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- W4377710421 abstract "Due to the low computational efficiency and high communication pressure caused by centralized control, decentralized coordination of electric vehicles (EVs) has become a research hotspot in recent years. However, the integration of numerous EVs with homogeneous parameters brings unprecedented challenges for the optimal scheduling of the power system. To explore symmetry-induced divergence in decentralized electric vehicle scheduling, the established centralized optimization scheduling model of electric vehicles is decomposed into a distributed optimization model by Lagrange relaxation, achieving parallel control of each EV aggregator (EVA). To solving the oscillation caused by parameter symmetry in the process of optimization, we propose a convergence acceleration algorithm based on a perturbation function, which is a random distribution function used to break parameter symmetry within an acceptable calculation error range. On the premise of sensitivity analysis, a closed form of the perturbation limit is theoretically derived. Case studies based on different scales of users validate the effectiveness and computational efficiency of the proposed method." @default.
- W4377710421 created "2023-05-24" @default.
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- W4377710421 date "2023-01-01" @default.
- W4377710421 modified "2023-10-15" @default.
- W4377710421 title "Exploring Symmetry-Induced Divergence in Decentralized Electric Vehicle Scheduling" @default.
- W4377710421 doi "https://doi.org/10.1109/tia.2023.3279058" @default.
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