Solar Energy最新文献

{"title":"Cooling with colour: Passive-Coloured Radiative Coolers for energy-efficient temperature regulation in adverse climatic conditions","authors":"Ioannis Kousis ,&nbsp;Hassan Saeed Khan ,&nbsp;Riccardo Paolini ,&nbsp;James Edric Alan Webb ,&nbsp;Jan Valenta ,&nbsp;Mat Santamouris","doi":"10.1016/j.solener.2025.113343","DOIUrl":"10.1016/j.solener.2025.113343","url":null,"abstract":"<div><div>Passive Daytime Radiative Cooling (PDRC) is a high-performance strategy to mitigate urban overheating by combining high solar reflectance and strong thermal emission, particularly within the Atmospheric Window wavelength range. However, several intrinsic challenges, such as glare, aesthetics, and winter overcooling, limit its widespread application. This study reports on the development and cooling performance of Passive Coloured Radiative Coolers (PCRCs) with a threefold heat-rejection mechanism: moderately high solar reflectance, high infrared emissivity, and sunlight-excited fluorescence. The objective was to create PCRCs with reduced reflectivity to diminish glare and aesthetic concerns, while the incorporation of fluorescence offsets the cooling decrease caused by lower reflectance. The development of PCRCs sought consistent performance throughout the year, reducing the winter heating penalty. Seven PCRCs–Green, Red, Orange, Reddish-orange, and Purple–were developed and tested in two climate zones with unfavourable conditions for radiative cooling: Sydney and Alice Springs, Australia, characterised by high humidity and dust concentrations, respectively. The developed PCRCs consistently maintained lower surface temperatures than their coloured non-fluorescent counterparts and the highly reflective white references. All PCRCs–except purple–outperformed the white reference, maintaining surface temperatures up to 5.4 °C lower in Sydney and 4.0 °C lower in Alice Springs. These findings highlight the potential of PCRCs to reduce urban surface temperatures and cooling energy demand and underline their role in advancing sustainable urban design. By addressing PDRCs’ limitations, PCRCs could facilitate the adoption of radiative cooling technologies in urban environments, supporting energy policy objectives and promoting resilient urban planning strategies aimed at combating climate change and urban overheating.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113343"},"PeriodicalIF":6.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487721","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}

{"title":"Electrodeposition of Sb2Se3 solar cells on ceramic tiles","authors":"Samuel Porcar ,&nbsp;Abderrahim Lahlahi ,&nbsp;Jaime González Cuadra ,&nbsp;Santiago Toca ,&nbsp;Pablo Serna-Gallén ,&nbsp;Diego Fraga ,&nbsp;Tariq Jawhari ,&nbsp;Xavier Alcobe ,&nbsp;Lorenzo Calvo Barrio ,&nbsp;Pedro Vidal-Fuentes ,&nbsp;Alejandro Pérez-Rodríguez ,&nbsp;Juan Bautista Carda","doi":"10.1016/j.solener.2025.113377","DOIUrl":"10.1016/j.solener.2025.113377","url":null,"abstract":"<div><div>This work presents the first reported synthesis of Sb₂Se₃ solar cells deposited on ceramic substrates. A novel low-temperature two-step electroplating method was introduced for fabricating high-quality Sb₂Se₃ thin films, aimed at creating efficient and reproducible solar cells. The films were deposited on Mo-coated ceramic substrates, as well as on glass substrates, addressing challenges such as high surface roughness and potential short-circuiting in ceramics. Detailed characterization of the films included X-ray diffraction (XRD), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The performance of the solar cells was evaluated through I-V curve analysis, demonstrating that ceramic substrates are a viable alternative to glass substrates. These results represent a significant advancement in integrating Sb₂Se₃ solar cells into building materials, enhancing the potential of building-integrated photovoltaics (BIPV) technology.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113377"},"PeriodicalIF":6.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487718","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}

{"title":"Estimation of non-uniform soiling loss in a utility-scale PV plant in India and strategies for enhanced performance through optimal cleaning schedules","authors":"Shoubhik De,&nbsp;Narendra Shiradkar,&nbsp;Anil Kottantharayil","doi":"10.1016/j.solener.2025.113345","DOIUrl":"10.1016/j.solener.2025.113345","url":null,"abstract":"<div><div>Soiling significantly impacts the efficiency of photovoltaic (PV) systems, especially in regions with heavy dust deposition like India. The issue is exacerbated by spatially non-uniform soiling in utility-scale PV plants, where certain areas of the plant experience higher losses than others, complicating maintenance efforts. In this study, we analysed string-level SCADA data from a 50 M<span><math><msub><mrow><mi>W</mi></mrow><mrow><mi>p</mi></mrow></msub></math></span> utility-scale PV plant in South India divided into several zones to create detailed soiling maps. Using these maps, we developed both string-optimized and zone-optimized cleaning methodologies. The string-optimized approach utilized four specific cleaning thresholds to help determine the most profitable cleaning areas in each zone, while the zone-optimized approach aimed to streamline cleaning processes, enhance PV plant performance, and resource efficiency. Additionally, unlike previous studies, this analysis accounted for DC cabling losses, further refining the evaluation of soiling impact. The results in-terms of cleaning profit generated were compared with the same made by actual logged cleaning.</div><div>Additionally, we performed a sensitivity analysis by varying solar PV electricity tariffs and cleaning costs to evaluate the economic viability of different cleaning strategies. The analysis indicated that the 85% cleaning threshold is the most economical, particularly as PV electricity prices continue to decline. Our findings suggest that structured cleaning schedules based on soiling data can significantly improve PV plant performance and profitability. This approach can be replicated in similar PV plants to support India’s growing PV sector, ultimately helping the country become a global leader in solar energy.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113345"},"PeriodicalIF":6.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478636","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}

{"title":"Data-driven models of a solar field used to power membrane distillation systems: A comparison study","authors":"A. Bueso ,&nbsp;J.D. Gil ,&nbsp;G. Zaragoza","doi":"10.1016/j.solener.2025.113349","DOIUrl":"10.1016/j.solener.2025.113349","url":null,"abstract":"<div><div>The pressing issue of water scarcity has led to increased research focussing on enhancing access to fresh water, with sustainable desalination emerging as a prominent solution. The use of solar energy is often proposed because of the geographical coincidence of high solar irradiance and water scarcity. However, the variability of the energy source in a stationary-designed process such as desalination must be addressed, and modelling solar desalination systems is crucial to understanding the dynamics and optimising the performance. Solar thermal energy is cheaper to store than photovoltaic energy, and powers advanced desalination technologies such as membrane distillation (MD) that can reach higher water recovery. This study investigates the application of data-driven modelling techniques to an innovative solar collector field providing heat for a MD system. The novelty of using mirrors in the solar field to boost the thermal power yielded renders the classical first-principles-based models presented in the literature invalid, as they cannot account for the nonlinear impact of mirrors in the solar field performance. This justifies the use of new data-driven techniques, and four modelling methodologies are compared, with the NARX artificial neural network that proves the most effective, with an R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span> value of 0.9741 and an RMSE value of 6.3151. The best model is validated by simulation of a solar MD plant.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113349"},"PeriodicalIF":6.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487719","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}

{"title":"Interpretable machine learning insights of power conversion efficiency for hybrid perovskites solar cells","authors":"Yudong Shi ,&nbsp;Jiansen Wen ,&nbsp;Cuilian Wen ,&nbsp;Linqin Jiang ,&nbsp;Bo Wu ,&nbsp;Yu Qiu ,&nbsp;Baisheng Sa","doi":"10.1016/j.solener.2025.113373","DOIUrl":"10.1016/j.solener.2025.113373","url":null,"abstract":"<div><div>Hybrid organic–inorganic perovskites (HOIPs) solar cells have presented broad application prospects in the photovoltaic field due to their high energy conversion efficiency, ease of preparation, and low production costs. With the flourishing development of artificial intelligence, machine learning (ML) has been recently used for novel HOIP designs. However, the practical application of ML models for the designing of HOIPs is hampered mainly due to the lack of interpretability. Herein, a data-driven interpretable ML approach is introduced to distill the universal simple descriptors for the power conversion efficiency (PCE) of HOIPs-based solar cells. It is highlighted that two descriptors consist of easily obtained parameters are proposed to accurately predict PCE, which are superior to the commonly used descriptor band gap (<em>E</em>_g). Remarkably, universal criterions for the high-throughput screening of HOIPs are proposed to accelerate the screening of HOIPs-based solar cells with high PCE performance. This work paves the way toward rapid and precise screening of efficient HOIPs-based solar cells using a data-driven interpretable ML approach.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113373"},"PeriodicalIF":6.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478635","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}

{"title":"Laboratory experimental analysis of crystalline silicon photovoltaic module degradation after operating over 6 years: A case study in Ghana","authors":"Qingfa MENG ,&nbsp;Honglie SHEN ,&nbsp;Jinjie ZHENG ,&nbsp;Xuemei LI","doi":"10.1016/j.solener.2025.113379","DOIUrl":"10.1016/j.solener.2025.113379","url":null,"abstract":"<div><div>This paper systematically analyzes and evaluates the performance of photovoltaic (PV) modules after six years of outdoor exposure in Winneba, Ghana, under a hot and humid climate. Unlike conventional field tests, all data were obtained through rigorous laboratory testing conducted on the PV modules and their materials in accordance with IEC 61215 standards to investigate the causes of power degradation. The results indicated an average power degradation of 35.36 %, equivalent to an annual degradation rate of 5.89 %. Although most modules met the wet insulation test criteria specified by IEC 61215, they exhibited potential safety risks for future field operations due to wet insulation values approaching the standard threshold of 24.5 MΩ. The primary cause of power degradation was identified as potential-induced degradation (PID), with modules experiencing power losses of 44.60 % and 99.57 % under PID testing with a 1000 V negative voltage stress. Electroluminescence (EL) images showing dark edges provided strong evidence supporting the presence of PID. Additionally, poor peel strength test results suggested a risk of delamination, which could be attributed to ion migration during the PID process. Four out of five tested module gel contents were comparable to those of typical unexposed ethylene–vinyl acetate (EVA), and two modules still met the standard requirements even after exposure to damp heat (DH1000), indicating that EVA degradation may not be the primary cause of power loss. The water vapor transmittance rate (WVTR) of the module backsheets, after six years of outdoor exposure, continued to meet the requirements of the Chinese National Standard, further suggesting that moisture ingress may not be a significant contributor to power degradation. This study represents a valuable effort to assess the long-term performance of field-exposed PV modules using accelerated aging tests conducted according to IEC 61215 standards.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113379"},"PeriodicalIF":6.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478637","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}

{"title":"Solar irradiance separation with deep learning: An interpretable multi-task and physically constrained model based on individual–interactive features","authors":"Mengmeng Song ,&nbsp;Dazhi Yang ,&nbsp;Bai Liu ,&nbsp;Disong Fu ,&nbsp;Hongrong Shi ,&nbsp;Xiang’ao Xia ,&nbsp;Martin János Mayer","doi":"10.1016/j.solener.2025.113353","DOIUrl":"10.1016/j.solener.2025.113353","url":null,"abstract":"<div><div>As an essential part of solar forecasting and resource assessment, separation modeling has received widespread attention over the past half a century. Despite the numerous proposals thus far, most models are semi-empirical in nature, with limited accuracy. The other option, namely, machine-learning models, does not show a definitive advantage and usually lacks comparisons with the latest quasi-universal model. This study proposes an interpretable multi-task and physically constrained separation model based on individual–interactive features (IIF-IMCSM). The model has three blocks: (1) an informative predictor identification block, (2) an individual–interactive feature extraction block, and (3) a physically constrained irradiance component estimation block, each carrying some modeling innovations. Differing from other separation models, IIF-IMCSM simultaneously produces estimates for both the beam and diffuse components that satisfy the closure equation, and it overcomes the common drawback of lacking interpretability of machine-learning models. Based on five comprehensive datasets covering diverse radiation regimes of the globe, it is found that the overall normalized root mean square errors of IIF-IMCSM for beam normal irradiance and diffuse horizontal irradiance are 12.51% and 24.50%, as compared to 16.32%, 34.86%, and 13.47%, 26.56% for the top-performing semi-empirical and machine-learning models.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113353"},"PeriodicalIF":6.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474071","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}

{"title":"A satellite-based novel method to forecast short-term (10 min − 4 h) solar radiation by combining satellite-based cloud transmittance forecast and physical clear-sky radiation model","authors":"Bing Hu ,&nbsp;Huaiyong Shao ,&nbsp;Changkun Shao ,&nbsp;Wenjun Tang","doi":"10.1016/j.solener.2025.113376","DOIUrl":"10.1016/j.solener.2025.113376","url":null,"abstract":"<div><div>Short-term forecasting of solar radiation is crucial for grid integration of solar photovoltaic (PV) power and for grid scheduling and optimization. Enhancing the interpretability of satellite-based short-term forecasts that rely on artificial intelligence is a research focus. In this study, we presented a novel approach to forecast short-term solar radiation by combining satellite-based cloud transmittance forecast and physical clear-sky radiation forecast. The innovation of this study lies in its foundation on atmospheric physics principles, specifically forecasting cloud transmittance and distinguishing between cloudy and clear skies. The cloud transmittance prediction was conducted based on Himawari-8 observations using widely adopted and well-known convolutional neural network (CNN) and long short-term memory (LSTM) networks, while the clear-sky radiation forecast can be conducted with clear-sky radiation model or prediction based on numerical weather prediction (NWP). Compared to other satellite-based baseline forecasting frameworks, the accuracy of our developed framework for short-term forecasting of solar radiation is improved, with an average root mean square error of about 62 W/m² over 116 sites and an average relative root mean square error of about 14.36 % with a forecast horizon of 10 min. When the forecast horizon was increased to ranging from 20 min to 4 h, the corresponding average root mean square error increased from 72.16 W/m² to 159.75 W/m², and the relative root mean square error increased from 16.71 % to 37 %. This work can forecast solar radiation maps and assist in the flexible regulation of solar PV generation.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113376"},"PeriodicalIF":6.0,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471195","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}

{"title":"Reducing the impact of climate change on renewable energy systems through wind–solar blending: A worldwide study with CMIP6","authors":"Xiaokang Liu ,&nbsp;Hongrong Shi ,&nbsp;Dazhi Yang ,&nbsp;Xiaolong Chen ,&nbsp;Xiang'ao Xia ,&nbsp;Yang Xie","doi":"10.1016/j.solener.2025.113365","DOIUrl":"10.1016/j.solener.2025.113365","url":null,"abstract":"<div><div>Mitigating climate change has hitherto been a pressing issue for global sustainable development. Climate change can alter the frequency and intensity of extreme weather events, which in turn impacts solar and wind power generation. This study employs data from 10 CMIP6 models to estimate potential changes in global wind and photovoltaic (PV) power generation under three different Shared Socioeconomic Pathways (SSPs) during the critical period for global carbon neutrality (2040–2064). Results indicate that in Central Europe, PV potential (PV_POT) increases by 8%, while extreme low PV output days (PV10) decrease by 10 days under SSP245. Conversely, in the Arabian Peninsula, PV_POT decreases by 4% with PV10 increasing by 16 days. For wind power (WP), significant reductions up to 35% are observed in regions like Southern Russia or the Eastern United States, while WP increases by 40% in areas such as the Sahel or Central South America. Notably, the wind–solar hybrid system effectively mitigates extreme low-output events, with combined output variability reduced by 0.04 in Central Europe. The SSP585 scenario demonstrates favorable trends for wind power, with increases up to 34% in Northern India. These findings emphasize the importance of integrating hybrid systems to construct a resilient energy supply chain and adapt to spatially heterogeneous climate impacts.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113365"},"PeriodicalIF":6.0,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471194","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}

{"title":"Thermal and electrical performance analysis of nanofluid beam splitting PV/T system based on full coupling of light heat and electricity","authors":"Jianqing Lin,&nbsp;Xianglong Chen,&nbsp;Lei Han,&nbsp;Gang Wang","doi":"10.1016/j.solener.2025.113363","DOIUrl":"10.1016/j.solener.2025.113363","url":null,"abstract":"<div><div>Optimizing the system structure and introducing beam splitting technology are effective strategies for enhancing the operational performance of concentrating solar photovoltaic/thermal (PV/T) systems. In this study, a two-stage concentrating PV/T system based on beam splitting is proposed, and the system is analyzed using a fully coupled optical-thermal-electrical method. First, the reliability of the established discrete ordinates (DO) radiation model is verified using the Monte Carlo Ray Tracing (MCRT) method. Next, the obtained quantitative results are applied as a volumetric heat source in a 3D flow heat transfer model. Finally, the operational characteristics of the two-stage concentrating nanofluid PV/T system under various operating conditions are investigated parametrically. The results demonstrate that the radiative fluxes obtained from the 2D DO radiation model are in good agreement with those derived from the MCRT method. Under the series operating condition of the 3D flow heat transfer model, the electrical efficiency of the PV subsystem is 22.13 %, the thermal efficiency of the integrated system is 71.85 %, and the exergy efficiency is 20.77 %, with a nanofluid inlet temperature of 25 °C and an inlet mass flow rate of 0.03 kg/s. This study also evaluates the system’s operating efficiency under series and parallel configurations, showing that the series configuration achieves higher exergy efficiency, while the parallel configuration enhances the thermal efficiency of the system.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"290 ","pages":"Article 113363"},"PeriodicalIF":6.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445949","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}