Applied Energy最新文献

{"title":"Multi-view graph contrastive representative learning for intrusion detection in EV charging station","authors":"Yi Li ,&nbsp;Guo Chen ,&nbsp;Zhaoyang Dong","doi":"10.1016/j.apenergy.2025.125439","DOIUrl":"10.1016/j.apenergy.2025.125439","url":null,"abstract":"<div><div>With the rapid proliferation of electric vehicles (EVs), the need to enhance EV charging infrastructure with integrated communication and software functionalities has become crucial. However, this integration also introduces new cybersecurity vulnerabilities, as sensitive data and operational control are increasingly exposed to potential attacks. Traditional intrusion detection systems often struggle with overfitting, low recall, and the scarcity of high-quality labeled data or fail to consider the correlation among different features, challenging the effectiveness of supervised learning approaches. To address these limitations, this paper proposes a novel Multi-View Graph Contrastive Representation Learning (MVGCRL) framework that leverages logs from Hardware Performance Counters (HPCs) collected from Electric Vehicle Supply Equipment (EVSE) and represents them as graph structure data. By constructing graph views for both hardware components and temporal windows, the framework utilizes a Graph Neural Network (GNN) model to capture correlations among various input features in a multi-view manner. This work designed a supervised intrusion detection system (IDS) for multi-class classification. Specifically, our method introduces hybrid graph augmentations through node feature masking and edge weight perturbation, and then employs a novel mask-attention Graph Transformer to capture complex feature correlations. Additionally, MVGCRL is extended to a self-supervised learning version by minimizing the distance between node embeddings and input features, followed by fine-tuning for improved classification. Experiments on real-world datasets demonstrate that our approach outperforms both traditional supervised methods and state-of-the-art self-supervised learning models, offering an effective solution for enhancing cybersecurity in EV charging infrastructures.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125439"},"PeriodicalIF":10.1,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel multivariable prognostic approach for PEMFC degradation and remaining useful life prediction using random forest and temporal convolutional network","authors":"Tian Zhang ,&nbsp;Zhengmeng Hou ,&nbsp;Xiaoqin Li ,&nbsp;Qianjun Chen ,&nbsp;Qichen Wang ,&nbsp;Christian Lüddeke ,&nbsp;Lin Wu ,&nbsp;Xuning Wu ,&nbsp;Wei Sun","doi":"10.1016/j.apenergy.2025.125569","DOIUrl":"10.1016/j.apenergy.2025.125569","url":null,"abstract":"<div><div>Data-driven methods are effective in predicting future degradation trends (FDT) and remaining useful life (RUL) of proton exchange membrane fuel cells (PEMFCs). However, the complex and dynamic degradation behaviour of PEMFCs, influenced by diverse operational variables, poses significant challenges to existing prognostic approaches. This paper proposes a novel multivariable prognostic approach, termed RF-TCN, which combines random forest (RF) with temporal convolutional networks (TCN) to address these challenges. The approach incorporates three key innovations: (1) A hybrid RF and recursive feature elimination (RFE) method is employed to automatically select features most relevant to fuel cell degradation, reducing manual intervention and enhancing input robustness. (2) An improved TCN-based model is developed to effectively capture temporal degradation patterns, enabling accurate FDT and RUL predictions. (3) Particle swarm optimization (PSO) is utilized for automatic hyperparameter configuration, further boosting predictive performance. Empirical validation on ageing durability datasets demonstrates that the RF-TCN approach achieves superior prediction accuracy with selected optimal features and outperforms baseline TCN, CNN, RNN, and existing methods in the literature. This work advances prognostic methodologies, contributing to extending fuel cell lifespan and optimizing control strategies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125569"},"PeriodicalIF":10.1,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bi-level Integrated Electricity and Natural Gas System retrofit planning model considering Carbon Capture, Utilization and Storage","authors":"Ang Xuan,&nbsp;Xinwei Shen,&nbsp;Yangfan Luo","doi":"10.1016/j.apenergy.2025.125476","DOIUrl":"10.1016/j.apenergy.2025.125476","url":null,"abstract":"<div><div>Integrated Electricity and Natural Gas System (IEGS) considers the interactions between electricity and natural gas systems with broad prospects in carbon emission mitigation to achieve the global low-carbon transition, which is an approachable pathway to tap the potential of different energy systems. Concurrently, advancements in technologies such as Carbon Capture, Utilization and Storage (CCUS), Gas-fired Power Generation (GPG), and Power to Gas (PtG) enable the integration of these two large systems, allowing for bi-directional energy flows. This paper proposes an original IEGS retrofit planning model, in which the traditional power plant/gas source (PP/GS) is retrofitted into the carbon capture power plant/carbon capture gas source (CCPP/CCGS) with CCUS and PtG/GPG, as well as the gas pipelines and electricity transmission lines, are considered. Additionally, the IEGS retrofit model employs a bi-level planning strategy to distinguish conflicts of interest between investors and investees. Furthermore, the reformulation and decomposition (R&amp;D) algorithm is developed to tackle the complexities of the bi-level mixed-integer programming problem. Numerical results demonstrate the effectiveness and superiority of the proposed model, showcasing its potential for practical application. Finally, the study analyzes the efficient boundaries associated with carbon price/tax and carbon capture/storage cost, providing valuable insights for policymakers and stakeholders.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125476"},"PeriodicalIF":10.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428816","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":"Experimental and simulation study on internal thermal runaway development drives venting and flammable gas risk evaluate of Lithium-ion battery","authors":"Peiben Wang ,&nbsp;Chengshan Xu ,&nbsp;Jingru Huang ,&nbsp;Mengqi Zhang ,&nbsp;Fachao Jiang ,&nbsp;Xuning Feng","doi":"10.1016/j.apenergy.2025.125545","DOIUrl":"10.1016/j.apenergy.2025.125545","url":null,"abstract":"<div><div>Heat generation and gas venting are the primary characteristics of thermal runaway in lithium-ion batteries. The convective and diffusive properties of the venting gas pose significant challenges for hazard analysis and safety assessment of thermal runaway venting. Quantifying the potential combustion risk associated with the vented flammable gases is crucial for ensuring battery safety. In this study, we investigated the thermal runaway venting behavior of Li(Ni_0.8Co_0.1Mn_0.1)O₂ prismatic cells through experimental and simulation methods. The results indicate that the battery has discharged 4.83 mol of combustible gas. The gas composition mainly consists of H₂ (20.5 %), C₂H₄ (12.5 %), CH₄ (5.5 %), CO (27.9 %), and CO₂ (28.6 %). Gas combustion account for 19.6 % of the total venting time. We propose an internal thermal runaway progression-driven venting and flammable gas risk evaluation model. This model assesses the combustion risk of flammable gases during the venting process and identifies high-risk areas where gas combustion may occur, specifically the area 1 m above the safety valve, which exhibits the highest risk for flammable gas combustion and possesses the greatest explosive power. This research is poised to make a significant contribution to the safe design of battery pack systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125545"},"PeriodicalIF":10.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437321","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":"Parallel-Execute-Based Real-time Energy Management Strategy for FTPSS integrated PV and ESS","authors":"Junhao Li ,&nbsp;Qi Guo ,&nbsp;Xin Wang ,&nbsp;Chunming Tu ,&nbsp;Fan Xiao ,&nbsp;Yuchao Hou ,&nbsp;Xia Shen","doi":"10.1016/j.apenergy.2025.125538","DOIUrl":"10.1016/j.apenergy.2025.125538","url":null,"abstract":"<div><div>Constructing a flexible traction power supply system (FTPSS) integrating railway power conditioner (RPC), energy storage system (ESS), and photovoltaic (PV) is essential to realize low-carbon and economical railway transportation. However, the existing rule-based energy management strategies (EMS) only focus on RPC and ESS, whose applicability and economy are limited for FTPSS accessed PV. In addition, the operational optimization model of FTPSS is complex and data-intensive, resulting in the existing optimization EMS being mostly poor at reliability and timeliness. To this end, a parallel-execute-based real-time EMS for FTPSS integrated ESS and PV is proposed. First, the real-time collaborative management of PV, ESS, and RPC is realized with the improved rule-based EMS. Then, considering the operation cost and the three-phase voltage unbalance rate (TVUR), the multi-objective optimization model of FTPSS is built. Further, a coordination mechanism between the rule-based and optimization EMS is proposed. By executing the rule-based and optimization EMS in parallel and switching their reference commands within the real-time management time threshold, the EMS's reliability, timeliness, and economy performance can be improved simultaneously. Finally, the proposed EMS is verified based on the measured data from a traction station.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125538"},"PeriodicalIF":10.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437322","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":"Online estimation of negative electrode overpotential and detection of lithium plating of batteries using electrochemistry-driven Kalman filter closed-loop framework","authors":"Shaochun Xu ,&nbsp;Chao Lyu ,&nbsp;Dazhi Yang ,&nbsp;Gareth Hinds ,&nbsp;Tu Lan ,&nbsp;Stefano Sfarra ,&nbsp;Hai Zhang ,&nbsp;Weilin Luo ,&nbsp;Dongxu Shen ,&nbsp;Miao Bai","doi":"10.1016/j.apenergy.2025.125487","DOIUrl":"10.1016/j.apenergy.2025.125487","url":null,"abstract":"<div><div>Diagnosing lithium plating in batteries can be achieved by monitoring the polarity of the negative electrode overpotential (NEO), which cannot be directly measured for commercial batteries. The electrochemical models have the ability to calculate the NEO, however, existing methods cannot guarantee estimation accuracy and computational efficiency simultaneously under complex working conditions, limiting their practicality. To address the problem, this work proposed a novel closed-loop NEO estimation framework that combines a simplified electrochemical model with a filtering algorithm. First, a parameter-corrected SP+ model with practical applicability under high C-rate conditions is built. Following that, a closed-loop NEO estimation framework involving the extended Kalman filtering (EKF) is constructed, in that, NEO is treated as the only state variable and adjusted by terminal voltage observations. Then the proposed method is validated experimentally by measuring NEO using a 50-Ah LFP battery with a referenced electrode. Results showed that the accuracy, efficiency, convergence, and robustness can all be guaranteed benefiting from the simplicity of the electrochemical model and the adaptiveness of the EKF, and the proposed method is well-suited for online monitoring lithium plating in battery energy storage applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125487"},"PeriodicalIF":10.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428809","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":"Optical and simulation investigation of effect of jet-wall interaction on combustion performance of methanol pre-chamber turbulent jet ignition system","authors":"Bin Wang ,&nbsp;Fangxi Xie ,&nbsp;Xiaoping Li ,&nbsp;Beiping Jiang ,&nbsp;Yan Su ,&nbsp;Zhongshu Wang ,&nbsp;Yuhao Liu ,&nbsp;Zhendong Liang","doi":"10.1016/j.apenergy.2025.125533","DOIUrl":"10.1016/j.apenergy.2025.125533","url":null,"abstract":"<div><div>The pre-chamber engine wall's structure has a significant effect on the ignition and combustion performance of pre-chamber turbulent jets. This study identified an abnormal combustion phenomenon in the case of secondary jets, which was characterized by the pre-chamber pressure rise rate exceeding 30 times the normal rate owing to pre-chamber jet impingement on the wall. To investigate this phenomenon, we examined the causes of ignition events resulting from the interaction between pre-chamber jets and the wall by using a visualized constant-volume combustion chamber experimental platform and by conducting CFD simulations. The results indicated that for a certain range of the wall-nozzle distance, pre-chamber jet impingement on the wall is advantageous for reducing the ignition delay and increasing the combustion speed. Under lean burn conditions, pre-chamber jets impinging on the wall led to both direct and delayed wall-impinging ignition owing to the wall structure. Pre-chamber jet impingement on concave or flat wall surfaces generated more intense impinging turbulence than that on convex wall surfaces, resulting in the improvement of both ignition and flame propagation speeds. Thus, the wall surface at the impingement point of pre-chamber jets should not be convex as this would reduce the jet ignition performance and increase the probability of secondary jet occurrence, leading to irreversible damage to the pre-chamber structure.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125533"},"PeriodicalIF":10.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428808","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":"Out of sight, out of mind? How electricity (un)reliability shapes residential energy transitions","authors":"Cristina Crespo Montañés ,&nbsp;Isha Ray ,&nbsp;Veronica Jacome","doi":"10.1016/j.apenergy.2025.125497","DOIUrl":"10.1016/j.apenergy.2025.125497","url":null,"abstract":"<div><div>Social norms on household energy consumption practices have been historically fostered through ideas of comfort, cleanliness and modernity, underpinned by reliable and affordable energy services. Contemporary discourses on energy transitions require households to conform to new expectations of “sustainable” living, calling for energy users to participate in the electrification of energy end-uses, provided sufficient economic incentives. Yet, a combination of emotional and social responses to the increased frequency of power outages complicate this account. Despite expectations of consumer cooperation in the clean energy transition, limited research explores how differing capabilities and lived experiences with energy infrastructure modify perspectives on these changes. Through semi-structured interviews with sixty Northern California residents, we explore how residents cope with energy unreliability and whether—or how—they envision transitioning to higher levels of electrification of their homes. By centering users' lived experiences, this work goes beyond formulations of “customer choices” to focus on how everyday energy practices are reimagined in the context of residential electrification policies, climate imperatives, and power outages —or the fear thereof. We argue that the emotional, social, and relational dimensions of grid reliability should complement the predominantly techno-economic lens through which electricity reliability is studied, highlighting the implications of this framing for electricity-intensive residential energy transitions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125497"},"PeriodicalIF":10.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428810","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":"Energy storage in combined gas-electric energy transitions models: The case of California","authors":"Dimitri M. Saad ,&nbsp;Mo Sodwatana ,&nbsp;Evan D. Sherwin ,&nbsp;Adam R. Brandt","doi":"10.1016/j.apenergy.2025.125480","DOIUrl":"10.1016/j.apenergy.2025.125480","url":null,"abstract":"<div><div>California’s vision for a net-zero future by 2045 relies heavily on variable renewable energy systems. Thus, energy storage - particularly long-duration storage - could play a fundamental role in reliably supplying low-carbon electricity. We study energy storage using the BRIDGES model, a combined gas-electric capacity expansion model for California across multiple investment periods (2025-2045), modeled with progressively decreasing carbon emission targets to a zero emissions by 2045. This least-cost optimization model includes renewable gas production via power-to-gas, long-term storage of energy in gaseous form, electric energy storage such as through batteries and hydrogen storage, and renewable energy generation, all with capacity tracking and investment. Multiple scenarios are evaluated to examine the sensitivity of the optimal storage portfolio to system-level and sector-level parameters. The scenario results show that all electric energy storage systems - which vary in storage duration - are deployed and required in a net-zero California in 2045, amounting to around 75 GW of storage capacity. Lithium ion systems make up approximately 80% of this power capacity and supply most short-run storage needs. Hydrogen storage - in the form of a power-to-gas-to-power system - emerges as a replacement to conventional natural gas storage, comprising most of the total energy storage capacity (<span><math><mo>∼</mo></math></span> 4 TWh). This capacity is less than 5% of the current natural gas storage capacity (94 TWh), indicating sufficient room for repurposing part of the gas infrastructure. A demand-side sensitivity analysis proves that higher electricity demand correlates with more builds of Li-ion batteries, while higher industrial heat demand leads to more builds of long-duration storage systems in a net-zero economy. Moreover, power-to-gas systems satisfy part of the industrial heat demand by locally supplying renewable gas, which overtakes the traditional centralized gas storage and transfers through pipelines, casting significant doubts on the future of the large-scale gas infrastructure.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125480"},"PeriodicalIF":10.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428815","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":"State-of-health estimation and knee point identification of lithium-ion battery based on data-driven and mechanism model","authors":"Yulong Ni ,&nbsp;Kai Song ,&nbsp;Lei Pei ,&nbsp;Xiaoyu Li ,&nbsp;Tiansi Wang ,&nbsp;He Zhang ,&nbsp;Chunbo Zhu ,&nbsp;Jianing Xu","doi":"10.1016/j.apenergy.2025.125539","DOIUrl":"10.1016/j.apenergy.2025.125539","url":null,"abstract":"<div><div>Accurate state-of-health (SOH) estimation and knee points identification are crucial for optimizing battery performance and lifecycle management. An SOH estimation method combining an improved Newton-Raphson-based optimizer algorithm for optimizing support vector regression and an adaptive boosting algorithm (INRBO-SVR-AdaBoost) is proposed, as well as a knee point identification method considering failure thresholds based on the maximum vertical distance method. Firstly, three improvements are introduced to enhance the global search ability and convergence speed of the standard NRBO algorithm, enabling the SVR method to obtain optimal parameters. Then, the AdaBoost algorithm is applied to integrate the INRBO-SVR method, improving SOH estimation accuracy. Experimental results show that the INRBO-SVR-AdaBoost method provides higher SOH estimation accuracy than other methods, with root mean square error and mean absolute error both below 0.89 % and 0.75 %, respectively. Secondly, based on the accurate SOH estimation, an empirical model combining a double-exponential and a second-order polynomial (<em>SOH</em>_EM) is constructed, and the maximum vertical distance (<em>VD</em>_max,LCD) between <em>SOH</em>_EM and the linear SOH degradation curve is calculated for different failure thresholds. By computing the maximum vertical distance (<em>VD</em>_max,LKC) between <em>VD</em>_max,LCD and the linear knee point curve for different failure thresholds, the final knee point is identified. Experimental results show that the identified knee points have an error within 46 cycles, with the identification accuracy of the knee points reaching at least 90 %, demonstrating strong flexibility and precision. The proposed high-precision SOH estimation method and flexible knee point identification method have significant guiding implications for battery life prediction and retirement management.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"385 ","pages":"Article 125539"},"PeriodicalIF":10.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421939","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}