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A physics-informed mitigation method for DC microgrids under cyber attacks
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AI
DOI：10.1016/j.asoc.2025.113691.png)
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Abstract
En 中文
• A denoising autoencoder is developed to enhance the data quality. • State estimation integrates features from historical and neighboring data. • The prediction network is trained with physics-informed constraints from microgrid. • Control compensation is conducted by utilizing the estimated state as recovery data.
Keywords:
denoising autoencoder
state estimation
physics-informed constraints
microgrid
control compensation
Journal
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6.6
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1.4W
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4.8W