Sustainable Energy Grids & Networks最新文献

Coordinated curtailment of uncontrollable distributed energy resources in isolated power systems 孤立电力系统中不可控分布式能源的协同弃电

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.segan.2026.102124

Phivos Therapontos , Savvas Panagi , Charalambos A Charalambous , Petros Aristidou

{"title":"Coordinated curtailment of uncontrollable distributed energy resources in isolated power systems","authors":"Phivos Therapontos , Savvas Panagi , Charalambos A Charalambous , Petros Aristidou","doi":"10.1016/j.segan.2026.102124","DOIUrl":"10.1016/j.segan.2026.102124","url":null,"abstract":"<div><div>The escalating integration of renewable energy sources (RES) into isolated, low-inertia power systems presents considerable challenges to maintaining frequency stability. To preserve operational security, system operators often impose stringent requirements that can necessitate RES curtailment, particularly during periods of low demand. While such measures predominantly affect large-scale distributed energy resources (DERs), prolonged curtailment scenarios may also compel output reductions from numerous small-scale, often uncontrollable, DERs (UDERs). Prevailing control strategies for UDERs typically rely on the deployment of dedicated control and communication hardware at each UDER site, incurring significant capital expenditure and implementation complexity. This paper introduces a novel methodology for the coordinated curtailment of UDERs, which circumvents the need for such supplementary equipment. The proposed approach utilizes the system frequency as an implicit communication conduit, leveraging the inherent active power-frequency (P-f) response capabilities of UDER inverters. A data-driven framework is employed to optimize a global active power-frequency reduction characteristic, tailored from historical operational data. This characteristic is subsequently implemented in a decentralized manner by individual UDERs, thereby effectively mitigating investment costs and cybersecurity vulnerabilities associated with conventional control architectures. The performance and efficacy of the proposed methodology are demonstrated through dynamic simulations on a model of the isolated, low-inertia power system of Cyprus.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102124"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The allocation of system costs: Future-proofed methodologies for decarbonising European power sectors 系统成本的分配：面向未来的欧洲电力部门脱碳方法

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-02-02 DOI: 10.1016/j.segan.2026.102143

José Pablo Chaves Ávila , Paolo Mastropietro , Matteo Troncia , Pedro González , Tomás Gómez San Román

{"title":"The allocation of system costs: Future-proofed methodologies for decarbonising European power sectors","authors":"José Pablo Chaves Ávila , Paolo Mastropietro , Matteo Troncia , Pedro González , Tomás Gómez San Román","doi":"10.1016/j.segan.2026.102143","DOIUrl":"10.1016/j.segan.2026.102143","url":null,"abstract":"<div><div>The increased use of renewable energy sources, among other factors, is causing system costs to grow quickly in European power sectors, especially those related to frequency control and congestion management. Currently, most European countries allocate these costs to consumers using simplistic methodologies, either via network tariffs or specific volumetric charges. These methodologies require urgent reform. This article reviews the economic theory and European experiences regarding the allocation of system costs and puts forward a comprehensive high-level proposal to improve the design of these charges. Balancing capacity costs should be partially embedded in the imbalance price, with price caps limiting the possibility of very high prices during periods of low imbalance volumes. Congestion management costs, like network expansion costs, are driven by transmission capacity scarcity and should be recovered through network tariffs. Any system costs that cannot be allocated according to cost causality should be recovered through stabilised residual charges that do not distort the efficient signals sent by cost-reflective charges and prices. Discounts and exemptions for certain categories of end users should only apply to these residual charges. The impact of this proposal has been tested in a case study based on the Spanish power system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102143"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Changing the paradigm of distribution networks planning and operation: A systematic review of the distributed energy resources impact 改变配电网规划和运行模式：分布式能源影响的系统回顾

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-02 DOI: 10.1016/j.segan.2025.102070

Lovro Lukač, Tomislav Antić, Tomislav Capuder

{"title":"Changing the paradigm of distribution networks planning and operation: A systematic review of the distributed energy resources impact","authors":"Lovro Lukač, Tomislav Antić, Tomislav Capuder","doi":"10.1016/j.segan.2025.102070","DOIUrl":"10.1016/j.segan.2025.102070","url":null,"abstract":"<div><div>The connection of new distributed energy resources (DER) is recently being delayed by the system operators primarily due to the approach where each connection request is separately assessed. The lack of coordination between connection requests is making the process time-consuming and also creating virtual congestion in the network, hindering further investments. With the development of advanced analytical tools and increased observability, Distribution System Operators (DSOs) are starting to adopt new planning and operational approaches. Calculating a network’s hosting capacity (HC) is one of the most investigated planning concepts in modern power systems. However, HC is a conservative approach that considers worst-case scenarios, thereby limiting new connections to the network. This has created the need to develop the dynamic operating envelopes (DOE) concept. DOEs are envisioned as the concept bridging the gap between planning and operational phases, as well as an approach to test the relaxation of conservative fixed connection rules defined in national grid codes. A step further is the near real-time upgrade of DOE defined as P-Q flexibility regions, improving the previous concepts by estimating system-level service provision capabilities. The concept is based on controlling active and reactive power and, consequently, increasing system’s flexibility. The paper contributes in the form of an extensive review of modeling techniques and algorithms, defining the necessary dataset for each of the concepts and models. Furthermore, it discusses the importance of including various technical constraints. Additionally, the paper identifies necessary improvements in data collection to properly assess the value and constraints of DER providing services to the distribution system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102070"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilization of machine learning approaches for enhancing sustainability of electric vehicles with optimization of lithium-ion battery health status 利用机器学习方法优化锂离子电池健康状态，提高电动汽车的可持续性

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-02-02 DOI: 10.1016/j.segan.2026.102144

Yijun Xu , Xuan Zhang , Andong Wang

{"title":"Utilization of machine learning approaches for enhancing sustainability of electric vehicles with optimization of lithium-ion battery health status","authors":"Yijun Xu , Xuan Zhang , Andong Wang","doi":"10.1016/j.segan.2026.102144","DOIUrl":"10.1016/j.segan.2026.102144","url":null,"abstract":"<div><div>Lithium-ion batteries play a central role in electric vehicles (EVs), renewable energy storage, and modern power networks due to their high energy density and efficiency. However, accurately estimating their State of Health (SOH) remains a major challenge, as battery degradation is governed by complex electrochemical and thermal processes influenced by dynamic operating conditions. Although numerous machine learning (ML) approaches have been proposed, many existing methods rely on narrowly scoped datasets, struggle with nonlinear degradation behavior, or lack robustness under real-world variability. These limitations hinder their applicability in large-scale sustainable energy systems. To address these gaps, this study introduces an Ensemble Stacking Regressor designed to provide accurate, generalizable, and noise-resilient SOH estimation. The framework integrates Extreme Gradient Boosting Random Forest (XGBRF), Histogram-based Gradient Boosting Regressor (HGBR), and Extra Trees Regressor (ETR), combined through a Support Vector Regression (SVR) meta-model. Extensive feature extraction from voltage, current, temperature, and internal resistance profiles enables the model to capture multi-dimensional degradation patterns essential for reliable SOH assessment. Experimental results on four MIT battery datasets reveal consistently high accuracy, with R² values above 0.990 and low RMSE, MAE, and RSE metrics. Additional validation on NASA and Oxford datasets confirms strong generalization, while noise-perturbation tests demonstrate high resilience under uncertain measurement conditions. These findings indicate that the proposed framework could enhance battery reliability, support smarter energy management strategies, and strengthen the integration of EVs and storage systems into sustainable energy networks. The model can offer a robust and transferable solution for improving SOH monitoring across diverse applications.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102144"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Moderately extreme weather contributions to power supply inadequacy: Identification using rapid loss-of-load estimation 中等极端天气对电力供应不足的贡献：使用快速负荷损失估计的识别

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-28 DOI: 10.1016/j.segan.2026.102135

Ruijie Chen , Benjamin F. Hobbs , Zongxiang Lu , Ying Qiao

{"title":"Moderately extreme weather contributions to power supply inadequacy: Identification using rapid loss-of-load estimation","authors":"Ruijie Chen , Benjamin F. Hobbs , Zongxiang Lu , Ying Qiao","doi":"10.1016/j.segan.2026.102135","DOIUrl":"10.1016/j.segan.2026.102135","url":null,"abstract":"<div><div>Power systems with high shares of variable renewable energy (VRE) are increasingly vulnerable to extreme weather events. While existing studies typically identify extremes based on meteorological thresholds, such as sustained low wind, low solar radiation, or extreme temperatures, these individual-variable extremes do not always cause the most severe power shortages. In contrast, moderately extreme events, namely compound weather conditions that are not individually severe in any single meteorological variable but jointly create unfavorable electricity supply-demand imbalances, can pose greater risks. To address this gap, this study aims to develop a consequence-based framework that directly identifies weather events causing the most severe power inadequacy risks, rather than relying solely on meteorological definitions of extremes. First, multi-decadal time series of wind, solar, and electricity demand are generated under various future capacity mixes with high VRE penetration. Then, a computationally efficient loss-of-load estimation method is proposed based on algebraic computations rather than mathematical optimization to identify weather events most likely to cause severe power shortfalls. Finally, power shortage risks are evaluated using power system economic dispatch simulations and compared across different types of extreme weather. Simulation results show that the proposed method can estimate loss-of-load with high accuracy and at a speed hundreds of times faster than dispatch optimization models. The case study reveals that identified events often involve moderately low VRE output and moderately high demand occurring simultaneously, resulting in severe shortages. At equal occurrence frequencies, these identified events pose several times the risk to power supply adequacy compared to individual-variable extremes and should be prioritized in power system planning.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102135"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing the stability of DC microgrids with novel negative current injection control to achieve fault ride-through capability 采用新型负注入电流控制提高直流微电网的稳定性，实现故障穿越能力

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.segan.2026.102139

Rohit Kumar Rastogi, Manoj Tripathy

{"title":"Enhancing the stability of DC microgrids with novel negative current injection control to achieve fault ride-through capability","authors":"Rohit Kumar Rastogi, Manoj Tripathy","doi":"10.1016/j.segan.2026.102139","DOIUrl":"10.1016/j.segan.2026.102139","url":null,"abstract":"<div><div>This paper presents a novel Negative Current Injection (NCI)-based control strategy for Distributed Generators (DGs) in DC Microgrids (DC MGs), enhancing system stability and Fault Ride-Through (FRT) capability. Unlike conventional methods such as adaptive droop control or physical Fault Current Limiters (FCLs), the proposed approach directly regulates fault currents without requiring additional hardware, ensuring improved protection and transient performance. It effectively mitigates high fault currents arising from increasing Electric Vehicle (EV) penetration, load fluctuations, and high-impedance faults (HIFs). By integrating seamlessly with existing protection schemes, this method prevents converter overloading and stabilizes bus voltage during both transient and steady-state conditions. Simulation results on a 380 V low-voltage DC (LVDC) microgrid demonstrate that the proposed control limits fault currents to 1.1 pu with a current interruption of no more than 10% of the rated value, while extending FRT time to 100 <span><math><mi>μ</mi></math></span>s before saturation. Moreover, it maintains bus voltage drops within 0.7–0.95 pu across varying fault resistances and locations, showcasing superior performance over existing techniques.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102139"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations 基于多阶段联合学习的微时刻推荐隐私保护能量优化

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-09 DOI: 10.1016/j.segan.2025.102100

Md Mosarrof Hossen , Aya Nabil Sayed , Faycal Bensaali , Armstrong Nhlabatsi , Muhammad E.H. Chowdhury

{"title":"Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations","authors":"Md Mosarrof Hossen , Aya Nabil Sayed , Faycal Bensaali , Armstrong Nhlabatsi , Muhammad E.H. Chowdhury","doi":"10.1016/j.segan.2025.102100","DOIUrl":"10.1016/j.segan.2025.102100","url":null,"abstract":"<div><div>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. Traditional methods often rely on centralized servers to gather and analyze consumption data, which can lead to significant privacy risks as personalized information becomes accessible online. To address this challenge, this study aims to optimize household energy consumption while preserving data privacy by proposing an innovative two-stage Federated Learning (FL) framework that delivers real-time micro-moment-based recommendations. Leveraging FL enables efficient model training across diverse end-user applications while preserving data privacy. The proposed framework employs a two-stage FL training methodology, utilizing the DRED and QUD datasets, and achieves substantial performance improvements. A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. The model achieves robust performance, with approximately 98 % accuracy and F1-score in the second training stage. These findings demonstrate the effectiveness of FL in enabling personalized, privacy-preserving energy recommendations. The novelty of this work lies in combining micro-moment prediction with a multi-stage FL architecture tailored for smart home energy optimization. This study highlights the potential of FL to enhance energy efficiency and sustainability while safeguarding user privacy, paving the way for future research in energy optimization and sustainable living.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102100"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal reactive current compensation for smart grids using linear programming: A novel algorithm with theoretical and real-world data validation 基于线性规划的智能电网最优无功电流补偿：一种具有理论和实际数据验证的新算法

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-11 DOI: 10.1016/j.segan.2025.102081

Francisco G. Montoya , Jorge Ventura , Xabier Prado , Jorge Mira

{"title":"Optimal reactive current compensation for smart grids using linear programming: A novel algorithm with theoretical and real-world data validation","authors":"Francisco G. Montoya , Jorge Ventura , Xabier Prado , Jorge Mira","doi":"10.1016/j.segan.2025.102081","DOIUrl":"10.1016/j.segan.2025.102081","url":null,"abstract":"<div><div>This paper presents an innovative optimization approach for reactive current compensation in modern distribution networks, based on a novel algorithmic solution using linear programming techniques. The proposed method determines optimal shunt compensator parameters by effectively linearizing nonlinear systems in high-harmonic environments without requiring negative reactive elements. Unlike traditional methods, this approach ensures reliable compensator values across diverse operational scenarios, making it particularly valuable for smart grid applications where power quality and energy efficiency are crucial. The theoretical framework is validated through comprehensive mathematical analysis and simulations, complemented by a real-world case study using data from an actual installation. Results demonstrate the method’s effectiveness in handling non-sinusoidal conditions through both theoretical cases and actual power system measurements. Furthermore, a parametric analysis of the real-world data reveals a key practical insight: a reduced-order compensator, targeting only the most dominant harmonics, can achieve nearly all of the source current reduction provided by a full compensator, thus offering an optimal trade-off between cost and performance. This research contributes to power systems theory by providing a computationally efficient and flexible approach for power quality enhancement in modern distribution systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102081"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A risk-optimized pre-disaster defense strategy for island integrated energy systems based on energy storage configuration 基于储能配置的海岛综合能源系统风险优化灾前防御策略

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.segan.2026.102155

Dongyue Zhou, Xueping Pan, Jinpeng Guo, Xiaorong Sun, Yongkai Wei

{"title":"A risk-optimized pre-disaster defense strategy for island integrated energy systems based on energy storage configuration","authors":"Dongyue Zhou, Xueping Pan, Jinpeng Guo, Xiaorong Sun, Yongkai Wei","doi":"10.1016/j.segan.2026.102155","DOIUrl":"10.1016/j.segan.2026.102155","url":null,"abstract":"<div><div>The unique natural environment of islands and the increasing frequency of extreme disasters, exacerbated by climate change, will inevitably lead to high failure probabilities of Island Integrated Energy Systems (IIES), and deteriorate its inspection and recovery process, thus posing substantial challenges to the operational safety of IIES. To reduce the risk of IIES under typhoon and its secondary disasters, a novel risk-optimized pre-disaster defense strategy is proposed by configuring energy storages (ESs). Firstly, the failure probabilities of IIES are calculated by considering combined effects of typhoon and its secondary disaster, and the cascading failure model is used to evaluate overall failure probability of IIES. Secondly, the risk and resilience of IIES is compared and discussed. Followed by this, a new ES optimal configuration strategy is proposed to minimize the risk of IIES under the combined effects of typhoon and its secondary disasters, which is validated by a test IIES system. Results show that the risk is reduced by 26.4 % after ES deployment, and the overall cost is 15 % and 27 % less than the results of resilience-based optimization strategy. This study contributes to improving the operational safety and risk resistance capability of IIES with reasonable investment.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102155"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time analytical equivalent factor ECMS for multi-mode hybrid electric vehicles 多模混合动力汽车实时分析等效因子ECMS

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-02-06 DOI: 10.1016/j.segan.2026.102145

Wei Wang , Zhenjiang Cai , Yi Tian , Jian Wang

引用次数: 0