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Virtual Inertia Regulation based High-Order Observer for Weak Microgrids Using Deep Sequential Learning
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DOI：10.1016/j.isatra.2025.10.005.png)
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Abstract
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• Developing an adaptive VIC control for regulation of hybrid Micro-grid system (HMGS) with high penetration of sustainable energy resources (SERs). • Designing an adaptive virtual controller based on high-order extended disturbance observer (HOEDO). • Training of deep sequential action-value learning (SAVL) to dynamically adjust the gains embedded in the controller. • Conducting comparative analysis with the conventional virtual inertia control (CVIC) deisnged by odel predictive control (MPC) and fractional-order proportional-integral-derivative (FOPID) control.
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