Pub Date : 2025-06-11DOI: 10.1016/j.adapen.2025.100226
Rodolfo S.M. Freitas , Zhihao Xing , Fernando A. Rochinha , Roger F. Cracknell , Daniel Mira , Nader Karimi , Xi Jiang
To achieve net zero CO2 emissions by 2050–2060, decarbonising the hard-to-abate sectors such as long-distance, heavy-duty transport is a top priority worldwide. These sectors are particularly challenging to decarbonise due to the use of high-energy-density liquid fossil fuels. In this context, designing low-carbon alternative fuels compatible with existing engines and fuel infrastructures is essential. This work presents an advanced fuel design framework to develop sustainable fuels that meet the high energy density requirements of heavy-duty vehicles. The fuel design approach is built upon a probabilistic perspective by considering a conditional generative model to predict the physicochemical properties of pure compounds and fuel blends with confidence bounds required for decision-making tasks. The probabilistic model is then integrated into an inverse design framework to design fuels with specific requirements. Finally, the fuel design framework is employed to develop new diesel fuel compositions according to the desired targets: ignition quality (cetane number) and sooting tendency (yielding sooting index). The AI-assisted fuel design approach can potentially lead to sustainable liquid fuels that are fully compatible with the existing utilisation equipment and can satisfy the requirements of different application sectors.
{"title":"Pathways to sustainable fuel design from a probabilistic deep learning perspective","authors":"Rodolfo S.M. Freitas , Zhihao Xing , Fernando A. Rochinha , Roger F. Cracknell , Daniel Mira , Nader Karimi , Xi Jiang","doi":"10.1016/j.adapen.2025.100226","DOIUrl":"10.1016/j.adapen.2025.100226","url":null,"abstract":"<div><div>To achieve net zero CO<sub>2</sub> emissions by 2050–2060, decarbonising the hard-to-abate sectors such as long-distance, heavy-duty transport is a top priority worldwide. These sectors are particularly challenging to decarbonise due to the use of high-energy-density liquid fossil fuels. In this context, designing low-carbon alternative fuels compatible with existing engines and fuel infrastructures is essential. This work presents an advanced fuel design framework to develop sustainable fuels that meet the high energy density requirements of heavy-duty vehicles. The fuel design approach is built upon a probabilistic perspective by considering a conditional generative model to predict the physicochemical properties of pure compounds and fuel blends with confidence bounds required for decision-making tasks. The probabilistic model is then integrated into an inverse design framework to design fuels with specific requirements. Finally, the fuel design framework is employed to develop new diesel fuel compositions according to the desired targets: ignition quality (cetane number) and sooting tendency (yielding sooting index). The AI-assisted fuel design approach can potentially lead to sustainable liquid fuels that are fully compatible with the existing utilisation equipment and can satisfy the requirements of different application sectors.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"19 ","pages":"Article 100226"},"PeriodicalIF":13.0,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-11DOI: 10.1016/j.adapen.2025.100227
Fabio Frank, Till Gnann, Daniel Speth, Bastian Weißenburger, Benjamin Lux
The increasing diffusion of electric vehicles contributes to a growing electricity demand in the coming years. At the same time, this integrates millions of mobile storage units into the electricity system, which has a rising need for flexibility to balance the intermittent generation from photovoltaic systems and wind turbines. To capture the potential of electric cars as a flexibility resource, we simulate 7,000 vehicle driving profiles in an agent-based model, generating load profiles as well as charging power and state-of-charge boundaries for the German car fleet, which serve as restrictions in energy system optimization. In a scenario-based study for Germany in 2030 and 2045, we compare the installed electric capacities in the optimized system, depending on whether electric vehicle charging is uncontrolled, controlled, or bidirectional. Here we show that a bidirectionally charged car fleet has the potential to replace 32 GW (84 %) of stationary battery storage and 31 GW (64 %) of hydrogen-fired peaking power plants, while enabling an additional solar power expansion of 7 GW (2 %) until 2045. Notably, implementing vehicle-to-grid can limit hydrogen-fired electricity generation to winter months and enable a shift toward combined heat and power plants. On the demand side, it can reduce the expansion of electrolyzers by 19 GW (28 %) and power-to-heat capacities by 25 GW (60 %). Overall, the integrated energy system can substantially benefit from the implementation of smart and especially bidirectional charging as it lowers the need for future capacity expansion in the electricity system but also in coupled hydrogen and heat systems.
{"title":"Potential impact of controlled electric car charging and vehicle-to-grid on Germany’s future power system","authors":"Fabio Frank, Till Gnann, Daniel Speth, Bastian Weißenburger, Benjamin Lux","doi":"10.1016/j.adapen.2025.100227","DOIUrl":"10.1016/j.adapen.2025.100227","url":null,"abstract":"<div><div>The increasing diffusion of electric vehicles contributes to a growing electricity demand in the coming years. At the same time, this integrates millions of mobile storage units into the electricity system, which has a rising need for flexibility to balance the intermittent generation from photovoltaic systems and wind turbines. To capture the potential of electric cars as a flexibility resource, we simulate 7,000 vehicle driving profiles in an agent-based model, generating load profiles as well as charging power and state-of-charge boundaries for the German car fleet, which serve as restrictions in energy system optimization. In a scenario-based study for Germany in 2030 and 2045, we compare the installed electric capacities in the optimized system, depending on whether electric vehicle charging is uncontrolled, controlled, or bidirectional. Here we show that a bidirectionally charged car fleet has the potential to replace 32 GW (84 %) of stationary battery storage and 31 GW (64 %) of hydrogen-fired peaking power plants, while enabling an additional solar power expansion of 7 GW (2 %) until 2045. Notably, implementing vehicle-to-grid can limit hydrogen-fired electricity generation to winter months and enable a shift toward combined heat and power plants. On the demand side, it can reduce the expansion of electrolyzers by 19 GW (28 %) and power-to-heat capacities by 25 GW (60 %). Overall, the integrated energy system can substantially benefit from the implementation of smart and especially bidirectional charging as it lowers the need for future capacity expansion in the electricity system but also in coupled hydrogen and heat systems.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"19 ","pages":"Article 100227"},"PeriodicalIF":13.0,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.adapen.2025.100225
Dingming Liu, Yupeng Wu
In recent years, significant advancements have been made in thermochromic (TC) window technologies, particularly in vanadium dioxide (VO2)-based TC glazing. Innovations such as integrating pigments with polyurethane (PU) composite coatings have enabled colour modulation and improved colorimetric properties. However, their effects on building energy performance and indoor luminance environment are both critical for occupant comfort, health, and broader energy efficiency goals have been underexplored. This study evaluates conventional and coloured TC windows (blue, red, and grey), fabricated with one to three VO2 layers, focusing both on building energy consumption and daylight performance. TC windows were assessed under three window-to-wall ratios of 30%, 60%, and 90% across three climatic conditions: Changsha, Ankara, and New York. Five key criteria were evaluated: energy savings, daylight availability, glare control, daylight uniformity, and colour quality. A multi-objective analysis revealed that the conventional 2-layer TC (TC2), 3-layer TC (TC3), red 3-layer TC (Red-TC3), and grey 2-layer TC (Grey-TC2) consistently outperformed other variants. These windows achieved up to 14% higher annual energy savings and 5–15% greater daylight availability (UDI300-2000lux) compared to standard double-glazed (DG) windows. The results highlight the strong potential of coloured TC windows as climate-adaptive solutions for reducing building operational energy demand and enhancing indoor environmental quality, contributing to future energy transition and sustainable building practices.
{"title":"Evaluating coloured thermochromic windows for energy efficiency and visual comfort in buildings","authors":"Dingming Liu, Yupeng Wu","doi":"10.1016/j.adapen.2025.100225","DOIUrl":"10.1016/j.adapen.2025.100225","url":null,"abstract":"<div><div>In recent years, significant advancements have been made in thermochromic (TC) window technologies, particularly in vanadium dioxide (VO<sub>2</sub>)-based TC glazing. Innovations such as integrating pigments with polyurethane (PU) composite coatings have enabled colour modulation and improved colorimetric properties. However, their effects on building energy performance and indoor luminance environment are both critical for occupant comfort, health, and broader energy efficiency goals have been underexplored. This study evaluates conventional and coloured TC windows (blue, red, and grey), fabricated with one to three VO<sub>2</sub> layers, focusing both on building energy consumption and daylight performance. TC windows were assessed under three window-to-wall ratios of 30%, 60%, and 90% across three climatic conditions: Changsha, Ankara, and New York. Five key criteria were evaluated: energy savings, daylight availability, glare control, daylight uniformity, and colour quality. A multi-objective analysis revealed that the conventional 2-layer TC (TC2), 3-layer TC (TC3), red 3-layer TC (Red-TC3), and grey 2-layer TC (Grey-TC2) consistently outperformed other variants. These windows achieved up to 14% higher annual energy savings and 5–15% greater daylight availability (UDI<sub>300-2000lux</sub>) compared to standard double-glazed (DG) windows. The results highlight the strong potential of coloured TC windows as climate-adaptive solutions for reducing building operational energy demand and enhancing indoor environmental quality, contributing to future energy transition and sustainable building practices.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100225"},"PeriodicalIF":13.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High-density urban buildings contain substantial thermal mass, storing significant energy and offering notable potential for heating energy savings. However, effectively harnessing this energy remains challenging due to the spatiotemporal variability of heat storage–release behavior in building components, which often misaligns with building operational demands. This study reveals that thermal mass tends to store heat when it is not needed and release it when buildings do not require it, especially in cities where some buildings are only occupied during the day and others at night. To address these challenges, this study proposes a novel thermal mass arrangement strategy, derived from extensive real-world data analysis. Significant variations in component thermal behavior across different operational schedules were first identified from data collected in 76 rooms. Subsequently, key factors influencing these variations were pinpointed using stepwise linear regression, informing optimization strategies developed through simulations. These strategies were then validated in cold regions using conduction transfer function models (error margin of 3.6 %), which confirmed their year-round effectiveness for both individual buildings with distinct occupancy patterns and groups of buildings. The results demonstrate that optimizing thermal mass arrangements tailored to specific building schedules can significantly enhance energy efficiency. Contrary to prior research advocating for the sole increase in thermal mass, this study indicates that without strategic guidelines, such measures may exacerbate thermal utilization inefficiencies, complementing existing research on thermal storage materials in buildings. Reducing excess heat storage is shown to be beneficial for daytime-use buildings, while nighttime-use buildings benefit from storing heat for evening use. Adjusting the quantity and orientation of thermal mass, alongside optimizing operational schedules, achieves 4–12 % energy savings, with greater benefits in high-solar-radiation areas.
{"title":"Enhancing building energy efficiency with thermal mass optimization","authors":"Yichen Han, Zhengyu He, Shuangdui Wu, Yuqiu Liu, Yingkai Lian, Chaohong Wang, Jiajia Feng, Zhengnan Zhou","doi":"10.1016/j.adapen.2025.100224","DOIUrl":"10.1016/j.adapen.2025.100224","url":null,"abstract":"<div><div>High-density urban buildings contain substantial thermal mass, storing significant energy and offering notable potential for heating energy savings. However, effectively harnessing this energy remains challenging due to the spatiotemporal variability of heat storage–release behavior in building components, which often misaligns with building operational demands. This study reveals that thermal mass tends to store heat when it is not needed and release it when buildings do not require it, especially in cities where some buildings are only occupied during the day and others at night. To address these challenges, this study proposes a novel thermal mass arrangement strategy, derived from extensive real-world data analysis. Significant variations in component thermal behavior across different operational schedules were first identified from data collected in 76 rooms. Subsequently, key factors influencing these variations were pinpointed using stepwise linear regression, informing optimization strategies developed through simulations. These strategies were then validated in cold regions using conduction transfer function models (error margin of 3.6 %), which confirmed their year-round effectiveness for both individual buildings with distinct occupancy patterns and groups of buildings. The results demonstrate that optimizing thermal mass arrangements tailored to specific building schedules can significantly enhance energy efficiency. Contrary to prior research advocating for the sole increase in thermal mass, this study indicates that without strategic guidelines, such measures may exacerbate thermal utilization inefficiencies, complementing existing research on thermal storage materials in buildings. Reducing excess heat storage is shown to be beneficial for daytime-use buildings, while nighttime-use buildings benefit from storing heat for evening use. Adjusting the quantity and orientation of thermal mass, alongside optimizing operational schedules, achieves 4–12 % energy savings, with greater benefits in high-solar-radiation areas.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100224"},"PeriodicalIF":13.0,"publicationDate":"2025-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-16DOI: 10.1016/j.adapen.2025.100222
Martin Lindberg, Jennifer Leijon
The aviation sector is investigating opportunities to reduce pollution and to limit the dependence on fossil fuels. The design of new electric and hybrid aircraft requires airport developments to meet the need for charging. This review article provides an overview of recent developments and the latest research and innovation on electrification at and around airports. The paper describes technical innovations in electrified aviation, sustainable aviation fuels, and hydrogen, and the infrastructure needed at airports to meet the future electricity demand of electric aircraft charging. This study finds that plug-in charging of future electric aircraft will lead to elevated fluctuations in electric power demand at airports, while battery swapping has a more constant electricity demand. The review reveals a significant interest in energy storage and renewable energy systems to supply electricity and mitigate peak power at airports, suggesting high potential for batteries and solar power. Hydrogen for airport energy storage could support electric aircraft charging and be used as a fuel for hydrogen-powered aircraft. More research is needed regarding the optimal configuration of airport infrastructure to support electric aircraft development.
{"title":"Electrifying aviation: Innovations and challenges in airport electrification for sustainable flight","authors":"Martin Lindberg, Jennifer Leijon","doi":"10.1016/j.adapen.2025.100222","DOIUrl":"10.1016/j.adapen.2025.100222","url":null,"abstract":"<div><div>The aviation sector is investigating opportunities to reduce pollution and to limit the dependence on fossil fuels. The design of new electric and hybrid aircraft requires airport developments to meet the need for charging. This review article provides an overview of recent developments and the latest research and innovation on electrification at and around airports. The paper describes technical innovations in electrified aviation, sustainable aviation fuels, and hydrogen, and the infrastructure needed at airports to meet the future electricity demand of electric aircraft charging. This study finds that plug-in charging of future electric aircraft will lead to elevated fluctuations in electric power demand at airports, while battery swapping has a more constant electricity demand. The review reveals a significant interest in energy storage and renewable energy systems to supply electricity and mitigate peak power at airports, suggesting high potential for batteries and solar power. Hydrogen for airport energy storage could support electric aircraft charging and be used as a fuel for hydrogen-powered aircraft. More research is needed regarding the optimal configuration of airport infrastructure to support electric aircraft development.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100222"},"PeriodicalIF":13.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-15DOI: 10.1016/j.adapen.2025.100221
Jue Chen , Sven Patrick Mattus , Wenjiong Cao , Dirk Uwe Sauer , Weihan Li
High-fidelity electrochemical-thermal models are essential for performance improvement, charge/discharge strategy optimization, and the safe operation of lithium-ion batteries. However, model performance significantly relies on the accuracy of parameters, whose measurement is limited by laboratory conditions. Non-invasive methods based on relatively accessible current, voltage, and temperature data combined with artificial intelligence are promising for rapid parameterization of battery models. However, the model’s complexity and the data’s poor quality increase the difficulty of applying the methodology. To design a reasonable identification framework and obtain reliable data, the identifiability of model parameters must be analyzed under different operating conditions. This paper develops an identifiability analysis framework to investigate the impact of model parameters on voltage and temperature outputs and the impact of key operating variables, i.e., current rate and ambient temperature. By adjusting operating conditions, the sensitivity of specific parameters can be improved by two orders of magnitude. The results are discussed in detail concerning the model modeling mechanism and the physical meaning of the parameters, with a focus on improving non-invasive parameterization in terms of experimental design and identification strategy.
{"title":"Global sensitivity analysis towards non-invasive parameterization of the electrochemical-thermal model for lithium-ion batteries","authors":"Jue Chen , Sven Patrick Mattus , Wenjiong Cao , Dirk Uwe Sauer , Weihan Li","doi":"10.1016/j.adapen.2025.100221","DOIUrl":"10.1016/j.adapen.2025.100221","url":null,"abstract":"<div><div>High-fidelity electrochemical-thermal models are essential for performance improvement, charge/discharge strategy optimization, and the safe operation of lithium-ion batteries. However, model performance significantly relies on the accuracy of parameters, whose measurement is limited by laboratory conditions. Non-invasive methods based on relatively accessible current, voltage, and temperature data combined with artificial intelligence are promising for rapid parameterization of battery models. However, the model’s complexity and the data’s poor quality increase the difficulty of applying the methodology. To design a reasonable identification framework and obtain reliable data, the identifiability of model parameters must be analyzed under different operating conditions. This paper develops an identifiability analysis framework to investigate the impact of model parameters on voltage and temperature outputs and the impact of key operating variables, i.e., current rate and ambient temperature. By adjusting operating conditions, the sensitivity of specific parameters can be improved by two orders of magnitude. The results are discussed in detail concerning the model modeling mechanism and the physical meaning of the parameters, with a focus on improving non-invasive parameterization in terms of experimental design and identification strategy.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100221"},"PeriodicalIF":13.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-14DOI: 10.1016/j.adapen.2025.100223
Zixin Jiang , Xuezheng Wang , Han Li , Tianzhen Hong , Fengqi You , Ján Drgoňa , Draguna Vrabie , Bing Dong
Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.
{"title":"Physics-informed machine learning for building performance simulation-A review of a nascent field","authors":"Zixin Jiang , Xuezheng Wang , Han Li , Tianzhen Hong , Fengqi You , Ján Drgoňa , Draguna Vrabie , Bing Dong","doi":"10.1016/j.adapen.2025.100223","DOIUrl":"10.1016/j.adapen.2025.100223","url":null,"abstract":"<div><div>Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100223"},"PeriodicalIF":13.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-28DOI: 10.1016/j.adapen.2025.100219
Zi-Tong Zhao , Jie Ding , Geng Luo , Bo-Yuan Wang , Han-Jun Sun , Bing-Feng Liu , Guang-Li Cao , Mei-Yi Bao , Nan-Qi Ren , Ji-Wei Pang , Shan-Shan Yang
Dark fermentation has been widely regarded and appraised as an efficient and green route for biohydrogen production. Lignocellulosic biomass is a readily available and abundant feedstock that could be used as a sustainable feedstock for biohydrogen generation. However, low yield of biohydrogen is an inherent issue of the bioprocess restricting its further development towards commercial margins. Recently, the supplement of nano-additives has aroused more attention as a process improvement strategy because of their ability to accelerate process performance and their strengths of low energy consumption and easy operation. Nevertheless, the utilization of nanomaterials for biomass fermentation is still in its infancy. Here we review and evaluate the feasibility of nanotechnology in each procedure of biomass to biohydrogen to improve the economic feasibility of the process. Numerous aspects such as the possibility of utilizing nanomaterials as an alternative to chemical pretreatment techniques have been highlighted in this review. Additionally, the effect of these nanostructured materials (e.g., metal-based nanoparticles, nanocomposites, and graphene-based nanomaterials) on biohydrogen fermentation and the potential functional mechanisms were also analyzed in detail. Moreover, the assessment on how the immobilized nanoparticles affect enzymatic efficiency and how well they can block inhibitory chemicals were elaborated. Further, the sustainability of biomass fermentation was assessed in terms of science economics as well as carbon neutrality to improve the overall benefits of the process. Finally, the review suggests ways in which the nano-engineered bioprocesses might be improved, as well as suggested avenues for further research.
{"title":"Current challenges in nano-engineered biomass valorization: A comprehensive review from the whole procedure of biomass fermentation perspective","authors":"Zi-Tong Zhao , Jie Ding , Geng Luo , Bo-Yuan Wang , Han-Jun Sun , Bing-Feng Liu , Guang-Li Cao , Mei-Yi Bao , Nan-Qi Ren , Ji-Wei Pang , Shan-Shan Yang","doi":"10.1016/j.adapen.2025.100219","DOIUrl":"10.1016/j.adapen.2025.100219","url":null,"abstract":"<div><div>Dark fermentation has been widely regarded and appraised as an efficient and green route for biohydrogen production. Lignocellulosic biomass is a readily available and abundant feedstock that could be used as a sustainable feedstock for biohydrogen generation. However, low yield of biohydrogen is an inherent issue of the bioprocess restricting its further development towards commercial margins. Recently, the supplement of nano-additives has aroused more attention as a process improvement strategy because of their ability to accelerate process performance and their strengths of low energy consumption and easy operation. Nevertheless, the utilization of nanomaterials for biomass fermentation is still in its infancy. Here we review and evaluate the feasibility of nanotechnology in each procedure of biomass to biohydrogen to improve the economic feasibility of the process. Numerous aspects such as the possibility of utilizing nanomaterials as an alternative to chemical pretreatment techniques have been highlighted in this review. Additionally, the effect of these nanostructured materials (e.g., metal-based nanoparticles, nanocomposites, and graphene-based nanomaterials) on biohydrogen fermentation and the potential functional mechanisms were also analyzed in detail. Moreover, the assessment on how the immobilized nanoparticles affect enzymatic efficiency and how well they can block inhibitory chemicals were elaborated. Further, the sustainability of biomass fermentation was assessed in terms of science economics as well as carbon neutrality to improve the overall benefits of the process. Finally, the review suggests ways in which the nano-engineered bioprocesses might be improved, as well as suggested avenues for further research.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100219"},"PeriodicalIF":13.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-22DOI: 10.1016/j.adapen.2025.100220
Lingyun Xie , Kui Shan , Hong Tang , Shengwei Wang
Adopting Artificial Intelligence for optimizing building system controls has gained significant attention due to the growing emphasis on building energy efficiency. However, substantial gaps remain between academic research and the practical implementation of AI-based algorithms. Key factors hindering implementation include computational efficiency requirements and concerns about reliability in online applications. This paper addresses these challenges by presenting AI-empowered online control optimization technologies designed for practical implementation. A simplified deep learning-enabled Genetic Algorithm is developed to accelerate optimization processes, ensuring optimization intervals are short enough for online applications. This algorithm also significantly reduces CPU and memory usage, enabling deployment on miniaturized control station for field implementation. To enhance stability and reliability, a robust assurance scheme is introduced, which switches to expert knowledge-based control under abnormal conditions. Hardware-in-the-loop tests validate the proposed strategy's computation efficiency, control performance and operational robustness using a physical smart station controlling a simulated real-time dynamic cooling system. Test results show that the optimal control strategy achieves 7.66 % energy savings and exhibits strong operational robustness.
{"title":"AI-empowered online control optimization for enhanced efficiency and robustness of building central cooling systems","authors":"Lingyun Xie , Kui Shan , Hong Tang , Shengwei Wang","doi":"10.1016/j.adapen.2025.100220","DOIUrl":"10.1016/j.adapen.2025.100220","url":null,"abstract":"<div><div>Adopting Artificial Intelligence for optimizing building system controls has gained significant attention due to the growing emphasis on building energy efficiency. However, substantial gaps remain between academic research and the practical implementation of AI-based algorithms. Key factors hindering implementation include computational efficiency requirements and concerns about reliability in online applications. This paper addresses these challenges by presenting AI-empowered online control optimization technologies designed for practical implementation. A simplified deep learning-enabled Genetic Algorithm is developed to accelerate optimization processes, ensuring optimization intervals are short enough for online applications. This algorithm also significantly reduces CPU and memory usage, enabling deployment on miniaturized control station for field implementation. To enhance stability and reliability, a robust assurance scheme is introduced, which switches to expert knowledge-based control under abnormal conditions. Hardware-in-the-loop tests validate the proposed strategy's computation efficiency, control performance and operational robustness using a physical smart station controlling a simulated real-time dynamic cooling system. Test results show that the optimal control strategy achieves 7.66 % energy savings and exhibits strong operational robustness.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100220"},"PeriodicalIF":13.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-09DOI: 10.1016/j.adapen.2025.100218
Haowen Liu , Limei Shen , Yunhai Li , Xudong Zhao , Guiqiang Li , Zeyu Liu , Hongxing Yang
Due to structural limitations, the hot and cold sides of conventional thermoelectric coolers (TECs) are fully integrated, making it challenging to directly incorporate TECs into building facades or ceilings to utilize natural ventilation from the building exterior assisting cooling the hot junction. This constraint renders TECs unsuitable for direct application in building façade. To overcome these challenges, an innovative separately-configured thermoelectric cooler (SC-TEC) has been developed. This original design enables the direct integration of TECs into building façades for air conditioning while utilizing the outdoor environment as auxiliary cooling for the TEC's hot side, thereby enhancing overall system performance. Our preliminary study showed that, in a TECs-ceiling system, the novel SC-TEC achieves a 13 % higher cooling capacity compared to a traditional TEC-ceiling. The unit cooling output increased from 16.66 W/m² to 18.82 W/m². And the temperature profiles shows that the cooling capacity of the SC-TEC could be further enhanced with a higher-performance connecting material. Given its advantages, such as no moving parts, noiseless operation, and efficient heat transfer, the SC-TEC has potential to open up new research direction in the building-TEC sector.
{"title":"Investigation of a novel separately-configured thermoelectric cooler: A pathway toward the building integrated thermoelectric air conditioning","authors":"Haowen Liu , Limei Shen , Yunhai Li , Xudong Zhao , Guiqiang Li , Zeyu Liu , Hongxing Yang","doi":"10.1016/j.adapen.2025.100218","DOIUrl":"10.1016/j.adapen.2025.100218","url":null,"abstract":"<div><div>Due to structural limitations, the hot and cold sides of conventional thermoelectric coolers (TECs) are fully integrated, making it challenging to directly incorporate TECs into building facades or ceilings to utilize natural ventilation from the building exterior assisting cooling the hot junction. This constraint renders TECs unsuitable for direct application in building façade. To overcome these challenges, an innovative separately-configured thermoelectric cooler (SC-TEC) has been developed. This original design enables the direct integration of TECs into building façades for air conditioning while utilizing the outdoor environment as auxiliary cooling for the TEC's hot side, thereby enhancing overall system performance. Our preliminary study showed that, in a TECs-ceiling system, the novel SC-TEC achieves a 13 % higher cooling capacity compared to a traditional TEC-ceiling. The unit cooling output increased from 16.66 W/m² to 18.82 W/m². And the temperature profiles shows that the cooling capacity of the SC-TEC could be further enhanced with a higher-performance connecting material. Given its advantages, such as no moving parts, noiseless operation, and efficient heat transfer, the SC-TEC has potential to open up new research direction in the building-TEC sector.</div></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"18 ","pages":"Article 100218"},"PeriodicalIF":13.0,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号