IEEE Transactions on Industry Applications最新文献_第9页

Mass-Block-Dragging-Based Starting Method for Synchronous Generator/Motor of Gravity Energy Storage System 基于质量块拖动的重力储能系统同步发电机/电机起动方法

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-01-19 DOI: 10.1109/TIA.2026.3655622

Zufan Wang;Gaoyun Wu;Shuyang Fang;Tian Gao;Chenyang Li;Hassan H. Eldeeb;Yongzhang Huang;Guorui Xu;Haisen Zhao

{"title":"Mass-Block-Dragging-Based Starting Method for Synchronous Generator/Motor of Gravity Energy Storage System","authors":"Zufan Wang;Gaoyun Wu;Shuyang Fang;Tian Gao;Chenyang Li;Hassan H. Eldeeb;Yongzhang Huang;Guorui Xu;Haisen Zhao","doi":"10.1109/TIA.2026.3655622","DOIUrl":"https://doi.org/10.1109/TIA.2026.3655622","url":null,"abstract":"A gravity energy storage system (GESS) typically adopts the synchronous generator-motor (SGM) that is directly connected to the grid, in order to provide inertia and reactive power support to power systems with high penetration of renewable energy. However, due to the lack of line-starting capability, it is a critical challenge for a GESS to meet the frequent start-stop requirements in practice. To solve this problem, an SGM starting method based on mass block (MB) dragging is proposed in this study, for a chain-rail-based slope GESS (SGESS) as example. Through the analysis of the loss components of GESS, an optimal mass determination method for the starting MB is derived. The MB-dragging-based starting of 1-kW and 500-kW chain-rail-based SGESSs are then simulated and analyzed, and the dynamic grid-connection characteristics of the SGM started by different starting MBs are compared. Finally, the MB-dragging-based starting of the 1-kW chain-rail-based SGESS prototype is tested for validation, and an experiment bench of SGM-grid connection is established to emulate the starting and grid-connection processes and evaluate their impacts on the grid. The experiment results demonstrate that the proposed method suppresses the inrush current successfully and enables smooth starting of SGM.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"8291-8299"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011302","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

Distribution Network Optimization for Low-Carbon Energy Supply in Data Centers: A Boundary-Interpretable Feasible Region Method 面向数据中心低碳能源供应的配电网优化：一种边界可解释可行域方法

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-03-31 DOI: 10.1109/TIA.2026.3677816

Weihao Yin;Tiance Zhang;Gengyin Li;Jianxiao Wang;Ming Zhou;Qiang Guo

{"title":"Distribution Network Optimization for Low-Carbon Energy Supply in Data Centers: A Boundary-Interpretable Feasible Region Method","authors":"Weihao Yin;Tiance Zhang;Gengyin Li;Jianxiao Wang;Ming Zhou;Qiang Guo","doi":"10.1109/TIA.2026.3677816","DOIUrl":"https://doi.org/10.1109/TIA.2026.3677816","url":null,"abstract":"With the proliferation of lightweight generative artificial intelligence, data centers (DCs) are increasingly deployed within distribution networks (DNs). Their highly stochastic and high-power demands pose significant challenges to achieving low-carbon and secure power supply. Thus, coordinating the operation of DNs and DCs is critical for ensuring reliable low-carbon electricity delivery. However, significant barriers persist due to the integration of numerous distributed energy resources (DERs) and operational privacy requirements among stakeholders. To enable secure coordination while safeguarding model confidentiality, a boundary-interpretable feasible region (BIFR) method is proposed in this paper. This method can capture the intrinsic relationship between the controllable variables and the boundary responses that affect both carbon emissions and system safety performance. Based on the BIFR, a bidirectional coordinated optimization mechanism for DC-DN systems is established. The mechanism determines optimization strategies for low-carbon collaborative operation according to the coupled BIFR by iterative bidirectional adjustments until convergence. This mechanism achieves efficient DC-DN coordination through minimal information exchange while preventing privacy breaches. Case studies on modified IEEE 33-bus and Caracas 141-bus distribution networks validate the effectiveness and efficiency of the proposed method.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"8545-8557"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011323","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 Scheduling of Multiple Data Center Microgrids Considering the Spatiotemporal Equilibrium Allocation of Carbon Emission Allowance 考虑碳排放配额时空均衡分配的多数据中心微电网优化调度

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-03-24 DOI: 10.1109/TIA.2026.3677240

Chengling Hu;Changzheng Shao;Hanxin Zhang;Kaigui Xie

{"title":"Optimal Scheduling of Multiple Data Center Microgrids Considering the Spatiotemporal Equilibrium Allocation of Carbon Emission Allowance","authors":"Chengling Hu;Changzheng Shao;Hanxin Zhang;Kaigui Xie","doi":"10.1109/TIA.2026.3677240","DOIUrl":"https://doi.org/10.1109/TIA.2026.3677240","url":null,"abstract":"The optimal scheduling of data center microgrids (DCMGs) considering the coupled trading of energy and carbon emission allowance (CEA) has been extensively studied. While CEA is typically allocated and assessed on an annual basis, DCMGs’ operation and energy trading are conducted on a daily schedule. This discrepancy in temporal scales poses challenges for aligning daily operational decisions with long-term carbon compliance goals. This paper investigates the optimal scheduling of multiple DCMGs, considering the spatiotemporal equilibrium allocation of CEA. First, a CEA spatiotemporal decomposition model is developed. Then, a Lyapunov optimization-based low-carbon scheduling model is introduced, which decouples long-term constraints and significantly reduces computational complexity while ensuring both annual carbon compliance and economic efficiency. Furthermore, a two-layer game-theoretic energy–carbon coupling trading model is presented to conduct collaborative optimization for multiple DCMGs. Finally, a test system is used to demonstrate the significant effects of emission reduction and the economic benefits of the proposed methods.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"8516-8529"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011324","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

Bidirectional DC-DC Converter With High Voltage Step-Up/down Ratio and Voltage Balance Capability for the Interconnection of Unipolar and Bipolar DC Microgrids 单极和双极直流微电网互联中具有高电压升压比和电压平衡能力的双向DC-DC变换器

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-01-20 DOI: 10.1109/TIA.2026.3655649

V. Fernão Pires;Armando Cordeiro;Daniel Foito;Joaquim Monteiro;A. J. Pires

{"title":"Bidirectional DC-DC Converter With High Voltage Step-Up/down Ratio and Voltage Balance Capability for the Interconnection of Unipolar and Bipolar DC Microgrids","authors":"V. Fernão Pires;Armando Cordeiro;Daniel Foito;Joaquim Monteiro;A. J. Pires","doi":"10.1109/TIA.2026.3655649","DOIUrl":"https://doi.org/10.1109/TIA.2026.3655649","url":null,"abstract":"The importance of DC microgrids is growing in the realm of the today’s electrical energy distribution networks. When it comes to the configuration of DC microgrids, several options exist. Yet, two structures have emerged as the most widely adopted: unipolar and bipolar DC microgrids. Consequently, their interconnection could be crucial for various applications. Given that these microgrids can operate at significantly different voltage levels, interconnection must account for this variation. Accordingly, this paper introduces a novel bidirectional DC-DC converter with a high voltage step-up/down ratio for interconnecting these two DC microgrids. The converter boasts a non-isolated configuration, enabling the transfer of energy between DC microgrids while simultaneously supporting the balance of the bipolar infrastructure. Results from the experimental tests obtained from a laboratory prototype showing the capability to transfer energy in both directions are presented. The findings indicate that the proposed solution aligns with the anticipated outcomes.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"7356-7369"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011364","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

Physical System-Constrained Transactive Bidding Strategy for Data Centers With Workload Flexibility in Electricity Markets 电力市场中具有工作负载灵活性的数据中心物理系统约束的交易竞价策略

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-01-15 DOI: 10.1109/TIA.2026.3654487

Ke Zhang;Xu Wang;Chuanwen Jiang;Yahan Dong;Mohammad Shahidehpour;Chongyu Wang

{"title":"Physical System-Constrained Transactive Bidding Strategy for Data Centers With Workload Flexibility in Electricity Markets","authors":"Ke Zhang;Xu Wang;Chuanwen Jiang;Yahan Dong;Mohammad Shahidehpour;Chongyu Wang","doi":"10.1109/TIA.2026.3654487","DOIUrl":"https://doi.org/10.1109/TIA.2026.3654487","url":null,"abstract":"The workload flexibility in data centers remains underutilized in electricity markets, limiting their market-driven adaptability and overlooking dynamic market conditions. To address this challenge, we propose a physical system-constrained transactive bidding method for data centers to leverage market-driven flexibility of workload. First, we construct the energy model of data centers considering virtual machine multiplexing and support infrastructure constraints. Second, the market-driven flexibility of computational jobs is analyzed based on market requirements for classification and clustering. To reduce the computational burden of spectral clustering, we replace the intensive eigen-decomposition step with a lightweight orthogonal iteration method, enhancing scalability for large-scale datasets in data centers. Finally, the physical system models are integrated into the modified multi-agent deep deterministic policy gradient (MADDPG) method to ensure the inclusion of operation constraints and the optimal transactive bidding strategy. Numerical tests validate that the proposed method enables data centers to achieve higher profits across various ancillary markets while significantly improving computational speed.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"8621-8633"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011382","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

IEEE Industry Applications Society Information IEEE工业应用学会信息

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-09-21 DOI: 10.1109/TIA.2026.3714160

引用次数: 0

IEEE Women in Engineering IEEE工程女性

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-09-21 DOI: 10.1109/TIA.2026.3724633

引用次数: 0

Deep Suppression of Vibration and Noise for IPMSMs Based on Synergistic Optimization of Multiple Excitation Forces 基于多激励力协同优化的ipmsm振动噪声深度抑制

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-01-20 DOI: 10.1109/TIA.2026.3656139

Wendi Pan;Haiyang Fang;Zicheng Liu;Yu Wang;Chunqing Li;Dawei Li;Ronghai Qu

{"title":"Deep Suppression of Vibration and Noise for IPMSMs Based on Synergistic Optimization of Multiple Excitation Forces","authors":"Wendi Pan;Haiyang Fang;Zicheng Liu;Yu Wang;Chunqing Li;Dawei Li;Ronghai Qu","doi":"10.1109/TIA.2026.3656139","DOIUrl":"https://doi.org/10.1109/TIA.2026.3656139","url":null,"abstract":"With the rapid development of interior permanent magnet synchronous machines (IPMSMs), increasing attention has been paid to their vibration and noise issues. Conventional vibration and noise optimization methods typically consider only the radial electromagnetic force as the primary excitation source, while the effects of other excitation forces are often neglected—potentially leading to unsatisfactory results. In this paper, a vibration and noise optimization method for IPMSMs taking into account multiple excitation forces is proposed. In the proposed method, concentrated radial force (CRF), concentrated tangential force (CTF), and bending moment (BM) are treated as the excitation sources, and their combined effects on vibration are comprehensively analyzed. Based on the analysis, a semi-analytical method is employed to optimize the machine's vibration and noise performance. A 12-slot 10-pole IPMSM is used as an example for study. Using an identical rotor slotting scheme, both the conventional and proposed optimization methods are applied for comparison. Analytical and experimental results demonstrate that, compared with the conventional method, the proposed method achieves greater suppression of vibration and noise.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"7077-7087"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011186","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

Spatial-Temporal Attention Mechanism and Graph Convolutional Networks Based Distributed PV Ultra-Short-Term Probabilistic Power Forecasting 基于图卷积网络的分布式光伏超短期概率功率预测的时空注意机制

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-02-03 DOI: 10.1109/TIA.2026.3660789

Chen Huang;Yuqing Wang;Zhao Zhen;Fei Xu;Fei Wang;Xinyu Liu;Xu Xie;Qin Fang

{"title":"Spatial-Temporal Attention Mechanism and Graph Convolutional Networks Based Distributed PV Ultra-Short-Term Probabilistic Power Forecasting","authors":"Chen Huang;Yuqing Wang;Zhao Zhen;Fei Xu;Fei Wang;Xinyu Liu;Xu Xie;Qin Fang","doi":"10.1109/TIA.2026.3660789","DOIUrl":"https://doi.org/10.1109/TIA.2026.3660789","url":null,"abstract":"To ensure the safe and stable operation of the distribution network with high penetration of distributed photovoltaics (PVs), reliable power forecasting of the distributed PV cluster is significant. However, the lack dynamic spatial-temporal correlation modeling ability and representative spatial-temporal feature extraction ability of the existing methods limits the further improvement of forecasting accuracy. Moreover, the existing power forecasting results are mostly presented as deterministic form, which is difficult to describe the forecasting credibility. Therefore, a spatial-temporal attention mechanism and graph convolutional networks based distributed PV ultra-short-term probabilistic power forecasting method is proposed in this paper. Firstly, the target distributed PV cluster is divided into sub-regions and the original distributed PV graph-structured time series is generated by abstracting each sub-region as a graph node and regarding the aggregated power of each sub-region as the original node feature. Then, the spatial-temporal attention mechanism is used to adaptively capture dynamic spatial-temporal correlations from the distributed PV graph-structured times series. Supported by the dynamic spatial-temporal correlations, spatial-temporal convolution is applied to extract representative spatial-temporal features from the distributed PV graph-structured times series. Finally, a non-crossing joint quantile loss function is introduced to the training process to construct a complete probabilistic power forecasting model of a distributed PV cluster that can provide power forecasting intervals at multiple confidence levels at once for the next four hours. The validity and progressiveness of the proposed model have been verified in real-world datasets.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"7830-7843"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011190","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

Robust Stability Control of Droop-Controlled Microgrids Under Worst-Case Parameter Uncertainty via Adversarial Deep Reinforcement Learning 基于对抗深度强化学习的最坏情况参数不确定性下下垂微电网鲁棒稳定性控制

IF 5.2 2区工程技术

IEEE Transactions on Industry Applications Pub Date : 2026-09-01 Epub Date: 2026-01-19 DOI: 10.1109/TIA.2026.3655665

Wenhao Chen;Yu Wang;Bikash Pal

{"title":"Robust Stability Control of Droop-Controlled Microgrids Under Worst-Case Parameter Uncertainty via Adversarial Deep Reinforcement Learning","authors":"Wenhao Chen;Yu Wang;Bikash Pal","doi":"10.1109/TIA.2026.3655665","DOIUrl":"https://doi.org/10.1109/TIA.2026.3655665","url":null,"abstract":"Microgrids based on droop-controlled inverters can achieve small-signal stability control by adjusting the droop coefficients. However, due to discrepancies between modeling parameters and actual system parameters in inverter-based microgrids, the droop settings determined from the model often fail to deliver the expected control performance in real-world applications. To address this critical issue, this paper proposes a droop coefficient tuning strategy based on adversarial reinforcement learning, which exhibits strong robustness against system parameter uncertainties. The uncertain parameter behavior and the robust tuning of droop coefficients are respectively modeled as a Markov Decision Process (MDP) and an Adversarial Markov Decision Process (AMDP). The twin delayed deep deterministic policy gradient (TD3) algorithm is employed to solve these processes, yielding the worst-case uncertainty policy and the corresponding robust droop control strategy. Finally, case studies are conducted on a microgrid system with four inverter-based resources (IBRs) and a modified IEEE 33-bus distribution system to validate the effectiveness and scalability of the proposed method.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"62 5","pages":"8018-8029"},"PeriodicalIF":5.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011200","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