8 papers
AIDC Microgrid Vulnerability Assessment Under Computing-Power Coordinated Attacks
Ze Yu, Hongwei Zhen, Chao Shen +1
The rapid growth of large language model (LLM) services is expanding AI data centers (AIDCs), increasing electricity demand and associated carbon emissions. Renewable energy integr…
A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework
Xinming Wang, Fan Tang, Yingli Wei +6
With large-scale integration of emerging power electronic devices represented by grid-forming inverters, power system dynamics increasingly exhibit strong nonlinearity, multi-times…
OptArgus: A Multi-Agent System to Detect Hallucinations in LLM-based Optimization Modeling
Zhong Li, Zihan Guo, Xiaohan Lu +5
Large language models (LLMs) are increasingly used to translate natural-language optimization problems into mathematical formulations and solver code, but matching the reference ob…
LLM-Guided Safe Reinforcement Learning for Energy System Topology Reconfiguration
Zongyan Zhang, Chao Shen, Xu Wan +2
The increasing penetration of renewable generation and the growing variability of electrified demand introduce substantial operational uncertainty to modern power systems. Topology…
ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
Chao Shen, Zihan Guo, Xu Wan +6
Growing renewable penetration introduces substantial uncertainty into power system operations, necessitating frequent adaptation of dispatch objectives and constraints and challeng…
LLM-DMD: Large Language Model-based Power System Dynamic Model Discovery
Chao Shen, Zihan Guo, Ke Zuo +2
Current model structural discovery methods for power system dynamics impose rigid priors on the basis functions and variable sets of dynamic models while often neglecting algebraic…
CSCBench: A PVC Diagnostic Benchmark for Commodity Supply Chain Reasoning
Yaxin Cui, Yuanqiang Zeng, Jiapeng Yan +8
Large Language Models (LLMs) have achieved remarkable success in general benchmarks, yet their competence in commodity supply chains (CSCs) -- a domain governed by institutional ru…
Universal Transient Stability Analysis: A Pre-trained Generative Transformer-Enabled Power System Dynamics Prediction Framework
Chao Shen, Ke Zuo, Mingyang Sun
Existing dynamics prediction frameworks for transient stability analysis (TSA) fail to achieve multi-scenario "universality": the inherent ability of a single, pre-trained architec…