2026-10-14T06:30:08Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33973204 2026-09-23T12:56:19Z category_26482 item_type_3 month_year_09_2026

<b>Multi-Agent Reinforcement Learning via Mean Field Game for Power Grid Fault Diagnosis & Prediction</b> Xi Gao (25097287) Electrical engineering not elsewhere classified Multi-Agent Reinforcement Learning (MARL) Mean field game power grid fault diagnosis Fault Prediction <p dir="ltr">Power grid fault diagnosis and prediction represent critical challenges in modern electrical infrastructure management, requiring rapid, accurate, and scalable decision-making under complex, dynamic conditions. This paper proposes a novel framework integrating MARL with MFG theory to address the inherent scalability limitations of conventional multi-agent approaches in large-scale power systems. Each monitoring agent observes local grid states and interacts with the collective behavior of neighboring agents through a mean field approximation, substantially reducing the computational complexity from exponential to linear scaling with respect to the number of agents. The fault diagnosis and prediction problem are formulated as a stochastic differential game and derive the corresponding mean field equilibrium conditions. Extensive experiments conducted on the IEEE 14-bus, 39-bus, and 118-bus benchmark systems demonstrate that the MFG-MARL framework achieves a fault detection accuracy of 97.3%, 96.1%, and 94.8%, a false positive rate of 1.8%, 2.1%, and 2.7%, separately and prediction lead time of 450 milliseconds. Relative to the strongest MARL baseline evaluated (MAPPO), MFG-MARL improves diagnosis accuracy by 2.3-6.1 percentage points and lowers the false-positive rate by 0.6-2.2 percentage points across the three benchmark systems, while reducing inference latency by 65% on the IEEE 118-bus system (23.4 ms vs. 67.3 ms) , consistent with the linear-scaling argument underlying the mean field approximation.</p> 2026-09-23T12:56:19Z Dataset Dataset 10.6084/m9.figshare.33973204.v1 https://figshare.com/articles/dataset/_b_Multi-Agent_Reinforcement_Learning_via_Mean_Field_Game_for_Power_Grid_Fault_Diagnosis_Prediction_b_/33973204 CC BY 4.0