Energy最新文献

{"title":"Hybrid ensemble learning model for predicting external characteristics of proton exchange membrane fuel cells under various operating conditions","authors":"Xilei Sun ,&nbsp;Guanjie Zhang ,&nbsp;Jianqin Fu ,&nbsp;Dexiang Xi ,&nbsp;Wuqiang Long","doi":"10.1016/j.energy.2025.135913","DOIUrl":"10.1016/j.energy.2025.135913","url":null,"abstract":"<div><div>An accurate and efficient predictive model for external characteristics of proton exchange membrane fuel cells (PEMFCs) is essential for boosting performance and guiding system-level design. In this study, a dedicated PEMFC test bench was designed and influence mechanisms of intake temperature, pressure and relative humidity on cell performance were decoupled and systematically analyzed. On this basis, a hybrid ensemble learning model was proposed to enhance the precision and efficiency of external characteristic predictions. The results demonstrate that elevated intake temperatures improve cell voltage by accelerating reaction kinetics, and low pressures hinder performance through limited reactant supply, while optimal PEMFC performance is achieved at medium humidity levels. Additionally, voltage sampling errors are found to increase under conditions of high temperature, pressure and humidity, reflecting challenges in water management and gas flow regulation. The hybrid ensemble learning model outperforms standalone models, which achieves minimal mean squared errors (MSEs) of 0.2254 for voltage and 1.48 × 10⁻⁴ for voltage sampling error. Its integration of multiple models enhances predictive accuracy and avoids overfitting, demonstrating superior predictive accuracy and adaptability to complex data. These findings provide a crucial data foundation and robust model support for analyzing influence mechanisms of PEMFC external characteristics and accurately predicting performance.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135913"},"PeriodicalIF":9.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The nexus between energy legislation, energy transition, and energy resilience: Evidence from 55 countries worldwide","authors":"Zhenhua Zhang ,&nbsp;Mingcheng Zhao ,&nbsp;Yongxi Chen ,&nbsp;Melody C. Song ,&nbsp;Yue Gao ,&nbsp;Yanchao Feng","doi":"10.1016/j.energy.2025.135906","DOIUrl":"10.1016/j.energy.2025.135906","url":null,"abstract":"<div><div>It has become a global concern as to whether or not energy legislation can accelerate energy transition and enhance national energy resilience. This study aims to explore the relationship between energy legislation, energy transition, and energy resilience globally, using various econometric methods. The results indicate that, in the short term, energy legislation and energy transition have no significant impact on energy resilience. In the long term, for every one-unit increase in the cumulative amount of energy legislation, energy resilience increases by 0.0022234 units, and for every one percentage point increase in energy transition, energy resilience rises by 0.0009812 units. Given that the value of energy resilience ranges from 0 to 1, this suggests that an increase in both the amount of energy legislation and the degree of energy transition has a positive effect on boosting energy resilience over the long term to some extent. The results of the mechanism analysis indicate that an increase in the amount of energy legislation can facilitate the energy transition, thereby enhancing energy resilience. Our findings have important theoretical implications and provide practical guidance for improving energy resilience by enhancing energy legislation and facilitating energy transition.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135906"},"PeriodicalIF":9.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the indicated efficiency of a high-speed triple-screw pump for internal combustion engine cooling","authors":"Giammarco Di Giovine,&nbsp;Marco Di Bartolomeo,&nbsp;Roberto Cipollone","doi":"10.1016/j.energy.2025.135915","DOIUrl":"10.1016/j.energy.2025.135915","url":null,"abstract":"<div><div>Improved thermal management of Internal Combustion Engines (ICEs) can help meet stringent emissions regulations in the road transportation sector. This strategy requires high-efficiency pumps capable of controlling the cooling flow precisely and efficiently. Compared to centrifugal pumps, screw-type volumetric ones maintain high efficiency even when operating far from the design point, resulting in significant energy and emissions reductions.</div><div>This paper investigates a Triple-Screw Pump (TSP) optimized for an engine cooling system, with particular emphasis on the complex fluid-dynamic phenomena occurring inside it. Indeed, the relatively high rotational speed needed to reduce the pump size worsens volumetric and indicated efficiencies with respect to more conventional operating conditions (low speed), making fluid-dynamic phenomena even more complex. A zero-dimensional mathematical model for predicting the indicated efficiency even at high revolution speeds was developed. The model was validated experimentally thanks to a complex procedure based on the measurement of pressure variations inside the volumes among the screws. A close match with the average pressures measured inside these volumes was found, leading to an error in the indicated power below 7.3 %. The pump global efficiency was higher than 50 % even at high revolution speeds, useful in all applications (as engine cooling) requiring high pump efficiency.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135915"},"PeriodicalIF":9.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hierarchical power output prediction for floating photovoltaic systems","authors":"Mohd Herwan Sulaiman ,&nbsp;Zuriani Mustaffa ,&nbsp;Mohd Shawal Jadin ,&nbsp;Mohd Mawardi Saari","doi":"10.1016/j.energy.2025.135883","DOIUrl":"10.1016/j.energy.2025.135883","url":null,"abstract":"<div><div>Accurate forecasting of power output in Floating Photovoltaic (FPV) systems is essential for optimizing renewable energy generation and improving energy management strategies. This study introduces a novel hierarchical prediction framework that enhances FPV power forecasting by systematically modeling energy output at three levels: (1) Maximum Power Point Tracking (MPPT) level, (2) phase-wise level, and (3) total system level. This structured approach captures the interdependencies between different operational levels, improving both prediction accuracy and interpretability. A high-resolution dataset, spanning one year with 5-min interval measurements, was collected from an operational FPV system at Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) and used for model training and validation. The dataset comprises meteorological parameters (solar irradiation, ambient temperature) and electrical characteristics (MPPT voltage, current, and phase-wise power output). Five machine learning models—Feedforward Neural Network (FFNN), Random Forest (RF), Extreme Learning Machine (ELM), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost)—were evaluated within the hierarchical framework. Results indicate that FFNN outperforms all other models, achieving an RMSE of 0.0125, MAE of 0.0024, and an R² of 1 at the system level. The hierarchical structure improves predictive robustness, reduces error propagation across levels, and enhances real-time monitoring by facilitating localized performance analysis. This framework offers a scalable and adaptable solution for FPV forecasting, contributing to enhanced grid stability and more effective energy management. The findings demonstrate the practical benefits of hierarchical modeling in renewable energy prediction, providing a foundation for future research into adaptive forecasting models for dynamic environmental conditions.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135883"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demographic development in waste production forecasts for energy recovery planning","authors":"Veronika Smejkalová ,&nbsp;Petr Jirásek ,&nbsp;Boris Burcin ,&nbsp;Tomáš Kučera ,&nbsp;Jaroslav Pluskal ,&nbsp;Vlastimír Nevrlý ,&nbsp;Radovan Šomplák","doi":"10.1016/j.energy.2025.135895","DOIUrl":"10.1016/j.energy.2025.135895","url":null,"abstract":"<div><div>The transition to a circular economy is driving dynamic changes in waste management. While many waste fractions cannot be materially recovered, energy recovery remains a viable solution. Planning a long-term sustainable system requires accurate forecasts of waste production and treatment, closely tied to population trends, which pose challenges for smaller territorial units due to data variability. This study analyses the impact of demographic projections on waste production forecasts, focusing on fractions suitable for energy recovery with the territorial detail. The output is the identification of the difference in forecasts including demography development and without this factor. In the Czech Republic, population change of approximately 0.5 % is expected by 2035. Despite this, significant differences emerge at the regional and micro-regional levels. Forecasts at the micro-regional level vary by more than 10 %, with the extreme case where the difference exceeds 30 %. Forecasts indicate that municipal waste suitable for energy recovery will exceed 2600 kt, while the current facility capacity in the Czech Republic is only about 750 kt. Increasing waste-to-energy facility capacities will be necessary. The findings of this study enable targeted planning of new capacities in regions with high expected waste production and thus create a sustainable system of waste management.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135895"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature response spatiotemporal correlation model of lithium-ion battery and temperature field reconstruction during charging and discharging processes","authors":"Tao Zhang ,&nbsp;Guangjun Wang ,&nbsp;Hong Chen ,&nbsp;Zhaohui Mao ,&nbsp;Yalan Ji","doi":"10.1016/j.energy.2025.135902","DOIUrl":"10.1016/j.energy.2025.135902","url":null,"abstract":"<div><div>This study introduces an innovative approach aimed at estimating the temperature distribution inside a lithium-ion battery: By establishing a temperature response spatiotemporal correlation model (RSTCM) for battery, the transient temperature field inside the battery is directly reconstructed according to the surface temperature of the battery. Firstly, an external description of the temperature at the battery charging and discharging process is established. The presence of a definitive spatiotemporal correlation among the temperatures at various nodes within the battery is confirmed. Furthermore, a spatiotemporal correlation matrix for temperature responses is constructed using regularization optimization techniques. The temperature RSTCM for battery is established, which utilizes surface temperature measurement data to estimate the temperature distribution. This study utilizes discharge experiment data from lithium battery to validate the RSTCM model. Additionally, numerical simulations are conducted to analyze the impact of various factors on the reconstruction results, including the number of measurement points, charge and discharge rates, measurement errors, and model mismatches. During the charging/discharging process, the reconstructed battery temperature field exhibits an instantaneous maximum error of roughly 1.5 K. With a measurement noise standard deviation of 1.0 K, the temperature field reconstruction exhibits an instantaneous maximum error of approximately 1.3 K.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"324 ","pages":"Article 135902"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-combustion of sewage sludge and high ash coal: Thermal behavior, ash formation behavior, interaction mechanisms and economic analysis","authors":"Shuning Qin,&nbsp;Xuefu He,&nbsp;Zikuo Li,&nbsp;Li Jia,&nbsp;Xiaolei Qiao,&nbsp;Xinyue Chang,&nbsp;Peng Cheng,&nbsp;Yan Jin","doi":"10.1016/j.energy.2025.135847","DOIUrl":"10.1016/j.energy.2025.135847","url":null,"abstract":"<div><div>Co-combustion of sewage sludge with high ash coal enables both waste valorization and sustainable disposal, yet its combined impacts on boiler efficiency, slagging risks, and economic viability require systematic investigation. This study developed a comprehensive evaluation system including combustion characteristics, operational safety, and techno-economic analysis to reveal the interactions between components and mineral evolution during sewage sludge-high ash coal co-combustion. The results demonstrated that blending sewage sludge significantly improved the ignition performance of high ash coal. When the sewage sludge blending ratio exceeded 50 %, combustion transitioned from a fixed carbon-dominant to a volatile-dominated mode. A 50 % sewage sludge blend (sewage sludge to high ash coal mass ratio of 5:5) achieved a comprehensive combustion characteristic index of 4.80 × 10⁻⁸, representing a 100.58 % enhancement compared with coal. Synergistic interactions enhanced the combustion efficiency of fixed carbon, as evidenced by a 25.12 % increase in the fixed carbon weight-loss rate for the 60 % sewage sludge blend, compared to theoretical predictions. Minerals (CaO, Fe₂O₃, AlPO₄) exhibited dual catalytic-inhibitory regulation: optimal concentrations enhanced combustion via catalytic cracking and oxygen storage-release mechanisms, while excessive minerals promoted slag formation impeding oxygen diffusion, with the efficacy hierarchy following CaO &gt; AlPO₄ &gt; Fe₂O₃. Ash chemistry analysis revealed that the addition of sewage sludge increased the alkaline oxide content, promoting silicate network depolymerization. At blending ratios exceeding 50 %, the ash deformation temperature sharply decreased to 1157 °C, increasing the risks of slagging. Economic evaluation indicated dynamic payback periods of 2.91 years for a 50 % blend and 7.67 years for a 60 % blend. Multi-objective optimization identified the optimal sludge-to-coal ratio as 5:5, achieving balanced improvements in combustion efficiency, ash fusion control, and economic viability. This study explores the feasibility of sewage sludge-high ash coal co-combustion, providing a new approach for intensive sewage sludge treatment.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135847"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molten salt induces starch-based carbon aerogels with microsurface wrinkles for high-performance supercapacitors","authors":"Zuozhao Zhai ,&nbsp;Junfeng Miao ,&nbsp;Yangfan Ji ,&nbsp;Hanqing Peng ,&nbsp;Bin Ren ,&nbsp;Haitao Yu","doi":"10.1016/j.energy.2025.135900","DOIUrl":"10.1016/j.energy.2025.135900","url":null,"abstract":"<div><div>Biomass carbon aerogels are widely used as electrode materials for supercapacitors due to high specific surface area, excellent conductivity, low cost, and environmental friendliness. However, the electrochemical performance of biomass carbon aerogels decrease significantly at high power. Herein, starch-based carbon aerogels with microsurface wrinkles are designed in this study. Starch hydrogels are rapidly prepared by using the property that KOH/KCl can gelatinize starch at room temperature. During high-temperature carbonization, the molten salt that is formed by KOH and KCl gives the starch-based aerogels (KCA-KCl) a porous structures with a high specific surface area (2014 m²/g) and microsurface wrinkles. The porous structures and the microsurface wrinkles enables the material to maintain good electrochemical performance at both low and high power. When it is used as electrode material for supercapacitors, the specific capacitance of KCA-KCl is 246.0 F/g at a current density of 1.0 A/g and the capacitance retention of 10 A/g for KCA-KCl is 77.9 % in three electrode system. In two electrode system, KCA-KCl exhibited an energy density of 14.72 Wh/kg at a power density of 0.5 kW/kg and the specific capacitance can maintain 96.33 % after 10,000 cycles. This study provides a feasible strategy to prepare high-performance electrode materials for supercapacitors.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135900"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication and experimental investigation of a laboratory-scale organic Rankine cycle and data-driven optimization","authors":"Mayank Srivastava ,&nbsp;Jahar Sarkar ,&nbsp;Arnab Sarkar ,&nbsp;Anil Antony","doi":"10.1016/j.energy.2025.135905","DOIUrl":"10.1016/j.energy.2025.135905","url":null,"abstract":"<div><div>Electricity harvesting from low-medium grade heat sources through the organic Ranking cycle (ORC) is still immature in many countries (like India). Hence, a laboratory-scale ORC system has been designed and developed for the source temperature of 90–180 °C. The experimentation involves component selection, fluid selection, design, fabrication and testing. A custom-designed separator has been fabricated and used to ensure saturated vapor at the expander inlet. Isopentane has been used as a powering fluid due to its environmental-friendly nature. Effects of heat input (5–11.5 kW), source fluid (oil) flow rate (40–60 lpm), and cold air inlet temperature (29–37 °C) on the system performance have been examined. Maximum net power, thermal efficiency, pump isentropic efficiency and expander isentropic efficiency of 0.939 kW, 8.08 %, 66 % and 78 %, respectively, have been achieved. Based on test data, the RSM-ANOVA tool identifies the optimal operating conditions (11.5 kW heat input, 35 °C cold air inlet temperature and 48 lpm oil flow rate) to predict net power output (0.920 kW) and cycle efficiency (8.037 %), which are closely matched the experimental values. Desirability analysis confirms that the effect of heat input is more crucial on performance, as compared to the effects of cold air inlet temperature and hot oil flow rate.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135905"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modern panelizing and optimization techniques for renewable energy projects; perspectives on how CO2 emissions impact the circular economy","authors":"Xiumin Zheng ,&nbsp;Muhammad Imran ,&nbsp;Muhammad Umair ,&nbsp;Chen Lin ,&nbsp;Yue Dong","doi":"10.1016/j.energy.2025.135881","DOIUrl":"10.1016/j.energy.2025.135881","url":null,"abstract":"<div><div>The transition towards renewable energy is critical for addressing global climate challenges, yet achieving optimal integration and minimizing CO2 emissions remain significant barriers to sustainability. This study investigates the role of advanced panelizing and optimization techniques in renewable energy projects, focusing on their potential to mitigate CO2 emissions and enhance the circular economy across ten countries: the United Kingdom, United States, China, Canada, India, Germany, Japan, Russia, Korea Republic, and Iran, over the period 1990–2024. The primary aim is to evaluate how CO2 emissions interact with renewable energy integration, resource efficiency, and waste minimization to foster a sustainable circular economy. Using a robust methodological framework, the study employs Hurlin causality evaluation to assess causative relationships, Dumitrescu's heterogeneous panel analysis for variability across regions, and panel-based fully modified least-squares methods to ensure consistency and reliability in long-term analysis. The findings reveal four key insights: (1) Renewable energy adoption significantly reduces CO2 emissions, particularly in high-emission economies like China, the United States, and India. (2) Circular economy initiatives are positively correlated with renewable energy use, with European nations like Germany and the United Kingdom demonstrating the strongest synergies. (3) Technological advancements in renewable energy yield more substantial emission reductions in developed nations, while emerging economies show slower but steady progress. (4) A decoupling effect between economic growth and CO2 emissions is observable in most countries, but remains limited in energy-intensive economies such as Iran and Russia. These results underscore the need for policymakers to incentivize renewable energy innovation, prioritize circular economy frameworks, and establish region-specific strategies to accelerate the transition towards a low-carbon, resource-efficient future.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"323 ","pages":"Article 135881"},"PeriodicalIF":9.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}