International Journal of Electrical Power & Energy Systems最新文献_第4页

Novel Multi-Scale joint approach for estimating Lithium-ion battery model parameters and SOC considering hysteresis effect and temperature

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-18 DOI: 10.1016/j.ijepes.2025.110618

Xinhui Zhang , Wenyuan Bai , Shuyu Xie , Jiatong Wang , Danny Sutanto , Kashem M. Muttaqi

{"title":"Novel Multi-Scale joint approach for estimating Lithium-ion battery model parameters and SOC considering hysteresis effect and temperature","authors":"Xinhui Zhang , Wenyuan Bai , Shuyu Xie , Jiatong Wang , Danny Sutanto , Kashem M. Muttaqi","doi":"10.1016/j.ijepes.2025.110618","DOIUrl":"10.1016/j.ijepes.2025.110618","url":null,"abstract":"<div><div>Precise estimating of the state of charge (SOC) in lithium-ion (Li-ion) batteries is crucial for effective energy management and safety assurance in electric vehicles. This paper proposes a novel multi-scale joint estimation method for model parameters and SOC to enhance estimation accuracy under temperature variations and hysteresis effects. First, an improved second-order RC equivalent circuit model is developed by incorporating temperature dependencies and hysteresis effects, where the hysteresis parameters are calibrated offline using a data-driven approach. Then, the joint estimation approach employs an adaptive forgetting factor recursive least squares (AFFRLS) algorithm to dynamically update model parameters during SOC estimation, thereby maintaining model fidelity across diverse temperature conditions (−10 °C to 50 °C). Finally, an extended Kalman filter (EKF) is implemented for SOC estimation based on the real-time updated model parameters. Experimental validation under DST, US06, and FUDS conditions demonstrates the effectiveness of the proposed method, achieving a maximum voltage prediction error of 0.0650 and a maximum SOC estimation error of 0.0092 across the full temperature range.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110618"},"PeriodicalIF":5.0,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-regional energy sharing approach for shared energy storage and local renewable energy resources considering efficiency optimization

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-18 DOI: 10.1016/j.ijepes.2025.110592

Wenyang Deng , Dongliang Xiao , Mingli Chen , Muhammad Faizan Tahir , Dongrui Zhu

{"title":"Multi-regional energy sharing approach for shared energy storage and local renewable energy resources considering efficiency optimization","authors":"Wenyang Deng , Dongliang Xiao , Mingli Chen , Muhammad Faizan Tahir , Dongrui Zhu","doi":"10.1016/j.ijepes.2025.110592","DOIUrl":"10.1016/j.ijepes.2025.110592","url":null,"abstract":"<div><div>As distributed photovoltaic and shared energy storage systems expanded on the user side, developing an energy-sharing mechanism across different regions became crucial for fully utilizing local renewable energy resources and maximizing the system’s overall economic performance. This paper established a multi-regional energy operator (MREO) model considering shared energy storage, and a two-layer trading and optimization framework based on a master–slave game was developed. Initially, a trading system was devised to evaluate the interests of the power grid, MREO, and end-users. Next, an optimization model was formulated to capture the dynamic interactions between MREO decisions and user responses. The top-layer model was managed by MREO and focused on energy sharing among regions, which is used to set flexible electricity prices according to regional demand and optimize the use of shared energy storage. Meanwhile, the bottom-layer model addressed user demand response, allowing users to modify their energy consumption and select more advantageous trading areas based on information provided by the MREO. Simulation results confirmed that the proposed model accurately evaluated each party’s income, iteratively balanced their interests, and increased economic returns for both users and MREO. Additionally, the proposed approach supported greater local photovoltaic energy consumption, reduced grid load fluctuations, and fostered mutually beneficial outcomes for all stakeholders.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110592"},"PeriodicalIF":5.0,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Search direction optimization of power flow analysis based on physics-informed deep learning 基于物理信息深度学习的电力流分析搜索方向优化

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-17 DOI: 10.1016/j.ijepes.2025.110602

Baoliang Li , Qiuwei Wu , Yongji Cao , Changgang Li

{"title":"Search direction optimization of power flow analysis based on physics-informed deep learning","authors":"Baoliang Li , Qiuwei Wu , Yongji Cao , Changgang Li","doi":"10.1016/j.ijepes.2025.110602","DOIUrl":"10.1016/j.ijepes.2025.110602","url":null,"abstract":"<div><div>Power flow analysis is crucial for obtaining power system operation states and optimizing control measures. The increasing integration of renewable energy sources has resulted in a more complex power system, posing challenges to the computational efficiency and convergence of conventional power analysis methods. Based on the physics-informed deep learning, this paper proposes an optimization scheme for the search direction to improve the performance of power flow analysis. The higher-order information originating from the Taylor series expansion of the power flow equation is utilized to optimize the search direction. The deep belief network is used to establish a nonlinear mapping between the power flow equations and the optimized search direction. Additionally, the physical information of the power system is encoded into the deep learning model to meet the real physical constraints. Case study results show that the proposed scheme contributes to improve the computational efficiency and convergence in power analysis, and is feasible for the scenarios of ill-conditioned power flow.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110602"},"PeriodicalIF":5.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive torque feed-forward control for wind turbine MPPT considering predicted wind speed characteristics

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-17 DOI: 10.1016/j.ijepes.2025.110598

Liangwen Qi , Min Zhao , Songsong Wu , Xiaohan Zhang , Pengfei Meng , Yong Zhao , Wei Deng

{"title":"Adaptive torque feed-forward control for wind turbine MPPT considering predicted wind speed characteristics","authors":"Liangwen Qi , Min Zhao , Songsong Wu , Xiaohan Zhang , Pengfei Meng , Yong Zhao , Wei Deng","doi":"10.1016/j.ijepes.2025.110598","DOIUrl":"10.1016/j.ijepes.2025.110598","url":null,"abstract":"<div><div>The growing inertia exacerbates the conflict between the slow dynamic response of wind turbines and rapidly changing wind speed, thereby diminishing the effectiveness of maximum power point tracking (MPPT). Conventional optimal torque (OT) control exhibits limited MPPT tracking bandwidth under low wind speeds with high frequency due to its exclusive focus on steady-state performance and neglect of dynamic wind characteristics. In this regard, an adaptive feed-forward torque control (AFTC) approach is proposed to dynamically adjust the MPPT tracking bandwidth in response to wind variations. The approach integrates a Kalman observer for aerodynamic torque estimation and employs the Newton-Raphson method to derive real-time wind speed. A single exponential smoothing method predicts future mean wind speed and equivalent turbulence frequency. These predicted values adaptively schedule the feed-forward gain, enabling bandwidth adaptation without altering steady-state equilibrium. Comparative analyses with the conventional OT control and the typical feed-forward control demonstrate that ATFC achieves a better trade-off between the power improvement and torque fluctuations.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110598"},"PeriodicalIF":5.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hierarchical time-varying optimization algorithm for Photovoltaic-energy storage to suppress three-phase imbalances in active distribution networks

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-17 DOI: 10.1016/j.ijepes.2025.110608

Xingxu Zhu , Jiyu Wang , Haozheng Yu , Jie Ma , Junhui Li , Cuiping Li

{"title":"A hierarchical time-varying optimization algorithm for Photovoltaic-energy storage to suppress three-phase imbalances in active distribution networks","authors":"Xingxu Zhu , Jiyu Wang , Haozheng Yu , Jie Ma , Junhui Li , Cuiping Li","doi":"10.1016/j.ijepes.2025.110608","DOIUrl":"10.1016/j.ijepes.2025.110608","url":null,"abstract":"<div><div>For three-phase unbalance problems due to excessive single-phase loads, unbalanced load connections and ground faults, etc. This paper proposes a hierarchical time-varying optimization algorithm for active distribution networks to suppress three-phase voltage imbalance. First, an evaluation index of three-phase voltage unbalance is established, and a time-varying optimization model of the distribution network that includes three-phase unbalance constraints is developed by taking into account the regulation of photovoltaic (PV) and energy storage systems; second, a time-varying optimization method for distribution networks based on voltage measurement feedback is designed, in this method, the sensitivity of PV and energy storage regulation to mitigate three-phase imbalance is calculated based on voltage measurements, the sensitivity related to the three-phase imbalance is decoupled at the boundaries of different zones within the distribution network, this sensitivity can be obtained by combining voltage measurement feedback from within the zones and information exchange between zones; finally, the results are iteratively refined using the distribution network information obtained through measurements, this iterative process achieves a time-varying optimization tracking effect that suppresses three-phase imbalance. The effectiveness and superiority of the proposed algorithm were validated through an IEEE 123–101 node medium–low voltage distribution network case study. The case study results demonstrate that the algorithm can effectively reduce system three-phase voltage imbalance degree.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110608"},"PeriodicalIF":5.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unmasking stealthy attacks on nonlinear DAE models of power grids 揭开电网非线性 DAE 模型隐形攻击的面纱

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-17 DOI: 10.1016/j.ijepes.2025.110569

Abdallah Alalem Albustami , Ahmad F. Taha , Elias Bou-Harb

{"title":"Unmasking stealthy attacks on nonlinear DAE models of power grids","authors":"Abdallah Alalem Albustami , Ahmad F. Taha , Elias Bou-Harb","doi":"10.1016/j.ijepes.2025.110569","DOIUrl":"10.1016/j.ijepes.2025.110569","url":null,"abstract":"<div><div>Smart grids are inherently susceptible to various types of malicious cyberattacks that have all been documented in the recent literature. Traditional cybersecurity research on power systems often utilizes simplified models that fail to capture the interactions between dynamic and steady-state behaviors, potentially underestimating the impact of cyber threats. This paper presents the first attempt to design and assess stealthy false data injection attacks (FDIAs) against nonlinear differential algebraic equation (NDAE) models of power networks. NDAE models, favored in industry for their ability to accurately capture both dynamic and steady-state behaviors, provide a more accurate representation of power system behavior by coupling dynamic and algebraic states. We propose novel FDIA strategies that simultaneously evade both dynamic and static intrusion detection systems while respecting the algebraic power flow and operational constraints inherent in NDAE models. We demonstrate how the coupling between dynamic and algebraic states in NDAE models significantly restricts the attacker’s ability to manipulate state estimates while maintaining stealthiness. This highlights the importance of using more comprehensive power system models in cybersecurity analysis and reveals potential vulnerabilities that may be overlooked in simplified representations. The proposed attack strategies are validated through simulations on the IEEE 39-bus system.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110569"},"PeriodicalIF":5.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flexible robust optimization for Renewable-only VPP bidding on electricity markets with economic risk analysis

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-17 DOI: 10.1016/j.ijepes.2025.110594

Hadi Nemati, Pedro Sánchez-Martín, Lukas Sigrist, Luis Rouco, Álvaro Ortega

{"title":"Flexible robust optimization for Renewable-only VPP bidding on electricity markets with economic risk analysis","authors":"Hadi Nemati, Pedro Sánchez-Martín, Lukas Sigrist, Luis Rouco, Álvaro Ortega","doi":"10.1016/j.ijepes.2025.110594","DOIUrl":"10.1016/j.ijepes.2025.110594","url":null,"abstract":"<div><div>This paper investigates the joint participation of Renewable-only Virtual Power Plants (RVPPs) in the energy and reserve markets while considering the imbalance costs in the balancing market. Existing research on robust optimization typically relies on the well-known parameter called the <em>uncertainty budget</em> to define the level of conservatism. However, this parameter is not defined based on economic factors but rather on the nature of each uncertainty. This work introduces a regret-based flexible robust optimization problem to address this gap, accounting for various sources of uncertainty in energy and reserve prices, as well as the production of non-dispatchable renewable energy sources and demand consumption. The concept of average regret is developed and implemented through a set of mixed-integer linear constraints to help the RVPP operator gain relevant economic insights regarding this parameter. Simulation results demonstrate the applicability of the regret-based robust optimization formulation in determining an interpretable level of conservatism against different uncertainties.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110594"},"PeriodicalIF":5.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resilient unit commitment against extreme cold events considering decision-dependent uncertainty-featured EV demand response

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-16 DOI: 10.1016/j.ijepes.2025.110552

Wenqian Yin , Kun Zhuang , Pengcheng Fan , Zhengyang Sun , Jing Zhu , Jilei Ye

{"title":"Resilient unit commitment against extreme cold events considering decision-dependent uncertainty-featured EV demand response","authors":"Wenqian Yin , Kun Zhuang , Pengcheng Fan , Zhengyang Sun , Jing Zhu , Jilei Ye","doi":"10.1016/j.ijepes.2025.110552","DOIUrl":"10.1016/j.ijepes.2025.110552","url":null,"abstract":"<div><div>With the escalating frequency of extreme cold events, power systems integrating electric vehicles (EVs) will continually confront resource inadequacy challenges due to the changes of temperature-sensitive EV loads. Despite the potential of EV loads offering emergency demand response (DR) for addressing such challenges, the willingness of EVs to respond to DR and the actual response quantity are uncertain. Furthermore, the uncertainty level in EV response varies along with DR incentive decisions, which further aggravates operation challenges. This paper proposes a resilient unit commitment (UC) model for EV-integrated power systems against extreme cold events. Specifically, first, we model how the temperature-sensitive EV charging loads change under extreme cold events considering the actual driving range and air conditioning load in EVs. Then, the inter-coupling relationship between uncertainties in EV response quantity and the DR incentive decisions is modeled. To overcome the limitations of conventional modeling approaches for decision-independent uncertainty, an affine function-based tractable model reformulation is presented addressing decision-dependent uncertainty (DDU) in EV response. Subsequently, we establish the resilient UC model within a two-stage stochastic framework considering temperature-sensitive EV loads and DDU in EVs’ response behaviors. Case studies on a modified IEEE 30-bus system verify the effectiveness of the proposed UC model in cost-efficiently and reliably accommodating increased EV loads under extreme cold events.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110552"},"PeriodicalIF":5.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-16 DOI: 10.1016/j.ijepes.2025.110595

Xueqiang Shen, Jiaxin Wang

{"title":"Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm","authors":"Xueqiang Shen, Jiaxin Wang","doi":"10.1016/j.ijepes.2025.110595","DOIUrl":"10.1016/j.ijepes.2025.110595","url":null,"abstract":"<div><div>This study addresses the multi-objective optimization challenges in seasonal heat-power load distribution for cogeneration units by proposing a multi-objective artificial fish swarm algorithm based on intuitionistic fuzzy entropy (IFEMOAFSA). The algorithm enhances the original intuitionistic fuzzy entropy framework, integrating membership, non-membership, and hesitation degrees to guide fish swarm behavior. It dynamically categorizes swarm particles into three states, improving solution space coverage and priority-based solution identification. Convergence direction is adaptively adjusted using intuitionistic fuzzy entropy, with Pareto frontier solutions determining optimal load allocation. Evaluated via the Zitzler-Deb-Thiele (ZDT) benchmark functions, IFEMOAFSA achieves a 42.63% comprehensive performance improvement over four benchmark algorithms, verified by Mean Inverted Generational Distance (MIGD) and Mean Hypervolume Metric (MHV). A cogeneration unit model incorporating operational characteristics and historical data demonstrates the method’s efficacy: multi-objective balance is maintained across iterations, achieving a 1.41% thermoelectric load increase and 1.54% optimal coal consumption reduction. The algorithm reduces heat/electricity losses and operational costs under diverse conditions while enhancing load utilization rates. These results validate IFEMOAFSA’s effectiveness in solving annual load optimization challenges for cogeneration systems, showing promising applications for similar multi-objective optimization problems requiring dynamic adaptability and robust convergence properties.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110595"},"PeriodicalIF":5.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hydrogen–electric–thermal coupling analysis and validation of superconducting turbo-electric hybrid propulsion system 超导涡轮-电力混合推进系统的氢-电-热耦合分析与验证

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-15 DOI: 10.1016/j.ijepes.2025.110551

Mingliang Bai , Wenjiang Yang , Ruopu Zhang , Zibing Qu , Juzhuang Yan

{"title":"Hydrogen–electric–thermal coupling analysis and validation of superconducting turbo-electric hybrid propulsion system","authors":"Mingliang Bai , Wenjiang Yang , Ruopu Zhang , Zibing Qu , Juzhuang Yan","doi":"10.1016/j.ijepes.2025.110551","DOIUrl":"10.1016/j.ijepes.2025.110551","url":null,"abstract":"<div><div>The superconducting turbo-electric hybrid propulsion system (TEHPS) integrates superconducting technology and hydrogen energy technology, presenting a potential solution to achieve efficient and high-power propulsion. This study focuses on the design of a liquid hydrogen-cooled superconducting TEHPS, incorporating detailed models for key components, including the hydrogen turbine engine, fuel cell, and superconducting machines. A comprehensive hydrogen–electric–thermal (HET) analysis framework is introduced to optimize system fuel and temperature performance, with feasibility and effectiveness evaluated under conservative, baseline, and optimistic 2035 scenarios. Simulation results for typical mission profiles demonstrate that a hybrid propulsion scheme, combining the engine and fuel cell during takeoff, climb, and cruise phases, and utilizing either the engine or fuel cell alone during the descent phase, can effectively balance fuel and coolant demands, leading to a fuel consumption reduction of up to 22.3% in the optimistic scenario. Improvements in component parameters can significantly reduce the powertrain mass, increase power-to-weight ratio and enhance energy conversion efficiency. Under the optimistic scenario, the system achieves a peak power density of 2.15 kW/kg and an energy conversion efficiency of 75%. Furthermore, a scaled ground testbed for the superconducting TEHPS validated the feasibility of cryogenic cooling, superconducting generators, and hybrid-electric distributed propulsion technologies.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110551"},"PeriodicalIF":5.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0