Pub Date : 2025-12-08DOI: 10.1016/j.solener.2025.114207
Lelia Deville , Kevin S. Anderson , Juergen Sutterlueti , Terrence L. Chambers , Karel De Brabandere , Felix Perez Cicala , Javier Lopez-Lorente , Brian Mirletz , Anja Neubert , Maitheli Nikam , Michele Oliosi , Matthew Prilliman , Kurt Rhee , Branislav Schnierer , Jason Spokes , Bruno Wittmer , Marios Theristis
While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.
{"title":"Feature review of photovoltaic modeling software utilizing blind performance assessment","authors":"Lelia Deville , Kevin S. Anderson , Juergen Sutterlueti , Terrence L. Chambers , Karel De Brabandere , Felix Perez Cicala , Javier Lopez-Lorente , Brian Mirletz , Anja Neubert , Maitheli Nikam , Michele Oliosi , Matthew Prilliman , Kurt Rhee , Branislav Schnierer , Jason Spokes , Bruno Wittmer , Marios Theristis","doi":"10.1016/j.solener.2025.114207","DOIUrl":"10.1016/j.solener.2025.114207","url":null,"abstract":"<div><div>While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114207"},"PeriodicalIF":6.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733981","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 : 2025-12-08DOI: 10.1016/j.solener.2025.114233
Hayder Mohsin Ali , Ali M. Ashour , Hamzah M. Jaffar , Saif Ali Kadhim , Farhan Lafta Rashid , Abdallah Bouabidi
This study represents an experimental characterization of a solar air-lift pump developed to dismantle solar-heated compressed air into bubbles inside a vertically submerged pipe for water lifting with no moving mechanical parts. The outdoor testing was done during the summer and winter periods, from 6:00 AM to 6:00 PM. Solar radiation, ambient temperature, water lift height, and volume flow rate were accounted for in the analysis and efficiency matrices, like thermal efficiency, air-to-mechanical, isentropic, pump, air-lift hydraulic, and overall efficiencies as well. The results showed a very high positive correlation between system performance and solar radiation, with the summer peaks always exceeding the winter values. The maximum water lift height was 85.8 cm in summer, compared to 58.5 cm in winter, and the maximum flow rate increased from 0.985 mL/s in winter to 1.716 mL/s in summer. The maximum value of thermal efficiency achieved in summer was 47.9 % in summer and 35.9 % in winter. A maximum overall efficiency was 5.0 % in summer and 3.73 % in winter was observed, clearly depicting the seasonal variation of the performance of solar air-lift pump. Results indicate that the thermal-to-hydraulic energy conversion recovery is efficiently influenced by seasonal effects, where summer shows significant benefit and is effective for bubble generation, water lifting ability, and overall system performance. This work offers valuable insights for the design of solar air-lift pump applications in irrigation, aquaculture, and off-grid drinking water supply systems.
{"title":"Experimental investigation of solar air lift pump seasonal performance and efficiency","authors":"Hayder Mohsin Ali , Ali M. Ashour , Hamzah M. Jaffar , Saif Ali Kadhim , Farhan Lafta Rashid , Abdallah Bouabidi","doi":"10.1016/j.solener.2025.114233","DOIUrl":"10.1016/j.solener.2025.114233","url":null,"abstract":"<div><div>This study represents an experimental characterization of a solar air-lift pump developed to dismantle solar-heated compressed air into bubbles inside a vertically submerged pipe for water lifting with no moving mechanical parts. The outdoor testing was done during the summer and winter periods, from 6:00 AM to 6:00 PM. Solar radiation, ambient temperature, water lift height, and volume flow rate were accounted for in the analysis and efficiency matrices, like thermal efficiency, air-to-mechanical, isentropic, pump, air-lift hydraulic, and overall efficiencies as well. The results showed a very high positive correlation between system performance and solar radiation, with the summer peaks always exceeding the winter values. The maximum water lift height was 85.8 cm in summer, compared to 58.5 cm in winter, and the maximum flow rate increased from 0.985 mL/s in winter to 1.716 mL/s in summer. The maximum value of thermal efficiency achieved in summer was 47.9 % in summer and 35.9 % in winter. A maximum overall efficiency was 5.0 % in summer and 3.73 % in winter was observed, clearly depicting the seasonal variation of the performance of solar air-lift pump. Results indicate that the thermal-to-hydraulic energy conversion recovery is efficiently influenced by seasonal effects, where summer shows significant benefit and is effective for bubble generation, water lifting ability, and overall system performance. This work offers valuable insights for the design of solar air-lift pump applications in irrigation, aquaculture, and off-grid drinking water supply systems.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"305 ","pages":"Article 114233"},"PeriodicalIF":6.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697896","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 : 2025-12-08DOI: 10.1016/j.solener.2025.114200
Jingxian He , Jianxia Liu , Jiabin Zhu , Hao Gou , Shuaibing Li , Zhuoqun Li , Yishu Zhang , Yong He , Zhaoxin Yan , Lei Ling
Utilizing solar energy to drive interface heating to achieve water evaporation, while the photothermal catalyst decomposes water vapor to produce hydrogen. This synergistic strategy integrates clean energy conversion and water resource utilization, providing an innovative technological path for alleviating global energy crises and freshwater scarcity. To achieve both low production cost and high solar-thermal hydrogen production efficiency, an interfacial solar photothermal-photocatalytic system based on modified polyethylene foam (M−EPE), referred to as Co3O4@ZIS/M−EPE, was developed. Notably, the Co3O4@ZIS/M−EPE system exhibited high synergistic photothermal effects in both steam generation and hydrogen production, attributed to its unique two-dimensional channel structure, hydrophilicity, thermal insulation properties, and low thermal conductivity. Under an optical power density of 250 mW/cm2, the water evaporation rate of the Co3O4@ZIS/M−EPE system was noted to be 0.785 kg·m−2h−1, with a hydrogen production rate of 3411.75 µmol g−1h−1. In this scenario, the solar-to-steam conversion efficiency (η1) can reach up to 84.8 %, the solar-to-hydrogen energy conversion efficiency (η2) can reach 34 %. Cyclic experiments confirmed the long-term stability of the system. Moreover, the hydrogen production efficiency of the Co3O4@ZIS/M−EPE system using non-pure water was comparable to that achieved with pure water. This study highlights the potential of interfacial photothermal evaporation systems for hydrogen production from non-pure water and their relevance to industrial contexts.
{"title":"Waste polymer-based interfacial solar photothermal catalytic system for hydrogen production and vapor generation","authors":"Jingxian He , Jianxia Liu , Jiabin Zhu , Hao Gou , Shuaibing Li , Zhuoqun Li , Yishu Zhang , Yong He , Zhaoxin Yan , Lei Ling","doi":"10.1016/j.solener.2025.114200","DOIUrl":"10.1016/j.solener.2025.114200","url":null,"abstract":"<div><div>Utilizing solar energy to drive interface heating to achieve water evaporation, while the photothermal catalyst decomposes water vapor to produce hydrogen. This synergistic strategy integrates clean energy conversion and water resource utilization, providing an innovative technological path for alleviating global energy crises and freshwater scarcity. To achieve both low production cost and high solar-thermal hydrogen production efficiency, an interfacial solar photothermal-photocatalytic system based on modified polyethylene foam (M−EPE), referred to as Co<sub>3</sub>O<sub>4</sub>@ZIS/M−EPE, was developed. Notably, the Co<sub>3</sub>O<sub>4</sub>@ZIS/M−EPE system exhibited high synergistic photothermal effects in both steam generation and hydrogen production, attributed to its unique two-dimensional channel structure, hydrophilicity, thermal insulation properties, and low thermal conductivity. Under an optical power density of 250 mW/cm<sup>2</sup>, the water evaporation rate of the Co<sub>3</sub>O<sub>4</sub>@ZIS/M−EPE system was noted to be 0.785 kg·m<sup>−2</sup>h<sup>−1</sup>, with a hydrogen production rate of 3411.75 µmol g<sup>−1</sup>h<sup>−1</sup>. In this scenario, the solar-to-steam conversion efficiency (η<sub>1</sub>) can reach up to 84.8 %, the solar-to-hydrogen energy conversion efficiency (η<sub>2</sub>) can reach 34 %. Cyclic experiments confirmed the long-term stability of the system. Moreover, the hydrogen production efficiency of the Co<sub>3</sub>O<sub>4</sub>@ZIS/M−EPE system using non-pure water was comparable to that achieved with pure water. This study highlights the potential of interfacial photothermal evaporation systems for hydrogen production from non-pure water and their relevance to industrial contexts.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114200"},"PeriodicalIF":6.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733955","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 : 2025-12-08DOI: 10.1016/j.solener.2025.114202
Jingjing Xie , Yan Ma , Conghao Wang , Yanting Wang , Sen Yang , Quan Ouyang
Improved prediction accuracy of regional photovoltaic (PV) generation significantly enhances multi-area coordination efficiency in modern power systems. This paper proposes a novel PV power forecasting model IIMGAT that integrates Improved Variational Mode Decomposition (IVMD), an improved Time-series Mixer architecture (Tsmixer), and a multi-head Graph Attention Network (GAT). First, the IVMD effectively extracts the key trend components from PV data as model inputs to mitigate interference from abrupt cloud cover changes. An innovative spatiotemporal dual-design framework is then employed to capture temporal patterns and extract spatial features. The proposed IIMGAT model achieves high precision forecasting by comprehensively capturing spatio-temporal correlations among regional PV power stations. The proposed model achieves values of 0.981 and 0.991 on the PVOD and DKASC datasets, respectively. The values of indicate the model’s high robustness.
{"title":"Spatio-temporal multi-head graph attention network for power forecasting of regional photovoltaic plants","authors":"Jingjing Xie , Yan Ma , Conghao Wang , Yanting Wang , Sen Yang , Quan Ouyang","doi":"10.1016/j.solener.2025.114202","DOIUrl":"10.1016/j.solener.2025.114202","url":null,"abstract":"<div><div>Improved prediction accuracy of regional photovoltaic (PV) generation significantly enhances multi-area coordination efficiency in modern power systems. This paper proposes a novel PV power forecasting model IIMGAT that integrates Improved Variational Mode Decomposition (IVMD), an improved Time-series Mixer architecture (Tsmixer), and a multi-head Graph Attention Network (GAT). First, the IVMD effectively extracts the key trend components from PV data as model inputs to mitigate interference from abrupt cloud cover changes. An innovative spatiotemporal dual-design framework is then employed to capture temporal patterns and extract spatial features. The proposed IIMGAT model achieves high precision forecasting by comprehensively capturing spatio-temporal correlations among regional PV power stations. The proposed model achieves <span><math><msup><mrow><mtext>R</mtext></mrow><mn>2</mn></msup></math></span> values of 0.981 and 0.991 on the PVOD and DKASC datasets, respectively. The values of <span><math><msup><mrow><mtext>R</mtext></mrow><mn>2</mn></msup></math></span> indicate the model’s high robustness.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114202"},"PeriodicalIF":6.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733982","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 : 2025-12-08DOI: 10.1016/j.solener.2025.114212
Sahibzada Imad Ud Din , Adnan Ibrahim , Ahmad Fazlizan , Norasikin Ahmad Ludin , Muhammad Aqil Afham Rahmat , Muhammad Ashhad Shahid , Anwer.B. Al-Aasam , Mohd Afzanizam Mohd Rosli , Muhammad Amir Aziat Bin Ishak
There is a growing focus on solar air heater systems due to their enhanced efficiency and performance. However, due to poor convective heat transfer coefficient and the intermittent nature of solar energy, these systems cannot provide reliable thermohydraulic performance. This research study introduced a novel design to improve the thermal and hydraulic performance of a double-pass solar air heater. For this purpose, a three-dimensional numerical analysis is performed to evaluate the thermohydraulic performance of a newly developed DPSAH design with sandwich-structured PCM cylinders in the second channel. The parameters selected for this study include PCM cylinder diameter ranging from 0.06 to 0.09 m, channel height-to-total height ratio ranging from 0.19 to 0.38, and Reynolds number ranging from 4700 to 23,250. The maximum Nusselt number was found to be 278 with a corresponding friction factor value of 0.074, and a maximum thermohydraulic performance parameter value of 2.17 was attained for a cylinder diameter of 0.07 m and a channel height ratio of 0.38 at a Reynolds number of 23,250. For the same parameters, the heat transfer enhancement ratio was 4.63 times with a friction factor increment ratio of 11.1 compared to the smooth plate.
{"title":"Heat transfer and flow analysis of a double-pass solar air heater with sandwich-structured PCM cylinders","authors":"Sahibzada Imad Ud Din , Adnan Ibrahim , Ahmad Fazlizan , Norasikin Ahmad Ludin , Muhammad Aqil Afham Rahmat , Muhammad Ashhad Shahid , Anwer.B. Al-Aasam , Mohd Afzanizam Mohd Rosli , Muhammad Amir Aziat Bin Ishak","doi":"10.1016/j.solener.2025.114212","DOIUrl":"10.1016/j.solener.2025.114212","url":null,"abstract":"<div><div>There is a growing focus on solar air heater systems due to their enhanced efficiency and performance. However, due to poor convective heat transfer coefficient and the intermittent nature of solar energy, these systems cannot provide reliable thermohydraulic performance. This research study introduced a novel design to improve the thermal and hydraulic performance of a double-pass solar air heater. For this purpose, a three-dimensional numerical analysis is performed to evaluate the thermohydraulic performance of a newly developed DPSAH design with sandwich-structured PCM cylinders in the second channel. The parameters selected for this study include PCM cylinder diameter ranging from 0.06 to 0.09 m, channel height-to-total height ratio ranging from 0.19 to 0.38, and Reynolds number ranging from 4700 to 23,250. The maximum Nusselt number was found to be 278 with a corresponding friction factor value of 0.074, and a maximum thermohydraulic performance parameter value of 2.17 was attained for a cylinder diameter of 0.07 m and a channel height ratio of 0.38 at a Reynolds number of 23,250. For the same parameters, the heat transfer enhancement ratio was 4.63 times with a friction factor increment ratio of 11.1 compared to the smooth plate.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114212"},"PeriodicalIF":6.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733957","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 : 2025-12-06DOI: 10.1016/j.solener.2025.114197
Paul Brown, Murat Göl
This paper describes a novel probabilistic forecasting method for photovoltaic power for use in energy management for an agricultural microgrid. The forecasting method utilizes recent historical data and a general weather forecast to fit a spline + Gaussian process (GP) model using no-u-turn sampling (NUTS) to infer model parameters in a Bayesian modeling framework. The method seamlessly transitions from a near-term forecast dominated by recent output to a regime where output is dominated by the meteorological forecast. The forecasts are evaluated using proper scoring rules for multivariate probabilistic forecasts and are compared to a reference multivariate persistence forecast and to an LSTM-based forecasting method. The probabilistic method is integrated into a simulation of stochastic model-predictive control (SMPC) for an off-grid agricultural microgrid incorporating photovoltaic generation, a battery storage system, irrigation pumping, and local electrical loads. A 20 %–35 % reduction in simulated operating cost is achieved using the probabilistic forecast compared to a simple expected-value point forecast.
{"title":"Bayesian probabilistic photovoltaic power forecasting and stochastic model-predictive control for an agricultural microgrid","authors":"Paul Brown, Murat Göl","doi":"10.1016/j.solener.2025.114197","DOIUrl":"10.1016/j.solener.2025.114197","url":null,"abstract":"<div><div>This paper describes a novel probabilistic forecasting method for photovoltaic power for use in energy management for an agricultural microgrid. The forecasting method utilizes recent historical data and a general weather forecast to fit a spline + Gaussian process (GP) model using no-u-turn sampling (NUTS) to infer model parameters in a Bayesian modeling framework. The method seamlessly transitions from a near-term forecast dominated by recent output to a regime where output is dominated by the meteorological forecast. The forecasts are evaluated using proper scoring rules for multivariate probabilistic forecasts and are compared to a reference multivariate persistence forecast and to an LSTM-based forecasting method. The probabilistic method is integrated into a simulation of stochastic model-predictive control (SMPC) for an off-grid agricultural microgrid incorporating photovoltaic generation, a battery storage system, irrigation pumping, and local electrical loads. A 20 %–35 % reduction in simulated operating cost is achieved using the probabilistic forecast compared to a simple expected-value point forecast.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114197"},"PeriodicalIF":6.0,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682079","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 : 2025-12-06DOI: 10.1016/j.solener.2025.114175
Chinedu I. Otuka , Dongsheng Cai , Chiagoziem C. Ukwuoma , Shuang Luo , Zhihui Yang , Olusola Bamisile , Chibueze D. Ukwuoma , Chizoba U. Otuka , Nkiruka O. Otuka , Qi Huang
The growing demand for clean energy has greatly improved solar energy forecasting, especially for Global Horizontal Irradiance (GHI), which is important for solar photovoltaic (PV) installation planning, grid integration, and energy management. Traditional forecasting methods, such as statistical and physical models, often fail to capture solar irradiance data’s complex, nonlinear, and dynamic nature. Researchers have turned to deep learning techniques, which have demonstrated superior accuracy by effectively capturing spatiotemporal dependencies. While previous surveys have explored traditional forecasting and deep learning approaches for GHI solar forecasting, many focus on limited model types, lack of comprehensive analysis of the different model disadvantages, a Benchmark dataset, feature extraction techniques, and experimental analysis to support their claims. To address this gap, this Prisma-based systematic and Experimental Review critically examines recent improvements in deep learning techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), hybrid and ensemble methods, and Transformers, providing an analysis of their strengths, weaknesses, and real-world applicability for solar irradiance forecasting while supporting its claim with experimental analysis. This review identifies that CNNs excel in spatial feature extraction, particularly from sky images, while RNNs are well-suited for sequential data analysis. Hybrid and ensemble methods leverage multiple approaches to improve robustness and forecasting precision. Transformers have brought about a breakthrough in long-range dependency handling through their attention mechanisms, enhancing sequence-to-sequence tasks, which can be seen from the reported experiment. However, challenges such as dependency on large labelled datasets, overfitting with limited data, and computational demands remain significant limitations. In addition, this review article presents a novel dual-input transformer-based model for 30-minute solar forecasting. The designed dual-feature input transformer fuses information from sky images and numerical data to make a forecast of solar irradiance (SI) with high accuracy, specifically an R2 of 0.979 on sunny days and 0.976 on cloudy days, showing robust performance under different weather conditions. The findings emphasise the practical implications of deep learning models in enhancing energy production, improving grid stability, and optimising energy storage, thereby contributing to a sustainable energy future.
{"title":"Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction","authors":"Chinedu I. Otuka , Dongsheng Cai , Chiagoziem C. Ukwuoma , Shuang Luo , Zhihui Yang , Olusola Bamisile , Chibueze D. Ukwuoma , Chizoba U. Otuka , Nkiruka O. Otuka , Qi Huang","doi":"10.1016/j.solener.2025.114175","DOIUrl":"10.1016/j.solener.2025.114175","url":null,"abstract":"<div><div>The growing demand for clean energy has greatly improved solar energy forecasting, especially for Global Horizontal Irradiance (GHI), which is important for solar photovoltaic (PV) installation planning, grid integration, and energy management. Traditional forecasting methods, such as statistical and physical models, often fail to capture solar irradiance data’s complex, nonlinear, and dynamic nature. Researchers have turned to deep learning techniques, which have demonstrated superior accuracy by effectively capturing spatiotemporal dependencies. While previous surveys have explored traditional forecasting and deep learning approaches for GHI solar forecasting, many focus on limited model types, lack of comprehensive analysis of the different model disadvantages, a Benchmark dataset, feature extraction techniques, and experimental analysis to support their claims. To address this gap, this Prisma-based systematic and Experimental Review critically examines recent improvements in deep learning techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), hybrid and ensemble methods, and Transformers, providing an analysis of their strengths, weaknesses, and real-world applicability for solar irradiance forecasting while supporting its claim with experimental analysis. This review identifies that CNNs excel in spatial feature extraction, particularly from sky images, while RNNs are well-suited for sequential data analysis. Hybrid and ensemble methods leverage multiple approaches to improve robustness and forecasting precision. Transformers have brought about a breakthrough in long-range dependency handling through their attention mechanisms, enhancing sequence-to-sequence tasks, which can be seen from the reported experiment. However, challenges such as dependency on large labelled datasets, overfitting with limited data, and computational demands remain significant limitations. In addition, this review article presents a novel dual-input transformer-based model for 30-minute solar forecasting. The designed dual-feature input transformer fuses information from sky images and numerical data to make a forecast of solar irradiance (SI) with high accuracy, specifically an R<sup>2</sup> of 0.979 on sunny days and 0.976 on cloudy days, showing robust performance under different weather conditions. The findings emphasise the practical implications of deep learning models in enhancing energy production, improving grid stability, and optimising energy storage, thereby contributing to a sustainable energy future.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114175"},"PeriodicalIF":6.0,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682081","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 : 2025-12-06DOI: 10.1016/j.solener.2025.114159
Tushima Basak , Tista Basak
The optimal performance of perovskite solar cells (PSCs) is critically dependent on the appropriate selection of stable and high-efficiency hole transporting materials (HTMs) that facilitate directional hole-transfer and impede electron-flow. This computational work demonstrates a unique technique for designing potential HTMs by the site-selective incorporation of suitable dopants in the radicals of graphene quantum dots (GQDs). We first demonstrate that band-gap tuning is dictated by the electron-inducing capability of the dopant atoms, spin multiplicity of the ground-state and the spin-paired/unpaired radical character of the GQDs. The computed spectral profile establishes that doping results in a generic red-shift of the optical profile and the magnitude of this shift is more pronounced for electron-donating Al dopants as compared to electron-withdrawing N substituents. A comprehensive analysis of the essential properties for prospective HTMs such as interfacial layer alignment, dipole moment, open-circuit voltage, fill-factor, mobility, light harvesting efficiency, excitonic character and binding energy highlights that the selective integration of N dopants in the spin-paired radicals of GQD with singlet ground state yields a suitable HTM for high-efficiency PSCs. This operational approach can be exploited for the rational design of stable, cost-effective HTMs that can successfully overcome the fabrication complexity and high-expenses associated with the conventional Spiro-OMeTAD HTM.
{"title":"DFT investigation of spin-tuned radicals of doped graphene quantum dots for efficient hole transport","authors":"Tushima Basak , Tista Basak","doi":"10.1016/j.solener.2025.114159","DOIUrl":"10.1016/j.solener.2025.114159","url":null,"abstract":"<div><div>The optimal performance of perovskite solar cells (PSCs) is critically dependent on the appropriate selection of stable and high-efficiency hole transporting materials (HTMs) that facilitate directional hole-transfer and impede electron-flow. This computational work demonstrates a unique technique for designing potential HTMs by the site-selective incorporation of suitable dopants in the radicals of graphene quantum dots (GQDs). We first demonstrate that band-gap tuning is dictated by the electron-inducing capability of the dopant atoms, spin multiplicity of the ground-state and the spin-paired/unpaired radical character of the GQDs. The computed spectral profile establishes that doping results in a generic red-shift of the optical profile and the magnitude of this shift is more pronounced for electron-donating Al dopants as compared to electron-withdrawing N substituents. A comprehensive analysis of the essential properties for prospective HTMs such as interfacial layer alignment, dipole moment, open-circuit voltage, fill-factor, mobility, light harvesting efficiency, excitonic character and binding energy highlights that the selective integration of N dopants in the spin-paired radicals of GQD with singlet ground state yields a suitable HTM for high-efficiency PSCs. This operational approach can be exploited for the rational design of stable, cost-effective HTMs that can successfully overcome the fabrication complexity and high-expenses associated with the conventional Spiro-OMeTAD HTM.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114159"},"PeriodicalIF":6.0,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682015","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 : 2025-12-05DOI: 10.1016/j.solener.2025.114216
Saba Roostaei , Mina Ahmadi-Kashani , Hiba J. Turki , Zainab Muhsin Bdaiwi , Layth S. Jasim , Masoud Salavati-Niasari
Air, water, and soil contamination form a worldwide crisis, posing grave risks to the health of Earth’s ecosystems and all living beings, particularly humans. Considerable efforts have been made to develop low-cost, green, and highly effective strategies for degrading organic dyes and contaminants in aqueous environments. This study introduces, for the first time, the design and controlled synthesis of a novel ternary CoFe2O4/CoCo2O4/CeO2 nano-photocatalyst with magnetic recyclability, achieved via a facile single-step sol–gel auto-combustion strategy. This pioneering approach highlights the integration of three components for efficient pollutant degradation. This ternary photocatalyst combines the magnetic properties of CoFe2O4, the structural stability and redox versatility of CoCo2O4, and the oxygen storage capacity and photocatalytic functionality of CeO2. The coexistence of variable oxidation states in transition metals (e.g., Co2+/Co3+, Fe2+/Fe3+, and Ce3+/Ce4+) enables efficient multi-electron redox processes, which are critical for generating reactive oxygen species (•OH, •O2–) that drive rapid dye degradation. This ternary nano-photocatalyst exhibited superior photocatalytic capabilities by degrading 86.15 % of Erythrosine (ER). Scavenger experiments confirmed that holes (h+) were the dominant reactive species in the CoFe2O4/CoCo2O4/CeO2 nanocomposite under visible-light irradiation, playing the most critical role in driving the photocatalytic degradation mechanism. In addition, a detailed mechanism for the catalytic reaction under light irradiation, along with the hole-creation process in the CoFe2O4/CoCo2O4/CeO2 system, was outlined. A detailed analysis of kinetic behavior, catalyst reusability, and variable effects like pollutant concentration and catalyst dosage was conducted during photocatalytic testing. Owing to its multi-functional design, the CoFe2O4/CoCo2O4/CeO2 system demonstrates exceptional promise for eco-friendly water treatment, efficiently degrading diverse pollutants without secondary waste generation.
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Pub Date : 2025-12-05DOI: 10.1016/j.solener.2025.114184
Evangelos I. Sakellariou , Petros J. Axaopoulos , Giorgos Sofiadis , Kosmas A. Kavadias
This study experimentally investigates the nocturnal operation of a photovoltaic thermal (PVT) collector to assess its heat rejection capacity during summer nights in a Mediterranean climate. A key objective was to evaluate the proportion of heat rejection attributed to thermal radiation. The PVT collector was connected to a storage tank in a closed-loop configuration through a circulation pump. The experimental setup was installed in Argolis, Greece, and operated during July and August under varying summer weather conditions, fluid flow rates, and collector inclinations. The results show that the average specific cooling power of the collector ranged between 43 and 60 W m−2, values comparable to those reported in the literature for unglazed PVT collectors. Radiative cooling contributed 10–18 % of the total cooling power, while natural convection was the dominant mechanism. During nighttime operation, the PVT collector was capable of reducing the storage tank water temperature slightly below ambient, primarily due to thermal radiation from the collector to the sky. Using the experimental dataset, a multivariable polynomial regression model was developed to predict cooling power as a function of inlet water temperature, ambient temperature, relative humidity, wind speed, and fluid flow rate. The model achieved an R2 of 0.889 with a standard error of 10.34 W, demonstrating strong predictive performance under clear-sky conditions, though reduced accuracy was observed during overcast nights. These findings indicate that nocturnal PVT operation can enhance the performance of shallow geothermal heat pump systems in Mediterranean climates by cooling down the ground temperatures adjacent to the ground heat exchanger during cooling-dominated periods, thereby improving the performance of the heat pump system.
本研究通过实验研究了一个光伏热（PVT）集热器的夜间运行，以评估其在地中海气候下夏夜的散热能力。一个关键的目标是评估由于热辐射而产生的热量流失的比例。PVT收集器通过循环泵以闭环配置连接到储罐上。实验装置安装在希腊的Argolis，并于7月和8月在不同的夏季天气条件、流体流速和收集器倾角下运行。结果表明，集热器的平均比冷却功率在43 ~ 60 W m−2之间，与文献中报道的无釉PVT集热器的值相当。辐射冷却占总冷却功率的10 - 18%，而自然对流是主要的冷却机制。在夜间运行期间，PVT收集器能够将储罐水温降低到略低于环境温度，这主要是由于收集器对天空的热辐射。利用实验数据，建立了一个多变量多项式回归模型，预测了进口水温、环境温度、相对湿度、风速和流体流量对冷却功率的影响。该模型的R2为0.889，标准误差为10.34 W，在晴空条件下显示出较强的预测性能，尽管在阴天夜间观察到精度降低。这些结果表明，夜间PVT运行可以通过降低地面热交换器附近的地面温度，从而提高地中海气候条件下浅层地源热泵系统的性能，从而提高热泵系统的性能。
{"title":"Experimental performance of a PVT collector during nocturnal operation","authors":"Evangelos I. Sakellariou , Petros J. Axaopoulos , Giorgos Sofiadis , Kosmas A. Kavadias","doi":"10.1016/j.solener.2025.114184","DOIUrl":"10.1016/j.solener.2025.114184","url":null,"abstract":"<div><div>This study experimentally investigates the nocturnal operation of a photovoltaic thermal (PVT) collector to assess its heat rejection capacity during summer nights in a Mediterranean climate. A key objective was to evaluate the proportion of heat rejection attributed to thermal radiation. The PVT collector was connected to a storage tank in a closed-loop configuration through a circulation pump. The experimental setup was installed in Argolis, Greece, and operated during July and August under varying summer weather conditions, fluid flow rates, and collector inclinations. The results show that the average specific cooling power of the collector ranged between 43 and 60 W m<sup>−2</sup>, values comparable to those reported in the literature for unglazed PVT collectors. Radiative cooling contributed 10–18 % of the total cooling power, while natural convection was the dominant mechanism. During nighttime operation, the PVT collector was capable of reducing the storage tank water temperature slightly below ambient, primarily due to thermal radiation from the collector to the sky. Using the experimental dataset, a multivariable polynomial regression model was developed to predict cooling power as a function of inlet water temperature, ambient temperature, relative humidity, wind speed, and fluid flow rate. The model achieved an R<sup>2</sup> of 0.889 with a standard error of 10.34 W, demonstrating strong predictive performance under clear-sky conditions, though reduced accuracy was observed during overcast nights. These findings indicate that nocturnal PVT operation can enhance the performance of shallow geothermal heat pump systems in Mediterranean climates by cooling down the ground temperatures adjacent to the ground heat exchanger during cooling-dominated periods, thereby improving the performance of the heat pump system.</div></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":"304 ","pages":"Article 114184"},"PeriodicalIF":6.0,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682071","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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