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Improving Primary Frequency Response in Networked Microgrid Operations using MLP-Driven Reinforcement Learning
2020
IET Smart Grid
Individual microgrids can improve the reliability of power systems during extreme events, and networked microgrids can further improve efficiency through resource sharing and increase the resilience of critical end-use loads. However, networked microgrid operations can be subject to large transients due to switching and end-use loads, which can cause dynamic instability and lead to system collapse. These transients are especially prevalent in microgrids with high penetrations of grid-following
doi:10.1049/iet-stg.2019.0261
fatcat:oysw4sgv4rbuxkovfqpwalpyiq