Renewable and Sustainable Energy Reviews最新文献

{"title":"Optimization and dynamic control of green energy-saving process for azeotropes separation by mixed solvent extractive distillation","authors":"Zhen Wang ,&nbsp;Leilei Xin ,&nbsp;Yangyang Wang,&nbsp;Qiming Wu,&nbsp;Wenwu Xu,&nbsp;Zhaoyou Zhu,&nbsp;Yinglong Wang,&nbsp;Peizhe Cui","doi":"10.1016/j.rser.2025.115813","DOIUrl":"10.1016/j.rser.2025.115813","url":null,"abstract":"<div><div>Extractive distillation (ED) is an effective method by adding solvents to separate azeotropes, where solvents can affect the separation performance of the process. In order to improve the economic and environmental performance of the ED process, different kinds of mixed solvents have been widely concerned by scholars in recent years. In this work, from the effect of mixed solvents on ED, the process design, process energy saving and dynamic control of different types of mixed solvent technology are discussed. In addition, the computer-assisted screening model of the composition of mixed solvents is introduced, and the thermodynamic model Conductor-like Screening Model (COSMO) can analyze the interaction mechanism of solvents and azeotropic system from a microscopic point of view, it has the advantages of accuracy and efficiency in selecting mixed solvents, which provides a new idea for solvent screening. Furthermore, a new green solvent with deep eutectic solvents that is affordable and less toxic is proposed as a component of the mixed solvent in view of the problems existing in the current mixed solvents. The research provides an outlook on the future development direction of mixed solvent ED.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115813"},"PeriodicalIF":16.3,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916128","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":"Social acceptance of green hydrogen in European Union and the United Kingdom: A systematic review","authors":"Lydia Maketo ,&nbsp;Peta Ashworth","doi":"10.1016/j.rser.2025.115827","DOIUrl":"10.1016/j.rser.2025.115827","url":null,"abstract":"<div><div>This paper presents the results of a systematic review on social acceptance of green hydrogen in European Union (EU) and the United Kingdom (UK). The study found that key factors influencing hydrogen acceptance are knowledge, information provision, trust, communication, cost, safety, environmental and climate issues, experience with technology and socio-demographic characteristics. The reception of green hydrogen across EU and the UK differs and can be categorised as outright rejection, neutrality, or positivity. There is high acceptance of green hydrogen and little evidence of resistance. Most people perceive hydrogen neutrally, without a strong sense of acceptance or rejection. Future research could investigate effective public engagement strategies to address green hydrogen knowledge gaps. Additionally, more qualitative studies are required to provide greater depth and more context-specific insights to understand the complex factors influencing green hydrogen acceptance. We recommend creative financing models to help accelerate the green hydrogen industry.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115827"},"PeriodicalIF":16.3,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913188","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":"An integrated identification framework for analyzing air pollutants mitigation potential from crop residue burning","authors":"Chenshuo Ma ,&nbsp;Chao Yuan ,&nbsp;Yifei Zhang","doi":"10.1016/j.rser.2025.115826","DOIUrl":"10.1016/j.rser.2025.115826","url":null,"abstract":"<div><div>Crop residue burning is a key contributor to air pollution, highlighting the need for comprehensive emission assessments and reduction strategies to promote sustainable development. Biomass power (BP), open biomass burning (OBB), and indoor biomass burning (IBB) are the primary forms of crop residue burning. While previous studies have established emission inventories for individual burning forms, there is a significant gap in spatial assessments that integrate multiple forms to better inform crop residue management. This study developed a framework that integrates BP, OBB, and IBB to generate a high-resolution (10 × 10 km) emission map. Notably, it is the first to establish a spatially explicit emission inventory considering multiple forms of crop residue burning. Focusing on Northeast China as a case study, the results indicate that the quantity of crop residue burned was 16,900 tons, with OBB and IBB accounting for 99.7 %. The emissions of PM_2.5, NO_x, and SO₂ were 666,000 tons, 107,000 tons, and 14,500 tons, respectively. Transitioning all crop residues to BP could reduce these emissions by 96 %. Additionally, this study identified spatial heterogeneity in emission reduction potential, partitioned counties accordingly, and proposed spatially differentiated mitigation strategies. These insights can inform crop residue planning and contribute to achieving sustainable development goals.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115826"},"PeriodicalIF":16.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913185","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":"Recent advances of energetic valorization technologies for waste tires: A systematic review of thermochemical and integrated processes, challenges, and future directions","authors":"Jingyuan Liu,&nbsp;Jianzhao Zhou,&nbsp;Jingzheng Ren","doi":"10.1016/j.rser.2025.115800","DOIUrl":"10.1016/j.rser.2025.115800","url":null,"abstract":"<div><div>Increasing amounts of waste tires have constantly placed a huge burden on the environment, highlighting the urgency of waste tires valorization. This review aims to provide an overview of recent advances in energetic valorization technologies including incineration, pyrolysis, and gasification. The underlying correlations between critical factors and products are concluded based on experimental and theoretical studies. Co-valorization studies were reviewed to assess the synergistic effects. Lastly, poly-generation has been introduced for the production of multiple value-added products and for reducing negative environmental impacts. It can be observed that large amounts of escaping pollutants resulting from the lack of aftertreatment units undermine the competitiveness of the incineration process. Pyrolysis and gasification processes of waste tires are complex and costly, but the products are more valuable, highlighting the potential to improve efficiency and profitability by optimizing operation conditions. Energetic co-valorization processes have the advantages of enhancing the quality of products and reducing energy consumption. H₂ production is a more common selection favored by the market in poly-generation processes. Some recommendations have been made to address current challenges faced by waste tire energetic valorization including updating the pretreatment techniques to improve overall efficiency, building comprehensive assessment models with consideration of multi-dimensional analysis and sustainable development goals (SDGs), developing superstructure optimization frameworks, and collecting mechanism data to enhance the accuracy of forecasts. This review outlines the achieved advances and future development directions in this field, underscoring the significance of energetic valorization technologies for sustainable waste tires management.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115800"},"PeriodicalIF":16.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906508","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":"Advancing renewable energy scenarios with graph theory and ensemble meta-optimized approach","authors":"Amin Arjmand Bafti,&nbsp;Mohsen Rezaei","doi":"10.1016/j.rser.2025.115806","DOIUrl":"10.1016/j.rser.2025.115806","url":null,"abstract":"<div><div>Transitioning to renewable energy (RE) in Iran is crucial for reducing its dependence on fossil fuel revenues and for advancing global climate goals. This article presents the Ensemble Meta-Optimized Scenario Graph Planning (EMOSGP) method to explore future RE scenarios.The EMOSGP framework applies Micmac and k-means techniques to identify the key factors influencing renewable energy scenarios. By integrating the graph theory with scenario planning, EMOSGP employs a variety of algorithms, including hybrid k-means models enhanced by Particle Swarm Optimization (PSO) and the Artificial Hummingbird Algorithm (AHA), to provide insightful analyses through ensemble spectral graph partitioning of trend interactions. Moreover, the EMOSGP offers a novel approach for creating a comprehensive ensemble dataset derived from multiple spectral graph partitioning results, along with an advanced technique for weighting the foundational algorithms. Additionally, the strategic application of trend weights in feature weighting significantly improves the performance of the ensemble clustering process. By utilizing the ensemble learning through simple k-means, the EMOSGP method effectively addresses clustering limitations in scenario planning, resulting in the generation of reliable scenarios. Among the five scenarios produced, one stands out as particularly optimistic.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115806"},"PeriodicalIF":16.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913186","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 new transportation energy review: methanol catalytic synthesis from CO2 green hydrogenation","authors":"Peng Zhang ,&nbsp;Qi Chen ,&nbsp;Hao Chen ,&nbsp;Limin Geng ,&nbsp;Han Wu ,&nbsp;Zhanming Chen ,&nbsp;Jianming Cao ,&nbsp;Donghui Qi ,&nbsp;Yanlei Ma","doi":"10.1016/j.rser.2025.115819","DOIUrl":"10.1016/j.rser.2025.115819","url":null,"abstract":"<div><div>The growing emphasis on reducing global greenhouse gas emissions has highlighted challenges associated with transitioning to carbon peaking and carbon neutrality. The increasing utilization of renewable but intermittent energy sources, such as solar and wind, and the need to manage supply and demand has driven the development of energy storage fuels such as methanol, which is clean, versatile, and abundant. As a result, the hydrogenation of carbon dioxide (CO₂) to methanol using various catalysts is gaining momentum. This review analyzes and summarizes the performance of Cu-based, In-based, noble metal-, and solid solution-based catalysts in terms of preparation, reaction mechanism, CO₂ conversion efficiency, and methanol selectivity. The optimal reaction conditions for these catalysts typically fall within 200–300 °C and 1.5–5 MPa. The Cu-based are the most widely studied and exhibit a median CO₂ conversion efficiency and methanol selectivity of 13.6 % and 69.2 % respectively, whereas In- and solid solution-based catalysts exhibit similar performances but superior stabilities. The noble metal-based catalysts exhibit different CO₂ conversion efficiencies (0.6 %–66 %) and methanol selectivities (11 %–100 %) with limited data on stability. This comprehensive analysis provides a theoretical foundation and reference assisting researchers selecting the catalysts for the production of methanol using CO₂ hydrogenation.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115819"},"PeriodicalIF":16.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913187","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":"Polyaniline hydrogel in flexible energy systems: Synthesis techniques, hybrid architecture, sustainability and techno-economic analysis","authors":"Md Shohan Parvez ,&nbsp;Md Mustafizur Rahman ,&nbsp;Izan Izwan Misnon ,&nbsp;Mahendran Samykano","doi":"10.1016/j.rser.2025.115784","DOIUrl":"10.1016/j.rser.2025.115784","url":null,"abstract":"<div><div>This review presents the progressive advances in polyaniline (PANI)-based conductive polymer hydrogels (CPHs) for next-generation flexible energy storage systems, revealing a significant improvement in synthesis methodologies, sustainable progress, and applications. The review demonstrates how surfactants, crosslinkers, co-polymerization, and binder-free formulations can effectively achieve superior electrochemical performance and mechanical solidity. The analysis uncovers the developments addressing key challenges like cycle stability and capacitance fading through novel hybrid architectures of PANI with emerging materials like MXenes, Graphene, and Carbon nanotubes. An exceptional specific capacitance of 936.8 F g⁻¹ at 1 A g⁻¹ and energy density reaching 40.98 Wh kg⁻¹ is also observed from the assisted dynamically crosslinked PANI/PVA hydrogel sheet. Moreover, dual-doping strategies and controlled crystallinity have led to remarkable stability improvements, with capacitance retention exceeding 92 % after 10,000 cycles. Crucial correlations between synthesis parameters and performance metrics reveal that γ-radiation-induced synthesis can enhance elongation up to 1400 % while maintaining superior conductivity. The control of optimum porosity has enabled the development of high-mass-loading electrodes (&gt;43.2 mg cm⁻²) with outstanding rate capability (92.7 % retention from 20 to 500 mA cm⁻²). Novel freeze-thaw-shrink treatments and self-healing mechanisms have produced mechanically robust devices capable of operating under extreme conditions (−30 °C∼90 °C). Sustainable production approaches incorporating bio-friendly dopants and electrolytes demonstrate reduced environmental impact. This work also emphasises the optimum synthesis strategies for production scalability from a techno-economic viewpoint. These findings establish a framework for developing cutting-edge flexible supercapacitors with significant implications for advanced portable electronics, wearable devices, and grid-scale energy storage solutions.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115784"},"PeriodicalIF":16.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903564","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":"Deep learning framework designed for high-performance lithium-ion batteries state monitoring","authors":"Paul Takyi-Aninakwa ,&nbsp;Shunli Wang ,&nbsp;Guangchen Liu ,&nbsp;Carlos Fernandez ,&nbsp;Wenbin Kang ,&nbsp;Yingze Song","doi":"10.1016/j.rser.2025.115803","DOIUrl":"10.1016/j.rser.2025.115803","url":null,"abstract":"<div><div>Accurate state of charge (SOC) estimation is crucial for ensuring the safety of batteries, especially in real-time battery management system (BMS) applications. Deep learning methods have become increasingly popular, driving significant advancements in battery research across various fields. However, their accuracy is limited due to the nonlinear adverse driving conditions batteries experience during operation and an over-reliance on raw battery information. In this work, a deep-stacked denoising autoencoder is established for a long short-term memory model that incorporates a transfer learning mechanism to estimate and study the SOC from an electrochemical perspective. More importantly, this proposed model is designed to extract and optimize the electrochemical features from the training data on a secondary scale, improving noise reduction and the precision of initial weights. This adaptation allows for accurate SOC estimation of batteries while minimizing interference and divergence. For large-scale applicability, the proposed model is tested with high-performance lithium-ion batteries featuring different morphologies under a range of complex loads and driving conditions. The experimental results highlight the distinct behaviors of the tested batteries. Moreover, the performance of the proposed model demonstrates its effectiveness and outperforms existing models, achieving a mean absolute error of 0.04721% and a coefficient of determination of 98.99%, facilitating more precise state monitoring of batteries through secondary feature extraction.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115803"},"PeriodicalIF":16.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903548","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":"Corrigendum to ‘Enhancing ecosystem services and biodiversity in agrivoltaics through habitat-enhancing strategies’ [Renew Sustain Energy Reviews, Volume 212, April 2025, start page–end page]","authors":"A. Ludzuweit ,&nbsp;J. Paterson ,&nbsp;K. Wydra ,&nbsp;C. Pump ,&nbsp;K. Müller ,&nbsp;Y. Miller","doi":"10.1016/j.rser.2025.115775","DOIUrl":"10.1016/j.rser.2025.115775","url":null,"abstract":"","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115775"},"PeriodicalIF":16.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071223","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":"Resource-energy-environment nexus in converting food waste to biobutanol: Potential for resource recovery, energy security, and greenhouse gas mitigation","authors":"Guandong Su ,&nbsp;Chen Zhang ,&nbsp;Yizheng Li","doi":"10.1016/j.rser.2025.115781","DOIUrl":"10.1016/j.rser.2025.115781","url":null,"abstract":"<div><div>Resource shortages, energy scarcity, and environmental degradation pose significant challenges to sustainable development, while waste-to-bioenergy technology provides a promising solution to overcome the above challenge. To quantify the associated socioeconomic impact, food waste in Singapore was investigated as a model case to evaluate the resource potential, energy security, and environmental sustainability of the food waste derived biobutanol. Results showed that positive policy interventions reduced food waste generation, but food waste remained reliable bioresource to produce biobutanol despite fluctuations, reducing the reliance of energy system on geo-resources such as petroleum. Biobutanol generated from food waste could function as part of natural gas stock or fulfill the transport energy needs previously satisfied by natural gas, improving energy diversity and security, in addition to decarbonizing energy system by food waste valorization and fossil fuel substitution. Analogous results could be extended to other countries with food waste issues. In conclusion, the waste-to-energy scenario is a sustainable option for food waste management, which synergized energy security, circular economy and decarbonization to reconstruct a sustainable resource-energy-environment nexus with a benign technology node.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"218 ","pages":"Article 115781"},"PeriodicalIF":16.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906507","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}