite-based photovoltaics toward greater performance and long-term operational stability.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114276"},"PeriodicalIF":6.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837691","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}
Geostationary satellites provide highly accurate, gridded solar irradiance data on a global scale. However, because satellite-derived irradiance is based on instantaneous measurements, temporal aggregation techniques are needed for practical applications. In this study, we show that various temporal aggregation techniques for hourly solar radiation values are currently employed in both research publications and software tools for the widely adopted SARAH datasets. Our benchmarking reveals that these differing approaches lead to significant discrepancies, with mean absolute deviations up to three times. Notably, many studies neglect the influence of local satellite scan times, even though our results demonstrate that accounting for them significantly enhances aggregation accuracy. To address this gap, we introduce a simple, latitude-based heuristic that efficiently adjusts for scan time differences. Overall, our findings highlight the need to harmonize temporal aggregation methods, as they have a pronounced impact on the quality and consistency of solar radiation data and offer a practical technique to achieve this.
{"title":"Harmonizing the hourly solar radiation calculation from satellite-derived irradiance","authors":"Matthias Zech , Annette Hammer , Jörg Trentmann , Uwe Pfeifroth","doi":"10.1016/j.solener.2025.114243","DOIUrl":"10.1016/j.solener.2025.114243","url":null,"abstract":"<div><div>Geostationary satellites provide highly accurate, gridded solar irradiance data on a global scale. However, because satellite-derived irradiance is based on instantaneous measurements, temporal aggregation techniques are needed for practical applications. In this study, we show that various temporal aggregation techniques for hourly solar radiation values are currently employed in both research publications and software tools for the widely adopted SARAH datasets. Our benchmarking reveals that these differing approaches lead to significant discrepancies, with mean absolute deviations up to three times. Notably, many studies neglect the influence of local satellite scan times, even though our results demonstrate that accounting for them significantly enhances aggregation accuracy. To address this gap, we introduce a simple, latitude-based heuristic that efficiently adjusts for scan time differences. Overall, our findings highlight the need to harmonize temporal aggregation methods, as they have a pronounced impact on the quality and consistency of solar radiation data and offer a practical technique to achieve this.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114243"},"PeriodicalIF":6.0,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788339","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}
Pub Date : 2025-12-18DOI: 10.1016/j.solener.2025.114237
Vinicius Marson , Gabriel Bertacco dos Santos , Jean-Pierre Bedecarrats , José Lara Cruz , Elaine Maria Cardoso
Photovoltaic (PV) systems face significant performance losses and material degradation due to their high operating temperature, a challenge that this study addresses by introducing a climate-adaptive framework for passive thermal regulation using bio-based phase change materials (bioPCMs). This approach addresses the circular dependency of conventional phase change material (PCM) sizing methods by integrating site-specific meteorological data and material properties to optimize selection and thickness. A validated three-dimensional (3D) transient computational model demonstrates the efficacy of a 4 cm eutectic mixture of lauric acid with palmitic acid (LA:PA) configuration, achieving mean temperature reduction () and 2.8 % energy yield improvement, comparable to paraffin benchmarks while ensuring full biodegradability. The framework indicates that a 4 cm layer is able to deliver 92 % of the temperature reduction of a 5 cm layer while offering a 20 % mass-saving advantage. This work establishes bioPCMs as scalable, eco-friendly solutions for photovoltaic (PV) thermal management, bridging technical performance with environmental sustainability across diverse climatic regions.
{"title":"Transient performance of a commercial photovoltaic panel integrated with a bio-based phase change material: a numerical study","authors":"Vinicius Marson , Gabriel Bertacco dos Santos , Jean-Pierre Bedecarrats , José Lara Cruz , Elaine Maria Cardoso","doi":"10.1016/j.solener.2025.114237","DOIUrl":"10.1016/j.solener.2025.114237","url":null,"abstract":"<div><div>Photovoltaic (PV) systems face significant performance losses and material degradation due to their high operating temperature, a challenge that this study addresses by introducing a climate-adaptive framework for passive thermal regulation using bio-based phase change materials (bioPCMs). This approach addresses the circular dependency of conventional phase change material (PCM) sizing methods by integrating site-specific meteorological data and material properties to optimize selection and thickness. A validated three-dimensional (3D) transient computational model demonstrates the efficacy of a 4 cm eutectic mixture of lauric acid with palmitic acid (LA:PA) configuration, achieving <span><math><mrow><mn>10</mn></mrow><msup><mspace></mspace><mrow><mo>∘</mo></mrow></msup><mtext>C</mtext></math></span> mean temperature reduction (<span><math><mi>Δ</mi><msub><mi>T</mi><mtext>peak</mtext></msub><mo>=</mo><mrow><mn>13.1</mn></mrow><msup><mspace></mspace><mrow><mo>∘</mo></mrow></msup><mtext>C</mtext></math></span>) and 2.8 % energy yield improvement, comparable to paraffin benchmarks while ensuring full biodegradability. The framework indicates that a 4 cm layer is able to deliver 92 % of the temperature reduction of a 5 cm layer while offering a 20 % mass-saving advantage. This work establishes bioPCMs as scalable, eco-friendly solutions for photovoltaic (PV) thermal management, bridging technical performance with environmental sustainability across diverse climatic regions.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114237"},"PeriodicalIF":6.0,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788296","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}
Pub Date : 2025-12-18DOI: 10.1016/j.solener.2025.114256
Nesrine Faraj , Daha Hassan Daher , Francesca Brunetti , Anna Lushnikova , Marcello Baricco , Christophe Ménézo , Nadia Barbero
The transition to renewable energy is essential for mitigating climate change, especially in mountainous regions where energy access and climate vulnerability pose challenges. This study explores photovoltaic (PV) system performance across high- and low-altitude sites in Lebanon, Italy, France, and Switzerland using simulations from the Photovoltaic Geographical Information System (PVGIS). Results show that while low-altitude areas typically yield higher annual energy outputs, high-altitude locations demonstrated seasonal advantages, particularly in spring and summer. Solar irradiation was up to 17.2% higher at lower altitudes overall. However, Performance Ratios, ranging from 73.73% to 88.64%, were generally higher year-round in mountainous areas, indicating greater efficiency at cooler temperatures. A strong inverse correlation between Performance Ratio and module temperature highlights the effect of temperature on PV performance. The Capacity Utilization Factor also varied seasonally, with higher values observed at high-altitude sites during certain months of spring, summer, and autumn. This factor strongly correlated with in-plane radiation, emphasizing irradiation’s role in energy yield. Conducted in accordance with IEC 61724 standards, this research supports energy planning in remote regions. The findings underline the importance of both altitude and geography in solar energy performance, offering valuable insights for expanding renewable energy in diverse and challenging terrains.
{"title":"Solar power at new heights: comparing photovoltaic performance across altitudes","authors":"Nesrine Faraj , Daha Hassan Daher , Francesca Brunetti , Anna Lushnikova , Marcello Baricco , Christophe Ménézo , Nadia Barbero","doi":"10.1016/j.solener.2025.114256","DOIUrl":"10.1016/j.solener.2025.114256","url":null,"abstract":"<div><div>The transition to renewable energy is essential for mitigating climate change, especially in mountainous regions where energy access and climate vulnerability pose challenges. This study explores photovoltaic (PV) system performance across high- and low-altitude sites in Lebanon, Italy, France, and Switzerland using simulations from the Photovoltaic Geographical Information System (PVGIS). Results show that while low-altitude areas typically yield higher annual energy outputs, high-altitude locations demonstrated seasonal advantages, particularly in spring and summer. Solar irradiation was up to 17.2% higher at lower altitudes overall. However, Performance Ratios, ranging from 73.73% to 88.64%, were generally higher year-round in mountainous areas, indicating greater efficiency at cooler temperatures. A strong inverse correlation between Performance Ratio and module temperature highlights the effect of temperature on PV performance. The Capacity Utilization Factor also varied seasonally, with higher values observed at high-altitude sites during certain months of spring, summer, and autumn. This factor strongly correlated with in-plane radiation, emphasizing irradiation’s role in energy yield. Conducted in accordance with IEC 61724 standards, this research supports energy planning in remote regions. The findings underline the importance of both altitude and geography in solar energy performance, offering valuable insights for expanding renewable energy in diverse and challenging terrains.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114256"},"PeriodicalIF":6.0,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788340","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}
Pub Date : 2025-12-17DOI: 10.1016/j.solener.2025.114242
Gabriel López , Benjamin Ivorra , Pablo Ferrada , Christian A. Gueymard
This work introduces a novel methodology for the extension and upscaling of direct solar irradiance spectra measured with spectroradiometers, using Genetic Algorithms (GAs) to address the associated inverse problem. Acquiring accurate spectral data of solar irradiance is critical for various applications, including photovoltaic (PV) technology, environmental monitoring, and biotechnology. However, limitations in spectroradiometer instrumentation often restrict the availability of detailed spectral information. The proposed methodology specifically targets periods when the sun is unobscured by clouds, under which accurate retrievals and spectral extensions can be obtained irrespective of the cloudiness status of the rest of the sky. This approach leverages the SMARTS radiative transfer model to generate synthetic spectra under diverse atmospheric conditions and employs GAs to estimate key atmospheric parameters that align the simulated spectra with the observed measurements. Compared to traditional methods, the GA-based optimization significantly improves computational efficiency and estimation accuracy. Unlike conventional approaches that rely on selected narrow spectral ranges, this methodology utilizes full-spectrum (350–1050 nm) observations, enabling comprehensive spectral upscaling, improving spectroradiometer calibration, and offering a framework for benchmarking other algorithms. With median overall errors typically below 1–2 % in the validation range, it achieves a close match between optimized and actual spectra. The experimental validation of the method, based on more than 2000 observed spectra near Huelva, Spain demonstrates robust performance across varying local conditions, enabling the accurate determination of three key atmospheric quantities: aerosol optical depth, precipitable water, and the Ångström exponent. Application to real measurements further confirms the methodology’s potential in identifying calibration issues in spectroradiometers. This methodology offers a powerful tool for expanding spectral coverage in solar energy and related fields, with the added benefit of scalability to diverse geographic and atmospheric conditions. The developed approach facilitates accurate solar irradiance modeling and has promising implications for advancing PV efficiency assessments, agrivoltaics, and climate research.
{"title":"An efficient genetic algorithm method to extend and upscale direct solar irradiance spectra measured with spectroradiometers","authors":"Gabriel López , Benjamin Ivorra , Pablo Ferrada , Christian A. Gueymard","doi":"10.1016/j.solener.2025.114242","DOIUrl":"10.1016/j.solener.2025.114242","url":null,"abstract":"<div><div>This work introduces a novel methodology for the extension and upscaling of direct solar irradiance spectra measured with spectroradiometers, using Genetic Algorithms (GAs) to address the associated inverse problem. Acquiring accurate spectral data of solar irradiance is critical for various applications, including photovoltaic (PV) technology, environmental monitoring, and biotechnology. However, limitations in spectroradiometer instrumentation often restrict the availability of detailed spectral information. The proposed methodology specifically targets periods when the sun is unobscured by clouds, under which accurate retrievals and spectral extensions can be obtained irrespective of the cloudiness status of the rest of the sky. This approach leverages the SMARTS radiative transfer model to generate synthetic spectra under diverse atmospheric conditions and employs GAs to estimate key atmospheric parameters that align the simulated spectra with the observed measurements. Compared to traditional methods, the GA-based optimization significantly improves computational efficiency and estimation accuracy. Unlike conventional approaches that rely on selected narrow spectral ranges, this methodology utilizes full-spectrum (350–1050 nm) observations, enabling comprehensive spectral upscaling, improving spectroradiometer calibration, and offering a framework for benchmarking other algorithms. With median overall errors typically below 1–2 % in the validation range, it achieves a close match between optimized and actual spectra. The experimental validation of the method, based on more than 2000 observed spectra near Huelva, Spain demonstrates robust performance across varying local conditions, enabling the accurate determination of three key atmospheric quantities: aerosol optical depth, precipitable water, and the Ångström exponent. Application to real measurements further confirms the methodology’s potential in identifying calibration issues in spectroradiometers. This methodology offers a powerful tool for expanding spectral coverage in solar energy and related fields, with the added benefit of scalability to diverse geographic and atmospheric conditions. The developed approach facilitates accurate solar irradiance modeling and has promising implications for advancing PV efficiency assessments, agrivoltaics, and climate research.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114242"},"PeriodicalIF":6.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788338","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}
Perovskite solar cells (PvSCs) have emerged as leading next-generation photovoltaics, achieving certified power conversion efficiencies (PCE) of up to 27 % since their introduction. Among various device optimisation strategies for PvSCs, optical management remains pivotal in minimising front-surface reflection losses and enhancing photon harvesting. In this study, we underscore the critical importance of integrating wavelength-dependent optical losses into simulation frameworks for more realistic device performance predictions. A coupled opto-electrical modelling is performed to evaluate the impact of optical losses on key photovoltaic metrics, like short circuit current density (JSC), external quantum efficiency (EQE), interface-specific JSC losses resulting from reflection and optical field intensity distribution within the device. To bridge the gap between optical and electrical simulation, a modified AM1.5G spectrum accounting for reflection losses is incorporated into electrical simulation, an aspect often overlooked in many simulations. Instead of relying on the default AM1.5G spectrum, the modified one ensures an accurate representation of light propagation and optical losses within the device. Furthermore, to mitigate the reflection losses, magnesium fluoride (MgF2) is introduced as an anti-reflective coating (ARC) to improve light coupling. In optical modelling, the optimised device with the MgF2 ARC exhibits an improved JSC of 21.40 mAcm−2 compared to 19.76 mAcm−2 for the device without ARC. This research emphasises the necessity of incorporating realistic optical losses in simulations to enhance the credibility and accuracy of predicted device performance.
{"title":"Modeling optical losses in perovskite solar cells: A modified framework toward realistic performance projection","authors":"Satyabrata Guruprasad, Ashish Malik, Abhisek Saidarsan, Pilik Basumatary, Dhriti Sundar Ghosh","doi":"10.1016/j.solener.2025.114251","DOIUrl":"10.1016/j.solener.2025.114251","url":null,"abstract":"<div><div>Perovskite solar cells (PvSCs) have emerged as leading next-generation photovoltaics, achieving certified power conversion efficiencies (PCE) of up to 27 % since their introduction. Among various device optimisation strategies for PvSCs, optical management remains pivotal in minimising front-surface reflection losses and enhancing photon harvesting. In this study, we underscore the critical importance of integrating wavelength-dependent optical losses into simulation frameworks for more realistic device performance predictions. A coupled opto-electrical modelling is performed to evaluate the impact of optical losses on key photovoltaic metrics, like short circuit current density (J<sub>SC</sub>), external quantum efficiency (EQE), interface-specific J<sub>SC</sub> losses resulting from reflection and optical field intensity distribution within the device. To bridge the gap between optical and electrical simulation, a modified AM1.5G spectrum accounting for reflection losses is incorporated into electrical simulation, an aspect often overlooked in many simulations. Instead of relying on the default AM1.5G spectrum, the modified one ensures an accurate representation of light propagation and optical losses within the device. Furthermore, to mitigate the reflection losses, magnesium fluoride (MgF<sub>2</sub>) is introduced as an anti-reflective coating (ARC) to improve light coupling. In optical modelling, the optimised device with the MgF<sub>2</sub> ARC exhibits an improved J<sub>SC</sub> of 21.40 mAcm<sup>−2</sup> compared to 19.76 mAcm<sup>−2</sup> for the device without ARC. This research emphasises the necessity of incorporating realistic optical losses in simulations to enhance the credibility and accuracy of predicted device performance.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114251"},"PeriodicalIF":6.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788295","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}
Pub Date : 2025-12-17DOI: 10.1016/j.solener.2025.114236
Tongtong Zhao , Zhixiang Cao , Yi Wang , Songheng Wu , Peizeng Huang , Zhe Li , Liang Chen
Dust accumulation on photovoltaic (PV) modules is a critical factor limiting long-term power generation, especially in dusty environments such as deserts and industrial rooftops. Developing wind cleaning strategies is essential to improve the cost-effectiveness of PV deployment. This study introduces a method that enhances wind cleaning efficiency using flexible substrates. First, the optimal parameters for strip-assisted airflow dust removal were determined by evaluating the electrical performance recovery and surface cleanliness of the contaminated PV modules. Subsequently, a 21-day rooftop field experiment was conducted. Daily energy yield, power generation efficiency (), performance ratio (PR), and infrared thermal imaging were monitored to assess the power gains and thermal safety of modules equipped with strips. The results showed that flexible strips significantly enhanced wind cleaning performance, with the 50-um strip achieving the best results by restoring PV efficiency to 93.4 % of the clean baseline, compared with only 72.2 % for modules without strips. Under natural exposure with an average PM10 concentration of 118 μg/m3 and wind speeds corresponding to Beaufort scales 1–3, modules fitted with strips achieved a cumulative 1.9 % increase in energy yield during the field period, while consistently maintaining higher and PR values. Surface imaging confirmed effective dust removal, and infrared thermography showed a slight temperature increase (<1 °C) in the covered areas. This work demonstrates the feasibility and practical benefits of wind cleaning, underscoring its potential as a low-cost, energy-free strategy to sustain PV performance in dusty environments.
{"title":"Experimental and field study of flexible structure enhanced wind cleaning for photovoltaic modules","authors":"Tongtong Zhao , Zhixiang Cao , Yi Wang , Songheng Wu , Peizeng Huang , Zhe Li , Liang Chen","doi":"10.1016/j.solener.2025.114236","DOIUrl":"10.1016/j.solener.2025.114236","url":null,"abstract":"<div><div>Dust accumulation on photovoltaic (PV) modules is a critical factor limiting long-term power generation, especially in dusty environments such as deserts and industrial rooftops. Developing wind cleaning strategies is essential to improve the cost-effectiveness of PV deployment. This study introduces a method that enhances wind cleaning efficiency using flexible substrates. First, the optimal parameters for strip-assisted airflow dust removal were determined by evaluating the electrical performance recovery and surface cleanliness of the contaminated PV modules. Subsequently, a 21-day rooftop field experiment was conducted. Daily energy yield, power generation efficiency (<span><math><mi>η</mi></math></span>), performance ratio (PR), and infrared thermal imaging were monitored to assess the power gains and thermal safety of modules equipped with strips. The results showed that flexible strips significantly enhanced wind cleaning performance, with the 50-um strip achieving the best results by restoring PV efficiency to 93.4 % of the clean baseline, compared with only 72.2 % for modules without strips. Under natural exposure with an average PM10 concentration of 118 μg/m<sup>3</sup> and wind speeds corresponding to Beaufort scales 1–3, modules fitted with strips achieved a cumulative 1.9 % increase in energy yield during the field period, while consistently maintaining higher <span><math><mi>η</mi></math></span> and PR values. Surface imaging confirmed effective dust removal, and infrared thermography showed a slight temperature increase (<1 °C) in the covered areas. This work demonstrates the feasibility and practical benefits of wind cleaning, underscoring its potential as a low-cost, energy-free strategy to sustain PV performance in dusty environments.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114236"},"PeriodicalIF":6.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788401","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}
Pub Date : 2025-12-17DOI: 10.1016/j.solener.2025.114253
Bing Guo
Solar photovoltaic soiling loss is influenced by the angle of incidence of solar radiation. Quantifying this effect is critical for interpreting optical soiling sensor data and comparing soiling losses across different locations and time periods. Building on previous laboratory studies, this work presents outdoor experiments that measure both solar-tracking normal-incidence soiling loss and fixed-tilt soiling loss. The solar-tracking normal-incidence soiling loss results closely matched laboratory results. The previously developed Guo-Javed model accurately described the relationship between the normal-incidence soiling loss and the fixed-tilt soiling loss. It also reliably predicted irradiance-weighted daily soiling loss based on normal-incidence measurements. Furthermore, the model was used to isolate the angle of incidence effect and provide insight into seasonal variations in apparent dust potency. This study confirms the Guo-Javed model’s value in applications such as converting soiling sensor readings into daily PV soiling loss and establishes a practical, low-cost approach for measuring normal-incidence soiling loss using solar tracking.
{"title":"A study of PV soiling loss and angle of incidence in outdoor conditions","authors":"Bing Guo","doi":"10.1016/j.solener.2025.114253","DOIUrl":"10.1016/j.solener.2025.114253","url":null,"abstract":"<div><div>Solar photovoltaic soiling loss is influenced by the angle of incidence of solar radiation. Quantifying this effect is critical for interpreting optical soiling sensor data and comparing soiling losses across different locations and time periods. Building on previous laboratory studies, this work presents outdoor experiments that measure both solar-tracking normal-incidence soiling loss and fixed-tilt soiling loss. The solar-tracking normal-incidence soiling loss results closely matched laboratory results. The previously developed Guo-Javed model accurately described the relationship between the normal-incidence soiling loss and the fixed-tilt soiling loss. It also reliably predicted irradiance-weighted daily soiling loss based on normal-incidence measurements. Furthermore, the model was used to isolate the angle of incidence effect and provide insight into seasonal variations in apparent dust potency. This study confirms the Guo-Javed model’s value in applications such as converting soiling sensor readings into daily PV soiling loss and establishes a practical, low-cost approach for measuring normal-incidence soiling loss using solar tracking.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114253"},"PeriodicalIF":6.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788297","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}
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