A Master-Slave Deep Learning Framework for Real-Time Transient Stability-Constrained Optimal Power Flow

IF 6.5 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Power Systems Pub Date : 2024-11-19 DOI:10.1109/tpwrs.2024.3502201
Yuchen Zhang, Yan Xu, Yateendra Mishra, Zhao Yang Dong
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来源期刊
IEEE Transactions on Power Systems
IEEE Transactions on Power Systems 工程技术-工程:电子与电气
CiteScore
15.80
自引率
7.60%
发文量
696
审稿时长
3 months
期刊介绍: The scope of IEEE Transactions on Power Systems covers the education, analysis, operation, planning, and economics of electric generation, transmission, and distribution systems for general industrial, commercial, public, and domestic consumption, including the interaction with multi-energy carriers. The focus of this transactions is the power system from a systems viewpoint instead of components of the system. It has five (5) key areas within its scope with several technical topics within each area. These areas are: (1) Power Engineering Education, (2) Power System Analysis, Computing, and Economics, (3) Power System Dynamic Performance, (4) Power System Operations, and (5) Power System Planning and Implementation.
期刊最新文献
Line Model Tuning for Distribution System State Estimation Transient Stability-Driven Planning for the Optimal Sizing of Resilient AC/DC Hybrid Microgrids Fuzzy-Adaptive Droop Gain Selection for Enhanced Frequency Support and DC Voltage Regulation in MTDC System Voltage Regulation and Loss Minimization of Active Distribution Networks with Uncertainties Using Chance-Constrained Model Predictive Control Dynamic Modeling and Stability Analysis for Repeated LVRT Process of Wind Turbine Based on Switched System Theory
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