6 papers
VeraGrid-Agent: Tool-Augmented LLMs for Distribution Optimal Power Flow at the Grid Edge
Shivanshu Tripathi, Hamed Mohsenian-Rad, Maziar Raissi
Language models have demonstrated remarkable success in solving a wide range of tasks. However, answering complex scientific questions about the power flow often requires solving t…
Spectrogram-Based Joint Detection, Localization, and Classification of Events in Continuously Recorded IBR Waveforms
Shivanshu Tripathi, Maziar Raissi, Hamed Mohsenian-Rad
Continuously recorded high-resolution waveform measurements provide rich information about fast power system dynamics. However, they require automated methods to identify events. T…
Online Optimization with Unknown Time-Varying Parameters from Noisy Gradient Measurements
Shivanshu Tripathi, Maziar Raissi
We study online optimization problems in which the cost function depends on latent, time-varying parameters that are unmeasurable and governed by unknown dynamics. Specifically, we…
Test-Driven Agentic Framework for Reliable Robot Controller
Shivanshu Tripathi, Reza Akbarian Bafghi, Maziar Raissi
In this work, we present a test-driven, agentic framework for synthesizing a deployable low-level robot controller for navigation tasks. Given a 2D map with an image of an ultrason…
Data-Efficient Physics-Informed Learning to Model Synchro-Waveform Dynamics of Grid-Integrated Inverter-Based Resources
Shivanshu Tripathi, Hossein Mohsenzadeh Yazdi, Maziar Raissi +1
Inverter-based resources (IBRs) exhibit fast transient dynamics during network disturbances, which often cannot be properly captured by phasor and SCADA measurements. This shortcom…
Online Optimization with Unknown Time-varying Parameters
Shivanshu Tripathi, Abed AlRahman Al Makdah, Fabio Pasqualetti
In this paper, we study optimization problems where the cost function contains time-varying parameters that are unmeasurable and evolve according to linear, yet unknown, dynamics.…