8 papers · 1 filter
Unlocking Innate Computing Abilities in Electric Grids
Yubo Song, Subham Sahoo
Electric power grids are engineered energy systems whose forward electrical responses embody high-dimensional and memory-bearing transformations of input signals. In this work, we…
Quantized Probabilistic AI for Gear Fault Diagnosis in Motor Drives
Subham Sahoo, Huai Wang, Frede Blaabjerg
Deploying large artificial intelligence (AI) models in power electronics often demands high computational resources. Driven by the quantization paradigm, this digest proposes a qua…
Unlocking Embodied Probabilistic Computational Features in Motor Drives
Subham Sahoo, Huai Wang, Frede Blaabjerg
Artificial intelligence (AI)-driven fault diagnosis in motor drives often requires significant computational efforts and time for re-training, in addition to the limited knowledge…
Carbon and Reliability-Aware Computing for Heterogeneous Data Centers
Yichao Zhang, Yubo Song, Subham Sahoo
The rapid expansion of data centers (DCs) has intensified energy and carbon footprint, incurring a massive environmental computing cost. While carbon-aware workload migration strat…
Data-Driven Graph Switching for Cyber-Resilient Control in Microgrids
Suman Rath, Subham Sahoo
Distributed microgrids are conventionally dependent on communication networks to achieve secondary control objectives. This dependence makes them vulnerable to stealth data integri…
Inferring Ingrained Remote Information in AC Power Flows Using Neuromorphic Modality Regime
Xiaoguang Diao, Yubo Song, Subham Sahoo
In this paper, we infer remote measurements such as remote voltages and currents online with change in AC power flows using spiking neural network (SNN) as grid-edge technology for…