Pub Date : 2024-10-09DOI: 10.1109/TSTE.2024.3471774
Zao Tang;Jia Liu;Yikui Liu;Tong Su;Pingliang Zeng
Compared to one-type of energy storage device, hybrid energy storage systems (HESSs) offer benefits for Auto generation control (AGC) command tracking and can reduce investment in energy storage. Traditional control method, although effective in meeting the matching of AGC commands at a specific moment, often lacks coordination across multiple time intervals, resulting in frequent and irregular charging/ discharging which reduces the overall lifetime. To address this, this paper presents an approximate optimal operation strategy for Thermal-HESS system, aiming to enhance the AGC performance of the generating unit and improve the energy management capability of the HESSs. Firstly, an auto-adjust Markov Chain prediction method is proposed to forecast the power demand of the AGC command tracking to determine power demand's tendency. Secondly, a stochastic model predictive control (SMPC)-based optimal model, which considers the current step and cost-to-go function, is proposed. However, the SMPC based model is multiple-step optimal operational problem, which will increase the computational burden of the controller. Therefore, this paper further designs a Multiple-Input-Multiple-output (MIMO) fuzzy logic controller to approximate the optimal alternative to the cost-to-go function of SMPC model, meeting the computational and application requirements more effectively. Finally, numerical case studies are conducted to demonstrate the effectiveness of the proposed method in AGC command tracking and HESSs energy management.
{"title":"Approximate Optimal Energy Management of Thermal-HESS System for MIMO Fuzzy Logic Controller Based AGC","authors":"Zao Tang;Jia Liu;Yikui Liu;Tong Su;Pingliang Zeng","doi":"10.1109/TSTE.2024.3471774","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3471774","url":null,"abstract":"Compared to one-type of energy storage device, hybrid energy storage systems (HESSs) offer benefits for Auto generation control (AGC) command tracking and can reduce investment in energy storage. Traditional control method, although effective in meeting the matching of AGC commands at a specific moment, often lacks coordination across multiple time intervals, resulting in frequent and irregular charging/ discharging which reduces the overall lifetime. To address this, this paper presents an approximate optimal operation strategy for Thermal-HESS system, aiming to enhance the AGC performance of the generating unit and improve the energy management capability of the HESSs. Firstly, an auto-adjust Markov Chain prediction method is proposed to forecast the power demand of the AGC command tracking to determine power demand's tendency. Secondly, a stochastic model predictive control (SMPC)-based optimal model, which considers the current step and cost-to-go function, is proposed. However, the SMPC based model is multiple-step optimal operational problem, which will increase the computational burden of the controller. Therefore, this paper further designs a Multiple-Input-Multiple-output (MIMO) fuzzy logic controller to approximate the optimal alternative to the cost-to-go function of SMPC model, meeting the computational and application requirements more effectively. Finally, numerical case studies are conducted to demonstrate the effectiveness of the proposed method in AGC command tracking and HESSs energy management.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"641-653"},"PeriodicalIF":8.6,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1109/TSTE.2024.3476688
Gengming Liu;Rui Cheng;Wenxia Liu;Qingxin Shi;Zhaoyu Wang
With the increasing electrification of urban transportation, urban power and traffic systems are highly coupled and influence each other, leading to a challenge for the post-event resilience enhancement of urban electric-traffic interdependent network (ETIN). In this context, we propose a multi-layer electric-metro-road interdependent network where the metro network (MN) depends on the distribution power network (DPN) and interacts with the road traffic network (RTN) synchronously. Electric buses (EBs), as one public dispatchable resource, are considered and explored to provide bridging routes for disabled MNs and supply power for failed DPNs, with consideration of three different service trips, i.e., the original trip, bridging trip, and charge-discharge trip. On this basis, a spatio-temporal network-based EB route schedule model is constructed. To consider the evacuation demand of affected MN routes, a fast DPN restoration strategy is proposed to minimize the time cost of lost load by integrating the network reconfiguration with the collaborative allocation of repair crews (RCs) and EBs. Finally, a distributed method is further devised for the coordination among different stakeholders. The proposed method is verified on two electric-traffic systems to show that the collaborative scheduling of RCs and EBs can effectively enhance the resilience of ETIN under metro service disruptions.
{"title":"Enhancing Resilience of Urban Electric-Road-Metro Interdependent Network Considering Electric Bus Scheduling","authors":"Gengming Liu;Rui Cheng;Wenxia Liu;Qingxin Shi;Zhaoyu Wang","doi":"10.1109/TSTE.2024.3476688","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3476688","url":null,"abstract":"With the increasing electrification of urban transportation, urban power and traffic systems are highly coupled and influence each other, leading to a challenge for the post-event resilience enhancement of urban electric-traffic interdependent network (ETIN). In this context, we propose a multi-layer electric-metro-road interdependent network where the metro network (MN) depends on the distribution power network (DPN) and interacts with the road traffic network (RTN) synchronously. Electric buses (EBs), as one public dispatchable resource, are considered and explored to provide bridging routes for disabled MNs and supply power for failed DPNs, with consideration of three different service trips, i.e., the original trip, bridging trip, and charge-discharge trip. On this basis, a spatio-temporal network-based EB route schedule model is constructed. To consider the evacuation demand of affected MN routes, a fast DPN restoration strategy is proposed to minimize the time cost of lost load by integrating the network reconfiguration with the collaborative allocation of repair crews (RCs) and EBs. Finally, a distributed method is further devised for the coordination among different stakeholders. The proposed method is verified on two electric-traffic systems to show that the collaborative scheduling of RCs and EBs can effectively enhance the resilience of ETIN under metro service disruptions.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"654-672"},"PeriodicalIF":8.6,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1109/TSTE.2024.3473011
Bo Tong;Lu Zhang;Gen Li;Bo Zhang;Fang Xie;Wei Tang
The increasing renewable generation increase the probability of voltage violation. The spatial and temporal power transfer can be achieved in AC/DC distribution networks based on voltage source converters (VSCs) and energy storage (ES), which can effectively avoid system voltage violation. However, the existing voltage violation mitigation methods in uncertain scenarios are either limited by the long solution time or complex modeling, which are difficult to meet the overvoltage probability reduction requirements of intra-day dispatch. In addition, the power transfer will simultaneously affect interconnected systems because the power is coupled through the VSCs. Overvoltage probability reduction on one line may lead to an increase on the other. This paper proposes a two-stage overvoltage-averse model considering the sensitivity of voltage violation probability. The proposed method analytically depicts the impact of power adjustment on the system overvoltage probability. The day-ahead optimization model is established as chance-constrained model. The intra-day optimization model is established as a quadratic convex model, which can be efficiently solved. Simulation results verify that the method proposed can effectively achieve the overvoltage probability reduction of renewable-rich AC/DC distribution networks.
{"title":"An Overvoltage-Averse Model for Renewable-Rich AC/DC Distribution Networks Considering the Sensitivity of Voltage Violation Probability","authors":"Bo Tong;Lu Zhang;Gen Li;Bo Zhang;Fang Xie;Wei Tang","doi":"10.1109/TSTE.2024.3473011","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3473011","url":null,"abstract":"The increasing renewable generation increase the probability of voltage violation. The spatial and temporal power transfer can be achieved in AC/DC distribution networks based on voltage source converters (VSCs) and energy storage (ES), which can effectively avoid system voltage violation. However, the existing voltage violation mitigation methods in uncertain scenarios are either limited by the long solution time or complex modeling, which are difficult to meet the overvoltage probability reduction requirements of intra-day dispatch. In addition, the power transfer will simultaneously affect interconnected systems because the power is coupled through the VSCs. Overvoltage probability reduction on one line may lead to an increase on the other. This paper proposes a two-stage overvoltage-averse model considering the sensitivity of voltage violation probability. The proposed method analytically depicts the impact of power adjustment on the system overvoltage probability. The day-ahead optimization model is established as chance-constrained model. The intra-day optimization model is established as a quadratic convex model, which can be efficiently solved. Simulation results verify that the method proposed can effectively achieve the overvoltage probability reduction of renewable-rich AC/DC distribution networks.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"613-626"},"PeriodicalIF":8.6,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1109/TSTE.2024.3476308
Haoxuan Chen;Yinliang Xu;Hongbin Sun
Wave energy is essential for sustainable marine development. However, complex marine weather conditions cause fluctuating wave power outputs, resulting in a mimicking phenomenon in predictions. Moreover, the lack of accurate numerical weather prediction (NWP) data sources aggravates the prediction inaccuracy. To address these obstacles, a series characteristic perception (SCP) method coordinated with an advanced hybrid model, the quantile liberty loss gated recurrent unit kernel density estimation (QLB-GRU-KDE), is proposed for the floating point absorber wave energy system. In the first stage, the SCP method gains prior knowledge via ensemble approaches. In the second stage, a liberty loss function is used to mitigate the mimicking phenomenon. Furthermore, a hybrid model that integrates a GRU and KDE is adopted for the probabilistic forecasting of wave energy generation. In addition, a metric is proposed to evaluate the severity of the mimicking. A case study based on a real-world wave dataset is conducted, where both deterministic and probabilistic prediction approaches are examined. Comparisons with the cutting-edge counterparts reveal that the designed liberty loss effectively mitigates the mimicking issue. The comprehensive performance of the proposed model, including the accuracy, stability, reliability and sharpness in wave power prediction, is validated by multiple metrics.
{"title":"A Mimicking-Avoiding Short-Term Probabilistic Power Forecasting Method for Wave Energies","authors":"Haoxuan Chen;Yinliang Xu;Hongbin Sun","doi":"10.1109/TSTE.2024.3476308","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3476308","url":null,"abstract":"Wave energy is essential for sustainable marine development. However, complex marine weather conditions cause fluctuating wave power outputs, resulting in a mimicking phenomenon in predictions. Moreover, the lack of accurate numerical weather prediction (NWP) data sources aggravates the prediction inaccuracy. To address these obstacles, a series characteristic perception (SCP) method coordinated with an advanced hybrid model, the quantile liberty loss gated recurrent unit kernel density estimation (QLB-GRU-KDE), is proposed for the floating point absorber wave energy system. In the first stage, the SCP method gains prior knowledge via ensemble approaches. In the second stage, a liberty loss function is used to mitigate the mimicking phenomenon. Furthermore, a hybrid model that integrates a GRU and KDE is adopted for the probabilistic forecasting of wave energy generation. In addition, a metric is proposed to evaluate the severity of the mimicking. A case study based on a real-world wave dataset is conducted, where both deterministic and probabilistic prediction approaches are examined. Comparisons with the cutting-edge counterparts reveal that the designed liberty loss effectively mitigates the mimicking issue. The comprehensive performance of the proposed model, including the accuracy, stability, reliability and sharpness in wave power prediction, is validated by multiple metrics.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"627-640"},"PeriodicalIF":8.6,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modularization of Hydrogen Electrolyzers (HEs) is projected to be immediate, resilient, and efficient for load management in large-scale Hydrogen Consuming Industries (HCIs). It offers a scalable and flexible solution that can adapt to changes in hydrogen and power system demands. However, Modular HEs are studied primarily as small-scale wind hydrogen systems only, converting excess Renewable Energy (RE) into hydrogen without the integration of rigid downstream operations. Downstream constraints in HCIs, like rigid hydrogen demands, device operational/ramping limits, and storage constraints, can limit or regulate modular HE's use for power system services. Furthermore, oversimplified HE operational modeling within HCIs leads to suboptimal outcomes for integrated modular HCI and RE-rich power system (RPS) operations, resulting in RE curtailments and inaccurate flexibility estimations. This happens due to improper loading rates arising from unrealistic inter and intra-modular HE operations. This work proposes a comprehensive model for modular HE management in integrated ammonia (HCI) and power systems for flexibility in sector-coupled scenarios. The work considers and demonstrates how downstream constraints regulate HEs flexibility through a unit commitment problem framework. HE operations with detailed and extended electrochemical dynamics are considered to improve and enhance operational flexibility calculations of growing RPS-based modular HCIs. This allows for better sectoral integration and estimation of power system services.
{"title":"Short-Term Operation Flexibility in Modular Power to Hydrogen Based Ammonia Industries","authors":"Aaquib Firdous;Chandra Prakash Barala;Parul Mathuria;Rohit Bhakar","doi":"10.1109/TSTE.2024.3475415","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3475415","url":null,"abstract":"Modularization of Hydrogen Electrolyzers (HEs) is projected to be immediate, resilient, and efficient for load management in large-scale Hydrogen Consuming Industries (HCIs). It offers a scalable and flexible solution that can adapt to changes in hydrogen and power system demands. However, Modular HEs are studied primarily as small-scale wind hydrogen systems only, converting excess Renewable Energy (RE) into hydrogen without the integration of rigid downstream operations. Downstream constraints in HCIs, like rigid hydrogen demands, device operational/ramping limits, and storage constraints, can limit or regulate modular HE's use for power system services. Furthermore, oversimplified HE operational modeling within HCIs leads to suboptimal outcomes for integrated modular HCI and RE-rich power system (RPS) operations, resulting in RE curtailments and inaccurate flexibility estimations. This happens due to improper loading rates arising from unrealistic inter and intra-modular HE operations. This work proposes a comprehensive model for modular HE management in integrated ammonia (HCI) and power systems for flexibility in sector-coupled scenarios. The work considers and demonstrates how downstream constraints regulate HEs flexibility through a unit commitment problem framework. HE operations with detailed and extended electrochemical dynamics are considered to improve and enhance operational flexibility calculations of growing RPS-based modular HCIs. This allows for better sectoral integration and estimation of power system services.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"601-612"},"PeriodicalIF":8.6,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing penetration of wind power, the line-commutated converter-based high-voltage direct-current (LCC-HVDC) system in sending AC grid faces a potential risk of sub/super-synchronous oscillations (SSSOs), which threatens the stability of the power system. The impedance-based method is an effective way to analyze and suppress the SSSOs. However, since the effects of each control part in LCC-HVDC on the stability of sending AC grid are not yet well-investigated, there is a lack of theoretical guidance for implementing the impedance reshaping strategy for LCC-HVDC. Therefore, this paper establishes and analyzes the modular impedance model of LCC-HVDC, to elucidate the contribution of each control part and the interaction between different control loops. On this basis, an impedance reshaping strategy based on phase-locked angle feedforward (PAF) is proposed to improve system stability by attenuating the interaction. Compared to the existing virtual impedance-based method, the proposed PAF-based method addresses its possible failure in suppressing the SSSOs of sending AC grid. The theoretical analysis and experimental results validate the aforementioned conclusions and the effectiveness of the proposed impedance reshaping strategy.
{"title":"Impedance Characteristic Analysis and Phase-Locked Angle Feedforward-Based Stability Improvement for LCC-HVDC in Sending AC Grid","authors":"Haipan Li;Bin Hu;Heng Nian;Yuming Liao;Li Xiong;Zhencheng Liang","doi":"10.1109/TSTE.2024.3473894","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3473894","url":null,"abstract":"With the increasing penetration of wind power, the line-commutated converter-based high-voltage direct-current (LCC-HVDC) system in sending AC grid faces a potential risk of sub/super-synchronous oscillations (SSSOs), which threatens the stability of the power system. The impedance-based method is an effective way to analyze and suppress the SSSOs. However, since the effects of each control part in LCC-HVDC on the stability of sending AC grid are not yet well-investigated, there is a lack of theoretical guidance for implementing the impedance reshaping strategy for LCC-HVDC. Therefore, this paper establishes and analyzes the modular impedance model of LCC-HVDC, to elucidate the contribution of each control part and the interaction between different control loops. On this basis, an impedance reshaping strategy based on phase-locked angle feedforward (PAF) is proposed to improve system stability by attenuating the interaction. Compared to the existing virtual impedance-based method, the proposed PAF-based method addresses its possible failure in suppressing the SSSOs of sending AC grid. The theoretical analysis and experimental results validate the aforementioned conclusions and the effectiveness of the proposed impedance reshaping strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"588-600"},"PeriodicalIF":8.6,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1109/TSTE.2024.3455054
{"title":"Share Your Preprint Research with the World!","authors":"","doi":"10.1109/TSTE.2024.3455054","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3455054","url":null,"abstract":"","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2875-2875"},"PeriodicalIF":8.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1109/TSTE.2024.3455058
{"title":"IEEE Transactions on Sustainable Energy Information for Authors","authors":"","doi":"10.1109/TSTE.2024.3455058","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3455058","url":null,"abstract":"","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"C4-C4"},"PeriodicalIF":8.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1109/TSTE.2024.3455052
{"title":"IEEE Transactions on Sustainable Energy Publication Information","authors":"","doi":"10.1109/TSTE.2024.3455052","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3455052","url":null,"abstract":"","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"C2-C2"},"PeriodicalIF":8.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1109/TSTE.2024.3455056
{"title":"IEEE Industry Applications Society Information","authors":"","doi":"10.1109/TSTE.2024.3455056","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3455056","url":null,"abstract":"","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"C3-C3"},"PeriodicalIF":8.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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