5 papers
RestoreBench: Can AI Agents Restore Power Flow Convergence?
Riccardo Mansutti, Andrea Pomarico, Robert Jakob +3
Large Language Model (LLM) agents increasingly automate multi-step engineering workflows through tool use, interpretation of intermediate results, and iterative planning. Diagnosin…
Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI
Andrea Pomarico, Yuxuan Bao, Liyao Mars Gao +4
Monitoring electromechanical oscillations is crucial for maintaining the stability of modern power systems, particularly in the presence of increasing penetrations of inverter-base…
A Shallow Recurrent Decoder for Dynamic State Estimation with a Limited Number of PMUs in Power Systems
Andrea Pomarico, Alberto Berizzi, J. Nathan Kutz
Dynamic State Estimation (DSE) will play a fundamental role in future power system operation by providing real-time estimates of the system state and enabling enhanced situational…
PowerAgentBench-Dyn: A Benchmark for Agentic AI in Power System Dynamic Studies
Qian Zhang, Andrea Pomarico, Costas Mylonas +3
Large Language Model (LLM)-based agents are increasingly being used to automate multi-step engineering work flows by interacting with software tools, interpreting intermediate resu…
PowerAgentBench-SS: A Benchmark for Agentic AI in Power System Steady-State Studies
Costas Mylonas, Magda Foti, Andrea Pomarico +3
Power system benchmarks usually evaluate numerical solvers, prediction models, or sequential controllers. These benchmarks are necessary, but they do not directly test whether a La…