Renewable Energy最新文献

{"title":"Machine learning-assisted optimization of a novel hybrid solar-geothermal system supported by proton exchange membrane fuel cell for sustainable and continuous energy supply","authors":"Mobin Korpeh ,&nbsp;Amirhosein Lotfollahi ,&nbsp;S. Navid Faraji ,&nbsp;Ayat Gharehghani ,&nbsp;Samareh Ahmadi","doi":"10.1016/j.renene.2025.123034","DOIUrl":"10.1016/j.renene.2025.123034","url":null,"abstract":"<div><div>This study proposes a solar-geothermal multi-generation system integrating proton exchange membrane fuel cells (PEMFCs) for continuous, reliable, and sustainable energy production. During the day, the system utilizes solar and geothermal energy to generate power, heating, fresh water, and hydrogen. At night, PEMFCs use stored hydrogen to maintain power generation and improve efficiency, with the heat released by the PEMFCs further enhancing overall performance. Performance analysis shows that extending nighttime from 8 to 14 h reduces hydrogen consumption from 286.38 to 102.27 kg/h and affects power output and exergy efficiency by 46.6 % and 20.7 %, respectively. To evaluate the system's feasibility at the selected location, hourly analyses were conducted across two different seasons. To expedite the optimization process, three machine learning techniques were employed and evaluated using metrics such as mean squared error, mean absolute error, and R² score. Among the methods tested, the extreme gradient boosting (XGBoost) regressor combined with the multi-output regressor algorithm provided the most accurate predictions. The XGBoost model was further optimized using a multi-objective approach with a genetic algorithm, leading to the identification of optimal operational points. Under optimal conditions, the system achieves an exergy round trip efficiency of 28.12 %, a total cost rate of 739.14 $/h, and is capable of producing 2.53 kg/s of fresh water and 204.19 kg/h of hydrogen.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123034"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785867","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":"Green hydrogen production via floating photovoltaic systems on irrigation reservoirs: An Italian case study","authors":"Gabriele Guglielmo Gagliardi,&nbsp;Carlotta Cosentini,&nbsp;Giuliano Agati,&nbsp;Domenico Borello,&nbsp;Paolo Venturini","doi":"10.1016/j.renene.2025.123040","DOIUrl":"10.1016/j.renene.2025.123040","url":null,"abstract":"<div><div>This study investigates the potential for establishing a self-sufficient renewable hydrogen production facility utilising a floating photovoltaic (FPV) system on an artificial irrigation reservoir, located in a small municipality in southern Italy. The analysis examines the impact of different system configurations and operating conditions on the technical, economic, and environmental performance, with a particular focus on hydrogen production and water conservation resulting from reduced evaporation. Different sizes of the FPV plant are considered, with and without a tracking system. The electrolyser performance is evaluated under both fixed and variable load conditions, also considering the integration of battery storage to ensure consistent operation. The findings indicate that the adoption of the largest FPV plant can result in the conservation of approximately 1.87 million m³ of water annually, while simultaneously producing up to 4199 tons of hydrogen per year in variable load mode—more than twice the output compared to fixed load conditions. Although battery integration increases hydrogen production, it also leads to higher investment and maintenance costs. Therefore, the variable load operation emerges as the most economically viable option, reducing the levelized cost of hydrogen (LCOH) to €13.18/kg, a 26 % reduction compared to fixed load operation. Moreover, the implementation of a vertical axis tracking system leads to only marginal LCOH reductions (maximum 2.2 %) and does not justify the additional complexity. In all tested scenarios, the system proves to be self-sustaining. Given the case study's location in southern Italy—where a pilot project for fuel cell–battery hybrid trains is underway—the hydrogen produced is assumed to be used for railway applications as a possible offtaker. The analysis shows that the potential of the system in terms of hydrogen production is much higher (tens of times) than the estimated demand of the present hydrogen railway configuration, thus suggesting that a significant expansion of the number of trains and routes served could be considered. Although this work is based on a specific case study, its key findings are potentially replicable in other contexts—particularly in Mediterranean or semi-arid regions where water scarcity may otherwise act as a limiting factor for the deployment of hydrogen production systems.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123040"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807913","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":"Hybrid wind energy and hydrogen system for direct CO2 air capture: A case study","authors":"Mohammed Daoudi","doi":"10.1016/j.renene.2025.123028","DOIUrl":"10.1016/j.renene.2025.123028","url":null,"abstract":"<div><div>This study addresses urgent environmental challenges by proposing an innovative hybrid system that integrates wind energy and green hydrogen production to power direct <em>CO</em>_<em>2</em> air capture <em>(DAC)</em> at three sites in northern Morocco. The novelty of this work lies in its scalable design, combining renewable energy with <em>DAC</em> technology to create a sustainable solution for carbon reduction. Wind potential was analyzed using the Weibull distribution to ensure statistical reliability for eight commercial turbines. Hydrogen production employed proton exchange membrane <em>(PEM)</em> electrolysis, recognized for its efficiency. Among the turbines, <em>T</em>_<em>5</em> demonstrated superior performance, producing 3971–7545 MWh/year with capacity factors from 29.5 % to 57.7 %. Hydrogen yields ranged from 53,575.02 to 101,793.90 kg, with storage volumes between 1413.79 and 2686.23 m³. A key strength of this study is its detailed techno-economic analysis, showing low costs of electricity <em>(LCOE)</em>, hydrogen <em>(LCOH)</em>, and <em>CO</em>_<em>2</em> capture <em>(LCOD)</em>. Additionally, <em>T</em>_<em>6</em> and <em>T</em>_<em>8</em> turbines were identified as competitive alternatives, while others were excluded due to higher costs. This study highlights the effectiveness of wind-hydrogen hybrid systems, with <em>CO</em>_<em>2</em> capture ranging from 1313.22 to 12,882.35 tons across the sites. It also demonstrates their economic feasibility, contributing to the goals of clean energy, sustainable cities, and climate action.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123028"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792256","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":"Hybrid ultra-short term solar irradiation forecasting using resource-efficient multi-step long-short term memory","authors":"Lilla Barancsuk ,&nbsp;Veronika Groma ,&nbsp;Barnabás Kocziha","doi":"10.1016/j.renene.2025.122962","DOIUrl":"10.1016/j.renene.2025.122962","url":null,"abstract":"<div><div>Accurate forecasting of solar irradiance is a key tool for optimizing the efficiency and service quality of solar energy systems. In this paper, a novel approach is proposed for multi-step solar irradiation forecasting using deep learning models optimized for low computational resource environments. Traditional forecasting models often lack accuracy, and modern, deep-learning based models, while accurate, require substantial computational resources, making them impractical for real-time or resource-constrained environments. Our method uniquely combines dimensionality reduction via image processing with an LSTM-based architecture, achieving significant input data reduction by a factor of 4250 while preserving essential sky condition information, resulting in a lightweight neural network architecture that balances prediction accuracy with computational efficiency. The forecasts are generated simultaneously for multiple time steps: 1<!--> <!-->minute, 5<!--> <!-->minutes, 10<!--> <!-->minutes and 20<!--> <!-->minutes. Models are evaluated against a custom dataset, spanning across more than 3 years, containing 1 min samples encompassing both all-sky imagery and meteorological measurements. The approach is demonstrated to achieve better forecasting accuracy, namely a forecast skill of 10<!--> <!-->% compared to persistence, and a significantly reduced computational overhead compared to benchmark ConvLSTM models. Moreover, utilizing the preprocessed image features reduces input size by a factor of 6 compared to the raw images. Our findings suggest that the proposed models are well-suited for deployment in embedded systems, remote sensors, and other scenarios where computational resources are limited.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 122962"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785863","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":"Multi-objective Bayesian optimisation over sparse subspaces for model predictive control of wind farms","authors":"Kiet Tuan Hoang ,&nbsp;Sjoerd Boersma ,&nbsp;Ali Mesbah ,&nbsp;Lars Struen Imsland","doi":"10.1016/j.renene.2025.122988","DOIUrl":"10.1016/j.renene.2025.122988","url":null,"abstract":"<div><div>As model mismatch (uncertainty) is inevitable, fine-tuning control strategies with closed-loop performance data is critical. This is relevant for model predictive control (MPC) in wind farms (WFs), as inaccurate wake models affect performance. However, challenges such as conflicting control objectives, limited closed-loop data due to expensive experiments, and the high-dimensional design spaces of these MPC formulations make tuning non-trivial. Inspired by the notion of performance-oriented learning, we propose a multi-objective (MO) Bayesian optimisation (BO) framework over sparse subspaces to address these challenges systematically for increased closed-loop MPC performance. To show the efficacy of the BO approach, a simulation case study with a 3x3 WF is investigated where the control objective is to provide secondary frequency regulation while minimising dynamic loading for an MPC with 28 design parameters to auto-tune. Simulations show that the proposed framework achieves a good balance between two conflicting WF control objectives, where dynamic loading is reduced by 51.59% compared to a nominal MPC whose performance is not tuned using closed-loop data while still achieving similar tracking performance. The proposed method is general and can be applied regardless of a closed-loop control goal, WF specifications (complexity, topology, location), or controller formulation for multi-objective constrained control of WFs.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 122988"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792154","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":"Activating reaction intermediates in steam reforming with microwave heating for suppressing coke formation","authors":"Yunyu Guo ,&nbsp;Yuchen Jiang ,&nbsp;Lihua Wang ,&nbsp;Linghui Kong ,&nbsp;Chao Li ,&nbsp;Yangfan Zhang ,&nbsp;Shu Zhang ,&nbsp;Xun Hu","doi":"10.1016/j.renene.2025.123030","DOIUrl":"10.1016/j.renene.2025.123030","url":null,"abstract":"<div><div>Microwave heating in steam reforming (SR) could selectively agitate reaction intermediates with polar functionalities including precursors of coke, which might affect tendency of coking and properties of coke. This was verified here by conducting SR of acetic acid, glycerol, toluene, and guaiacol with microwave heating and furnace heating at 300–600 °C with Ni/Mg-Al-LDH as a catalyst. The results showed that microwave heating promoted catalytic activity via enhancing mobilizing reaction intermediates and their collision/reactions. This accelerated gasification of carbonaceous intermediates with steam, forming less coke in SR of all the reactants. Specifically, coke from SR of toluene with microwave heating was only ca. 65 % of that from furnace heating, while the ratio of coke formed from microwave heating to furnace heating in SR of guaiacol even reached ca. 54 %. Enhanced gasification of carbonaceous species with microwave heating also formed aliphatic structures in coke. Generally, the coke from microwave heating was very aromatic with significantly higher C/H ratio and more disordered structures than that from furnace heating. Enhanced aromatization of reaction intermediates to carbon nanotubes was observed in SR of acetic acid with microwave heating, while the coke from furnace heating was highly amorphous. Abundant hydrocarbon intermediates from toluene and oxygen-rich intermediates from glycerol or guaiacol formed nanotube-form coke of smooth or rough surfaces.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123030"},"PeriodicalIF":9.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792257","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":"Thermogravimetric, kinetic and thermodynamic behaviour of raw and hydrothermally pretreated oil cakes during pyrolysis and TG-FTIR analysis of the gaseous products","authors":"Aleksandra Petrovič ,&nbsp;Sabina Vohl ,&nbsp;Sven Gruber ,&nbsp;Klemen Rola ,&nbsp;Tjaša Cenčič Predikaka ,&nbsp;Lidija Čuček ,&nbsp;Danijela Urbancl","doi":"10.1016/j.renene.2025.123041","DOIUrl":"10.1016/j.renene.2025.123041","url":null,"abstract":"<div><div>The pyrolysis of raw and hydrothermally (HTC) pretreated pumpkin (PC) and hemp (HC) oilseed cakes was investigated for the first time using thermogravimetric, kinetic and thermodynamic analyses. The influence of the HTC pretreatment and the type of reaction liquid (whey or water) on the pyrolysis was investigated and the pyrolysis gases were analysed.</div><div>The HTC pretreatment increases the biochar yield with values of up to 44 wt% compared to raw oil cakes (∼27 wt%). The HTC pretreatment with whey resulted in a higher energy and biochar yield and better biochar properties than the pretreatment with water. The tested oil cakes provided comparable energy yields, although HC provided higher biochar yields, while PC biochar showed higher hydrophobicity. The kinetic modelling shows that the activation energies (<span><math><mrow><msub><mi>E</mi><mi>α</mi></msub></mrow></math></span>) for the pyrolysis of the raw oil cakes varied between 93.6 and 529.9 kJ/mol for PC and between 71.3 and 669.9 kJ/mol for the HC sample. HTC pretreatment in water media increased the <span><math><mrow><msub><mi>E</mi><mi>α</mi></msub></mrow></math></span> values, while the use of whey led to a decrease in the <span><math><mrow><msub><mi>E</mi><mi>α</mi></msub></mrow></math></span> values. TG-FTIR analysis of the emitted gases showed that the HTC treatment affected the release of CO₂ and hydrocarbons as well as the pyrolysis mechanism and reaction pathways.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123041"},"PeriodicalIF":9.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785866","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":"Digestate derived porous biochar through thermochemical nitrogen self-doping as an efficient cathode catalyst for microbial fuel cells","authors":"Shiteng Tan ,&nbsp;Zhenghui Zhao ,&nbsp;Kai Zhang ,&nbsp;Bingdong Zhang ,&nbsp;Qianqian Yin ,&nbsp;Yue Zhang ,&nbsp;Ruikun Wang","doi":"10.1016/j.renene.2025.123033","DOIUrl":"10.1016/j.renene.2025.123033","url":null,"abstract":"<div><div>Microbial fuel cell (MFC) is a promising technology for sustainable energy production using renewable resources. The development of low-cost and efficient cathode catalysts is an effective way to promote the practical application of MFC. This study proposes a hydrothermal process combined with pyrolysis activation method to convert digestate into nitrogen-rich porous biochar catalysts. The nitrogen in the raw material is effectively embedded into the carbon skeleton during the hydrothermal process, increasing the number of active sites. The three-dimensional porous structure of the material promotes the transport and diffusion of reactants in the catalyst. The results show that the catalyst (HT-PC-KOH) with hydrothermal followed by KOH activation had the highest nitrogen retention rate and excellent pore structure. The maximum power density of the MFC loaded with HT-PC-KOH is 1814 mW/m², which represents 84 % of the power density of Pt/C. This work provides a new method for converting biomass into an oxygen reduction catalyst and makes a significant contribution to the efficient production of renewable energy from MFC.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123033"},"PeriodicalIF":9.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807912","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 choice of the parameter identification procedure in quasi-dynamic testing of low-temperature solar collectors","authors":"J.M. Rodríguez-Muñoz ,&nbsp;I. Bove ,&nbsp;R. Alonso-Suárez ,&nbsp;P.A. Galione","doi":"10.1016/j.renene.2025.122931","DOIUrl":"10.1016/j.renene.2025.122931","url":null,"abstract":"<div><div>The ISO 9806:2017 standard is widely used to characterize the thermal performance of solar collectors. It permits two test methods: Steady State Testing (SST) and Quasi-Dynamic Testing (QDT). While SST requires high stability and clear sky conditions, which limit its application, QDT offers more flexibility in sky conditions. In contrast, the QDT method adds complexity due to the handling of transient phenomena during data processing. There are two approaches to parameter identification in QDT: multilinear regression (MLR) and dynamic parameter identification (DPI). MLR, the most common tool, faces challenges with certain collector types and its results depend on the data averaging time. DPI, while more complex, has the potential to overcome MLR’s shortcomings. Which of these two methods is most suitable for testing low-temperature solar collectors in a broad sense is an issue that has not yet been addressed. This work provides evidence that the DPI procedure is more convenient than the MLR procedure, especially for evacuated tube collectors with heat pipes. Specifically, it is shown that DPI produces more reliable test results and provides more accurate estimates of useful power, and it exhibits less variability with respect to data averaging time, demonstrating its improved robustness.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 122931"},"PeriodicalIF":9.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768808","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":"Two-stage peer-to-peer energy trading with combined uniform and discriminatory pricing mechanism","authors":"N. Noorfatima,&nbsp;Y. Choi,&nbsp;J. Jung","doi":"10.1016/j.renene.2025.123014","DOIUrl":"10.1016/j.renene.2025.123014","url":null,"abstract":"<div><div>In peer-to-peer (P2P) energy trading, uniform pricing can improve market efficiency by lowering trading prices. However, this may result in fewer participants, particularly if P2P energy trading involves peers with a broad range of bidding prices. In contrast, discriminatory pricing can maximize the number of participants by offering multiple trading prices. Despite larger trading profits, discriminatory pricing mechanism is sensitive to computational issues and higher trading prices. Therefore, this study proposes two-stage P2P energy trading to obtain the merits of both methods by combining uniform and discriminatory pricing methods to improve the performance of market operations. In the first stage, market participants are classified using the Gaussian mixture model (GMM) and then, to handle security issues due to the uniform pricing mechanism, Stackelberg game theory is applied. The optimal number of trading capacity of each cluster was then determined through discriminatory pricing mechanism and alternating direction method of multipliers (ADMM) to improve the performance through distributive manner. The proposed method was evaluated based on community-based P2P energy trading by incorporating various types of customers. The findings demonstrate that the proposed method can obtain optimal compromised results that balance the features of uniform and discriminatory pricing methods.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"247 ","pages":"Article 123014"},"PeriodicalIF":9.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815343","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}