Applied Energy最新文献

{"title":"Effect of exchange current density and charge transfer coefficient on performance characteristics of voltage of alkaline electrolysis","authors":"Nur Nadhirah Syafiqa Binti Mohammad Musa ,&nbsp;Alhassan Salami Tijani","doi":"10.1016/j.apenergy.2025.126186","DOIUrl":"10.1016/j.apenergy.2025.126186","url":null,"abstract":"<div><div>Alkaline electrolysis is an emerging future technology that is very important for developing sustainable renewable energy systems such as hydrogen refuel filling stations and fuel cell (FC) vehicles. Many operating parameters such as exchange current density and charge transfer coefficient (CTC) contribute to the current voltage characteristics of alkaline electrolysis. This research aims to investigate the effect of operating parameters on the performance of alkaline electrolysis. In comparison with the cathode characteristics, it was observed that at exchange current density of <span><math><mn>3.15</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>7</mn></mrow></msup><mspace></mspace><mi>A</mi><mo>/</mo><msup><mi>cm</mi><mn>2</mn></msup></math></span>, the activation overvoltage was found to be 0.39 V, whereas at exchange current density of <span><math><mn>1</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>3</mn></mrow></msup><mspace></mspace><mi>A</mi><mo>/</mo><msup><mi>cm</mi><mn>2</mn></msup></math></span>, the activation overvoltage was observed to be 0.24 V, which corresponds to about a 38 % reduction in activation overvoltage for the cathode electrode. The most interesting observation of the findings is that the results of CTC produced at the anode electrode are higher than the cathode electrode at the same exchange current density.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126186"},"PeriodicalIF":10.1,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134541","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 review on pyrolysis and coking of liquid hydrocarbons in heated pipe","authors":"Haowen Li ,&nbsp;Hao Lan ,&nbsp;Yonghui Sun ,&nbsp;Qianshi Song ,&nbsp;Xiaohan Wang ,&nbsp;Fan Li ,&nbsp;Weigang Zhang","doi":"10.1016/j.apenergy.2025.126159","DOIUrl":"10.1016/j.apenergy.2025.126159","url":null,"abstract":"<div><div>Pyrolysis coking of hydrocarbon fuels in heated pipe has attracted extensive attention in regenerative cooling technology, ethylene cracking industry and combustion engine. The reactor geometry, feedstock types, and product detection and characterization mean of concern are abstracted from engineering practice. Liquid hydrocarbon produces small molecules of alkanes, alkenes and aromatics by gas phase pyrolysis, then transforms into coke through chemical vapor deposition. Due to the extremely low partial pressure of carbon on coke surface, the process from hydrocarbon gas to solid coke was modeled into a pseudo-homogeneous process. In order to realize the dynamic simulation of the coking process, researchers found the characteristic time of gas-phase reaction was much shorter than that of the surface reaction. Therefore, the corresponding coking kinetics model was built based on the specific experimental coking mode and was widely used in the multi-physical field coupling CFD calculation. This study demonstrates that the dynamic evolution of coke morphology plays a pivotal role in governing transient variations of coking rates. Therefore, capturing the instantaneous evolution of coke morphology could serve as a novel approach to constructing unsteady-state coking model. The in-situ carbon protective layer is formed to shield catalytic sites and precursors, addressing the challenges of poor adhesion between coatings and substrates, as well as the tendency of coatings to delamination. Moreover, coke-removal coatings that catalyze carbon conversion and enable online de-coking show significant potential for development. Additionally, the introduction of functional additives—such as O₂, CO₂, syngas, ammonia, alcohols, and furans—represents an emerging direction for suppressing coke formation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126159"},"PeriodicalIF":10.1,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134542","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":"Superior energy management for fuel cell vehicles guided by improved DDPG algorithm: Integrating driving intention speed prediction and health-aware control","authors":"Chunchun Jia ,&nbsp;Wei Liu ,&nbsp;Hongwen He ,&nbsp;K.T. Chau","doi":"10.1016/j.apenergy.2025.126195","DOIUrl":"10.1016/j.apenergy.2025.126195","url":null,"abstract":"<div><div>Despite the significant advantages of fuel cell (FC) vehicles in reducing urban air pollution and extending driving range, effectively managing their internal energy systems remains a major challenge. To maximize the operational efficiency and lifespan of the FC system without compromising fuel economy, this paper proposes a novel predictive energy management paradigm guided by deep reinforcement learning. This strategy innovatively integrates driving intention speed prediction and health-aware control. Specifically, we developed a multi-input bi-directional long short-term memory (BiLSTM) predictor incorporating driving intentions (DI-BiLSTM) using the fuzzy C-means algorithm to enhance the prediction accuracy of future vehicle state trajectories. Downstream control decisions are executed through an improved deep deterministic policy gradient (DDPG) algorithm, which optimizes action space selection based on the degradation characteristics of the FC system. Additionally, during the training and validation phases of the energy management strategy (EMS), we utilized high-quality driving data collected from real bus routes using a high-performance Beidou integrated navigation system, replacing conventional standard driving cycles to enhance the strategy's generalization ability across different scenarios. The results indicate that, compared with conventional prediction model relying solely on historical speed data, the DI-BiLSTM improves prediction accuracy by at least 7.86 % over 3 s, 5 s, and 8 s prediction horizons. Compared with conventional DDPG-based EMS, the proposed EMS increases the average efficiency of the FC system by 32.18 % and extends its lifespan by 16.50 %. In terms of overall driving costs, the proposed EMS improves driving economy by 9.97 % compared with conventional DDPG-based EMS.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126195"},"PeriodicalIF":10.1,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134540","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":"Quantifying the mitigation potential of energy and chemical consumption for a full-scale wastewater treatment plant with deep learning methods","authors":"Chenyang Yu ,&nbsp;Runyao Huang ,&nbsp;Jie Yu ,&nbsp;Shike Zhang ,&nbsp;Sitian Jin ,&nbsp;Qianrong Xu ,&nbsp;Jing Zhang ,&nbsp;Zisheng Ai ,&nbsp;Jacek Mąkinia ,&nbsp;Hongtao Wang","doi":"10.1016/j.apenergy.2025.126123","DOIUrl":"10.1016/j.apenergy.2025.126123","url":null,"abstract":"<div><div>Wastewater treatment plants (WWTPs) play an essential role in urban water system, assisting in realizing urbanization and sustainable development. They consume large amounts of energy and chemicals to remove the wastewater pollutants each year around the world, highlighting an urgent need to explore and discover the energy and chemical saving potential of WWTPs. Recently, deep learning model has attracted increasing attention in various research fields. This study evaluated an Attention optimized bidirectional Gated recurrent unit Long short-term memory (ABGL) model against several benchmark deep learning models. Comparative analysis revealed that while ABGL demonstrates superior performance, the optimal model selection should be carefully evaluated based on data accuracy and computational complexity. Among these models, ABGL showed best accuracy and feasibility for the ability of predicting energy and chemical consumption. The results of the model predictions showed that energy saving and chemical saving of studied WWTP could be as high as 9.21 % and 18.78 %, respectively. Accordingly, the energy intensity of the WWTP should be controlled below 0.28 kWh/m³ and the chemical intensity be controlled below 0.09 kg/m³. Implementation of the deep learning model such as ABGL will assist the decision-makers of WWTPs in optimizing the input efficiency, setting a novel paradigm that guides the smart operations of the whole sector by the state-of-the-art DNN model.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126123"},"PeriodicalIF":10.1,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134544","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":"Spatiotemporal feature encoded deep learning method for rooftop PV potential assessment","authors":"Jian Xu ,&nbsp;Zhiling Guo ,&nbsp;Qing Yu ,&nbsp;Kechuan Dong ,&nbsp;Hongjun Tan ,&nbsp;Haoran Zhang ,&nbsp;Jinyue Yan","doi":"10.1016/j.apenergy.2025.126171","DOIUrl":"10.1016/j.apenergy.2025.126171","url":null,"abstract":"<div><div>Rooftop photovoltaic (PV) systems represent a promising solution for enhancing renewable energy utilization in urban landscapes. Accurate estimation of rooftop PV power generation potential is hindered by shading effects induced by complex urban morphology, which significantly reduce solar irradiance on rooftop surfaces and lead to prediction errors. Traditional shading simulation methods are computationally expensive, underscoring the need for a nuanced equilibrium between computational efficiency and assessment accuracy. In this study, we introduce an innovative deep learning framework that effectively encodes a diverse array of spatiotemporal data sources to accurately predict shadow casting and calculate rooftop PV potential. Specifically, utilizing physics-based ground truth, the incorporation of the U-Net network along with three-dimensional (3D) building specifics, solar resource data, and meteorological parameters enables us to make precise forecasts regarding temporal changes in rooftop shadow patterns. This not only enhances computational efficiency but also ensures a high level of precision in power generation predictions. Experimental assessments carried out in Futian District, Shenzhen, reveal that shading effects alone result in an average energy loss of 5.32 % across rooftops. Moreover, our framework demonstrates superior performance compared to physics-based models, achieving an average Mean Absolute Percentage Error (MAPE) of 2.85 % for annual energy generation potential and a mean Intersection over Union (mIoU) of 89.23 % for shading effect evaluation. In addition, the proposed framework achieves approximately 158<span><math><mo>×</mo></math></span> and 65<span><math><mo>×</mo></math></span> speedup over traditional ray-casting and optimized ray-tracing methods respectively, highlighting its strong suitability for large-scale urban energy evaluations. Our contributions encompass the development of a novel deep learning framework for rooftop PV potential assessment, enhanced computational efficiency in urban analyses, and a resilient generalization capability with high accuracy across various urban settings.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126171"},"PeriodicalIF":10.1,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134538","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":"Review on crossover minimization and catalytic layer-promoted water dissociation in bipolar membranes","authors":"Fanxu Meng ,&nbsp;Dongbo Cheng ,&nbsp;Meng Lin ,&nbsp;Kuichang Zuo ,&nbsp;Zishuai Bill Zhang","doi":"10.1016/j.apenergy.2025.126176","DOIUrl":"10.1016/j.apenergy.2025.126176","url":null,"abstract":"<div><div>Bipolar membranes (BPMs) present a promising solution to reduce the ion and molecule crossover without substantial increases in the full cell voltage within water and CO₂ electrolyzers. The catalytic layer, positioned between an anion and cation exchange membrane within a BPM, is considered as the pivotal component influencing the water dissociation (WD) process and therefore the transmembrane voltage drop. Delving into the catalytic layer, this Review dissects the impact of descriptors, including thickness, electrical conductivity, hydrophilicity, p<em>K</em>_a, oxygenated functional groups, and surface hydroxyl coverage, on WD by coupling reported studies with the Multiphysics model analysis. We observed that the role of oxygenated functional groups towards WD is highly controversial and lacks sufficient experimental evidence. The Review emphasizes the significance of collaborative efforts to develop standardized protocols for BPM fabrications and measurements and advocates the establishment of systematic guidelines on optimizing the catalytic layer to advance BPM technology in the energy field.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126176"},"PeriodicalIF":10.1,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134539","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":"Techno-economic comparison of ammonia cracking and methane pyrolysis for hydrogen turbine integration in clean power generation: Insights from the world's first clean hydrogen portfolio standard market in South Korea","authors":"Hyun Seung Kim","doi":"10.1016/j.apenergy.2025.126170","DOIUrl":"10.1016/j.apenergy.2025.126170","url":null,"abstract":"<div><div>The global transition to low-carbon energy is accelerating, with increasing interest in hydrogen (H₂) turbines as a solution to the intermittency of renewable energy. A stable and efficient H₂ supply is crucial, and ammonia cracking (AC) and methane pyrolysis (MP) are considered economically viable and environmentally sustainable options. This study evaluates optimal clean H₂ production and power generation technologies within the South Korea clean hydrogen portfolio standard (CHPS) bidding market, considering both economic and environmental factors. An integrated H₂ production and power generation system is proposed, and its economic and environmental performance is analyzed. A levelized cost of electricity analysis indicates that both the MP-integrated H₂ turbine (MPHT; $0.344/kWh) and AC-integrated H₂ turbine (ACHT; $0.364/kWh) fall within the CHPS ceiling price, with the MPHT being the more cost-effective option. Both technologies are environmentally cleaner than conventional power sources; however, the ACHT emits 0.16 kg CO₂-eq/kWh less, making it the cleaner alternative, whereas the MPHT demonstrates greater resilience to economic uncertainties and shifts in carbon policy. Both technologies are viable within the South Korea CHPS bidding market. This study supports the development of sustainable energy policies and informs technology selection by assessing the competitiveness and feasibility of H₂-based power generation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126170"},"PeriodicalIF":10.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125153","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 critical review on the multidimensional complexity of sustainable energy development","authors":"Yu Qian,&nbsp;Zeshui Xu,&nbsp;Yong Qin,&nbsp;Xunjie Gou","doi":"10.1016/j.apenergy.2025.126194","DOIUrl":"10.1016/j.apenergy.2025.126194","url":null,"abstract":"<div><div>Energy issues occupy a very important place in the process of sustainable development, so policymakers should actively promote the development of sustainable energy development (SED) and be alert to the far-reaching implications that research and practice in this field may have on reality. As an interdisciplinary science, SED has obvious multiple attributes, which means that energy activities under the sustainable development transition are complex and difficult. Hence, this study attempts to present its multidimensionality from different perspectives to provide a clear and guiding intellectual framework for corresponding practical actions. To this end, we critically review the research in this field based on the selected relevant literatures. We find that the SED measurement system has been developed primarily on the basis of the economic, social and environmental dimensions, with a progressively stronger emphasis on the technological and institutional dimensions. Meanwhile, measuring the performances in terms of energy security, energy equity, energy sustainability and human well-being for particular objects is the main purpose of applying various SED indicator sets. The multidimensionality of SED is also manifested as the fact that its realization pathways can be divided into four interrelated dimensions: traditional fossil energy, alternative energy, pollution prevention and control, and energy mix. In addition, we believe that many methodologies in operations research have great potential to address the challenges posed by the multidimensional complexity of SED, including multi-criteria decision making, multi-objective optimization, data envelopment analysis, etc. To overcome the confusion and chaos caused by multidimensionality, future research also needs to focus on portraying the variability of SED in specific contexts so as to generate targeted and effective development strategies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126194"},"PeriodicalIF":10.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144130882","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":"Explorative application of discrete Bayesian networks as surrogate models for energy systems analysis","authors":"Rainer Kelk ,&nbsp;Luca Podofillini ,&nbsp;Vinh N. Dang ,&nbsp;Evangelos Panos","doi":"10.1016/j.apenergy.2025.126146","DOIUrl":"10.1016/j.apenergy.2025.126146","url":null,"abstract":"<div><div>This work investigates data-based discrete Bayesian Belief Networks (BBNs) as surrogate energy system models for result analysis and interactive analyses, such as what-if analyses. A simplified version of the Swiss TIMES (STEM) model, referred to as STEM-lite, is used for demonstration. A method to optimize the BBN model is devised, based on performance metrics related to the accuracy of the BBN predictions, calculated over data records unseen by the BBN in the training phase. Further validation of the BBN on a set of seven scenarios yielded an average relative error below 2 %, suggesting adequate performance as surrogate model. The application of the surrogate BBN model is demonstrated to highlight its benefits, which include enabling interactive analysis (supported by the visualization of key variables, their relationships and interactions), fast and intuitive uncertainty propagation, and support for goal-driven analysis (backward reasoning from outcomes to the inputs that produce these outcomes). The surrogate BBN presented here was developed to elaborate the methods for constructing, validating, and using BBN models for energy systems analysis and to demonstrate the benefits of such a model; at this stage, this model is not intended for energy systems and economics policy discussions. For practical applications, future work is needed to reduce the number of data records to construct the BBN, to introduce the option to treat the time dependence of the input variables, and to allow for larger BBN models (involving more variables) that reflect the increasing complexity of energy systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126146"},"PeriodicalIF":10.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144130884","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":"Optimizing renewable energy integration pathways: Inter-regional coordination and storage in India's power sector","authors":"Nikhil Thejesh Venkataramana ,&nbsp;Tejal Kanitkar ,&nbsp;Venkatasailanathan Ramadesigan ,&nbsp;Rangan Banerjee","doi":"10.1016/j.apenergy.2025.126134","DOIUrl":"10.1016/j.apenergy.2025.126134","url":null,"abstract":"<div><div>India's rapid economic growth and ambitious renewable energy (RE) targets require modeling frameworks capable of capturing the complexities of high RE integration. This study develops a capacity-expansion and dispatch model with a 15-min resolution for India's Western (WR) and Southern (SR) Regions, which together represent over half of the nation's electricity demand, covering 592 million people and 59 % of India's Gross Domestic Product. We examine multiple scenarios for RE integration, including the operationalization of India's policy for Renewable Purchase Obligations (RPO). The analysis considers capacity constraints on coal and hydro power, the role of battery storage, and two RPO compliance frameworks: one demanding each region individually meet its RE requirement (layered) and another allowing the WR + SR system to fulfill the target collectively (centralized). Results show that regional and inter-regional coordination reduces system costs and boosts RE penetration compared to purely state-based dispatch. Limiting coal or hydro expansions to pipeline projects increases reliance on battery storage, raising costs under current assumptions. When solar is paired with large-scale storage, RE shares often exceed mandated levels but with higher investment. Under layered compliance, each region expands RE more evenly but may incur larger costs. Centralized compliance concentrates capacity in areas with lower costs yet can introduce equity concerns in some regions. Overall, the findings underscore the importance of coordinated resource planning, robust transmission infrastructure, and adaptable policy mechanisms to meet India's climate objectives. By tailoring RPO strategies to regional resource endowments, India can move toward a cleaner and more reliable power system.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126134"},"PeriodicalIF":10.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125154","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}