1 citations · 1 across the 13 of their papers we have counts for
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LLMs and Agentic AI Systems for Smart Grids: A Tutorial on Architectures and Applications
Daniela Rojas, Abdulwahab Albassam, Aidan G. Leung +11
Large language models (LLMs) and agentic AI systems have evolved from natural language tasks to using external tools to plan, retrieve, and act in technical domains. In smart grids…
Efficient Policy Adaptation for Voltage Control Under Unknown Topology Changes
Jie Feng, Yuanyuan Shi, Deepjyoti Deka
Reinforcement learning (RL) has shown great potential for designing voltage control policies, but their performance often degrades under changing system conditions such as topology…
Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches
S. Sivaranjani, Yuanyuan Shi, Nikolay Atanasov +6
We survey classical, machine learning, and data-driven system identification approaches to learn control-relevant and physics-informed models of dynamical systems. Recently, machin…
Stability Constrained Voltage Control in Distribution Grids with Arbitrary Communication Infrastructure
Zhenyi Yuan, Jie Feng, Yuanyuan Shi +1
We consider the problem of designing learning-based reactive power controllers that perform voltage regulation in distribution grids while ensuring closed-loop system stability. In…
DiffOP: Reinforcement Learning of Optimization-Based Control Policies via Implicit Policy Gradients
Yuexin Bian, Jie Feng, Yuanyuan Shi
Real-world control systems require policies that are not only high-performing but also interpretable and robust. A promising direction toward this goal is model-based control, whic…
Online Event-Triggered Switching for Frequency Control in Power Grids with Variable Inertia
Jie Feng, Wenqi Cui, Jorge Cortés +1
The increasing integration of renewable energy resources into power grids has led to time-varying system inertia and consequent degradation in frequency dynamics. A promising solut…
Combining Neural Networks and Symbolic Regression for Analytical Lyapunov Function Discovery
Jie Feng, Haohan Zou, Yuanyuan Shi
We propose CoNSAL (Combining Neural networks and Symbolic regression for Analytical Lyapunov function) to construct analytical Lyapunov functions for nonlinear dynamic systems. Thi…