Sustainable Energy Grids & Networks最新文献_第6页

Reinforcement learning-based optimal scheduling strategy for charging and discharging of electric vehicle clusters 基于强化学习的电动汽车集群充放电最优调度策略

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-08 DOI: 10.1016/j.segan.2025.102087

Baoqiang Lao , Xu Zhang , Didi Liu , Yanli Zou

{"title":"Reinforcement learning-based optimal scheduling strategy for charging and discharging of electric vehicle clusters","authors":"Baoqiang Lao , Xu Zhang , Didi Liu , Yanli Zou","doi":"10.1016/j.segan.2025.102087","DOIUrl":"10.1016/j.segan.2025.102087","url":null,"abstract":"<div><div>The increasing integration of clustered electric vehicles (EVs) and intermittent renewable energy sources (RES) into power systems presents significant operational challenges to smart grids, notably heightened load fluctuations and reduced grid stability. This paper proposes an intelligent charging-discharging optimization model for EV clusters by leveraging their dual load-storage and spatial transfer characteristics, with EV aggregators (EVAs) acting as the coordinating entity. The model incorporates dynamic electricity pricing, the stochastic nature of RES, the temporal coupling of EV charging constraints, and battery aging effects. To address this stochastic optimization problem, a model-free reinforcement learning-based approximate state Q-learning algorithm is proposed. Through environmental interactions and reward feedback mechanisms, this algorithm enables EVAs to intelligently control the charging and discharging behaviors of EV clusters to dynamically respond to real-time electricity price fluctuations and RES output uncertainties, and ultimately mitigate operational stress on the power grid. While ensuring that the charging demands of EV owners are met, the proposed method achieves coordinated operation among the smart grid, EVAs, and end-users through optimized power scheduling strategies. Finally, comparative experiments with existing algorithms verify that the proposed method has significant advantages in reducing the charging costs of EV users and improving the operational profits of EVAs. Simulation results demonstrate that the proposed algorithm exhibits superior performance: under this algorithm, the monthly service profit of the EVA increases by 9.68 % compared with the unidirectional scheduling algorithm and by 22.97 % compared with the greedy algorithm.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102087"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738363","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

Integration of thermal energy harvesting in smart energy systems 智能能源系统中热能收集的集成

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.2025.102098

Amir Karimdoost Yasuri

{"title":"Integration of thermal energy harvesting in smart energy systems","authors":"Amir Karimdoost Yasuri","doi":"10.1016/j.segan.2025.102098","DOIUrl":"10.1016/j.segan.2025.102098","url":null,"abstract":"<div><div>The rising global demand for energy efficiency and the urgency of climate change mitigation have intensified interest in waste-heat utilization. Thermal Energy Harvesting (TEH) offers a scalable pathway to recover otherwise lost thermal energy and integrate it into Smart Energy Systems (SES). In this study, a unified analytical framework is developed that combines quantitative modeling, literature-derived performance data, and predictive optimization to evaluate TEH performance across industrial, residential, and transportation sectors. Results show that thermoelectric generators achieve efficiencies of 5–8 % under moderate gradients, while organic Rankine cycles reach up to 20 % at higher temperatures. Integrating TEH within SES can enhance overall energy utilization by 10–15 % and reduce CO₂ emissions by approximately 9 %. The analysis identifies that system-level integration—linking material properties, thermodynamic design, and control intelligence—is more decisive for practical performance than isolated device improvements. The paper concludes by outlining research and policy priorities to advance hybridized, intelligent TEH solutions for sustainable and resilient energy infrastructures.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102098"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738366","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

Consensus clustering-based electric vehicle charging considering inaccurate user preferences and efficient charging operation zone 考虑不准确用户偏好和高效充电操作区域的共识聚类电动车充电

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-26 DOI: 10.1016/j.segan.2025.102112

Shicong Zhang , Klaas Thoelen , Mohamed Yasko , Geert Deconinck

{"title":"Consensus clustering-based electric vehicle charging considering inaccurate user preferences and efficient charging operation zone","authors":"Shicong Zhang , Klaas Thoelen , Mohamed Yasko , Geert Deconinck","doi":"10.1016/j.segan.2025.102112","DOIUrl":"10.1016/j.segan.2025.102112","url":null,"abstract":"<div><div>The rapid adoption of electric vehicles (EVs) necessitates smart charging solutions to prevent distribution grid overload. However, existing optimization frameworks often overlook critical real-world factors: (1) behavioral uncertainties from inaccurate user preferences (e.g., energy requirements), and (2) non-negligible energy losses during charging operations. This paper addresses critical inefficiencies in EV charging optimization through data-driven behavioral analysis and operational innovation. Using two real-world datasets—from the EnergyVille smart charging platform and the public ACN dataset at the Caltech campus—we quantify critical estimation gaps in user-provided preferences, such as energy demand and departure time. These genuine behavioral inputs are typically missing from synthetic data. Building on these insights, we develop a consensus-clustering forecasting framework that enhances preference prediction accuracy by 18 % (EnergyVille) and 85 % (ACN) versus user inputs. Furthermore, we propose an efficient charging operation zone (ECOZ), a dynamic constraint model that adapts to nonlinear charging efficiency characteristics. Integrated within a mixed-integer linear programming (MILP) optimization formulation, ECOZ maintains 85 % energy conversion efficiency during power allocation. Through simulation, we demonstrate the effectiveness of the proposed method on real-world data and achieve a 5 % reduction in daily EV charging energy losses compared to unconstrained scheduling approaches.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102112"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884021","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

Capacity allocation of pumped hydro storage under marketization process: A transitional strategy 市场化进程下抽水蓄能容量配置：一种过渡性策略

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-25 DOI: 10.1016/j.segan.2025.102107

Yizhou Feng , Zhi Wu , Chen Chen , Liang Ma , Wei Gu , Suyang Zhou

{"title":"Capacity allocation of pumped hydro storage under marketization process: A transitional strategy","authors":"Yizhou Feng , Zhi Wu , Chen Chen , Liang Ma , Wei Gu , Suyang Zhou","doi":"10.1016/j.segan.2025.102107","DOIUrl":"10.1016/j.segan.2025.102107","url":null,"abstract":"<div><div>To address the challenges posed by renewable energy integration in power systems, China is advancing the development of Pumped Hydro Storage (PHS). However, the rapid growth of PHS installations, coupled with strict regulations and a high reliance on capacity compensation, has led to increasing financial burdens on other utilities. One solution is to reduce PHS’s capacity compensation through its marketization. To this end, a ‘partial-regulated dispatch’ mechanism is proposed as a transitional strategy for gradual marketization. Also, an operational policy analysis framework is proposed based on evaluating dispatch mechanisms and business models. The dispatch mechanism evaluates the capacity support PHS provides to the power system, while the business models focus on enhancing PHS profitability to reduce the dependency on capacity compensation while ensuring long-term economic sustainability. Furthermore, the flexibility of PHS is introduced into the capacity compensation to incentivize PHS to support the power system during transitional stages. This flexibility is mathematically defined using the discrete Minkowski sum, considering both the vibration characteristics of individual units and the unit-commitment of PHS as a whole. The case study shows that through partial-regulated dispatch, PHS can reduce its reliance on capacity compensation by nearly 50 % while ensuring its regulatory service via flexibility compensation. This policy effectively balances economic viability with system support capabilities. Moreover, flexibility compensation provides PHS operators with a risk mitigation strategy in the complex power market environment. Under an appropriate operational strategy and policy incentives, flexibility can be enhanced by nearly 30 % in a fully marketized scenario, thereby contributing to both system stability and operational efficiency.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102107"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926019","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

Dynamic security region modeling via conditional style transfer and causal representation learning 基于条件风格迁移和因果表征学习的动态安全区域建模

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-07 DOI: 10.1016/j.segan.2026.102119

Zixuan Zheng , Yuan Zeng , Junzhi Ren , Chao Qin , Changgang Li , Wei Xu , Weilun Ni

{"title":"Dynamic security region modeling via conditional style transfer and causal representation learning","authors":"Zixuan Zheng , Yuan Zeng , Junzhi Ren , Chao Qin , Changgang Li , Wei Xu , Weilun Ni","doi":"10.1016/j.segan.2026.102119","DOIUrl":"10.1016/j.segan.2026.102119","url":null,"abstract":"<div><div>The increasing complexity of power system operations poses challenges for traditional dynamic security region (DSR) modeling, particularly in critical sample transferability, boundary accuracy, and interpretability. This paper proposes a unified framework integrating conditional style transfer learning (CSTL), deep modeling, and causal inference to enhance DSR characterization across varying scenarios. First, a perturbation-style transfer method using conditional diffusion effectively generalizes critical samples across operating scenarios. Second, a deep feedforward neural network (DFNN) is employed to model complex nonlinear DSR boundaries, aided by a stability margin index for quantitative state assessment. The model achieves high accuracy, low latency, and strong noise robustness, supporting online deployment. Finally, to improve the physical interpretability, we incorporate a causal representation learning mechanism combining inverse probability weighting, doubly robust estimation, conditional shapley values and counterfactual inference. This enables causal attribution of perturbations to boundary variations and supports counterfactual analysis. Validation on the IEEE 39-bus and IEEE 145-bus systems confirms the effectiveness and scalability of the proposed approach.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102119"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926048","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

An optimal peer-to-peer market in energy communities: A game-theoretic approach with replicator dynamics 能源社区中最优点对点市场：具有复制因子动力学的博弈论方法

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-31 DOI: 10.1016/j.segan.2025.102114

Sofía Chacón , Katerine Guerrero , Germán Obando , Andrés Pantoja

{"title":"An optimal peer-to-peer market in energy communities: A game-theoretic approach with replicator dynamics","authors":"Sofía Chacón , Katerine Guerrero , Germán Obando , Andrés Pantoja","doi":"10.1016/j.segan.2025.102114","DOIUrl":"10.1016/j.segan.2025.102114","url":null,"abstract":"<div><div>Energy communities (ECs) enable prosumers, consumers, and distributed energy resources (DERs) to jointly manage energy in a coordinated and economically efficient manner. In this work, we propose an energy management system (EMS) for ECs that integrates a demand response (DR) program with a peer-to-peer (P2P) market based on sealed-bid auctions and continuous Stackelberg dynamics. The buyers determine prices according to their energy demand and risk aversion, and generators decide on the amount of energy to sell based on the rewards received and their associated costs. Methodologically, we develop three algorithms to maximize the welfare of the community. The first algorithm incorporates a DR program and generation constraints to keep the EC competitive with grid prices over time. The second and third algorithms use replicator dynamics (RD) to find equilibria that optimize the system’s welfare, using Lagrangian relaxation (LR) to handle the model constraints. We integrate the models for sellers and buyers via a system of differential equations that simulate a Stackelberg game. Additionally, a filtering mechanism is employed to improve convergence and reduce computation time. We validate the EMS in a case study, showing that the proposed approach achieves greater self-sufficiency compared to a system without demand response and enables better resource management, enhanced fairness, and a more equitable distribution of benefits compared to a non-hierarchical and decoupled model.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102114"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926050","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

Exploring dimensional distinctions of residential heat load profiles using an unsupervised machine learning clustering framework 使用无监督机器学习聚类框架探索住宅热负荷分布的维度差异

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-02 DOI: 10.1016/j.segan.2025.102117

Vasilis Michalakopoulos , Elissaios Sarmas , Viktor Daropoulos , Giannis Kazdaridis , Stratos Keranidis , Vangelis Marinakis , Dimitris Askounis

{"title":"Exploring dimensional distinctions of residential heat load profiles using an unsupervised machine learning clustering framework","authors":"Vasilis Michalakopoulos , Elissaios Sarmas , Viktor Daropoulos , Giannis Kazdaridis , Stratos Keranidis , Vangelis Marinakis , Dimitris Askounis","doi":"10.1016/j.segan.2025.102117","DOIUrl":"10.1016/j.segan.2025.102117","url":null,"abstract":"<div><div>Decarbonizing the heating sector is central to achieving the energy transition, as heating systems provide essential space heating and hot water in residential and industrial environments. A major challenge lies in effectively profiling large clusters of buildings to improve demand estimation and enable efficient Demand Response schemes. This paper addresses this challenge by introducing a novel unsupervised machine learning framework for clustering residential heating load profiles, focusing on natural gas space heating and hot water preparation boilers, while analyzing five different dimensions: boiler usage, heating demand, weather conditions, building characteristics, and user behavior. Three distance metrics, Euclidean Distance, Dynamic Time Warping, and Derivative Dynamic Time Warping, are applied and evaluated using established clustering indices. The proposed method is assessed considering 29 residential buildings in Greece equipped with smart heating controllers throughout a calendar heating season (i.e. 210 days). This study demonstrates that Dynamic Time Warping is demonstrably the most suitable metric. A subsequent correlation analysis of the clustering results from each dimension reveals strong, time-dependent relationships between boiler usage, heat demand and temperature, identifying them as the most important and correlated directions. These findings shed light on heating load behavior, establishing a solid foundation for developing more targeted and effective demand response programs.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102117"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926052","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 novel bilevel model for service restoration in distribution systems integrating technical constraints and the energy market environment 考虑技术约束和能源市场环境的配电系统服务恢复新二层模型

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2025-12-13 DOI: 10.1016/j.segan.2025.102092

Etiane O.P. Carvalho , Wandry R. Faria , Leonardo H. Macedo , Gregorio Muñoz-Delgado , Javier Contreras , Benvindo R. Pereira Junior , João Bosco A. London Junior

引用次数: 0

Validation of a data-driven multi-ancillary services framework for photovoltaic/Storage units via power hardware-in-the-loop testing 通过电力硬件在环测试验证数据驱动的光伏/存储单元多辅助服务框架

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-29 DOI: 10.1016/j.segan.2026.102133

Kalliopi D. Pippi , Georgios C. Kryonidis , Theofilos A. Papadopoulos , Zhiwang Feng , Mazheruddin H. Syed , Graeme M. Burt

{"title":"Validation of a data-driven multi-ancillary services framework for photovoltaic/Storage units via power hardware-in-the-loop testing","authors":"Kalliopi D. Pippi , Georgios C. Kryonidis , Theofilos A. Papadopoulos , Zhiwang Feng , Mazheruddin H. Syed , Graeme M. Burt","doi":"10.1016/j.segan.2026.102133","DOIUrl":"10.1016/j.segan.2026.102133","url":null,"abstract":"<div><div>This paper presents the experimental validation of a unified multi-ancillary services (AS) architecture for distributed photovoltaic–battery energy storage (PV-DBESS) systems using power hardware-in-the-loop (PHiL) testing. The focus is on voltage regulation (VR) and voltage unbalance mitigation (VUM), with full decoupling between the two control schemes to ensure interference-free operation. Experiments are conducted on a small-scale distribution network using a hybrid PHiL setup that combines real-time simulation with physical hardware, bridging the simulation-to-practice gap. A detailed three-phase four-leg converter model with embedded VR and VUM algorithms is implemented in RSCAD, and simplified controllable current source models are also evaluated to balance computational efficiency with accuracy. The results demonstrate that the proposed control strategies effectively mitigate overvoltage and unbalance events across varying operating conditions and network characteristics. The VUM scheme leverages reactive power through virtual damping susceptances, while the VR scheme coordinates active and reactive power to regulate the positive-sequence voltage. Interoperability with conventional constant-power converters is also verified. The study confirms that the proposed AS architecture provides a robust and practical solution for enhancing reliability and hosting capacity in active distribution networks, while indicating its potential suitability for future large-scale real-time studies and integration with advanced grid operation systems, particularly through the use of simplified converter models.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102133"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395523","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

An advanced predictive battery control strategy for plus energy building flexibility: Simulation-based assessment and laboratory experimental setup 一种先进的预测电池控制策略：基于仿真的评估和实验室实验设置

IF 5.6 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2026-03-01 Epub Date: 2026-01-29 DOI: 10.1016/j.segan.2026.102127

Enrico Dalla Maria, Francesco Turrin, Annamaria Belleri, Grazia Barchi

{"title":"An advanced predictive battery control strategy for plus energy building flexibility: Simulation-based assessment and laboratory experimental setup","authors":"Enrico Dalla Maria, Francesco Turrin, Annamaria Belleri, Grazia Barchi","doi":"10.1016/j.segan.2026.102127","DOIUrl":"10.1016/j.segan.2026.102127","url":null,"abstract":"<div><div>Buildings account for 40% of energy use making them central to achieving climate neutrality goals. In this context, energy building flexibility emerges as a key enabler, particularly when combined with the Plus Energy Building (PEB) concept, where buildings generate more renewable energy than they consume annually to achieve climate-neutrality goals. As an energy system, the building can offer demand-side flexibility by responding to external penalty signals such as price, CO<sub>2</sub> emissions or grid congestion, thus enabling system operators to dynamically influence consumption patterns. In this work, we present a predictive advanced PV-battery management strategy in year-long simulations across different scenarios, obtained by combining a reference building archetype, various representative European geo-clusters, and electrical consumption resulting from tailored controls of the thermal assets. The heterogeneous results across geo-clusters underscore the influence of climate, culture, and system sizing on predictive control performance, with findings from the Mediterranean cluster (with expected best case flexibility improvement in the range of 14%). These outcomes motivate the implementation of a laboratory-scale setup to port the proposed control strategies to commercially available devices under real working conditions. We report observations of a year-long monitoring of such a laboratory setup, recording the ability to shift battery stored energy toward high-priced periods, with non-standard induced inverter operations observed 10% of the time, highlighting the system’s responsiveness under real-world conditions.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"45 ","pages":"Article 102127"},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395619","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