Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116623
Salman Harasis , Irfan Khan , Ahmed Massoud
Temperature is a critical parameter that significantly influences the performance, lifespan, and safety of lithium-ion batteries. It influences electrochemical reaction kinetics, internal resistance, and lithium inventory, which together determine capacity degradation, cycling efficiency, and state of health. High operating temperatures accelerate degradation by promoting the formation of undesirable byproducts, damaging electrode materials, and increasing the risk of thermal runaway. This paper presents a comprehensive review of LIB behavior under high-temperature conditions, focusing on automotive applications. It investigates the thermal characteristics, degradation mechanisms, and effectiveness of various thermal management strategies. The study distinguishes between hot and cold climatic conditions and examines temperature-induced capacity fade, cyclic degradation, and accelerated calendar aging. It also discusses the implications of high-temperature fast charging, considering both short-term and long-term impacts. Furthermore, temperature-based assessments and comparisons are performed at both the cell and pack levels for different lithium-ion chemistries. The aim is to provide a technical evaluation of the long-term viability of electric vehicles operating in hot and desert climates, to identify existing research gaps, and to highlight emerging directions in high-temperature battery technology.
{"title":"The impact of high ambient temperatures on lithium-ion batteries in electric vehicles: An in-depth review of thermal performance and chemistry-specific response","authors":"Salman Harasis , Irfan Khan , Ahmed Massoud","doi":"10.1016/j.rser.2025.116623","DOIUrl":"10.1016/j.rser.2025.116623","url":null,"abstract":"<div><div>Temperature is a critical parameter that significantly influences the performance, lifespan, and safety of lithium-ion batteries. It influences electrochemical reaction kinetics, internal resistance, and lithium inventory, which together determine capacity degradation, cycling efficiency, and state of health. High operating temperatures accelerate degradation by promoting the formation of undesirable byproducts, damaging electrode materials, and increasing the risk of thermal runaway. This paper presents a comprehensive review of LIB behavior under high-temperature conditions, focusing on automotive applications. It investigates the thermal characteristics, degradation mechanisms, and effectiveness of various thermal management strategies. The study distinguishes between hot and cold climatic conditions and examines temperature-induced capacity fade, cyclic degradation, and accelerated calendar aging. It also discusses the implications of high-temperature fast charging, considering both short-term and long-term impacts. Furthermore, temperature-based assessments and comparisons are performed at both the cell and pack levels for different lithium-ion chemistries. The aim is to provide a technical evaluation of the long-term viability of electric vehicles operating in hot and desert climates, to identify existing research gaps, and to highlight emerging directions in high-temperature battery technology.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116623"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789216","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}
Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116620
Zhen Wang , Renze Xu , Mengmeng Liu
Pure hydrogen direct reduction (H2-DR) is poised to be the cornerstone technology for deep decarbonization of the iron and steel sector to attain low-carbon development in the context of emissions peak and carbon neutrality goals. Unlike conventional hydrogen-rich CO-H2 reduction, pure H2-DR presents unique thermodynamic and kinetic characteristics, alongside distinct engineering challenges. This work provides a critical review of the fundamental differences between pure H2 and CO/CO-H2 mixtures in reducing iron oxides, highlighting the endothermic nature and superior kinetics of H2 reactions. The historical development and current status of industrial projects employing 100 % H2 are systematically analyzed, with them being categorized into fluidized bed and shaft furnace routes. Furthermore, this study identifies and elaborates on the pivotal scientific bottlenecks—such as morphological evolution and sticking mechanisms—and technical hurdles—including low-grade ore adaptation and heat supply strategies—that must be overcome to realize commercial-scale pure H2-DR. Finally, a targeted research agenda aimed at accelerating the development of a sustainable and economically viable pure hydrogen ironmaking ecosystem is proposed. This review distinguishes itself by focusing exclusively on the 100 % H2 pathway, offering strategic insights for future fundamental research and process development.
{"title":"Towards a 100 % hydrogen-driven direct reduction ironmaking future: A critical review on kinetics, bottlenecks, and research priorities","authors":"Zhen Wang , Renze Xu , Mengmeng Liu","doi":"10.1016/j.rser.2025.116620","DOIUrl":"10.1016/j.rser.2025.116620","url":null,"abstract":"<div><div>Pure hydrogen direct reduction (H<sub>2</sub>-DR) is poised to be the cornerstone technology for deep decarbonization of the iron and steel sector to attain low-carbon development in the context of emissions peak and carbon neutrality goals. Unlike conventional hydrogen-rich CO-H<sub>2</sub> reduction, pure H<sub>2</sub>-DR presents unique thermodynamic and kinetic characteristics, alongside distinct engineering challenges. This work provides a critical review of the fundamental differences between pure H<sub>2</sub> and CO/CO-H<sub>2</sub> mixtures in reducing iron oxides, highlighting the endothermic nature and superior kinetics of H<sub>2</sub> reactions. The historical development and current status of industrial projects employing 100 % H<sub>2</sub> are systematically analyzed, with them being categorized into fluidized bed and shaft furnace routes. Furthermore, this study identifies and elaborates on the pivotal scientific bottlenecks—such as morphological evolution and sticking mechanisms—and technical hurdles—including low-grade ore adaptation and heat supply strategies—that must be overcome to realize commercial-scale pure H<sub>2</sub>-DR. Finally, a targeted research agenda aimed at accelerating the development of a sustainable and economically viable pure hydrogen ironmaking ecosystem is proposed. This review distinguishes itself by focusing exclusively on the 100 % H<sub>2</sub> pathway, offering strategic insights for future fundamental research and process development.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116620"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789303","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}
Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116598
Zhihua Deng , Bin Miao , Qihong Chen , Jian Chen , Chengguang Tong , Hao Liu , Deendarlianto , Suwarno , Haijiang Wang , Siew Hwa Chan
Proton Exchange Membrane Fuel Cells (PEMFCs) represent a pivotal technology for sustainable energy conversion in automotive, portable, and stationary applications due to their high efficiency, rapid start-up capability, and near-zero emissions. However, widespread commercialization remains severely constrained by uncertainties related to operational durability, cost, and reliability. Consequently, accurate degradation prediction and remaining useful life estimation methods have become critical for facilitating predictive maintenance, which can improve reliability, and reduce lifecycle costs. This review synthesizes recent advances in PEMFCs prognostics, which integrate fundamental degradation mechanisms. Degradation mechanisms are categorized into irreversible and reversible mechanisms. In particular, the review provides protection measures against irreversible and reversible degradation. Subsequently, the review systematically compares various prognostic methods, including model-based model, advanced data-driven model, and hybrid degradation model. Moreover, both publicly available and proprietary PEMFCs durability datasets are systematically collected for the first time. Furthermore, key performance evaluation metrics for fuel cell prognostics models are thoroughly discussed. Finally, significant research challenges and promising future directions are identified, which reveal three key opportunities such as physics-informed artificial intelligence, standardized datasets benchmarking, and real-time onboard health prediction. All in all, this review systematically synthesizes fuel cell degradation mechanisms, prediction methods, aging datasets, and evaluation metrics, which provides a foundational reference to accelerate research in durability enhancement and predictive maintenance for next-generation fuel cell systems.
{"title":"Degradation prediction and remaining useful life estimation of PEMFCs: Mechanisms, methods, datasets, and challenges","authors":"Zhihua Deng , Bin Miao , Qihong Chen , Jian Chen , Chengguang Tong , Hao Liu , Deendarlianto , Suwarno , Haijiang Wang , Siew Hwa Chan","doi":"10.1016/j.rser.2025.116598","DOIUrl":"10.1016/j.rser.2025.116598","url":null,"abstract":"<div><div>Proton Exchange Membrane Fuel Cells (PEMFCs) represent a pivotal technology for sustainable energy conversion in automotive, portable, and stationary applications due to their high efficiency, rapid start-up capability, and near-zero emissions. However, widespread commercialization remains severely constrained by uncertainties related to operational durability, cost, and reliability. Consequently, accurate degradation prediction and remaining useful life estimation methods have become critical for facilitating predictive maintenance, which can improve reliability, and reduce lifecycle costs. This review synthesizes recent advances in PEMFCs prognostics, which integrate fundamental degradation mechanisms. Degradation mechanisms are categorized into irreversible and reversible mechanisms. In particular, the review provides protection measures against irreversible and reversible degradation. Subsequently, the review systematically compares various prognostic methods, including model-based model, advanced data-driven model, and hybrid degradation model. Moreover, both publicly available and proprietary PEMFCs durability datasets are systematically collected for the first time. Furthermore, key performance evaluation metrics for fuel cell prognostics models are thoroughly discussed. Finally, significant research challenges and promising future directions are identified, which reveal three key opportunities such as physics-informed artificial intelligence, standardized datasets benchmarking, and real-time onboard health prediction. All in all, this review systematically synthesizes fuel cell degradation mechanisms, prediction methods, aging datasets, and evaluation metrics, which provides a foundational reference to accelerate research in durability enhancement and predictive maintenance for next-generation fuel cell systems.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116598"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789223","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}
Incorporating hydrogen energy into microgrids (MGs) supports for developing reliable and eco-friendly energy solutions. Effective implementation of hydrogen energy system (HES)-integrated MGs requires a comprehensive understanding of system architecture and energy flow, with energy management systems (EMS) serving as critical components for operational optimization. These strategies are designed to boost the MG's performance during both stable and dynamic conditions, prolong the lifespan of HES components (cutting down on costly replacements and upkeep), and maintain a reliable energy flow by keeping a close eye on hydrogen storage levels. Additionally, they aim to maximize the system's overall efficiency by taking into account the HES's performance metrics. The review also explores multi-objective and multi-time-scale optimization methods for MGs with HESs, balancing technology, economy, and environment, and addressing short-term fluctuations and long-term planning. Ultimately, the paper consolidates the key findings and offers insights into future technical challenges and research directions.
{"title":"A comprehensive review of microgrids with hydrogen energy systems: energy management strategies and system optimization","authors":"Ying Zhu, Xinying Li, Yinjie Ma, Zhi Long, Hanwen Liu, Jiaqiang E","doi":"10.1016/j.rser.2025.116635","DOIUrl":"10.1016/j.rser.2025.116635","url":null,"abstract":"<div><div>Incorporating hydrogen energy into microgrids (MGs) supports for developing reliable and eco-friendly energy solutions. Effective implementation of hydrogen energy system (HES)-integrated MGs requires a comprehensive understanding of system architecture and energy flow, with energy management systems (EMS) serving as critical components for operational optimization. These strategies are designed to boost the MG's performance during both stable and dynamic conditions, prolong the lifespan of HES components (cutting down on costly replacements and upkeep), and maintain a reliable energy flow by keeping a close eye on hydrogen storage levels. Additionally, they aim to maximize the system's overall efficiency by taking into account the HES's performance metrics. The review also explores multi-objective and multi-time-scale optimization methods for MGs with HESs, balancing technology, economy, and environment, and addressing short-term fluctuations and long-term planning. Ultimately, the paper consolidates the key findings and offers insights into future technical challenges and research directions.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116635"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789217","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}
Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116638
Anh Tuan Hoang , Wei-Hsin Chen , María Cruz López-Escalante , M. Olga Guerrero-Pérez , Enrique Rodríguez-Castellón , Jerzy Kowalski , Thanh Tuan Le , Van Ga Bui , Xuan Phuong Nguyen
The growing concerns about greenhouse gas emissions and air pollution from maritime transport have led to increasing interest in researching cleaner and more sustainable fuel options. Thus, this work presented the feasibility, limitations, and potential benefits of using methanol as a sustainable alternative fuel for marine engines. This work examined various methanol production and application aspects, such as production processes, needs, infrastructure and availability, engine performance and emission characteristics, and cost. In the first stage, this work highlighted the importance of methanol in ocean shipping to achieve decarbonization goals and assessed the infrastructural availability for supplying methanol to ships. In the next stage, the methanol production process's input sources and critical characteristics were evaluated entirely. Also, the methanol properties and applications in marine engines under various strategies were comprehensively analyzed. In the third stage, the methanol cost for different production approaches and applications was scrutinized. The problems and possibilities for bunkering and storage facilities when using methanol for maritime engines were also thoroughly analyzed. Finally, the challenges and solutions for the methanol application for marine engines were critically presented. Overall, the present work provided a comprehensive assessment of the potential role of methanol in the maritime sector, aiming to establish sustainable maritime practices. More importantly, this work intends to inform policymakers, academics, and industry stakeholders about the prospects and challenges of using methanol as an alternative fuel for marine engines with a view to the decarbonization strategy and Sustainable Development Goals of the maritime sector.
{"title":"Methanol for decarbonization of the maritime sector: From ideological strategy to practical solutions","authors":"Anh Tuan Hoang , Wei-Hsin Chen , María Cruz López-Escalante , M. Olga Guerrero-Pérez , Enrique Rodríguez-Castellón , Jerzy Kowalski , Thanh Tuan Le , Van Ga Bui , Xuan Phuong Nguyen","doi":"10.1016/j.rser.2025.116638","DOIUrl":"10.1016/j.rser.2025.116638","url":null,"abstract":"<div><div>The growing concerns about greenhouse gas emissions and air pollution from maritime transport have led to increasing interest in researching cleaner and more sustainable fuel options. Thus, this work presented the feasibility, limitations, and potential benefits of using methanol as a sustainable alternative fuel for marine engines. This work examined various methanol production and application aspects, such as production processes, needs, infrastructure and availability, engine performance and emission characteristics, and cost. In the first stage, this work highlighted the importance of methanol in ocean shipping to achieve decarbonization goals and assessed the infrastructural availability for supplying methanol to ships. In the next stage, the methanol production process's input sources and critical characteristics were evaluated entirely. Also, the methanol properties and applications in marine engines under various strategies were comprehensively analyzed. In the third stage, the methanol cost for different production approaches and applications was scrutinized. The problems and possibilities for bunkering and storage facilities when using methanol for maritime engines were also thoroughly analyzed. Finally, the challenges and solutions for the methanol application for marine engines were critically presented. Overall, the present work provided a comprehensive assessment of the potential role of methanol in the maritime sector, aiming to establish sustainable maritime practices. More importantly, this work intends to inform policymakers, academics, and industry stakeholders about the prospects and challenges of using methanol as an alternative fuel for marine engines with a view to the decarbonization strategy and Sustainable Development Goals of the maritime sector.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116638"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789224","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}
Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116595
Soumya Basu, Takaya Ogawa, Manisha Das
This study develops two prospective hydrogen market indices for India—green (GrH) and grey (GyH)—and examines their time–frequency co-movements with international catalyst metal (ICM) markets between January 2019 and September 2023, a period marked by the COVID-19 demand shock and the Russia–Ukraine supply shock. Using wavelet coherence analysis, we uncover distinct patterns of stability and volatility across hydrogen pathways and catalyst markets.
For green hydrogen, GrH shows sustained long-run in-phase co-movements with copper and cobalt, as well as significant coherence with platinum and iridium. These results suggest that targeted hedges against selected ICM indices could stabilize GrH pricing and de-risk the deployment of proton-exchange and anion-exchange membrane technologies. Grey hydrogen, by contrast, exhibits long-run anti-phase relationships with iron, zinc, and aluminium, along with only sporadic coherence with nickel, underscoring weaker hedgeability for SMR/WGS pathways. Mid-to long-run coherence with ruthenium points to a potential—but critical raw material (CRM) dependent—hedging strategy.
The findings highlight that India's current reliance on grey hydrogen is vulnerable to catalyst-metal volatility, while green hydrogen pathways offer more favorable long-term market alignment. From a policy perspective, the results call for: (i) aligning green hydrogen exposure with Cu/Co and PGM indices while managing PGM supply risk, and (ii) designing liberalized market mechanisms to convert grey hydrogen's anti-phase catalyst ties into investable, in-phase linkages.
Beyond India, the proposed framework offers a transferable methodology for assessing hydrogen–metal interactions in other developing economies, informing investors, policymakers, and catalyst R&D on building resilient, shock-robust hydrogen markets in developing and emerging economies.
{"title":"Time-frequency connectedness of hydrogen markets and catalyst indices: A framework for resilient hydrogen transitions","authors":"Soumya Basu, Takaya Ogawa, Manisha Das","doi":"10.1016/j.rser.2025.116595","DOIUrl":"10.1016/j.rser.2025.116595","url":null,"abstract":"<div><div>This study develops two prospective hydrogen market indices for India—green (GrH) and grey (GyH)—and examines their time–frequency co-movements with international catalyst metal (ICM) markets between January 2019 and September 2023, a period marked by the COVID-19 demand shock and the Russia–Ukraine supply shock. Using wavelet coherence analysis, we uncover distinct patterns of stability and volatility across hydrogen pathways and catalyst markets.</div><div>For green hydrogen, GrH shows sustained long-run in-phase co-movements with copper and cobalt, as well as significant coherence with platinum and iridium. These results suggest that targeted hedges against selected ICM indices could stabilize GrH pricing and de-risk the deployment of proton-exchange and anion-exchange membrane technologies. Grey hydrogen, by contrast, exhibits long-run anti-phase relationships with iron, zinc, and aluminium, along with only sporadic coherence with nickel, underscoring weaker hedgeability for SMR/WGS pathways. Mid-to long-run coherence with ruthenium points to a potential—but critical raw material (CRM) dependent—hedging strategy.</div><div>The findings highlight that India's current reliance on grey hydrogen is vulnerable to catalyst-metal volatility, while green hydrogen pathways offer more favorable long-term market alignment. From a policy perspective, the results call for: (i) aligning green hydrogen exposure with Cu/Co and PGM indices while managing PGM supply risk, and (ii) designing liberalized market mechanisms to convert grey hydrogen's anti-phase catalyst ties into investable, in-phase linkages.</div><div>Beyond India, the proposed framework offers a transferable methodology for assessing hydrogen–metal interactions in other developing economies, informing investors, policymakers, and catalyst R&D on building resilient, shock-robust hydrogen markets in developing and emerging economies.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116595"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789298","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}
Pub Date : 2025-12-18DOI: 10.1016/j.rser.2025.116559
Deepak Rathod , Lata Gidwani
Accurate density forecasting and uncertainty quantification of wind power generation are critical to the reliable integration of wind power energy into reality. These methods are used to provide the full probability distribution of wind power production while accounting for uncertainties and variability. Despite approaches to density forecasting and uncertainty quantification, forecasting wind power generation remains challenging with definitive boundaries due to inherent limitations of weather forecasts, difficulties in modeling wind, and a lack of high-quality historical data. This study reviews the literature to summarize and highlight the newest developments in wind power forecasting. Specifically, this review compiles 127 largely peer-reviewed articles published from 2010 to 2025 and analyzes available information on density forecasting for wind energy production. In this review, the methods summarized and discussed can be categorized into deterministic and probabilistic forecasting methods, focusing on short- and long-term forecasting methods. This review highlights the key advantages, disadvantages, and potential drawbacks with recommendations provided to enhance wind power generation and use of density forecasting and uncertainty quantification methods, as well as advanced data preprocessing techniques and deep learning networks (e.g., Deep Neural Network (DNN), Deep Belief Network (DBN), Convolutional Neural Network (CNN), Spiking Neural Networks (SNN)) including model configurations with the assistance of metaheuristics (e.g., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Cuckoo Search (CS)). Furthermore, this study highlights the emerging role of Explainable Artificial Intelligence (XAI) techniques—including SHAP, LIME, and attention mechanisms—for improving model interpretability and transparency, which are vital for operational trust and decision-making in wind power systems. After thorough analysis, this paper articulates the limitations of current forecasting models and methods for wind energy production and seeks to use density forecasting frameworks and uncertainty quantification methods to improve the accuracy, reliability, and robustness of wind power forecasting systems.
{"title":"A literature review based on density forecasting and uncertainty quantification of wind power generation","authors":"Deepak Rathod , Lata Gidwani","doi":"10.1016/j.rser.2025.116559","DOIUrl":"10.1016/j.rser.2025.116559","url":null,"abstract":"<div><div>Accurate density forecasting and uncertainty quantification of wind power generation are critical to the reliable integration of wind power energy into reality. These methods are used to provide the full probability distribution of wind power production while accounting for uncertainties and variability. Despite approaches to density forecasting and uncertainty quantification, forecasting wind power generation remains challenging with definitive boundaries due to inherent limitations of weather forecasts, difficulties in modeling wind, and a lack of high-quality historical data. This study reviews the literature to summarize and highlight the newest developments in wind power forecasting. Specifically, this review compiles 127 largely peer-reviewed articles published from 2010 to 2025 and analyzes available information on density forecasting for wind energy production. In this review, the methods summarized and discussed can be categorized into deterministic and probabilistic forecasting methods, focusing on short- and long-term forecasting methods. This review highlights the key advantages, disadvantages, and potential drawbacks with recommendations provided to enhance wind power generation and use of density forecasting and uncertainty quantification methods, as well as advanced data preprocessing techniques and deep learning networks (e.g., Deep Neural Network (DNN), Deep Belief Network (DBN), Convolutional Neural Network (CNN), Spiking Neural Networks (SNN)) including model configurations with the assistance of metaheuristics (e.g., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Cuckoo Search (CS)). Furthermore, this study highlights the emerging role of Explainable Artificial Intelligence (XAI) techniques—including SHAP, LIME, and attention mechanisms—for improving model interpretability and transparency, which are vital for operational trust and decision-making in wind power systems. After thorough analysis, this paper articulates the limitations of current forecasting models and methods for wind energy production and seeks to use density forecasting frameworks and uncertainty quantification methods to improve the accuracy, reliability, and robustness of wind power forecasting systems.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116559"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789219","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}
Liquid Organic Hydrogen Carriers (LOHCs) are promising for safe and reversible hydrogen storage, yet their large-scale adoption is constrained by costly catalysts and harsh operating conditions. While chemo-catalytic conversion of plastic waste into arenes and cycloalkanes has recently emerged as a dual solution for plastic pollution and hydrogen storage, a systematic evaluation of heterogeneous catalysts in this context is lacking. This review addresses this gap by critically examining catalyst design strategies, structure–property–function relationships, and mechanistic insights relevant to LOHC production from plastic waste. Unlike prior reviews centred on pyrolysis or conventional hydrogenation, we highlight advances in active-site engineering and durability optimization, outline persistent challenges, and propose directions for integrating waste valorization with sustainable hydrogen storage.
{"title":"Heterogeneous catalysis for the production of LOHCs from plastic Waste: Enabling circular hydrogen solutions","authors":"Senthil Murugan Arumugam, Vandit Vijay, Ashish Bohre","doi":"10.1016/j.rser.2025.116634","DOIUrl":"10.1016/j.rser.2025.116634","url":null,"abstract":"<div><div>Liquid Organic Hydrogen Carriers (LOHCs) are promising for safe and reversible hydrogen storage, yet their large-scale adoption is constrained by costly catalysts and harsh operating conditions. While chemo-catalytic conversion of plastic waste into arenes and cycloalkanes has recently emerged as a dual solution for plastic pollution and hydrogen storage, a systematic evaluation of heterogeneous catalysts in this context is lacking. This review addresses this gap by critically examining catalyst design strategies, structure–property–function relationships, and mechanistic insights relevant to LOHC production from plastic waste. Unlike prior reviews centred on pyrolysis or conventional hydrogenation, we highlight advances in active-site engineering and durability optimization, outline persistent challenges, and propose directions for integrating waste valorization with sustainable hydrogen storage.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116634"},"PeriodicalIF":16.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789220","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}
Pub Date : 2025-12-17DOI: 10.1016/j.rser.2025.116604
Arnau Aliana , Tuomas Vanhanen , Georgios Mavromatidis
Bottom-up energy system models play a key role in supporting policy development. Therefore, understanding how policy instruments are integrated within these models is essential for shaping effective energy policies, particularly in emerging areas like sector coupling. Nevertheless, current literature lacks a comprehensive mapping of how policies are represented in bottom-up energy models.
To address this gap, this study reviews a representative sample of recent modelling studies with a strong policy representation and focus. It specifically examines the types of instruments modelled, how scenarios are constructed, the indicators used to assess policy performance and the treatment of sector coupling.
The review reveals that nearly all the analysed studies include CO2 pricing, followed by financial incentives, bans, and technology/sector performance standards. Additionally, over half of the studies examine policy instruments in isolation, lacking a more integrated policy mix approach. Scenario-building approaches are split between solution analysis and solution discovery, with some studies exploring more innovative methods beyond traditional scenario analysis. Regarding indicators, the majority of studies focus on CO2 emissions and system costs, with limited attention to cost distribution and social impacts. Finally, while sector coupling is recongised in most studies, specific policies to facilitate it are rarely addressed.
Based on these findings, this study provides recommendations for model developers to advance beyond currently established practices, while being aware of the capabilities and limitations of bottom-up energy system models.
{"title":"Bridging policy and modelling: A review of policy representation in bottom-up energy system models","authors":"Arnau Aliana , Tuomas Vanhanen , Georgios Mavromatidis","doi":"10.1016/j.rser.2025.116604","DOIUrl":"10.1016/j.rser.2025.116604","url":null,"abstract":"<div><div>Bottom-up energy system models play a key role in supporting policy development. Therefore, understanding how policy instruments are integrated within these models is essential for shaping effective energy policies, particularly in emerging areas like sector coupling. Nevertheless, current literature lacks a comprehensive mapping of how policies are represented in bottom-up energy models.</div><div>To address this gap, this study reviews a representative sample of recent modelling studies with a strong policy representation and focus. It specifically examines the types of instruments modelled, how scenarios are constructed, the indicators used to assess policy performance and the treatment of sector coupling.</div><div>The review reveals that nearly all the analysed studies include CO<sub>2</sub> pricing, followed by financial incentives, bans, and technology/sector performance standards. Additionally, over half of the studies examine policy instruments in isolation, lacking a more integrated policy mix approach. Scenario-building approaches are split between solution analysis and solution discovery, with some studies exploring more innovative methods beyond traditional scenario analysis. Regarding indicators, the majority of studies focus on CO<sub>2</sub> emissions and system costs, with limited attention to cost distribution and social impacts. Finally, while sector coupling is recongised in most studies, specific policies to facilitate it are rarely addressed.</div><div>Based on these findings, this study provides recommendations for model developers to advance beyond currently established practices, while being aware of the capabilities and limitations of bottom-up energy system models.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"229 ","pages":"Article 116604"},"PeriodicalIF":16.3,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789299","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}
Pub Date : 2025-12-17DOI: 10.1016/j.rser.2025.116611
Pengfei Duan , Xiaoyu Zhao , Jinxue Hu , Kang Li , Qingwen Xue , Xiaodong Cao , Yanmin Wang , Bingxu Zhao , Chenyang Zhang , Xiaoyang Yuan
Against the background of accelerated transformation of the global energy structure towards decarbonization and cleanliness, Integrated Energy Systems (IES) has achieved rapid development, but at the same time, it is also facing a number of challenges and problems that need to be solved. High-precision multi-energy load forecasting, as the basic guarantee for stable operation and demand response of IES system, has become a hot direction of current research. This study aims to sort out and analyze the research lineage and development trend of multi-energy load forecasting in the context of IES. First, the development history and research hotspots of multi-energy load forecasting were reviewed by analyzing the keyword co-occurrence of related literature with the help of CiteSpace software. Second, it systematically summarizes the latest progress in the application of artificial intelligence (AI) algorithms in this field, focuses on the analysis of methods and techniques to improve the prediction accuracy, and explores the coupling relationship and interdependence mechanism between different energy loads. It has been shown that feature extraction, data preprocessing, and model optimization strategies play a key role in improving prediction performance. Finally, this paper further explores the potential and application prospects of emerging AI methods in addressing the challenges of multi-energy load forecasting in IES, providing theoretical support and reference directions for related research.
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