Sustainable Energy Grids & Networks最新文献_第2页

Heterogeneous-agent coordinated secure and contribution-aware equilibrium strategy for integrated electricity-gas system: A fully decentralized approach

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-24 DOI: 10.1016/j.segan.2025.101691

Chaoxian Lv , Kang Peng , Qin He , Yuanyuan Chai , Kaiping Qu , Rui Liang

{"title":"Heterogeneous-agent coordinated secure and contribution-aware equilibrium strategy for integrated electricity-gas system: A fully decentralized approach","authors":"Chaoxian Lv , Kang Peng , Qin He , Yuanyuan Chai , Kaiping Qu , Rui Liang","doi":"10.1016/j.segan.2025.101691","DOIUrl":"10.1016/j.segan.2025.101691","url":null,"abstract":"<div><div>The individual voltage level and pressure stability for independent power distribution systems (PDSs) and natural gas systems (NGSs) are crucial for the secure and cost-effective operation of integrated electricity-gas systems (IEGSs). However, the interest coordination of different stakeholders with privacy preservation is challenging. Therefore, the heterogeneous-agent coordinated secure and contribution-aware equilibrium strategy for IEGS with a fully decentralized approach is proposed. The flexible operation of PDS, NGS, and community-integrated energy stations (CIESs) enables bidirectional power interaction between PDS and NGS, enhancing the security of IEGS. This interaction is optimized by integrating diverse demand responses, including interruptible, transferrable, and replaceable loads, to ensure more effective power exchanges. A contribution-aware asymmetric Nash bargaining method is proposed for revenue allocation, determined by the stakeholder contribution degrees calculated through a nonlinear energy sharing mapping method. Additionally, the study employs the adaptive alternating direction method of multipliers (ADMM) to resolve the coordinated secure operation challenges and contribution-aware equilibrium issues among heterogeneous agents, thereby achieving full decentralization of stakeholder collaboration with ensured privacy and operational independence. A numerical study on a modified IEEE 33-bus PDS and 9-node NGS, connecting 2 CIESs, proves the strategy’s efficacy. The proposed strategy boosts voltage by 60.96 % and pressure by 93.33 %. The profit rates of cost for PDS, NGS, CIES1, and CIES2 surge to 198.69 %, 112.55 %, 26.44 %, and 25.78 %.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101691"},"PeriodicalIF":4.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715261","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

Speed-up method to calculate distribution system security region

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-24 DOI: 10.1016/j.segan.2025.101688

Jun Xiao , Ruiwan Liu , Guowei He , Haishen Liang , Kangli Wang

{"title":"Speed-up method to calculate distribution system security region","authors":"Jun Xiao , Ruiwan Liu , Guowei He , Haishen Liang , Kangli Wang","doi":"10.1016/j.segan.2025.101688","DOIUrl":"10.1016/j.segan.2025.101688","url":null,"abstract":"<div><div>The calculation speed is critical for the practical application of the distribution system security region (DSSR). This paper proposes a new method to accelerate DSSR calculation. Firstly, the DSSR models are briefly introduced. Secondly, the influence mechanism of the main transformer capacity on the DSSR is observed and analyzed, forming the theoretical basis for simplifying the computation. Thirdly, a speed-up method based on neglecting the main transformer constraints is proposed. The method includes the calculation formula of the main transformer active capacity, forming main transformer active capacities for common distribution systems in China, and a convenient lookup table-based speed-up process. When the main transformer reaches or exceeds this active capacity condition, it is determined that the main transformer constraints can be ignored in the DSSR modeling, thereby simplifying the model and improving calculation speed. Finally, the proposed method is verified by an extended IEEE-RTBS-BUS4 case and a real distribution system case. The proposed method can accelerate the DSSR calculation by 701 times when it is individually used. The method is further integrated with another method, which combines two speed-up methods for the first time. As a result, the solving efficiency is improved by 6.02 times and 7.43 times, respectively, compared to using the two methods individually, which has achieved the best speed-up effect so far. This study finds that common distribution systems in China mostly satisfy the speed-up condition.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101688"},"PeriodicalIF":4.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705183","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 alternating direction method of multipliers approach for the reconfiguration of radial electrical distribution systems

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-24 DOI: 10.1016/j.segan.2025.101684

Yacine Mokhtari , Patrick Coirault , Emmanuel Moulay , Jérôme Le Ny , Didier Larraillet

{"title":"An alternating direction method of multipliers approach for the reconfiguration of radial electrical distribution systems","authors":"Yacine Mokhtari , Patrick Coirault , Emmanuel Moulay , Jérôme Le Ny , Didier Larraillet","doi":"10.1016/j.segan.2025.101684","DOIUrl":"10.1016/j.segan.2025.101684","url":null,"abstract":"<div><div>The electrical network reconfiguration problem aims to minimize losses in a distribution system by adjusting switches while ensuring the radiality (tree structure) of the network. Although this problem can be formulated as a mixed integer nonlinear program, solving the resulting optimization problem requires significant time and resources. A carefully selected initial solution, which can be identified by appropriate heuristics, reduces the search space, accelerates convergence, and ensures feasibility. This paper introduces two heuristic algorithms based on the Alternating Direction Method of Multipliers (ADMM) to address this problem. These heuristics break down the problem into smaller, more manageable subproblems that can be solved efficiently. Two algorithms are developed: one relies on natural variable substitution, and the other on a previously used relaxation technique. The challenge encountered in previous studies of incorporating radial constraints with ADMM is addressed by redefining the combinatorial subproblem in the projection step of ADMM as a minimum weight rooted arborescence problem, whose solutions are guaranteed to be radial. Convex optimization techniques can then handle the remaining subproblems. The performance of both heuristics is evaluated through numerical experiments on the 33-bus and 70-bus systems, as well as on a real-world electrical network.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101684"},"PeriodicalIF":4.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705184","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

Two-layer eco-driving approach of connected hybrid electric vehicles by convex optimization via signalized intersections

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-22 DOI: 10.1016/j.segan.2025.101687

Qiang Zhang , Jian Xiong , Ningyuan Guo , Zheng Chen , Yuanjian Zhang , Yonggang Liu , Jin Liu

{"title":"Two-layer eco-driving approach of connected hybrid electric vehicles by convex optimization via signalized intersections","authors":"Qiang Zhang , Jian Xiong , Ningyuan Guo , Zheng Chen , Yuanjian Zhang , Yonggang Liu , Jin Liu","doi":"10.1016/j.segan.2025.101687","DOIUrl":"10.1016/j.segan.2025.101687","url":null,"abstract":"<div><div>Developing a sophisticated energy-management-centered eco-driving method can significantly boost the driving economy of vehicles. However, current optimization methods for hybrid electric vehicles (HEV) in multi-traffic-light scenarios still have room to improve energy-saving optimality and computational efficiency. Hence, this paper proposes a two-layer convex approach for the eco-driving of connected HEVs at signalized intersections. In the upper layer, a convex motor-power model is built, and a position constraint within the green-light time window is decided using traffic light information and signal phase-and-timing data. Then, a convex velocity-planning problem to minimize motor energy consumption is formulated and efficiently solved. In the lower layer, the engine's optimal operating line and unified battery-power constraints are introduced, and a series of convexification steps are performed. This enables the establishment of a convex-optimization energy management problem for minimizing fuel consumption, facilitating fast solution. Results show that the proposed method can effectively manage multi-signal scenarios, allowing vehicles to pass through green lights and avoid red-light waits. Regarding motor energy and fuel consumption, it achieves near-optimal results, with a deviation of less than 2 % from the global optimum. The optimization takes only about 1 s (around 1/24000–1/6 to comparative methods’), indicating high computational efficiency.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101687"},"PeriodicalIF":4.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726205","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

Soft open points scheduling in unbalanced active distribution networks based on multi-agent graph reinforcement learning 基于多代理图强化学习的非平衡主动分配网络中的软开放点调度

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-22 DOI: 10.1016/j.segan.2025.101689

Liu Hong, Li Qizhe, Zhang Qiang, Xu Zhengyang, He Xingtang

{"title":"Soft open points scheduling in unbalanced active distribution networks based on multi-agent graph reinforcement learning","authors":"Liu Hong, Li Qizhe, Zhang Qiang, Xu Zhengyang, He Xingtang","doi":"10.1016/j.segan.2025.101689","DOIUrl":"10.1016/j.segan.2025.101689","url":null,"abstract":"<div><div>This paper proposes an innovative unbalanced ADN operation strategy utilizing multi-agent graph reinforcement learning (MAGRL), where SOPs are scheduled to mitigate the three-phase unbalance and minimize system loss. The SOP scheduling problem in unbalanced ADN is modeled as a multi-agent partially observable Markov decision process (POMDP). Then, a direct approach based Backward/Forward Sweep (BFS) power flow model is proposed in our framework to provide precise power flow results within a few iterations to the training environment. The graph convolution networks (GCNs) are embedded in the policy network to further improve the agent capability of learning and capturing spatial correlations and topological linkages among nodes in complex unbalanced ADN, hence promoting the effectiveness of action strategy for the agents. This model has been tested on modified three-phase unbalanced IEEE 123-node system and IEEE 8500-node system. The results illustrate the notable regulation capability of the proposed method for unbalanced ADN.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101689"},"PeriodicalIF":4.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705185","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

Resilience-oriented distributed generation planning of distribution network under multiple extreme weather conditions

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-19 DOI: 10.1016/j.segan.2025.101675

Junji Zhou, Xiong Wu, Xuhan Zhang, Fengshuo Xiao, Yifan Zhang, Xiuli Wang

{"title":"Resilience-oriented distributed generation planning of distribution network under multiple extreme weather conditions","authors":"Junji Zhou, Xiong Wu, Xuhan Zhang, Fengshuo Xiao, Yifan Zhang, Xiuli Wang","doi":"10.1016/j.segan.2025.101675","DOIUrl":"10.1016/j.segan.2025.101675","url":null,"abstract":"<div><div>Planning resilient and elastic distribution networks has become an effective strategy for withstanding extreme weather events. However, conventional research often overlooks the impact of multiple extreme weather conditions and only considers planning for one specific type of extreme weather. This paper proposes a resilience-oriented distributed generation planning approach for distribution networks, which takes into account multiple extreme weather conditions. Firstly, a line fault probability model is established to capture the impact of typhoons, rainstorms, ice and snow weather. Secondly, a fault scenario generation and simplification method based on modified monte carlo simulation and <em>k</em>-means clustering is proposed to ensure the representativeness and computational efficiency of the selected scenarios. Additionally, a two-stage stochastic mixed integer programming model is introduced to enhance system resilience through distributed generation configuration and network topology reconstruction. The first stage focuses on determining the number, location, and size of distributed generation with economic objectives, while the second stage addresses the recovery method after an uncertain extreme event based on the distributed generation configuration obtained in the first stage. The proposed model is applied to modified IEEE 33-bus system and IEEE 123-bus system. Compared with the conventional method, the DG configuration results are consistent and the solution time is reduced by 70–80 %, achieving a balance between accuracy and efficiency. Furthermore, it effectively reduces load shedding by nearly 90 % by optimizing DG utilisation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101675"},"PeriodicalIF":4.8,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679631","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

Large-scale generation of geo-referenced power distribution grids from open data with load clustering

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-17 DOI: 10.1016/j.segan.2025.101678

Alfredo Oneto, Blazhe Gjorgiev, Filippo Tettamanti, Giovanni Sansavini

{"title":"Large-scale generation of geo-referenced power distribution grids from open data with load clustering","authors":"Alfredo Oneto, Blazhe Gjorgiev, Filippo Tettamanti, Giovanni Sansavini","doi":"10.1016/j.segan.2025.101678","DOIUrl":"10.1016/j.segan.2025.101678","url":null,"abstract":"<div><div>The availability of real power distribution grid data is often restricted due to privacy concerns and the lack of digitized representations, limiting spatially-resolved assessments of these systems. This inaccessibility has motivated the development of methods for generating synthetic grids. However, existing methods face challenges such as computational intractability for large-scale zones, restrictive topological assumptions, insufficient representation of electrical components, and inadequate consideration of geographical constraints. This work addresses the challenges by developing a model for the large-scale generation of synthetic geo-referenced low- and medium-voltage grids using publicly accessible data. It comprises a geographic load clustering algorithm, a procedure for generating graphical grid layouts, and a method for selecting operational topologies and line types. The model’s effectiveness and computational performance are demonstrated by generating synthetic low- and medium-voltage grids for Switzerland, with all generated grids made openly available.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101678"},"PeriodicalIF":4.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679628","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

Behavioral analytics for optimized self-scheduling in sustainable local multi-carrier energy systems: A prospect theory approach

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-14 DOI: 10.1016/j.segan.2025.101679

Sobhan Dorahaki , S.M. Muyeen , Nima Amjady , Syed Shuibul Qarnain , Mohamed Benbouzid

{"title":"Behavioral analytics for optimized self-scheduling in sustainable local multi-carrier energy systems: A prospect theory approach","authors":"Sobhan Dorahaki , S.M. Muyeen , Nima Amjady , Syed Shuibul Qarnain , Mohamed Benbouzid","doi":"10.1016/j.segan.2025.101679","DOIUrl":"10.1016/j.segan.2025.101679","url":null,"abstract":"<div><div>The transition towards sustainable energy systems demands innovative solutions to overcome the challenges of integrating diverse energy carriers, fluctuating market dynamics, and operator decision-making complexities. The active involvement of local multi-carrier energy systems (LMCES) as virtual power plants in upstream energy markets is particularly hindered by the limitations of conventional optimization methods, which fail to capture the nuanced behavioral aspects of decision-making. This paper presents a novel prescriptive behavioral analytics framework for LMCES self-scheduling, integrating insights from prospect theory to address the operator’s behavioral tendencies, including loss aversion, subjective risk attitudes, and mental reference points. By embedding these behavioral considerations into a mixed integer linear programming (MILP) model, the proposed approach accounts for real-world decision-making complexities often overlooked in conventional economic theories based on rationality. Comparative analyses demonstrate that the proposed framework not only enhances the modeling of LMCES operators’ decision-making processes but also improves energy scheduling efficiency and supports sustainable energy transitions. The findings provide actionable insights for optimizing LMCES operations, advancing their role in achieving energy sustainability goals.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101679"},"PeriodicalIF":4.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643797","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 scalable energy internet approach for hop regulated peer-to-peer power trading with connectivity and preference constraints

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-13 DOI: 10.1016/j.segan.2025.101668

Neethu Maya , Bala Kameshwar Poolla , Seshadhri Srinivasan , Alessandra Parisio , Narasimman Sundararajan , Suresh Sundaram

{"title":"A scalable energy internet approach for hop regulated peer-to-peer power trading with connectivity and preference constraints","authors":"Neethu Maya , Bala Kameshwar Poolla , Seshadhri Srinivasan , Alessandra Parisio , Narasimman Sundararajan , Suresh Sundaram","doi":"10.1016/j.segan.2025.101668","DOIUrl":"10.1016/j.segan.2025.101668","url":null,"abstract":"<div><div>Incentives to maximize Peer-to-Peer (P2P) power trading and the establishment of consumer-friendly distributed power markets are essential contributions to the decarbonization of the power sector. This paper presents a Connectivity and Preference Constrained Hop-Regulated Approach for Peer-to-Peer Trading (CPHPT) in sparsely connected communities with reduced infrastructure requirements. The CPHPT approach leverages graph theory to optimize P2P subscriber matching by regulating the maximum hops between the nodes in each routed path of P2P exchange. Simulations using real-world datasets in a 10-home community demonstrate that the CPHPT increases community participation by 29.49%, with P2P power exchanges comparable to full connectivity at reduced infrastructure requirements. When scaled to a 100-home community, the CPHPT approach achieves a marginal performance difference of 2.71% compared to full connectivity while lowering the connectivity infrastructure by 93.4%. The CPHPT approach has a mean runtime of 8.9 s for a 3-h window with 30-min intervals in a 100-home community, indicating its scalability and feasibility for real-time implementation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101668"},"PeriodicalIF":4.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704196","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

Extreme value statistics of peak residential electricity demand: Effect of aggregation and moving-average smoothing

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-13 DOI: 10.1016/j.segan.2025.101674

M.W. Jack , M.M. Bandi

{"title":"Extreme value statistics of peak residential electricity demand: Effect of aggregation and moving-average smoothing","authors":"M.W. Jack , M.M. Bandi","doi":"10.1016/j.segan.2025.101674","DOIUrl":"10.1016/j.segan.2025.101674","url":null,"abstract":"<div><div>Understanding the fluctuations in power demand is critical to the integration of variable renewable resources and the design of future electricity grids. We present an approach to determining the full statistical distribution of peak values of power demand based on extreme value statistics. We apply this method to characterizing the tails of the consumer demand distribution and exploring how peak electricity demand scales with aggregation over increasing numbers of consumers and moving-average smoothing at increasing timescales for two very different consumer groups. The results show evidence of fat tail distributions for some consumers. For both consumer groups, extreme values scale as an inverse power law with aggregation over increasing numbers of consumers and as a decaying exponential with the timescale of moving-average smoothing. Peak reduction by moving-average smoothing is much more sensitive to different sets of consumers than aggregation. As smoothing about a moving average is the primary effect of battery storage, this means that, in general, battery storage cannot play the same role as aggregation in reducing peak demand.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101674"},"PeriodicalIF":4.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679630","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