Power Systems

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Overview

Power systems research examines how to generate, move, and use electricity reliably as grids incorporate renewables, storage, and flexible loads. It combines physical models and optimization with machine learning, including graph neural networks for grid structure, physics-informed models for power flow, and reinforcement learning for control and dispatch. Current work also uses forecasting and data-driven methods for fault detection, cybersecurity, outage response, and coordination between grids and large computing loads. A central challenge is making these tools generalize across changing networks and operating conditions while preserving physical feasibility, safety, and dependable performance in real-time deployment.

Latest papers

CardsList

232 papers20 papers in the last four weeks, down 39% on the four weeks before. 0.1% of all new papers.

  1. Two-Stage Active Distribution Network Voltage Control via LLM-RL Collaboration: A Hybrid Knowledge-Data-Driven Approach

    Feb 25, 2026Xu Yang, Chenhui Lin, Xiang Ma +4Power SystemsRL Control

    Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610213, China. · State Grid Zhejiang Electric Power Co., Ltd., Jinhua Power Supply Company, Jinhua 321017, China.

  2. PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow with Continual Learning

    Feb 24, 2026Chidozie Ezeakunne, Jose E. Tabarez, Reeju Pokharel +1Physics-Informed GNNsPower Systems

    Los Alamos National Laboratory, Los Alamos, NM, USA · Department of Physics, University of Central Florida, Orlando, FL 32816 USA

  3. An LLM-Enabled Frequency-Aware Flow Diffusion Model for Natural-Language-Guided Power System Scenario Generation

    Feb 23, 2026Zhenghao Zhou, Yiyan Li, Fei Xie +5Conditional Generative ModelingPower Systems

    College of Smart Energy, Shanghai Non-Carbon Energy Conversion and Utilization Institute, and Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200240, China. · Qinghai Photovoltaic Industry Innovation Center Co., Ltd., State Power Investment Corporation, Xining 810007, China. · Xinjiang Hami Co., Ltd., State Power Investment Corporation, Hami 839000, China. +1

  4. Parameter-Efficient Domain Adaptation of Physics-Informed Self-Attention based GNNs for AC Power Flow Prediction

    Feb 20, 2026Redwanul Karim, Changhun Kim, Timon Conrad +7Physics-Informed GNNsPower Systems

    Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  5. Deep Reinforcement Learning for Optimizing Energy Consumption in Smart Grid Systems

    Feb 20, 2026Abeer Alsheikhi, Amirfarhad Farhadi, Azadeh ZamanifarSample-Efficient RLPower Systems

    School of Computer Engineering, Iran university of Science and Technology, Tehran, Iran · Department of Computer Engineering, SR.C, Islamic Azad university, Tehran, Iran

  6. Generating adversarial inputs for a graph neural network model of AC power flow

    Feb 20, 2026Robert ParkerNeural Surrogate ModelingGraph Neural Networks

    Los Alamos National Laboratory, Los Alamos, NM, USA

  7. MARLEM: A Multi-Agent Reinforcement Learning Simulation Framework for Implicit Cooperation in Decentralized Local Energy Markets

    Feb 17, 2026Nelson Salazar-Pena, Alejandra Tabares, Andres Gonzalez-ManceraMulti-Agent CoordinationPower Systems

    Department of Mechanical Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia · Department of Industrial Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia

  8. Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets

    Feb 17, 2026Nelson Salazar-Pena, Alejandra Tabares, Andres Gonzalez-ManceraMulti-Agent CoordinationDecentralized MARL

    Department of Mechanical Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia · Department of Industrial Engineering, Universidad de los Andes, 111711, Bogotá D.C., Colombia

  9. Fine-Tuning LLMs to Generate Economical and Reliable Actions for the Power Grid

    Feb 17, 2026Mohamad Chehade, Hao ZhuPower SystemsLarge Language Model-Guided Optimization

    Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA

  10. Fault Detection in Electrical Distribution System using Autoencoders

    Feb 16, 2026Sidharthenee Nayak, Victor Sam Moses Babu, Chandrashekhar Narayan Bhende +2Power System Fault DiagnosisFault Detection

    ABB Ability Innovation Center, Asea Brown Boveri Company, Hyderabad, 500084, India. · School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, 751013, India. · Department of Electrical and Electronics Engineering, BITS Pilani Hyderabad Campus, Hyderabad, 500078, India.

  11. Joint Sensor Deployment and Physics-Informed Graph Transformer for Smart Grid Attack Detection

    Feb 16, 2026Mariam Elnour, Mohammad AlShaikh Saleh, Rachad Atat +6Power SystemsPhysics-Informed GNNs

    department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77840, USA · department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar · department of Computer Science and Mathematics, Lebanese American University, Beirut 1102-2801, Lebanon +4

  12. Probabilistic Wind Power Forecasting with Tree-Based Machine Learning and Weather Ensembles

    Feb 13, 2026Max Bruninx, Diederik van Binsbergen, Timothy Verstraeten +2Gradient-Boosted Decision TreesEnsemble Learning

    Vrije Universiteit Brussel, Brussels, Belgium · Norwegian University of Science and Technology, Trondheim, Norway

  13. CROCS: A Two-Stage Clustering Framework for Behaviour-Centric Consumer Segmentation with Smart Meter Data

    Jan 15, 2026Luke W. Yerbury, Ricardo J. G. B. Campello, G. C. Livingston +2ClusteringDemand Response

  14. Accounting for Optimal Control in the Sizing of Isolated Hybrid Renewable Energy Systems Using Imitation Learning

    Jan 7, 2026Simon Halvdansson, Lucas Ferreira Bernardino, Brage Rugstad KnudsenPower Systems

    SINTEF Energy Research, Trondheim, Norway.

  15. Comparing Object Detection Models for Electrical Substation Component Mapping

    Dec 27, 2025Namish Bansal, Haley Mody, Dennies Kiprono Bor +2Object DetectionPower Systems

    George Mason University

  16. Reinforcement Learning to Initialize Newton-Raphson for AC Power Flow with Quantum Annealing-Based Environment Updates

    Nov 25, 2025Zeynab Kaseb, Matthias Moller, Lindsay Spoor +4Reinforcement LearningQuantum Annealing

    Electrical Sustainable Energy, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands. · Applied Mathematics, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands. · Leiden Institute of Advanced Computer Science, Leiden University, P.O. Box 9512, 2300 RA Leiden, The Netherlands. +3

  17. ProDER: A Continual Learning Approach for Fault Classification and Localization in Evolving Smart Grids

    Nov 7, 2025Emad Efatinasab, Nahal Azadi, Davide Dalle Pezze +3Replay-Based Continual LearningPrototype-Based Classification

    Department of Information Engineering, University of Padova. · School of Computing, Newcastle University.

  18. Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk

    Oct 29, 2025Weimin Huang, Ryan Piansky, Bistra Dilkina +1Mixed-Integer Linear ProgrammingLearning to Optimize

    Department of Computer Science University of Southern California Los Angeles, CA, USA · School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta, GA, USA

  19. Physics-informed GNN for medium-high voltage AC power flow with edge-aware attention and line search correction operator

    Sep 26, 2025Changhun Kim, Timon Conrad, Redwanul Karim +6Efficient Neural Network InferenceGraph Attention Networks

    Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  20. Unsupervised Clustering for Fault Analysis in High-Voltage Power Systems Using Voltage and Current Signals

    May 23, 2025Julian Oelhaf, Georg Kordowich, Andreas Maier +2Unsupervised ClusteringPower System Fault Diagnosis

    Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany

  21. Predicting Estimated Times of Restoration for Electrical Outages Using Longitudinal Tabular Transformers

    May 1, 2025Bogireddy Sai Prasanna Teja, Valliappan Muthukaruppan, Carls BenjaminEvent Time PredictionTransformer

    Exelon Corporation, Chicago, IL, USA

  22. LOOP-MAC: Learning-Based Multi-Agent Coordination with Guaranteed Local Feasibility in a Virtual Power Plant

    Oct 27, 2023Meiyi Li, Lucas Ruda, Javad MohammadiMulti-Agent CoordinationPower Systems