Power Systems

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10 papers in the last four weeks, up 233% on the four weeks before. 0.1% of all new papers.

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From Benchmarks to Production: Transferring Time Series Anomaly Detection Methods for Electricity Production Monitoring
Sep 30, 2026Nicolas Vautier, Paul Caron, Nardi Xhepi +4Time-Series Anomaly Detection Power Systems
EDF Lab Paris Saclay · EDF, DOAAT · Inria, Ecole Normale Sup´erieure (PSL), CNRS
PowerZooJax: A JAX-based Power System Benchmark for Reinforcement Learning
Sep 28, 2026Zhanhua Pan, Xiao Liu, Zhilong Cao +2Power Systems
Nanyang Technological University, Singapore. · Cornell University, USA. · University of Bristol, UK.
PowerBench: A Benchmark for Agentic Retrieval and Reasoning in Power Systems
Sep 28, 2026Xijing Wang, Yinsheng Yao, Jinru Ding +5Power Systems
Tongji University · Johns Hopkins University · Shanghai Artificial Intelligence Laboratory +3
Probabilistic electrical power demand forecasting with uncertainty quantification
Sep 28, 2026Mahesh Neupane, Pragya Dhungana, Pradip Khatri +2Electricity Price Forecasting Probabilistic Forecasting
Interconnection and Numbering Section Nepal Telecommunications Authority Kathmandu, Nepal · Nepal Electricity Authority Kathmandu, Nepal · Department of Global Public Health and Primary Care University of Bergen Bergen, Norway +1
EvEMTBench: An Open Benchmark for Machine Learning in Power System Protection
Sep 23, 2026Julian Oelhaf, Georg Kordowich, Christian Bergler +3Power Systems Fault Diagnosis
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91058, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91058, Germany · Department of Electrical Engineering, Media and Computer Science, Ostbayerische Technische Hochschule Amberg-Weiden, Amberg 92224, Germany
Offline Reinforcement Learning for Distribution-Grid Protection
Sep 21, 2026Julian Oelhaf, Alexander Luce, Christian Bergler +2Power Systems Q-Learning
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen–Nürnberg, Erlangen, Germany · Department of Electrical Engineering, Media and Computer Science, Ostbayerische Technische Hochschule Amberg-Weiden, Amberg, Germany
Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds
Sep 20, 2026Rishabh Jain, Anuja Saini, Vishal JainPoint Clouds Power Systems
AiDash
A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids
Sep 15, 2026Julian Oelhaf, Georg Kordowich, Paula Andrea Pérez-Toro +4Power Systems
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg
Unified Heterogeneous Graph Neural Network solver for Power Flow, Optimal Power Flow and State Estimation
Sep 15, 2026Ferran Bohigas-Daranas, Hamid Latif-Martínez, Eduardo Prieto-Araujo +2Optimal Power Flow Power Systems
Data-Optimized Contingency Screening: A Machine Learning Approach to Power System Security
Sep 7, 2026Joshua Salako, Folajimi Osikomaiya, Olakorede OlamijuPower Systems Optimal Power Flow
dept. of Electrical and Electronics Engineering, Federal University of Agriculture, Abeokuta, Nigeria
RestoreBench: Can AI Agents Restore Power Flow Convergence?
Aug 31, 2026Riccardo Mansutti, Andrea Pomarico, Robert Jakob +3Power Systems Optimal Power Flow
1ETH Zürich · 2Politecnico di Milano · 3Harvard University
Safety Screening for Voltage Control in Active Distribution Grids via Distributionally Robust Conformal Screening
Aug 31, 2026Sarra Bouchkati, Petros Ellinas, Adriana Geisler +4Power Systems Voltage
IAEW at RWTH Aachen University, Aachen, Germany · Department of Wind and Energy Systems, Technical University of Denmark, Kongens Lyngby, Denmark
GENCO - A Unified Neural Solver Embedded in a Development Framework for Steady-State Grid Analysis
Aug 10, 2026Alban Puech, Matteo Mazzonelli, Tamara R. Govindasamy +19Optimal Power Flow Power Systems
IBM Research · Reliability and Risk Engineering Laboratory, ETH Zurich, Switzerland · Hydro-Qu´ebec Research Institute, Canada +3
Tools to Explain Neural Networks for Power System Dynamics
Aug 8, 2026Petros Ellinas, Johanna Vorwerk, Spyros ChatzivasileiadisNeural Dynamics Machine Learning Surrogates
Department of Wind and Energy Systems, Technical University of Denmark, Lyngby, Denmark
Short-term load forecasting under EU-AI Act Requirements in Safety-Critical Environments: Results from a 41-day live challenge on the aggregated German transmission-grid load
Aug 5, 2026Thomas Bartz-Beielstein, Inalbek Akiev, Lalo MohamadAccurate Short-Term Electricity Load Forecasting Power Systems
THK-AI Research Cluster, Germany · TH Köln, Germany
Bridging Artificial Intelligence and Power Systems Education Using a Hands-On Executable Framework
Aug 3, 2026Junjie Yin, Buxin She, Xinyu Feng +2Artificial Intelligence Lifecycle Power Systems
Fran · EECS Department and the CURENT research center at The University of Tennessee, Knoxville, TN 37996 · ECE Department at Kansas State University, Manhattan, KS 66506
Event-Structured Physics-Informed Neural Networks for Differentiable Critical Clearing Boundaries
Jul 30, 2026Baoli Hao, Chenxi Hu, Ming Zhong +1Parametric Physics-Informed Neural Network Power Systems
Department of Applied Mathematics, Illinois Institute of Technology, Chicago, IL 60616, USA · Department of Computer Science, The Hang Seng University of Hong Kong, Sha Tin, Hong Kong · Department of Mathematics, University of Houston, Houston TX 77204, USA +1
PowerAtlas: Towards Electricity-Computing Co-Scheduling for Power Systems
Jul 29, 2026Kaiwen Jiang, Siya Xu, Ziyue Zhu +3Power Systems Data Centers
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications · Information and Communication Branch, State Grid Liaoning Electric Power Co., Ltd. · College of Computing and Data Science, Nanyang Technological University
Spectrogram-Based Joint Detection, Localization, and Classification of Events in Continuously Recorded IBR Waveforms
Jul 23, 2026Shivanshu Tripathi, Maziar Raissi, Hamed Mohsenian-RadWaveforms Power Systems
Department of Electrical and Computer Engineering, University of California, Riverside · Department of Mathematics, University of California, Riverside
A Phased Development Framework Enabling Islanded Operation of Sustainable AI Data Centers With Onsite Grid-Following and Grid-Forming Energy Architectures
Jul 19, 2026Soham Ghosh, Nabil Mohammed, Mohammad Ashraf Hossain SadiArtificial Intelligence Infrastructure Distributed Energy Resources
Black & Veatch, Overland Park, KS 66211, USA · Centre for New Energy Transition Research (CfNETR) at Federation University, Ballarat, Australia · University of Central Missouri, Warrensburg, MO 64093 USA
Revisiting data-driven dynamic security assessment with a tabular foundation model
Jul 17, 2026Olayiwola Arowolo, Maosheng Yang, Jochen CremerPower Systems Tabular Foundation Models
Electrical and Sustainable Energy, TU Delft
A Machine Learning Surrogate for Component Criticality Ranking in Interdependent Power-Communication Networks
Jul 9, 2026Sohini Roy, Xheni HylviuPower Systems Cyber-Physical System
Department of Computer Science University of Nevada, Las Vegas Las Vegas, USA
Smart charging of large fleets of Electric Vehicles: Independent Multi-Agent Reinforcement Learning approaches
Jun 30, 2026Xavier Rate, Eloann Le Guern, Raphaël Féraud +8Electric Vehicles Multi-Agent Reinforcement Learning
Orange · ENS Rennes · IMT Atlantique +1
PROTECT-90: A Fault Dataset for Power System Protection
Jun 23, 2026Julian Oelhaf, Georg Kordowich, Christian Bergler +3Power Systems Reproducibility
1Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Department of Electrical Engineering, Media and Computer Science, Ostbayerische Technische Hochschule Amberg-Weiden, Amberg, Germany
Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources
Jun 23, 2026Haoyuan Deng, Yihong Zhou, Thomas Morstyn +1Distributed Energy Resources Power Systems
The University of Hong Kong, Hong Kong SAR, China · University of Oxford, Oxford, U.K. · The University of Hong Kong Shenzhen Institute of Research and Innovation, Shenzhen, China
Urban Power Grid Topology and Hierarchy Identification from Open Data
Jun 19, 2026Shiliang Zhang, Sabita MaharjanPower Systems Infrastructure
University of Oslo, Oslo, Norway
Power Systems Agent Benchmark: Executable Evaluation of AI Agents in Electric Power Engineering
Jun 18, 2026Sergei TrashchenkovPower Systems Agentic Benchmarks
Pseudo-Feature Padding: A Lightweight Defense Against False Data Injection in Power Grids
Jun 18, 2026Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +2Cyber-Physical System Power Systems
Department of Electrical Engineering and Computer Science, University of Tennessee · Department of Computer Science, The University of Illinois at Springfield · Department of Electrical and Computer Engineering, Clemson University, South Carolina
Navigating the Safety-Fidelity Trade-off: Massive-Variate Time Series Forecasting for Power Systems via Probabilistic Scenarios
Jun 11, 2026Kaijie Xu, Anqi Wang, Xilin DaiPower Systems Probabilistic Forecasting
ZJU-UIUC Institute Zhejiang University Hangzhou, China
S3TS: Stochastic Scenario-Structured Tree Search for Advanced Planning Under Uncertainty
Jun 1, 2026Fabio Pavirani, Bert Claessens, Pierre Pinson +1Demand Response Power Systems
IDLab Ghent university – imec, Technologiepark Zwijnaarde 126, 9052 Gent, Belgium · Beebop.ai, Belgium · Imperial College London, London, UK
Interpretable Policy Distillation for Power Grid Topology Control
May 30, 2026Aleksandra Dmitruka, Karlis FreivaldsProximal Policy Optimization Power Systems
University of Latvia, Faculty of Exact Sciences and Technology, Riga, Latvia
Cycle-Space Informed Detection of Autoencoded Blind False Data Injection Attacks on Power Systems
May 27, 2026Xin Li, Chenhan Xiao, Jonathan Cohen +3Power Systems
Faculty of Computer and Information Science, Ben-Gurion-University, Be’er Sheva, Israel · School of Electrical, Computer and Energy Engineering, Arizona State University, AZ, USA · Department of Computer Science, Shamoon College of Engineering, Be’er Sheva, Israel
Learning Dynamic Stability Landscapes in Synchronization Networks
May 22, 2026Christian Nauck, Junyou Zhu, Michael Lindner +1Network Science Graph Neural Networks
Department of Complexity Science, Postdam Institute for Climate Impact Research, Potsdam, Germany · Machine Learning Group, Technical University of Berlin, 10587 Berlin, Germany · Department of Digital Transformation in Energy Systems, Institute of Energy Technology, Technical University of Berlin, Germany.
Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids
May 22, 2026Massimiliano Lupo Pasini, Yijiang Li, Kibaek Kim +1Optimal Power Flow Power Systems
Computational Sciences and Engineering Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831, USA
Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review
May 21, 2026Joseph NyangonParametric Physics-Informed Neural Network Power Systems
Energy Exemplar, Salt Lake City, UT, 84111, USA
Long-term Power Grid Planning via Answer Set Programming
May 19, 2026Antonio Ielo, Francesco Doria, Sandra Castellanos-Paez +3Power Systems Answer Set Programming
University of Calabria, Italy · University of Huddersfield, UK
Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids
May 17, 2026Emad Abukhousa, Saman Zonouz, A. P. Sakis MeliopoulosPower Systems Distributed Energy Resources
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks
May 15, 2026Mohammad A. Razzaque, Muta Tah HiraReal-World Cloud Fault Injection Dataset Power Systems
School of Computing, Engineering and Digital Technologies, Teesside University, UK · Smartifier Ltd, Stockton-on-Tees, UK
Quantifying Cyber-Vulnerability in Power Electronics Systems via an Impedance-Based Attack Reachable Domain
May 14, 2026Hongwei Zhen, Ze Yu, Xin Xiang +2Cyber-Physical System Power Systems
Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
May 12, 2026Boming Liu, Jin Dong, Jamie LianPower Systems Distributions
Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830 USA
TokaMind for Power Grid: Cross-Domain Transfer from Fusion Plasma
May 10, 2026JC Wu, Norton Lee, Kai Siang ChenPower Systems Transformer Architectures
TaiScience Research Group, affiliated with Fu Jen Catholic University, Taiwan · Center for Geometry and Physics, Institute for Basic Science (IBS), South Korea · Fu Jen Catholic University, Taiwan
Inductive Power Grid Cascading Failure Analysis with GRU-Gated Graph Attention
May 7, 2026Tianxin Zhou, Xiang Li, Haibing LuPower Systems Interleaved Graph Attention
Department of Computer Science & Engineering, Santa Clara University, Santa Clara, USA · Dept. of Information Systems & Analytics, Santa Clara University, Santa Clara, USA
Exact and Evolutionary Algorithms for Sequential Multi-Objective Transmission Topology Planning
May 5, 2026Job Groeneveld, Miguel Muñoz, Jan Viebahn +1Optimal Power Flow Power Systems
TenneT TSO B.V., Arnhem, The Netherlands · Artelys, Paris, France · Department of Mathematics, Vrije Universiteit Amsterdam, The Netherlands
MARS-DA: A Hierarchical Reinforcement Learning Framework for Risk-Aware Multi-Agent Bidding in Power Grids
May 4, 2026Jiayi Chen, Xuan Zhang, Guiling WangElectricity Markets Power Systems
Department of Computer Science, New Jersey Institute of Technology
From Barrier to Bridge: The Case for AI Data Center/Power Grid Co-Design
May 4, 2026Noman Bashir, Rob Sherwood, Le Xie +1Data Centers Artificial Intelligence Infrastructure
Massachusetts Institute of Technology, USA · SwitchDin, Australia · Harvard University, USA
LUMINA: A Grid Foundation Model for Benchmarking AC Optimal Power Flow Surrogate Learning
May 4, 2026Hongwei Jin, Keunju Song, Zeeshan Memon +5Optimal Power Flow Power Systems
Mathematics and Computer Science Division, Argonne National Laboratory · Department of Electronic Engineering, Sogang University · Department of Computer Science, Emory University +1
A Grid-Aware Agent-Based Model for Analyzing Electric Vehicle Charging Systems
Apr 30, 2026Khalil Al-Rahman Youssefi, Marija Gojkovic, Walter Stefanutti +2Electric Vehicles Power Systems
Lakeside Labs, Lakeside Park B04b, Klagenfurt, Austria · Alpen-Adria-Universität, Universitätsstraße 65–67, Klagenfurt, Austria · Silicon Austria Labs, Power Electronics division, High Tech Campus Villach - Europastraße 12, Austria
Predicting Power-System Dynamic Trajectories with Foundation Models
Apr 16, 2026Haoran Li, Lihao Mai, Chenhan Xiao +2Power Systems Ordinary Differential Equations
School of Electrical, Computer and Energy Engineering at Arizona State University, Tempe, AZ 85281 USA · MOVEJ Analytics, Dayton, OH 45324 USA
AutoB2G: Agentic Simulation and Reinforcement Learning for Spatio-Temporal Grid-Interactive Building Control
Mar 27, 2026Borui Zhang, Nariman Mahdavi, Subbu Sethuvenkatraman +1Power Systems Agentic Framework
University of New South Wales Sydney, NSW, Australia · CSIRO Newcastle, NSW, Australia
Unsupervised Clustering for Fault Analysis in High-Voltage Power Systems Using Voltage and Current Signals
May 23, 2025Julian Oelhaf, Georg Kordowich, Andreas Maier +2Power Systems Voltage
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany · Institute of Electrical Energy Systems, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany

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From Benchmarks to Production: Transferring Time Series Anomaly Detection Methods for Electricity Production Monitoring

Nicolas Vautier, Paul Caron, Nardi Xhepi, Félicie Bizeul+3

EDF Lab Paris Saclay · EDF, DOAAT · Inria, Ecole Normale Sup´erieure (PSL), CNRS

Time-Series Anomaly Detection Power Systems Time Series

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Accurate forecasting of electricity production is essential for maintaining the operational efficiency and strategic planning of energy utilities. In industrial settings, such forecasts are generated daily to ensure supply-demand balance and optimal management of production assets. However, the increasing complexity of modern power systems and data flows poses significant challenges for ensuring the reliability and consistency of these forecasts. This paper addresses the problem of anomaly detection in short-term production forecasts at EDF, formulated as identifying atypical intra-day patterns that may signal data quality issues or operational irregularities. We introduce TAMIS, a scalable and interpretable system that analyzes daily production time series to automatically detect anomalous days based on deviations from historical patterns learned from past data. Designed for human-in-the-loop workflows, TAMIS surfaces top-ranked anomalies through an automated daily newsletter, enabling efficient expert review and continuous monitoring. An extensive experimental evaluation on real-world industrial data demonstrates that TAMIS achieves the best accuracy-efficiency trade-off compared to baseline methods. To foster further research and reproducibility, we publicly release the anonymized application datasets used in our study.

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