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Reinforcement Learning-Based Control for Resilient Community Microgrid Applications
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作者 Md Mahmudul Hasan Ishtiaque Zaman +1 位作者 Miao He michael giesselmann 《Journal of Power and Energy Engineering》 2022年第9期1-13,共13页
A novel microgrid control strategy is presented in this paper. A resilient community microgrid model, which is equipped with solar PV generation and electric vehicles (EVs) and an improved inverter control system, is ... A novel microgrid control strategy is presented in this paper. A resilient community microgrid model, which is equipped with solar PV generation and electric vehicles (EVs) and an improved inverter control system, is considered. To fully exploit the capability of the community microgrid to operate in either grid-connected mode or islanded mode, as well as to achieve improved stability of the microgrid system, universal droop control, virtual inertia control, and a reinforcement learning-based control mechanism are combined in a cohesive manner, in which adaptive control parameters are determined online to tune the influence of the controllers. The microgrid model and control mechanisms are implemented in MATLAB/Simulink and set up in real-time simulation to test the feasibility and effectiveness of the proposed model. Experiment results reveal the effectiveness of regulating the controller’s frequency and voltage for various operating conditions and scenarios of a microgrid. 展开更多
关键词 MICROGRID Reinforcement Learning Q-Learning Algorithm Vehi-cle-to-Grid (V2G)
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Reliability Optimization in the Islanded Mode of Microgrid
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作者 Sundari Ramabhotla Stephen B. Bayne +1 位作者 Tyler J. Flack michael giesselmann 《Journal of Energy and Power Engineering》 2017年第2期103-114,共12页
关键词 可靠性优化 电网 WINDCHILL 故障树分析 分布式能源 风险价值 孤岛 天然气发电机
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