Pub Date : 2026-01-12DOI: 10.1016/j.solener.2026.114327
Xinzhe Liu , Ting Chen , Tiezhi Wang , Jinliang Xu , Ying He , Guohua Liu
This study proposes the “marine seeding” concept and develops an interfacial evaporator based on it for efficient seawater desalination. polyvinyl alcohol and graphene oxide are uniformly coated on cotton fibers to harden them, and self-floating is achieved with the help of polystyrene foam. The porous interconnected structure of the PVA/GO/cotton composite can shorten the water molecule transport path and achieve rapid water transport to meet the water supply demand during the evaporation process. And the gradient heat distribution formed on the evaporator surface due to photothermal conversion will drive the natural convection of brine, accelerate the diffusion of salt ions into the bulk solution, and effectively avoid surface salt accumulation. The marine seeding evaporator can reach a seawater evaporation rate as high as 2.451 kg·m−2·h−1 and shows no salt crystallization during 6 days long-term test. Moreover, the reduction in the evaporation enthalpy of water in the evaporator and the changes in water state have been confirmed through dark evaporation tests, Differential Scanning Calorimetry, and Raman spectroscopy. And the freshwater collection device assembled with the evaporator has a daily freshwater collection of up to 10.18 L·m−2. This research paves the way for a more efficient and sustainable seawater desalination solution.
{"title":"Bionic marine seaweed evaporator for effective seawater desalination","authors":"Xinzhe Liu , Ting Chen , Tiezhi Wang , Jinliang Xu , Ying He , Guohua Liu","doi":"10.1016/j.solener.2026.114327","DOIUrl":"10.1016/j.solener.2026.114327","url":null,"abstract":"<div><div>This study proposes the “marine seeding” concept and develops an interfacial evaporator based on it for efficient seawater desalination. polyvinyl alcohol and graphene oxide are uniformly coated on cotton fibers to harden them, and self-floating is achieved with the help of polystyrene foam. The porous interconnected structure of the PVA/GO/cotton composite can shorten the water molecule transport path and achieve rapid water transport to meet the water supply demand during the evaporation process. And the gradient heat distribution formed on the evaporator surface due to photothermal conversion will drive the natural convection of brine, accelerate the diffusion of salt ions into the bulk solution, and effectively avoid surface salt accumulation. The marine seeding evaporator can reach a seawater evaporation rate as high as 2.451 kg·m<sup>−2</sup>·h<sup>−1</sup> and shows no salt crystallization during 6 days long-term test. Moreover, the reduction in the evaporation enthalpy of water in the evaporator and the changes in water state have been confirmed through dark evaporation tests, Differential Scanning Calorimetry, and Raman spectroscopy. And the freshwater collection device assembled with the evaporator has a daily freshwater collection of up to 10.18 L·m<sup>−2</sup>. This research paves the way for a more efficient and sustainable seawater desalination solution.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"307 ","pages":"Article 114327"},"PeriodicalIF":6.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950106","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 : 2026-01-12DOI: 10.1016/j.solener.2026.114313
Haifeng Wu , Xinling Li , Cunhai Wang , Xiaofei Chai , Junhui Lu , Qing Shen , Hongsheng Wang , Ruixiang Wang
Solution spray coating enables the low-cost, large-area fabrication of perovskite photovoltaic devices, but the deposited light-absorbing layer generally has technical problems, such as uneven distribution of perovskite crystals and low coverage rate, which seriously affect the photoelectric conversion efficiency (PCE) of the devices. This review aims to achieve controllable atomization for fabricating high-quality perovskite solar cells (PSCs). Focusing on the three aspects of solution, droplet, and film, discusses the basic principles of solution atomization, spraying deposition processes, and key devices, while summarizing the recent advances in sprayed PSCs as well as typical fabrication strategies, including one-step and two-step methods. Given the crucial role of perovskite nucleation and crystallization kinetics in governing the formation of high-quality films, this work comprehensively summarizes the crystallization technologies that promote rapid supersaturation of perovskite precursor solutions for nucleation and crystallization, along with the crystallization enhancement strategies that increase perovskite crystal size, improve the uniformity and coverage of films, and reduce defect density. Additionally, a systematic overview and outlook are provided on the latest technological innovations, emerging theoretical and physical models, and the integrated application of intelligent and automated control methods. Finally, the thermophysical issues in the spraying deposition process, the regulation of droplet behavior, the application of curved and flexible substrates, and the industrialization advantages of full-spray technology for photovoltaic devices are discussed. It is anticipated that this review will offer valuable guidance for advancing the low-cost, intelligent, and industrialized development of PSCs.
{"title":"Advances and outlook of perovskite solar cells via spray coating technologies","authors":"Haifeng Wu , Xinling Li , Cunhai Wang , Xiaofei Chai , Junhui Lu , Qing Shen , Hongsheng Wang , Ruixiang Wang","doi":"10.1016/j.solener.2026.114313","DOIUrl":"10.1016/j.solener.2026.114313","url":null,"abstract":"<div><div>Solution spray coating enables the low-cost, large-area fabrication of perovskite photovoltaic devices, but the deposited light-absorbing layer generally has technical problems, such as uneven distribution of perovskite crystals and low coverage rate, which seriously affect the photoelectric conversion efficiency (PCE) of the devices. This review aims to achieve controllable atomization for fabricating high-quality perovskite solar cells (PSCs). Focusing on the three aspects of solution, droplet, and film, discusses the basic principles of solution atomization, spraying deposition processes, and key devices, while summarizing the recent advances in sprayed PSCs as well as typical fabrication strategies, including one-step and two-step methods. Given the crucial role of perovskite nucleation and crystallization kinetics in governing the formation of high-quality films, this work comprehensively summarizes the crystallization technologies that promote rapid supersaturation of perovskite precursor solutions for nucleation and crystallization, along with the crystallization enhancement strategies that increase perovskite crystal size, improve the uniformity and coverage of films, and reduce defect density. Additionally, a systematic overview and outlook are provided on the latest technological innovations, emerging theoretical and physical models, and the integrated application of intelligent and automated control methods. Finally, the thermophysical issues in the spraying deposition process, the regulation of droplet behavior, the application of curved and flexible substrates, and the industrialization advantages of full-spray technology for photovoltaic devices are discussed. It is anticipated that this review will offer valuable guidance for advancing the low-cost, intelligent, and industrialized development of PSCs.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"307 ","pages":"Article 114313"},"PeriodicalIF":6.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950151","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 : 2026-01-12DOI: 10.1016/j.solener.2026.114316
Ngoc Khang Dinh , Doan Vu , Dang Le Tri Nguyen
Organic solar cells (OSCs) have emerged as a sustainable energy source, offering unique advantages over traditional counterparts. The morphology control in OSCs plays a vital role in determining device characteristics. Volatile solid additives (VSAs) have been recently introduced as alternatives to traditional solvent additives, play a crucial role in modulating active layer morphology, thereby enhancing photovoltaic performance and morphological stability. The utilization of VSAs can address challenges associated with high-boiling-point solvent additives, such as device stability and reproducibility concerns. This review provides a comprehensive summary of the state-of-the-art utilization and the underlying mechanisms of VSAs employed to optimize OSC morphology and performance to develop comprehensive classification systems for VSAs. This review categorizes VSAs based on their skeleton structure and the removal methods used in thin-film processing. The categorization based on structural skeletons provides important guidelines for molecular design and selection of new VSAs in OSCs. The review also discusses the current limitations encountered in employing VSAs in OSCs and outlines future perspectives for their integration.
{"title":"Classification, design, and selection strategies of volatile solid additives for organic solar cells","authors":"Ngoc Khang Dinh , Doan Vu , Dang Le Tri Nguyen","doi":"10.1016/j.solener.2026.114316","DOIUrl":"10.1016/j.solener.2026.114316","url":null,"abstract":"<div><div>Organic solar cells (OSCs) have emerged as a sustainable energy source, offering unique advantages over traditional counterparts. The morphology control in OSCs plays a vital role in determining device characteristics. Volatile solid additives (VSAs) have been recently introduced as alternatives to traditional solvent additives, play a crucial role in modulating active layer morphology, thereby enhancing photovoltaic performance and morphological stability. The utilization of VSAs can address challenges associated with high-boiling-point solvent additives, such as device stability and reproducibility concerns. This review provides a comprehensive summary of the state-of-the-art utilization and the underlying mechanisms of VSAs employed to optimize OSC morphology and performance to develop comprehensive classification systems for VSAs. This review categorizes VSAs based on their skeleton structure and the removal methods used in thin-film processing. The categorization based on structural skeletons provides important guidelines for molecular design and selection of new VSAs in OSCs. The review also discusses the current limitations encountered in employing VSAs in OSCs and outlines future perspectives for their integration.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"307 ","pages":"Article 114316"},"PeriodicalIF":6.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950152","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 : 2026-01-12DOI: 10.1016/j.solener.2026.114324
Weijian Zhang , Ye Wang , Yun Liu , Bingyuan Feng , Zhuang Zhao , Zhenggang Ba
In solar air heater systems, a strong coupling exists between flow and temperature fields, where even minor adjustments to flow boundary conditions or structural parameters can markedly affect overall heat transfer efficiency. This study introduces a novel multi-inlet cylindrical double-pass solar air heater, analyzed using computational fluid dynamics to explore its internal flow and heat transfer behavior. Results demonstrate that the multi-inlet configuration significantly improves flow field uniformity, while the central hole structure enhances inter-pass heat exchange. A systematic investigation was conducted on the effects of inlet aspect ratio, central hole area, and central hole shape under various flow conditions. Response surface methodology was applied to capture parameter interactions and identify optimal conditions. The best performance was achieved at a Reynolds number of 13,698, an inlet aspect ratio of 9.145, and an equilateral triangular central hole with a side length of 136.6 mm. Under these conditions, the solar air heater attained thermal and thermo-hydraulic efficiencies of 92.1% and 85.2%, respectively, surpassing reported designs. The findings provide valuable guidance for developing high-efficiency solar air heaters and hold ecological significance in promoting solar energy utilization, reducing dependence on fossil fuels, and advancing environmental sustainability.
{"title":"Optimization of a multi-inlet cylindrical double-pass solar air heater","authors":"Weijian Zhang , Ye Wang , Yun Liu , Bingyuan Feng , Zhuang Zhao , Zhenggang Ba","doi":"10.1016/j.solener.2026.114324","DOIUrl":"10.1016/j.solener.2026.114324","url":null,"abstract":"<div><div>In solar air heater systems, a strong coupling exists between flow and temperature fields, where even minor adjustments to flow boundary conditions or structural parameters can markedly affect overall heat transfer efficiency. This study introduces a novel multi-inlet cylindrical double-pass solar air heater, analyzed using computational fluid dynamics to explore its internal flow and heat transfer behavior. Results demonstrate that the multi-inlet configuration significantly improves flow field uniformity, while the central hole structure enhances inter-pass heat exchange. A systematic investigation was conducted on the effects of inlet aspect ratio, central hole area, and central hole shape under various flow conditions. Response surface methodology was applied to capture parameter interactions and identify optimal conditions. The best performance was achieved at a Reynolds number of 13,698, an inlet aspect ratio of 9.145, and an equilateral triangular central hole with a side length of 136.6 mm. Under these conditions, the solar air heater attained thermal and thermo-hydraulic efficiencies of 92.1% and 85.2%, respectively, surpassing reported designs. The findings provide valuable guidance for developing high-efficiency solar air heaters and hold ecological significance in promoting solar energy utilization, reducing dependence on fossil fuels, and advancing environmental sustainability.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114324"},"PeriodicalIF":6.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973525","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 : 2026-01-10DOI: 10.1016/j.solener.2025.114295
Ismael Medina , Ana M. Martínez , Ewan Dunlop
The definition of climatic zones for photovoltaics (PV) is critical for improving resource simulation, energy forecasting, and performance evaluation. Existing classifications provide valuable frameworks, but suffer from limitations in integrating relevant PV parameters into the classification pipeline and remaining technology-agnostic. This paper addresses these shortcomings by introducing a classification tailored to key PV performance metrics: the PV array energy yield () and module performance ratio (), using the annual irradiation () and a novel irradiation-weighted module temperature () as core climatic parameters. These parameters ensure a technology-independent yet performance-relevant classification for the two most widely used parameters in the PV community. The classification is backed by high-resolution climatic data () and recent advancements in PV simulations and data science. Additionally, we explore a distribution-based approach to account for the increasing importance of variability in PV generation. Applying the theory of optimal transport to the distribution of daily irradiation, we devise a novel classification concept that groups locations with similar daily generation characteristics. This method is better suited for applications where the variability of the generation, rather than annual averages, is the main feature of interest, such as firm power generation. We apply our framework to a global and pan-European classification to illustrate the effectiveness of our methodology.
{"title":"Parametric and distribution-based definition of climatic zones for photovoltaics","authors":"Ismael Medina , Ana M. Martínez , Ewan Dunlop","doi":"10.1016/j.solener.2025.114295","DOIUrl":"10.1016/j.solener.2025.114295","url":null,"abstract":"<div><div>The definition of climatic zones for photovoltaics (PV) is critical for improving resource simulation, energy forecasting, and performance evaluation. Existing classifications provide valuable frameworks, but suffer from limitations in integrating relevant PV parameters into the classification pipeline and remaining technology-agnostic. This paper addresses these shortcomings by introducing a classification tailored to key PV performance metrics: the PV array energy yield (<span><math><msub><mi>Y</mi><mi>A</mi></msub></math></span>) and module performance ratio (<span><math><mrow><mtext>MPR</mtext></mrow></math></span>), using the annual irradiation (<span><math><msub><mi>H</mi><mrow><mi>y</mi><mi>e</mi><mi>a</mi><mi>r</mi></mrow></msub></math></span>) and a novel irradiation-weighted module temperature (<span><math><msub><mi>T</mi><mi>w</mi></msub></math></span>) as core climatic parameters. These parameters ensure a technology-independent yet performance-relevant classification for the two most widely used parameters in the PV community. The classification is backed by high-resolution climatic data (<span><math><msup><mn>0.1</mn><mo>∘</mo></msup><mrow></mrow><mo>×</mo><mspace></mspace><msup><mn>0.1</mn><mo>∘</mo></msup><mrow></mrow></math></span>) and recent advancements in PV simulations and data science. Additionally, we explore a distribution-based approach to account for the increasing importance of variability in PV generation. Applying the theory of optimal transport to the distribution of daily irradiation, we devise a novel classification concept that groups locations with similar daily generation characteristics. This method is better suited for applications where the variability of the generation, rather than annual averages, is the main feature of interest, such as firm power generation. We apply our framework to a global and pan-European classification to illustrate the effectiveness of our methodology.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114295"},"PeriodicalIF":6.0,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973395","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 : 2026-01-09DOI: 10.1016/j.solener.2026.114320
Chuntian Xu , Hao Zheng , Xu Zong , Hancheng Liu , Xiangtai Jia , Qian Zhao , Linlin Wang
The efficiency of photovoltaic(PV) panels is currently the main focus of attention in the field of solar energy. However, PV trackers may produce shading when tracking the sun between adjacent PV panels, which affects their efficiency. Improving the tracking accuracy of PV modules becomes a key technology to solve such challenges. Regrading the dual-axis solar tracker, which accounts for energy losses due to both solar incidence angle deviations and shading coverage, an improved backtracking algorithm (IBA) is proposed in this paper. And to improve computational efficiency while maintaining calculation accuracy, the calculation process of IBA is optimized based on particle swarm optimization (PSO) algorithm. The calculation results show that the output power of the PV panel controlled by the IBA can be significantly enhanced compared with the traditional backtracking algorithm. Meanwhile, the effectiveness of the IBA algorithm is verified by experiments. Therefore, under the condition that the efficiency of single-crystal silicon PV cells is fixed, it has a significant value through continuously improving the algorithm accuracy of tracking and enhancing the conversion efficiency of PV panels.
{"title":"Improved solar backtracking algorithm based on particle swarm optimization for photovoltaic modules' output power","authors":"Chuntian Xu , Hao Zheng , Xu Zong , Hancheng Liu , Xiangtai Jia , Qian Zhao , Linlin Wang","doi":"10.1016/j.solener.2026.114320","DOIUrl":"10.1016/j.solener.2026.114320","url":null,"abstract":"<div><div>The efficiency of photovoltaic(PV) panels is currently the main focus of attention in the field of solar energy. However, PV trackers may produce shading when tracking the sun between adjacent PV panels, which affects their efficiency. Improving the tracking accuracy of PV modules becomes a key technology to solve such challenges. Regrading the dual-axis solar tracker, which accounts for energy losses due to both solar incidence angle deviations and shading coverage, an improved backtracking algorithm (IBA) is proposed in this paper. And to improve computational efficiency while maintaining calculation accuracy, the calculation process of IBA is optimized based on particle swarm optimization (PSO) algorithm. The calculation results show that the output power of the PV panel controlled by the IBA can be significantly enhanced compared with the traditional backtracking algorithm. Meanwhile, the effectiveness of the IBA algorithm is verified by experiments. Therefore, under the condition that the efficiency of single-crystal silicon PV cells is fixed, it has a significant value through continuously improving the algorithm accuracy of tracking and enhancing the conversion efficiency of PV panels.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114320"},"PeriodicalIF":6.0,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922855","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 : 2026-01-07DOI: 10.1016/j.solener.2025.114310
Fanqian Liu , Qingping Zhou , Lu Chen , Jiangyan Zhao , Zhiyuan Leng
Short-term dispatch of photovoltaic (PV)-hydro hybrid systems (PHHSs) typically formulates the PV prediction intervals and determines generation and reserve dispatch plans in sequence. In this paradigm, the prediction intervals focus on statistical quality but fail to account for the operational costs and risks they impose on the dispatch process. This poses challenges to the safe and stable operation of hydropower units. The study introduces a closed-loop forecast and decision framework for the risk-averse dispatch of the PHHS. First, a dynamic interval forecasting model is designed to formulate the prediction intervals with time-varying quantile proportions. Second, a risk-averse dispatching model is established to minimize the adverse operating conditions and water consumption of hydropower units. Prediction intervals are integrated as chance constraints into the dispatching model and dispatch outcomes are fed back to update the time-varying quantile proportions. Then, a joint solution method combining orthogonal experimental design and two‐dimensional dynamic programming is proposed to effectively solve the co-optimization problem. A PHHS in the Yalong River basin, China, is employed as a case study. Compared with the forecast-then-decision approach, the proposed approach achieves a 2.38 % average reduction in water consumption and a 22.63% reduction in the frequency of adverse operating conditions of hydropower units, improving the economic performance and operational stability of the hydropower plant. Moreover, the effectiveness of the proposed approach is more pronounced under high PV output and low inflow conditions.
{"title":"Risk-averse energy management of photovoltaic-hydro hybrid systems based on closed-loop forecasting and decision approach","authors":"Fanqian Liu , Qingping Zhou , Lu Chen , Jiangyan Zhao , Zhiyuan Leng","doi":"10.1016/j.solener.2025.114310","DOIUrl":"10.1016/j.solener.2025.114310","url":null,"abstract":"<div><div>Short-term dispatch of photovoltaic (PV)-hydro hybrid systems (PHHSs) typically formulates the PV prediction intervals and determines generation and reserve dispatch plans in sequence. In this paradigm, the prediction intervals focus on statistical quality but fail to account for the operational costs and risks they impose on the dispatch process. This poses challenges to the safe and stable operation of hydropower units. The study introduces a closed-loop forecast and decision framework for the risk-averse dispatch of the PHHS. First, a dynamic interval forecasting model is designed to formulate the prediction intervals with time-varying quantile proportions. Second, a risk-averse dispatching model is established to minimize the adverse operating conditions and water consumption of hydropower units. Prediction intervals are integrated as chance constraints into the dispatching model and dispatch outcomes are fed back to update the time-varying quantile proportions. Then, a joint solution method combining orthogonal experimental design and two‐dimensional dynamic programming is proposed to effectively solve the co-optimization problem. A PHHS in the Yalong River basin, China, is employed as a case study. Compared with the forecast-then-decision approach, the proposed approach achieves a 2.38 % average reduction in water consumption and a 22.63% reduction in the frequency of adverse operating conditions of hydropower units, improving the economic performance and operational stability of the hydropower plant. Moreover, the effectiveness of the proposed approach is more pronounced under high PV output and low inflow conditions.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114310"},"PeriodicalIF":6.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922856","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 : 2026-01-07DOI: 10.1016/j.solener.2025.114311
Xujiang Liu , Guangyu Zhu , Zhigang Li , Dongjing Li
This study proposes a comprehensive evaluation framework to objectively assess the performance of generative adversarial networks (GANs) for generating photovoltaic infrared defect images under small-sample conditions. Focusing on realism and diversity, the framework integrates quantitative metrics with semantic-level evaluation. A weighting system is constructed by combining the Entropy Weight Method (EWM) and the Analytic Hierarchy Process (AHP), enabling systematic calculation of comprehensive scores. Five GAN models, namely DCGAN, LSGAN, WGAN, WGAN-GP, and R3GAN-LS, were evaluated, and their generated images were used to augment the datasets for two defect categories (“Hot-Spot-Multi” and “Soiling”). Classification experiments were subsequently conducted by combining these augmented datasets with images from the “No_Anomaly” category. Results indicate that LSGAN achieves the highest comprehensive score of 0.537 and a classification accuracy of 89.61% for the Hot-Spot-Multi task, whereas WGAN-GP performs best for Soiling, with a comprehensive score of 0.655 and an accuracy of 93.62%. To further validate the framework’s generalizability, additional defect types (“Diode-Multi” and “Cell-Multi”) were respectively assigned to the established “Hot-Spot-Multi” and “Soiling” weighting schemes based on their visual characteristics. Different GAN models were then used to generate “Diode-Multi” and “Cell-Multi” defect images, which were used to augment the corresponding datasets in the subsequent classification experiments. Results show strong consistency between comprehensive evaluation scores and actual test accuracies, confirming the robustness and reliability of the proposed framework. These findings highlight the practical applicability of the framework for guiding GAN-based data augmentation in photovoltaic defect classification.
{"title":"A comprehensive evaluation framework using generative adversarial networks for infrared defect images in photovoltaic modules","authors":"Xujiang Liu , Guangyu Zhu , Zhigang Li , Dongjing Li","doi":"10.1016/j.solener.2025.114311","DOIUrl":"10.1016/j.solener.2025.114311","url":null,"abstract":"<div><div>This study proposes a comprehensive evaluation framework to objectively assess the performance of generative adversarial networks (GANs) for generating photovoltaic infrared defect images under small-sample conditions. Focusing on realism and diversity, the framework integrates quantitative metrics with semantic-level evaluation. A weighting system is constructed by combining the Entropy Weight Method (EWM) and the Analytic Hierarchy Process (AHP), enabling systematic calculation of comprehensive scores. Five GAN models, namely DCGAN, LSGAN, WGAN, WGAN-GP, and R3GAN-LS, were evaluated, and their generated images were used to augment the datasets for two defect categories (“Hot-Spot-Multi” and “Soiling”). Classification experiments were subsequently conducted by combining these augmented datasets with images from the “No_Anomaly” category. Results indicate that LSGAN achieves the highest comprehensive score of 0.537 and a classification accuracy of 89.61% for the Hot-Spot-Multi task, whereas WGAN-GP performs best for Soiling, with a comprehensive score of 0.655 and an accuracy of 93.62%. To further validate the framework’s generalizability, additional defect types (“Diode-Multi” and “Cell-Multi”) were respectively assigned to the established “Hot-Spot-Multi” and “Soiling” weighting schemes based on their visual characteristics. Different GAN models were then used to generate “Diode-Multi” and “Cell-Multi” defect images, which were used to augment the corresponding datasets in the subsequent classification experiments. Results show strong consistency between comprehensive evaluation scores and actual test accuracies, confirming the robustness and reliability of the proposed framework. These findings highlight the practical applicability of the framework for guiding GAN-based data augmentation in photovoltaic defect classification.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114311"},"PeriodicalIF":6.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922854","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 : 2026-01-07DOI: 10.1016/j.solener.2026.114315
Felipe Moraes do Nascimento, Julio Cezar Mairesse Siluk, Paula Donaduzzi Rigo, Graciele Rediske, Flávia Ferrari dos Santos
The growing adoption of sustainable technologies is steadily increasing, creating uncertainty for Distribution System Operators (DSOs), which are responsible for delivering energy to end consumers. Although DSOs collect large amounts of data, these datasets are underexplored in addressing the adoption of photovoltaic (PV) systems. In this context, this study proposes a multi-criteria decision-making model to classify electricity consumers based on their potential for adopting photovoltaic distributed generation (PV DG), using data already available in distribution utility databases and integrating multi-criteria decision-making techniques. The proposed methodology is structured into four phases: (i) identification and weighting ten key performance indicators (KPIs) using the Best-Worst Method (BWM); (ii) identification of 19 relevant attributes within DSO databases capable of measuring the KPIs, through a systematic literature review (SLR); (iii) determination of the most appropriate attributes for measuring KPIs using the DEMATEL method; and (iv) calculation of an adoption potential index via the TOPSIS method. The model was applied using real data from the distributor ELETROCAR (Brazil), comprising 30,858 consumer units (CUs). The results demonstrate that the integrated multi-criteria model offers a robust, data-driven approach to identifying consumers with high potential for PV DG adoption, thereby supporting DSOs in strategic planning and decision-making.
{"title":"A data-driven multi-criteria model for anticipating consumer adoption of distributed photovoltaics","authors":"Felipe Moraes do Nascimento, Julio Cezar Mairesse Siluk, Paula Donaduzzi Rigo, Graciele Rediske, Flávia Ferrari dos Santos","doi":"10.1016/j.solener.2026.114315","DOIUrl":"10.1016/j.solener.2026.114315","url":null,"abstract":"<div><div>The growing adoption of sustainable technologies is steadily increasing, creating uncertainty for Distribution System Operators (DSOs), which are responsible for delivering energy to end consumers. Although DSOs collect large amounts of data, these datasets are underexplored in addressing the adoption of photovoltaic (PV) systems. In this context, this study proposes a multi-criteria decision-making model to classify electricity consumers based on their potential for adopting photovoltaic distributed generation (PV DG), using data already available in distribution utility databases and integrating multi-criteria decision-making techniques. The proposed methodology is structured into four phases: (i) identification and weighting ten key performance indicators (KPIs) using the Best-Worst Method (BWM); (ii) identification of 19 relevant attributes within DSO databases capable of measuring the KPIs, through a systematic literature review (SLR); (iii) determination of the most appropriate attributes for measuring KPIs using the DEMATEL method; and (iv) calculation of an adoption potential index via the TOPSIS method. The model was applied using real data from the distributor ELETROCAR (Brazil), comprising 30,858 consumer units (CUs). The results demonstrate that the integrated multi-criteria model offers a robust, data-driven approach to identifying consumers with high potential for PV DG adoption, thereby supporting DSOs in strategic planning and decision-making.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114315"},"PeriodicalIF":6.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922852","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 : 2026-01-07DOI: 10.1016/j.solener.2025.114312
Hongwei Qu , Yi Shi , Tianming Xu , Zhiming Xu
Previous studies indicate photovoltaic (PV) module efficiency decreases with rising operating temperature. Inspired by tree leaf vein nutrient transport, this paper proposes a novel PV-F-PCM system featuring a bionic dendritic fractal fin structure and studies its thermal management. Comparative experiments under 600–1000 W/m2 irradiance show the PV-F-PCM system reduces panel temperature by 3.6–4.5 °C, increases average maximum power by 7.9 %-9.4 %, and exhibits higher cooling efficiency with increased irradiance. A significant negative correlation exists between system tilt angle and panel temperature. When the tilt angle of the system is reduced from 60° to 30°, the average temperature of the front panel decreases by 3.95 °C, and the efficiency factor increases by 0.62 %. At 1000 W/m2 and an optimized 30° tilt, the PV-F-PCM system’s front plate temperature is reduced by 45.35 °C and 12.61 °C compared to PV-PCM and conventional PV systems, respectively. Peak power increased by 29.09 % and 13.07 %, while average power rose by 18.76 % and 9.43 %, respectively. The bionic fin structure significantly enhances PCM heat transfer, improving overall thermal management. The optimal condition is Crosswise fin arrangement at 1000 W/m2 and 30°. This study provides a theoretical basis for developing high-efficiency PV cooling technologies.
{"title":"Plant leaf vein bionic fin based experimental study on cooling performance of PV-F-PCM system","authors":"Hongwei Qu , Yi Shi , Tianming Xu , Zhiming Xu","doi":"10.1016/j.solener.2025.114312","DOIUrl":"10.1016/j.solener.2025.114312","url":null,"abstract":"<div><div>Previous studies indicate photovoltaic (PV) module efficiency decreases with rising operating temperature. Inspired by tree leaf vein nutrient transport, this paper proposes a novel PV-F-PCM system featuring a bionic dendritic fractal fin structure and studies its thermal management. Comparative experiments under 600–1000 W/m<sup>2</sup> irradiance show the PV-F-PCM system reduces panel temperature by 3.6–4.5 °C, increases average maximum power by 7.9 %-9.4 %, and exhibits higher cooling efficiency with increased irradiance. A significant negative correlation exists between system tilt angle and panel temperature. When the tilt angle of the system is reduced from 60° to 30°, the average temperature of the front panel decreases by 3.95 °C, and the efficiency factor increases by 0.62 %. At 1000 W/m<sup>2</sup> and an optimized 30° tilt, the PV-F-PCM system’s front plate temperature is reduced by 45.35 °C and 12.61 °C compared to PV-PCM and conventional PV systems, respectively. Peak power increased by 29.09 % and 13.07 %, while average power rose by 18.76 % and 9.43 %, respectively. The bionic fin structure significantly enhances PCM heat transfer, improving overall thermal management. The optimal condition is Crosswise fin arrangement at 1000 W/m<sup>2</sup> and 30°. This study provides a theoretical basis for developing high-efficiency PV cooling technologies.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"306 ","pages":"Article 114312"},"PeriodicalIF":6.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922932","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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