Renewable Energy最新文献

{"title":"Optimising biochar from agricultural residues: Predicting elemental composition with machine learning","authors":"Yao Fu,&nbsp;Peter Cleall,&nbsp;Fei Jin","doi":"10.1016/j.renene.2025.124071","DOIUrl":"10.1016/j.renene.2025.124071","url":null,"abstract":"<div><div>Biochar, a material whose properties are critically defined by its elemental composition, has been promoted as a sustainable way to treat various biomass wastes, including agricultural residues. However, considerable variability in these compositions across studies necessitates precise predictive techniques. This research followed the PRISMA rules for data collection and study selection, compiling data on feedstock properties and pyrolysis parameters from 38 published studies. A novel Feature-oriented Imputation method was established and employed, utilizing K-Nearest Neighbours (KNN) or Random Forest (RF) imputer to fill in missing values for features with differing characteristics. The reprocessed data were then fed into six distinct datasets and analyzed using a Gradient Boosting Regression model to predict the contents of carbon (C), hydrogen (H), oxygen (O), nitrogen (N), phosphorus (P), and potassium (K) in biochar. The rigorous machine learning process yielded excellent accuracy rates: C (R² = 0.9088, RMSE = 4.0614), H (R² = 0.9068, RMSE = 0.4180), O (R² = 0.9172, RMSE = 2.6475), N (R² = 0.8950, RMSE = 0.3416), P (R² = 0.9699, RMSE = 0.0244), and K (R² = 0.9464, RMSE = 0.3842). A comprehensive analysis of feature importance revealed that feedstock properties generally hold more significance in determining the elemental composition of biochar compared to pyrolysis parameters. The highest heating temperature (HHT) emerged as the most influential parameter for the content of H and O, while the contents of N, P, and K were predominantly determined by their respective levels in the feedstock. From these insights, optimal pyrolysis parameters were derived to tailor biochar with different elemental compositions for various applications. The developed models offer a robust framework for predicting the elemental compositions of biochar derived from various agricultural biomass, thereby eliminating the need for complex and resource-intensive laboratory trials.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124071"},"PeriodicalIF":9.0,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711113","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":"Vertically aligned NiFeP@Ni nanotubes for efficient electrochemical production of green hydrogen and sulfur: Circular economy meets sustainable energy","authors":"Krishna H. Modi ,&nbsp;Parikshit Sahatiya ,&nbsp;Pratik M. Pataniya ,&nbsp;C.K. Sumesh","doi":"10.1016/j.renene.2025.124070","DOIUrl":"10.1016/j.renene.2025.124070","url":null,"abstract":"<div><div>A massive quantity of hydrogen sulfide (H₂S) is produced in the industrial world as an unwanted waste due to the processing of fossil fuels, such as natural gas, petroleum, and coal gasification. This necessitates a more environmentally friendly method for its conversion into more valuable products, such as hydrogen (H₂) and sulfur (S). Herein, the scalable electrochemical alloying-dealloying approach is used to prepare the self-generated vertically aligned porous Ni nanotube on Ni foam. Benefiting from the excellent catalytic activity of phosphorus-based materials, NiFeP nanocomposite is fabricated using the electrochemical deposition technique. The fabricated composite illustrates the vertically aligned nanosheets on the Ni nanotubes, which efficiently increases the active sites of the electrode. The fabricated electrodes demonstrate excellent anodic sulfur oxidation reaction (SOR) and cathodic hydrogen evolution reaction (HER). The sulfur oxidation reaction was initiated at 0.093 V vs RHE, which is 1.13 V less than the thermodynamic potential of the oxygen evolution reaction (1.23 V). The stability of NiFeP@Ni@NF electrode for simultaneous HER and SOR in bi-functional electrolyser was measured for time interval of 25 h at 0.7 V cell voltage. This work provides a route for low-cost, large-scale hydrogen synthesis from industrial by-products by presenting a novel approach for effectively manufacturing hydrogen while recycling hazardous sulfide waste.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124070"},"PeriodicalIF":9.0,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714029","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":"Effectiveness of un-decimated wavelet transform in time-series forecasting: A PV power calculation case study in BTU","authors":"Mehmet Albayram ,&nbsp;Alper Yılmaz ,&nbsp;Gökay Bayrak ,&nbsp;Kivanc Basaran ,&nbsp;Luminita Georgeta Popescu","doi":"10.1016/j.renene.2025.124062","DOIUrl":"10.1016/j.renene.2025.124062","url":null,"abstract":"<div><div>This study explored the effectiveness of Un-Decimated Wavelet Transform (UWT) in time-series applications, using photovoltaic (PV) calculation as a case study. Real-time measurements of irradiance, ambient temperature, module temperature, and humidity were collected at 5-min intervals from a 1.2 kW rooftop PV system at Bursa Technical University. Wavelet-based features extracted with both UWT and the conventional Discrete Wavelet Transform (DWT) were combined with regression and tree-based learners to build 16 hybrid models. The results show that the shift-invariant UWT significantly improves both feature extraction and prediction accuracy compared to the DWT approach. The UWT–DT model achieved the highest accuracy, with the lowest MSE (0.0001), the lowest RMSE (0.0118) and the highest R² coefficient (0.9986). A Wilcoxon signed-rank test applied to paired RMSE values confirmed that these improvements were statistically significant (<span><math><mrow><mi>p</mi></mrow></math></span> value &lt; 0.05 for UWT-DT vs DWT-DT). In terms of computational complexity, the 'à trous' algorithm used in UWT requires convolution operations at every level, resulting in higher processing costs than DWT (12 ms feature extraction per 1024-sample input). However, the full-resolution features provided by UWT significantly reduced the error rates of tree-based models, raising R² above 0.99.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124062"},"PeriodicalIF":9.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714163","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":"Operational strategy and configuration optimization of a distributed energy supply system coupled with metal hydride hydrogen storage and PEMFC","authors":"Yuhang Wang ,&nbsp;Weiran Shi ,&nbsp;Suying Yan ,&nbsp;Wei Zhang ,&nbsp;Chunyu Zhu ,&nbsp;Ming Gao ,&nbsp;Xiaoyu Kan","doi":"10.1016/j.renene.2025.124055","DOIUrl":"10.1016/j.renene.2025.124055","url":null,"abstract":"<div><div>The volatility of solar energy and user demand affects the stability of hydrogen based distributed energy supply systems. To address this issue, this study takes a region in Shandong Province of China as an example and constructs a PEMFC-MH distributed energy system equipped with electric and heat storage devices. The focus is on investigating key indicators such as energy efficiency and investment payback period under six different configuration schemes. The findings indicate that Scheme 1 suffers from poor coordination between electric and heat management, while Schemes 5 and 6 effectively balance both, demonstrating superior electric-heat synergy. In terms of energy efficiency, Scheme 5 leads with 87.4 %, followed by Scheme 6 at 83.3 %, reflecting efficient waste heat utilization. Economically, Schemes 2, 5, and 6 show relatively short payback periods, with Scheme 5 emerging as the optimal option for further research. Additionally, optimizing the capacity allocation between battery and hydrogen storage during winter enhances thermal efficiency, with an optimal battery range of 450 Ah to 780 Ah ensuring high performance and favorable payback periods. This study offers valuable insights into resource allocation strategies, essential for improving the reliability and sustainability of renewable energy systems in the face of growing energy demands.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124055"},"PeriodicalIF":9.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714030","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 short-term wind power forecasting model using theoretical power curves and temporal fusion transformers","authors":"Vasilis Michalakopoulos,&nbsp;Antonis Zakynthinos,&nbsp;Elissaios Sarmas,&nbsp;Vangelis Marinakis,&nbsp;Dimitris Askounis","doi":"10.1016/j.renene.2025.124008","DOIUrl":"10.1016/j.renene.2025.124008","url":null,"abstract":"<div><div>Wind energy penetration has radically increased in the last decade constituting one of the main renewable energy resources of the energy transition. However, its intermittent nature necessitate the development of accurate Wind Power Forecasting (WPF), essential in several applications, including grid reliability and cost minimization. Despite advancements in this sector, a notable gap remains in integrating physics-informed (PI) approaches with transformer-based architectures. This study proposes a novel hybrid WPF model that integrates the Temporal Fusion Transformer (TFT) with theoretical power curve modeling techniques. The integration of manufacturer specifications, Numerical Weather Prediction (NWP) data and PI equations ensures robust and reliable input to the TFT. The proposed approach is validated using real-world datasets from two distinct wind turbines operating in different geographical locations. To comprehensively evaluate forecasting performance, a modified Forecast Skill Index (FSI) is introduced, FSI-WPF, benchmarking accuracy against the theoretical power curve rather than a persistence model. Experimental results demonstrate that the proposed method significantly outperforms conventional forecasting models, achieving up to a 60% reduction in Root Mean Squared Error (RMSE) and an <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> score of up to 99.47%. This study advances the integration of PI modeling with deep learning architectures, paving the way for more accurate and reliable WPF.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124008"},"PeriodicalIF":9.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711192","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":"Coordinated dispatch of electric, thermal, and hydrogen vectors in renewable-enriched microgrids using constrained harris hawks optimization under uncertainty","authors":"Cong Xu ,&nbsp;Ahmed N. Abdalla","doi":"10.1016/j.renene.2025.124064","DOIUrl":"10.1016/j.renene.2025.124064","url":null,"abstract":"<div><div>Microgrids (MGs) integrating renewable energy sources (RESs), plug-in hybrid electric vehicles (PHEVs), battery storage, and proton exchange membrane fuel cell-based combined heat and power (PEMFC-CHP) systems face increasing complexity due to uncertainty in both energy supply and demand, as well as dynamic electricity market prices. This paper proposes a comprehensive energy management strategy for renewable-enriched microgrids that simultaneously coordinate the dispatch of electric, thermal, and hydrogen energy vectors. The proposed system integrates photovoltaic (PV) and wind resources, a proton exchange membrane fuel cell combined heat and power unit (PEMFC-CHP), battery energy storage systems (BESS), plug-in hybrid electric vehicles (PHEVs), and a hydrogen production and storage subsystem. To address the inherent uncertainties in load demand, renewable generation, and market prices, a Monte Carlo Simulation (MCS)-based scenario framework is adopted. A constrained variant of the Harris Hawks Optimization (HHO) algorithm is introduced to solve the multi-objective optimization problem, minimizing total operational cost, carbon emissions, and load or storage violations. The optimization process enforces technical and economic constraints including power balance, storage capacity, thermal demand satisfaction, and hydrogen trading limits. The proposed framework is developed and simulated using MATLAB® software and validated on a modified 16-bus microgrid under multiple operational scenarios, ranging from uncontrolled PHEV charging to full vector coordination with PEMFC and CHP integration. Simulation results demonstrate that the proposed HHO-based energy management framework significantly outperforms benchmark algorithms in minimizing operational cost, emissions, and unmet energy demand. Case 6, which integrates smart PHEV charging with PEMFC-CHP coordination, achieves the most optimal performance—delivering the lowest cost (320 €), reduced emissions (520 kg CO₂), and zero unmet load across all scenarios.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124064"},"PeriodicalIF":9.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711198","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":"Renewable energy integration in the Belt and Road Initiative: Government expenditure, green finance, and economic growth","authors":"Yutao Hua ,&nbsp;Tianjie Tong","doi":"10.1016/j.renene.2025.123980","DOIUrl":"10.1016/j.renene.2025.123980","url":null,"abstract":"<div><div>China is leading in incorporating renewable energy into the Belt and Road Initiative (BRI), a vital first step toward sustainable development. From 2013 to 2023, this paper investigates how government expenditure, green finance, and economic development interact to support renewable energy within the BRI framework. This study especially catches the asymmetric and nonlinear impacts of green financing and renewable energy infrastructure investments—such as solar, wind, and hydropower—on economic growth and environmental sustainability using the Quantile Autoregressive Distributed Lag (QARDL) model. The results show that government subsidies and green financial instruments such sustainable loans and green bonds and loans have greatly hastened the shift to low-carbon energy sources. Furthermore, the QARDL approach distinguishes this study from standard methods by offering a sophisticated knowledge of the short- and long-term dynamics spanning several quantiles. The outcomes underline the need for international coordination among BRI countries and fiscal policy alignment to maximize the economic and environmental benefits of renewable energy. Under the BRI, this paper presents policy suggestions to improve the efficiency of green finance in reaching long-term sustainability objectives.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 123980"},"PeriodicalIF":9.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711197","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":"Distributed biomass pyrolysis equipment applied in the field of yard waste treatment: equipment design, recycling of by-products, physico-chemical analysis of products, economic efficiency analysis","authors":"Liangmeng Ni ,&nbsp;Aiyue Huang ,&nbsp;Yuge He ,&nbsp;Qi Gao ,&nbsp;Shanwen Rong ,&nbsp;Yanhang Zhong ,&nbsp;Shushu Liu ,&nbsp;Zhijia Liu","doi":"10.1016/j.renene.2025.124012","DOIUrl":"10.1016/j.renene.2025.124012","url":null,"abstract":"<div><div>To convert yard wastes including bamboo waste and wood waste into solid biofuel, a distributed biomass pyrolysis equipment was designed with the characteristics of recovering bio-tar, waste heat utilization and high efficiency in this research. Hydroxypropyl methyl cellulose (HPMC) and recovered bio-tar were utilized as a composite binder for molded charcoal. The mechanical, combustion, ash fusion characteristics and economics of molded charcoal were evaluated. The optimized operating conditions for the equipment included a pyrolysis temperature of 400 °C, a heating rate of 2.5 °C/min, and a holding time of 30 min. The yield of bamboo charcoal was 36.37 %, while the yield of wood charcoal was 34.20 %. The optimum mass ratio of HPMC to bio-tar was 3:1. At this ratio, the HHV of molded wood charcoal was 25.47 MJ/kg, with a compressive strength of 172.25 N/cm. Similarly, the HHV of molded bamboo charcoal was 25.88 MJ/kg, with a compressive strength of 143.38 N/cm. The minimum selling price (MSP) of molded charcoal was 861.96 USD/t with a profit of 5.14 USD/t. Consumable expenditure, labor cost, and yard waste cost were the major factors influencing the MSP of molded charcoal. These findings will provide scientific guidance for value-added utilization of yard wastes.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124012"},"PeriodicalIF":9.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711196","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":"A hybrid framework for optimal site selection and energy resource forecasting for off-grid hybrid energy systems: integrating GIS, hesitant fuzzy linguistic MCDM, and forecasting tools","authors":"Sayan Das ,&nbsp;Risav Dutta ,&nbsp;Souvanik De ,&nbsp;Sudipta De","doi":"10.1016/j.renene.2025.124058","DOIUrl":"10.1016/j.renene.2025.124058","url":null,"abstract":"<div><div>Transitioning to sustainable renewable energy is essential for achieving a carbon-neutral economy. Decentralized hybrid energy systems, which utilize locally available resources, can help bridge the gap between energy demand and supply. However, identifying optimal locations and forecasting renewable resource availability remain major challenges. This study proposes an integrated framework combining Geographic Information Systems (GIS), hesitant fuzzy multi-criteria decision-making, and fuzzy forecasting to address these issues. The primary goal is to identify the most suitable site for decentralized hybrid energy deployment. Sensitivity and obstacle degree analyses are conducted to test the robustness of the site selection and highlight key influencing factors. The methodology, demonstrated using spatial data from a central Indian state, is adaptable and broadly applicable. Among nine alternatives, Sailana emerged as the most favorable location due to its strong resource potential and favorable geographic, economic, and social conditions. Additionally, the fuzzy forecasting method showed superior accuracy over optimized neural network models, reducing mean relative error by 33–80 %. This research contributes both a practical tool for stakeholders and an enhancement to theoretical models for renewable energy site selection.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124058"},"PeriodicalIF":9.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711199","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":"Alternative non-optimal orientations in highly PV self-consumption integration: Exploring Spanish prosumers as a case study","authors":"Felipe García-Suso ,&nbsp;Angel Molina-García ,&nbsp;Ana Fernández-Guillamón ,&nbsp;María C. Bueso","doi":"10.1016/j.renene.2025.123987","DOIUrl":"10.1016/j.renene.2025.123987","url":null,"abstract":"<div><div>The urgency to mitigate the greenhouse effect and achieve sustainable production systems is driving the exploration of novel clean energy options. Indeed, some European nations are currently undergoing an energy transition characterized by a growing emphasis on renewable energy sources, with a particular focus on promoting the adoption of self-consumption photovoltaic systems. Among these, solar energy stands out as a particularly promising candidate due to its inherent lack of pollution. However, Photovoltaic (PV) energy is generally not considered a dispatchable resource due to its inherent limitations, including seasonal and daily fluctuations in output, as well as dependence on weather conditions. Therefore, and aiming to ensure that PV installations from prosumers on the distribution grid receive fair compensation for the value they provide to the system, reimbursement mechanisms should be designed to reflect the dynamic value of their electricity production. Under this framework, this paper describes and assesses the trade-off between annual economic profits and potential reductions in electricity generation by estimating the most appropriate PV installation orientations. To analyze future power systems with potentially high PV integration into households, different real PV installations representing current Spanish prosumer profiles are included as case study, assessing 2640 different generation profiles. Indeed, Spain exemplifies a remarkable case study in the widespread adoption of photovoltaic (PV) systems over the past few decades. This surge can be attributed to the relative ease of installation and competitive pricing of PV technology. Notably, the installed capacity of PV power in Spain has witnessed impressive growth, expanding by nearly 30% in the past year alone. Results provide numerous benefits for such specific non-optimal orientations. These findings, confirmed after a full year of operation, include an increase in annual economic benefits in spite of a lower energy production compared to the optimal-producing orientation.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 123987"},"PeriodicalIF":9.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685723","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}