This page contains all papers from our DRACOS GNN study, focusing on Graph Neural Networks applications in power systems. The papers are presented with their titles, authors, publication year, and citation counts.
Total Papers: 570
Years Covered: 2015 - 2024
Total Citations: 6358
| Title | Authors | Year | Citations | Categories | Search |
|---|---|---|---|---|---|
| A Neighborhood Reconstruction-Based Cyber Attack Detection Method for Smart Grid Security | Ren, W.; Peng, J.; Li, S.; Zhang, R.; Rong, J.; Li, H. | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Mining latent patterns with multi-scale decomposition for electricity demand and price forecasting using modified deep graph convolutional neural networks | Rawal, K.; Ahmad, A. | 2024 | 4 | Forecastingprediction | ๐ Search |
| Enhancing Electrical Network Vulnerability Assessment with Machine Learning and Deep Learning Techniques | Rahman, M.M.; Akash, A.S.; Pirim, H.; Le, C.; Le, T.Q.; Yadav, O.P. | 2024 | 2 | Reliabilityresilience | ๐ Search |
| Personnel Factors-Based Safety Risk Assessment Method for Dispatching Automation Master Station System* | Qian, Jianguo; Zhang, Jing; Hu, Zhenyu; Qian, Haifeng; Chu, Fei | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Spatio-Temporal Advanced Persistent Threat Detection and Correlation for Cyber-Physical Power Systems using Enhanced GC-LSTM | Presekal, Alfan; ลtefanov, Alexandru; Semertzis, Ioannis; Palensky, Peter | 2024 | 4 | Cybersecurityprivacy | ๐ Search |
| CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations | Piloto, Luis; Liguori, Sofia; Madjiheurem, Sephora; Zgubic, Miha; Lovett, Sean; Tomlinson, Hamish; Elster, Sophie; Apps, Chris; Witherspoon, Sims | 2024 | 8 | Planningoptimization | ๐ Search |
| Comparison of Empirical and Data Driven Digital Twins for a PV+Battery Fleet | Pierce, B.G.; Wieser, R.J.; Ciardi, T.G.; Yao, A.D.; French, R.H.; Bruckman, L.S.; Li, M. | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Constraints and Variables Reduction for Optimal Power Flow Using Hierarchical Graph Neural Networks with Virtual Node-Splitting | Phamh, Thuan; Li, Xingpeng | 2024 | 0 | Planningoptimization | ๐ Search |
| Graph Neural Network-Accelerated Network-Reconfigured Optimal Power Flow | Pham, Thuan; Li, Xingpeng | 2024 | 1 | Planningoptimization | ๐ Search |
| N-1 Reduced Optimal Power Flow Using Augmented Hierarchical Graph Neural Network | Pham, Thuan; Li, Xingpeng | 2024 | 2 | Planningoptimization | ๐ Search |
| Distributed Photovoltaic Power Prediction Based on Spatio-Temporal Diffusion Graph Convolution with Dynamic Graph Networks | Peijie, Liu; Shuiqiang, Zou; Huanhuan, Ye; Wensi, Lai; Simiao, Yu; Chunyu, Tao; Chunhui, Dong | 2024 | 0 | Forecastingprediction | ๐ Search |
| Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems | Pagnier, Laurent; Chertkov, Michael | 2021 | 48 | PlanningoptimizationOperationcontrol | ๐ Search |
| Unsupervised Optimal Power Flow Using Graph Neural Networks | Owerko, Damian; Gama, Fernando; Ribeiro, Alejandro | 2024 | 13 | Planningoptimization | ๐ Search |
| Unsupervised Optimal Power Flow Using Graph Neural Networks | Owerko, Damian; Gama, Fernando; Ribeiro, Alejandro | 2022 | 13 | Planningoptimization | ๐ Search |
| Physics-informed graphical neural network for power system state estimation | Ngo, Quang-Ha; Nguyen, Bang L. H.; Vu, Tuyen V.; Zhang, Jianhua; Ngo, Tuan | 2024 | 21 | Operationcontrol | ๐ Search |
| Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction | Nandanoori, Sai Pushpak; Guan, Sheng; Kundu, Soumya; Pal, Seemita; Agarwal, Khushbu; Wu, Yinghui; Choudhury, Sutanay | 2022 | 20 | Forecastingprediction | ๐ Search |
| Topology-Aware Neural Networks for Fast Contingency Analysis of Power Systems | Nakiganda, Agnes M.; Cheylan, Catherine; Chatzivasileiadis, Spyros | 2023 | 2 | Planningoptimization | ๐ Search |
| A multi-rate sampling PMU-based event classification in active distribution grids with spectral graph neural network | MansourLakouraj, Mohammad; Gautam, Mukesh; Livani, Hanif; Benidris, Mohammed | 2022 | 18 | Reliabilityresilience | ๐ Search |
| Graph Convolutional Networks based short-term load forecasting: Leveraging spatial information for improved accuracy | Mansoor, Haris; Gull, Muhammad Shuzub; Rauf, Huzaifa; Shaikh, Inam ul Hasan; Khalid, Muhammad; Arshad, Naveed | 2024 | 7 | Forecastingprediction | ๐ Search |
| Multi-Scales Hybrid Graph Attention Neural Network with Jaccard Correlation Embedding for Link Prediction | Mai, C.; Lin, J.; Zheng, H.; Zhang, H.; Bi, J.; Zhou, J. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Multi-Scope Spectral Graph Neural Network for Link Scheduling | Mai, C.; Lin, J.; Zhang, W. | 2024 | 0 | Planningoptimization | ๐ Search |
| Bi-Order Graph Attention Neural Network with Neighbor Node Correlation Embedding for Link Prediction | Mai, C.; Lin, J.; Zhang, W. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Graph Neural Network Based Deep Reinforcement Learning for Volt - Var Control in Distribution Grids | MA, Aoxiang; CAO, Jun; CORTES, Pedro RODRIGUEZ | 2024 | 0 | Operationcontrol | ๐ Search |
| A Graph Neural Network and Transformer Encoder Technique for Anomaly and Cyber Threat Detection in Smart Grids | M, Lakshmanan; Adnan, Myasar Mundher; Reddy, R. Archana; Vasukidevi, G; G, Aarthy | 2024 | 0 | ReliabilityresilienceCybersecurityprivacy | ๐ Search |
| Power flow analysis via typed graph neural networks | Lopez-Garcia, Tania B.; Domรญnguez-Navarro, Josรฉ A. | 2023 | 21 | Planningoptimization | ๐ Search |
| Proximal Policy Optimization with Graph Neural Networks for Optimal Power Flow | Lรณpez-Cardona, รngela; Bernรกrdez, Guillermo; Barlet-Ros, Pere; Cabellos-Aparicio, Albert | 2022 | 4 | Planningoptimization | ๐ Search |
| Research on Power Balance and Measurement of New Energy Power System Based on Graph Neural Network | Liyan, K.; He, C.; Leiyang, Z. | 2024 | 0 | General | ๐ Search |
| A GNN-Based Generative Model for Generating Synthetic Cyber-Physical Power System Topology | Liu, Yigu; Xie, Haiwei; Presekal, Alfan; Stefanov, Alexandru; Palensky, Peter | 2023 | 6 | Cybersecurityprivacy | ๐ Search |
| Research on the Application of Graph Neural Network in Topology Optimization of Distribution Network | Liu, Y.; Wang, X.; Guo, Y.; Wang, R. | 2024 | 1 | Planningoptimization | ๐ Search |
| Graph Neural Networks for Learning Real-Time Prices in Electricity Market | Liu, Shaohui; Wu, Chengyang; Zhu, Hao | 2021 | 10 | Forecastingprediction | ๐ Search |
| Security Constrained Unit Commitment Optimization Based on Graph Reinforcement Learning | Liu, J.; Pan, L.L.; Xu, P.; Sun, P. | 2024 | 0 | Planningoptimization | ๐ Search |
| Enhancing Power Distribution System Resilience with Fusion-GNN: A Dynamic Graph Representation Learning Approach | Liu, B.; Zhang, C.; Dong, J.; Balaprakash, P.; Liu, Y.; Eiffert, B. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Spatial-Temporal Residential Short-Term Load Forecasting via Graph Neural Networks | Lin, Weixuan; Wu, Di; Boulet, Benoit | 2021 | 134 | Forecastingprediction | ๐ Search |
| Fault Diagnosis of Power Transformers Using Graph Convolutional Network | Liao, Wenlong; Yang, Dechang; Wang, Yusen; Ren, Xiang | 2021 | 92 | Reliabilityresilience | ๐ Search |
| A Review of Graph Neural Networks and Their Applications in Power Systems | Liao, Wenlong; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna; Wang, Yuelong; Wang, Yusen | 2022 | 198 | Survey | ๐ Search |
| Power data analysis and mining technology in smart grid | Li, Xinjia; Zhu, Zixu; Zhang, Chongchao; Zhang, Yangrui; Liu, Mengjia; Wang, Liming | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| A Transient Angle Stability Assessment Method for DFIG Grid-Connected Systems Based on Heterogeneous Graph Attention Networks | Li, Xianzhen; Qin, Wenping; Zhu, Zhilong; Lu, Ruipeng; Qin, Penghui; Cui, Junjie | 2024 | 0 | Operationcontrol | ๐ Search |
| SFLGNN: Power Load Forecasting Based on Spectral-Frequency Learning and Graph Neural Network | Li, X.; Wei, X.; Liu, Z.; Xie, S.; Sun, J.; Qin, H.; Wei, Z. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems | Li, Qian; Li, Jianxin; Wang, Lihong; Ji, Cheng; Hei, Yiming; Sheng, Jiawei; Sun, Qingyun; Xue, Shan; Xie, Pengtao | 2022 | 8 | Reliabilityresilience | ๐ Search |
| A Novel State Estimation Method Based on Cross-Track Graph Neural Network | Li, P.; Huang, W.; Li, X.; Dai, Z.; Hou, J.; Feng, Q. | 2024 | 0 | Operationcontrol | ๐ Search |
| An interpretable graph convolutional neural network based fault diagnosis method for building energy systems | Li, G.; Yao, Z.; Chen, L.; Li, T.; Xu, C. | 2024 | 4 | Reliabilityresilience | ๐ Search |
| Optimal Power Flow in a highly renewable power system based on attention neural networks | Li, Chen; Kies, Alexander; Zhou, Kai; Schlott, Markus; Sayed, Omar El; Bilousova, Mariia; Stรถcker, Horst | 2024 | 8 | Planningoptimization | ๐ Search |
| PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming | Li, Bingheng; Yang, Linxin; Chen, Yupeng; Wang, Senmiao; Chen, Qian; Mao, Haitao; Ma, Yao; Wang, Akang; Ding, Tian; Tang, Jiliang; Sun, Ruoyu | 2024 | 4 | Planningoptimization | ๐ Search |
| Reinforcement Learning Optimizes Power Dispatch in Decentralized Power Grid | Lee, Yongsun; Choi, Hoyun; Pagnier, Laurent; Kim, Cook Hyun; Lee, Jongshin; Jhun, Bukyoung; Kim, Heetae; Kurths, Juergen; Kahng, B. | 2024 | 0 | Planningoptimization | ๐ Search |
| A graph policy network approach for Volt-Var Control in power distribution systems | Lee, Xian Yeow; Sarkar, Soumik; Wang, Yubo | 2022 | 28 | Operationcontrol | ๐ Search |
| State Estimation in Electric Power Systems Leveraging Graph Neural Networks | Kundacina, Ognjen; Cosovic, Mirsad; Vukobratovic, Dejan | 2022 | 23 | Operationcontrol | ๐ Search |
| Robust and Fast Data-Driven Power System State Estimator Using Graph Neural Networks | Kundacina, Ognjen; Cosovic, Mirsad; Vukobratovic, Dejan | 2022 | 1 | Operationcontrol | ๐ Search |
| Distributed Nonlinear State Estimation in Electric Power Systems using Graph Neural Networks | Kundacina, Ognjen; Cosovic, Mirsad; Miskovic, Dragisa; Vukobratovic, Dejan | 2022 | 4 | Operationcontrol | ๐ Search |
| Fault Detection in Solar Power System with Internet of Things using Multi resolution Sinusoidal Neural Network - Snow Geese Optimization Approach | Kumar, P.; Purushothaman, K.E.; Arunmozhi, R.V.; Jayachitra, S.; Rani, D.L.; Kaliappan, S. | 2024 | 0 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Real-Time Small-Signal Security Assessment Using Graph Neural Networks | Justin, Glory; Paternain, Santiago | 2024 | 1 | Cybersecurityprivacy | ๐ Search |
| Short-Term Power Load Forecasting Under COVID-19 Based on Graph Representation Learning With Heterogeneous Features | Yu, Z.; Yang, J.; Wu, Y.; Huang, Y. | 2021 | 9 | Forecastingprediction | ๐ Search |
| Question Answering Algorithm for Grid Fault Diagnosis based on Graph Neural Network | Yu, Y.; Wang, Y.; Zhang, G.; Yang, Y.; Wang, J. | 2022 | 0 | Reliabilityresilience | ๐ Search |
| Self-Supervised State Calculation for Distribution Network via Masked Graph Reconstruction | Yu, T.; Wang, Q.; Chu, H.; Xiong, X.; Huang, K.; Qiu, R.; Hu, B.; Yan, H.; Wang, F.; Bai, Y.; Wang, S.; Qi, J.; Liu, S.; Shi, D.; IEEE | 2023 | 0 | Operationcontrol | ๐ Search |
| A Graph Reinforcement Learning-Based Handover Strategy for Low Earth Orbit Satellites under Power Grid Scenarios | Yu, H.; Gao, W.; Zhang, K. | 2024 | 0 | General | ๐ Search |
| Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches | Yin, T.; Naqvi, S.A.R.; Nandanoori, S.P.; Kundu, S. | 2024 | 2 | Cybersecurityprivacy | ๐ Search |
| Switching Convolution of Node Graph and Line Graph-driven Method for Fast Static Security Analysis | Ye, X.; Chen, Z.; Huang, Y.; Zhu, T.; Wei, W.; Liao, B.; Jiang, A.; Chongqing Society of Electrical Engineering; Sichuan University; Southwest Jiaotong University; State Grid Sichuan Electric Power Company | 2023 | 4 | Cybersecurityprivacy | ๐ Search |
| Forecasting day-ahead electricity prices with spatial dependence | Yang, Y.; Guo, J.; Li, Y.; Zhou, J. | 2023 | 5 | Forecastingprediction | ๐ Search |
| Transient Voltage Prediction Method Based on Spatial-Temporal Graph Convolutional Network | Yang, X.; Dong, Y.; Wang, J.; Wang, C.; IEEE | 2022 | 0 | Forecastingprediction | ๐ Search |
| Advanced Persistent Threat Detection in Smart Grid Clouds Using Spatiotemporal Context-Aware Graph Embedding | Yang, W.; Gao, P.; Huang, H.; Wei, X.; Zhang, H.; Qu, Z. | 2022 | 5 | Cybersecurityprivacy | ๐ Search |
| Transient stability assessment of power systems with graph neural networks considering global features | Yang, S.; Ding, M.; Wtuan, Z.; Yang, H.; Liu, Y.; Fan, W. | 2023 | 1 | Operationcontrol | ๐ Search |
| Data-Driven Priors for Robust PSSE via Gauss-Newton Unrolled Neural Networks | Yang, Q.; Sadeghi, A.; Wang, G. | 2022 | 13 | Operationcontrol | ๐ Search |
| Wind Power Forecasting Based on a Spatial-Temporal Graph Convolution Network with Limited Engineering Knowledge | Yang, L.; Tsung, F.; Wang, K.; Zhou, J. | 2024 | 2 | ForecastingpredictionDatainfrastructuredecisionsupport | ๐ Search |
| Multi-label image recognition for electric power equipment inspection based on multi-scale dynamic graph convolution network | Yan, Y.; Han, Y.; Qi, D.; Lin, J.; Yang, Z.; Jin, L. | 2023 | 10 | Datainfrastructuredecisionsupport | ๐ Search |
| Rapid Active Power Support by Regional PV Aggregation Considering Physical Topological Correlation and Communication Delay | Yan, T.; Dou, C.; Yue, D.; Guo, W.; He, Z. | 2024 | 3 | Datainfrastructuredecisionsupport | ๐ Search |
| Predicting Power System Voltage Health Index with PMUs and Graph Convolutional Networks | Yamashita, K.; Qin, J.; Yu, N.; Farantatos, E.; Zhu, L. | 2023 | 4 | Forecastingprediction | ๐ Search |
| Anomaly detection based on a deep graph convolutional neural network for reliability improvement | Xu, G.; Hu, J.; Qie, X.; Rong, J. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Graph-Based Time Series Edge Anomaly Detection in Smart Grid | Xu, A.; Wu, T.; Zhang, Y.; Hu, Z.; Jiang, Y.; IEEE; IEEE Computer Society; IEEE STC Smart Computing; IEEE TCSC; Longxiang High Tech; North America Chinese Talents Association | 2021 | 11 | Reliabilityresilience | ๐ Search |
| Detection of Fittings Based on the Dynamic Graph CNN and U-Net Embedded with Bi-Level Routing Attention | Xie, Z.; Fu, M.; Liu, X. | 2023 | 1 | Method | ๐ Search |
| Graph neural network approach for anomaly detection | Xie, L.; Pi, D.; Zhang, X.; Chen, J.; Luo, Y.; Yu, W. | 2021 | 56 | Reliabilityresilience | ๐ Search |
| Deep Learning in Power Grid Enterprises to Help the Construction of New Energy Industry Chain Path Analysis | Xiao, S.; Li, Q.; Yuan, Y. | 2023 | 0 | Operationcontrol | ๐ Search |
| Locational Detection of False Data Injection Attacks in the Edge Space via Hodge Graph Neural Network for Smart Grids | Xia, W.; Li, Y.; Yu, L.; He, D. | 2024 | 7 | Cybersecurityprivacy | ๐ Search |
| State Estimation for Power System Based on Graph Neural Network | Wu, Z.; Wang, Q.; Liu, X.; China Electrotechnical Society (CES); Institute of Electrical nd Electronics Engineers (IEEE) Beijing Section; Southeast University (SEU) | 2022 | 6 | Operationcontrol | ๐ Search |
| Integrating model-driven and data-driven methods for fast state estimation | Wu, Z.; Wang, Q.; Hu, J.; Tang, Y.; Zhang, Y. | 2022 | 12 | Operationcontrol | ๐ Search |
| Spatialโtemporal short-term load forecasting framework via K-shape time series clustering method and graph convolutional networks | Wu, Z.; Mu, Y.; Deng, S.; Li, Y. | 2022 | 0 | Forecastingprediction | ๐ Search |
| Attentive multi-scale aggregation based action recognition and its application in power substation operation training | Wu, Y.; Ren, G.; Jiang, B.; Dai, W.; Ji, N.; Chen, X. | 2023 | 0 | Operationcontrol | ๐ Search |
| Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms | Wu, T.; Carreno, I.L.; Scaglione, A.; Arnold, D. | 2023 | 19 | Method | ๐ Search |
| Identification and correction of abnormal measurement data in power system based on graph convolutional network and gated recurrent unit | Wu, L.; Zhang, S.; Chen, W.; Hao, X. | 2023 | 7 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Unrolled Spatiotemporal Graph Convolutional Network for Distribution System State Estimation and Forecasting | Wu, H.; Xu, Z.; Wang, M. | 2023 | 22 | ForecastingpredictionOperationcontrol | ๐ Search |
| Graph Attention Enabled Convolutional Network for Distribution System Probabilistic Power Flow | Wu, H.; Wang, M.; Xu, Z.; Jia, Y. | 2022 | 20 | Planningoptimization | ๐ Search |
| Adaptive Graph Convolutional Network-Based Distribution System State Estimation | Wu, H.; Jia, Y.; Xu, Z. | 2022 | 1 | Operationcontrol | ๐ Search |
| Detecting False Data Injection Attacks using Spatial-temporal Graph Neural Network | Wei, X.; Liu, W.; Zhou, J.; Zhou, X.; Zhang, W.; Cao, Y.; Beijing Information Science and Technology University; CAA; et al.; IEEE Beijing Section; Qingdao University; Technical Committee on Data Driven Control, Learning and Optimization (DDCLO) | 2023 | 1 | Cybersecurityprivacy | ๐ Search |
| Research on Attack Behaviour Detection Based on Dynamic Graph Neural Network in Power IoT System | Wei, X.; Gao, P.; Xu, J.; Zhang, H.; Tian, Q.; Ma, Z.; Academic Exchange Information Center | 2022 | 0 | Cybersecurityprivacy | ๐ Search |
| A novel spatial electric load forecasting method based on LDTW and GCN | Wei, M.; wen, M.; Zhang, Y. | 2024 | 3 | Forecastingprediction | ๐ Search |
| Parameter Identification in Power Transmission Systems Based on Graph Convolution Network | Wang, Z.; Xia, M.; Lu, M.; Pan, L.; Liu, J. | 2022 | 56 | Planningoptimization | ๐ Search |
| Application of Multiattention Mechanism in Power System Branch Parameter Identification | Wang, Z.; Weng, L.; Lu, M.; Liu, J.; Pan, L. | 2021 | 9 | Planningoptimization | ๐ Search |
| Temporal Graph Super Resolution on Power Distribution Network Measurements | Wang, Z.; Chen, Y.; Huang, S.; Zhang, X.; Liu, X. | 2021 | 13 | Datainfrastructuredecisionsupport | ๐ Search |
| Graph Learning-Based Voltage Regulation in Distribution Networks With Multi-Microgrids | Wang, Y.; Qiu, D.; Wang, Y.; Sun, M.; Strbac, G. | 2024 | 24 | Operationcontrol | ๐ Search |
| Research and application of automatic mapping method of distribution network protection power supply based on knowledge graph and graph convolution network | Wang, Y.; Mo, L.; Wang, W.; Wei, J.; Yang, J. | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Spatio-Temporal Convolutional Network Based Identification of Voltage-Coupling Commutation Failures in Multi-Infeed HVDC Systems | Wang, X.; Lin, R.; Song, K.; Han, J. | 2022 | 0 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Wind Power Prediction Based on Spatio-Temporal Characteristics | Wang, W.; Zhang, T.; Chinese Society for Electrical Engineering; IEEE Power and Energy Society; State Grid Corporation of China | 2023 | 0 | Forecastingprediction | ๐ Search |
| Predict Locational Marginal Greenhouse Gas Emission Factors of Electricity with Spatial-Temporal Graph Convolutional Networks | Wang, W.; Li, Y.; Yu, N.; ENEDIS; et al.; GreenAlp; Le Reseau de Transport d'electricite (RTE); Schneider Electric; Think Smartgrids | 2023 | 2 | Forecastingprediction | ๐ Search |
| Comprehensive evaluation of power flow and adjustment method to restore solvability based on GCRNN and DDQN | Wang, T.; Tang, Y. | 2021 | 3 | Planningoptimization | ๐ Search |
| Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network | Wang, S.; Chen, A.; Wang, P.; Zhuge, C. | 2023 | 45 | Forecastingprediction | ๐ Search |
| Risk Early Warning of Power Systems With Partial State Observations Based on the Graph Attention Neural Network | Wang, Q.; Li, D.; Zhang, X.; Fan, X.; et al.; Huawei; IEEE; IEEE Circuits and Systems Society (CAS); Samsung Semiconductor; Synopsys | 2023 | 0 | ReliabilityresilienceOperationcontrol | ๐ Search |
| Synchronous Condenser Reactive Power Output Model Based on DAG-CNN | Wang, L.; Wang, H.; Lu, T.; Wang, C.; IEEE | 2021 | 1 | Forecastingprediction | ๐ Search |
| M2STAN: Multi-modal multi-task spatiotemporal attention network for multi-location ultra-short-term wind power multi-step predictions | Wang, L.; He, Y. | 2022 | 49 | Forecastingprediction | ๐ Search |
| GCNInformer: A combined deep learning model based on GCN and Informer for wind power forecasting | Wang, H.-K.; Li, D.; Chen, F.; Du, J.; Song, K. | 2023 | 3 | Forecastingprediction | ๐ Search |
| Real-time small-signal security assessment using graph neural networks | Justin, G.; Paternain, S. | 2024 | 1 | Cybersecurityprivacy | ๐ Search |
| Graph Neural Networks for Power System Security Assessment | Justin, G.; Paternain, S. | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement | Jin, Hongwei; Balaprakash, Prasanna; Zou, Allen; Ghysels, Pieter; Krishnapriyan, Aditi S.; Mate, Adam; Barnes, Arthur; Bent, Russell | 2024 | 1 | Datainfrastructuredecisionsupport | ๐ Search |
| Applications of Graph Computing and Graph Neural Networks in Power Systems: A Survey | Jiangang, Lu; Huijuan, Tan; Ruifeng, Zhao; Wenxin, Guo; Zhen, Dai; Ping, Li | 2024 | 0 | General | ๐ Search |
| Prediction and mitigation of nonlocal cascading failures using graph neural networks | Jhun, Bukyoung; Choi, Hoyun; Lee, Yongsun; Lee, Jongshin; Kim, Cook Hyun; Kahng, B. | 2023 | 8 | Reliabilityresilience | ๐ Search |
| Power System Transient Stability Assessment Method Based on Optimized Time-Spectral Graphical Neural Network | Huangfu, H.; Wang, Y.; Lin, H. | 2024 | 0 | PlanningoptimizationOperationcontrol | ๐ Search |
| Study of Total Transfer Capability Based on Deep Learning Theory | Huang, Y.; Chen, J.; Cai, D.; Wang, E. | 2024 | 0 | Operationcontrol | ๐ Search |
| A Power Forecasting Method in Multiple Time Scales Based on Attention Mechanism and Spatiotemporal Correlation Graph Convolutional Neural Network | Huang, Wei; Yin, Shaoyang; Shi, Jianfeng; Zhou, Hanyu; Ding, Ruoyang; Tian, Xing; Tang, Mingfu; Gao, Lengshan; Wu, Jiayu | 2024 | 0 | Forecastingprediction | ๐ Search |
| A Knowledge Graph Completion Method for the Power Transformer Based on Graph Neural Network and TransR | He, Hongying; Luo, Guangwei; Zhu, Jizhong; Luo, Diansheng; Liang, Wenju; Liu, Nan | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Resilient Temporal GCN for Smart Grid State Estimation Under Topology Inaccuracies | Haghshenas, Seyed Hamed; Naeini, Mia | 2024 | 0 | Operationcontrol | ๐ Search |
| Deep Statistical Solver for Distribution System State Estimation | Habib, Benjamin; Isufi, Elvin; van Breda, Ward; Jongepier, Arjen; Cremer, Jochen L. | 2024 | 15 | Operationcontrol | ๐ Search |
| Power System Transient Stability Assessment Based on Graph Neural Network with Interpretable Attribution Analysis | Gu, Sili; Qiao, Ji; Zhao, Zixuan; Zhu, Qiongfeng; Han, Fujia | 2022 | 4 | Operationcontrol | ๐ Search |
| PowerFlowMultiNet: Multigraph Neural Networks for Unbalanced Three-Phase Distribution Systems | Ghamizi, Salah; Cao, Jun; Ma, Aoxiang; Rodriguez, Pedro | 2024 | 2 | Planningoptimization | ๐ Search |
| SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids | Ghamizi, Salah; Bojchevski, Aleksandar; Ma, Aoxiang; Cao, Jun | 2024 | 2 | Cybersecurityprivacy | ๐ Search |
| Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks | Fusco, Francesco; Eck, Bradley; Gormally, Robert; Purcell, Mark; Tirupathi, Seshu | 2021 | 14 | Datainfrastructuredecisionsupport | ๐ Search |
| A Frequency Stability Prediction Method Using Spatial Temporal Graph Convolutional Networks and Self-attention Mechanism | Feng, K.; Zhou, H.; Qin, W.; Han, S.; Rong, N.; Du, D.; He, Y.; Yang, C. | 2024 | 0 | Operationcontrol | ๐ Search |
| Short-term Charging Quantity Prediction of Charging Stations Based on Graph Neural Networks | Feng, B.; Li, X.; Hou, Z.; Mao, J.; Liu, W. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Fault Location Method of Distribution Network Based on VGAE-GraphSAGE | Fan, M.; Xia, J.; Zhang, H.; Zhang, X. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Generalized FDIA Detection in Power Dependent Electrified Transportation Systems | Fahim, Shahriar Rahman; Atat, Rachad; Kececi, Cihat; Takiddin, Abdulrahman; Ismail, Muhammad; Davis, Katherine R.; Serpedin, Erchin | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Improved Physics-Informed Neural Network based AC Power Flow for Distribution Networks | Eeckhout, V.; Fani, H.; Hashmi, M.U.; Deconinck, G. | 2024 | 0 | Planningoptimization | ๐ Search |
| Graph Neural Network-Based Node Clustering for Dual-Focused Power Network Partitioning | Eddin, M.E.; Massaoudi, M.; Abu-Rub, H.; Shadmand, M.; Abdallah, M. | 2024 | 1 | General | ๐ Search |
| Graph Neural Solver for Power Systems | Donon, Balthazar; Donnot, Benjamin; Guyon, Isabelle; Marot, Antoine | 2019 | 57 | Planningoptimization | ๐ Search |
| Controlled Islanding of Power Systems Based on Structural Deep Clustering Network | Ding, Lijie; Shi, Huabo; Wang, Yongcan; Wang, Xi; Liu, Tingjian; Duan, Longxiang | 2024 | 0 | Operationcontrol | ๐ Search |
| An interpretable graph neural network for real-world satellite power system anomaly detection based on graph filtering | Di, Y.; Wang, F.; Zhao, Z.; Zhai, Z.; Chen, X. | 2024 | 5 | Reliabilityresilience | ๐ Search |
| Graph Neural Network Framework for Security Assessment Informed by Topological Measures | Dezvarei, Mojtaba; Tomsovic, Kevin; Sun, Jinyuan Stella; Djouadi, Seddik M. | 2023 | 2 | Cybersecurityprivacy | ๐ Search |
| Initial estimate of AC optimal power flow with graph neural networks | Deihim, A.; Apostolopoulou, D.; Alonso, E. | 2024 | 2 | Planningoptimization | ๐ Search |
| Physics-informed geometric deep learning for inference tasks in power systems | de Jongh, Steven; Gielnik, Frederik; Mueller, Felicitas; Schmit, Loris; Suriyah, Michael; Leibfried, Thomas | 2022 | 9 | Operationcontrol | ๐ Search |
| Solar Power Prediction Based on Satellite Measurements โ A Graphical Learning Method for Tracking Cloud Motion | Cheng, Lilin; Zang, Haixiang; Wei, Zhinong; Ding, Tao; Sun, Guoqiang | 2022 | 39 | Forecastingprediction | ๐ Search |
| Three-Phase Unbalance Control Method in Distribution Network Based on Model Predictive Control | Cheng, Cheng; Zhou, Guizhen; Ye, Chao; Ma, Yue; Lu, Haipeng | 2024 | 1 | ForecastingpredictionOperationcontrol | ๐ Search |
| Learning Power System Vulnerabilities through Multi-View Topological Neural Networks | Chen, Y.; Wang, S.; Du, L. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Graph Neural Network-Based Wind Farm Cluster Speed Prediction | Chen, Ruifeng; Liu, Jiaming; Wang, Fei; Ren, Hui; Zhen, Zhao | 2020 | 9 | Forecastingprediction | ๐ Search |
| Real-time Multi-stability Risk Assessment and Visualization of Power Systems: A Graph Neural Network-based Method | Chen, Q.; Bu, S.; Wang, H.; Lei, C. | 2024 | 0 | ReliabilityresilienceOperationcontrol | ๐ Search |
| A Method for Anomaly Detection in Power Energy Topology Graph Data Based on Domain Knowledge Graph and Graph Neural Networks | Chen, M.; Yang, S.; Dai, W.; Wang, Z.; Xu, J. | 2024 | 0 | ReliabilityresilienceDatainfrastructuredecisionsupport | ๐ Search |
| Powerformer: A Section-adaptive Transformer for Power Flow Adjustment | Chen, Kaixuan; Luo, Wei; Liu, Shunyu; Wei, Yaoquan; Zhou, Yihe; Qing, Yunpeng; Zhang, Quan; Song, Jie; Song, Mingli | 2024 | 2 | Planningoptimization | ๐ Search |
| Research on Optimization of Distribution Network Connection Mode Based on Graph Neural Network and Genetic Algorithm | Chen, G.; Hui, W.; Huan, Y.; Bingchen, L.; Xingxing, Z. | 2024 | 0 | Planningoptimization | ๐ Search |
| A Temporal Ensembling Based Semi-Supervised Graph Convolutional Network for Power Quality Disturbances Classification | Cai, J.; Wang, H.; Jiang, H. | 2024 | 1 | Other | ๐ Search |
| Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks | Boyaci, Osman; Narimani, Mohammad Rasoul; Davis, Katherine; Ismail, Muhammad; Overbye, Thomas J.; Serpedin, Erchin | 2022 | 84 | Cybersecurityprivacy | ๐ Search |
| Solving AC Power Flow with Graph Neural Networks under Realistic Constraints | Bรถttcher, Luis; Wolf, Hinrikus; Jung, Bastian; Lutat, Philipp; Trageser, Marc; Pohl, Oliver; Ulbig, Andreas; Grohe, Martin | 2023 | 10 | Planningoptimization | ๐ Search |
| Robust Sampling Methods for Accurate Power Flow Time-Sweep Approximations with Graph Neural Networks | Bolz, Valentin; Rueฮฒ, Johannes; Zell, Andreas | 2024 | 0 | Planningoptimization | ๐ Search |
| Power Flow Approximation Based on Graph Convolutional Networks | Bolz, Valentin; Rueร, Johannes; Zell, Andreas | 2019 | 42 | Planningoptimization | ๐ Search |
| Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks | Bhaila, Karuna; Wu, Xintao | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Real-time AI-based Line-Line Fault Detection and Localization in Power Electronics Dominated Grids | Baker, M.; Shadmand, M.B. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Anomaly Detection of Electrical Load in Power Systems Based on Graph Neural Networks | Bai, S. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Accelerating Power Flow Calculations in LV Networks Using Physics-Informed Graph Neural Networks | Azam, F.; Hermans, C.; Becker, T.; D'Hulst, R.; Vanthournout, K.; Deconinck, G. | 2024 | 0 | Planningoptimization | ๐ Search |
| Physics-informed Graph Neural Network for Dynamic Reconfiguration of power systems | Authier, J.; Haider, R.; Annaswamy, A.; Dรถrfler, F. | 2024 | 3 | Operationcontrol | ๐ Search |
| Determining Feasibility of DC Power Flow Using Graph Neural Networks | Alduaij, H.; Zhang, B.; Weng, Y. | 2024 | 0 | Planningoptimization | ๐ Search |
| Forecasting of Short-Term Load Using the MFF-SAM-GCN Model | Zou, Y.; Feng, W.; Zhang, J.; Li, J. | 2022 | 17 | Forecastingprediction | ๐ Search |
| A short-term voltage stability online prediction method based on graph convolutional networks and long short-term memory networks | Wang, G.; Zhang, Z.; Bian, Z.; Xu, Z. | 2021 | 65 | Operationcontrol | ๐ Search |
| Power System Network Topology Identification Based on Knowledge Graph and Graph Neural Network | Wang, Changgang; An, Jun; Mu, Gang | 2021 | 33 | PlanningoptimizationDatainfrastructuredecisionsupport | ๐ Search |
| Power system emergency control strategy based on severely disturbed units identification and STGCN-DDQN | Wang, B.; Tang, Y.; Huang, Y.; Wang, T. | 2024 | 2 | PlanningoptimizationOperationcontrol | ๐ Search |
| A Lightweight Graph-based Convolutional Neural Network for Fault Correlation Analysis in Power Systems | Wang, B.; Feng, L.; Tan, Y.; Xu, H.; Xu, J.; IEEE | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Research on vulnerability assessment method of electric power network based on graph neural | Wan, Z.; Liu, X.; Zhang, Y.; Wang, Y.; Zeng, Y. | 2023 | 0 | Reliabilityresilience | ๐ Search |
| A graph neural network based fault diagnosis strategy for power communication networks | Wan, Z.; Lin, L.; Huang, Y.; Wang, X. | 2024 | 2 | Reliabilityresilience | ๐ Search |
| Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems | Vincent, E.; Korki, M.; Seyedmahmoudian, M.; Stojcevski, A.; Mekhilef, S. | 2024 | 6 | Cybersecurityprivacy | ๐ Search |
| Detection of false data injection attacks in cyberโphysical systems using graph convolutional network | Vincent, E.; Korki, M.; Seyedmahmoudian, M.; Stojcevski, A.; Mekhilef, S. | 2023 | 41 | Cybersecurityprivacy | ๐ Search |
| Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production | Verdone, A.; Scardapane, S.; Panella, M. | 2024 | 20 | Forecastingprediction | ๐ Search |
| Cascades-Risk Informed Transmission Expansion Planning by Behavioural Cloning | Varbella, A.; Gjorgiev, B.; Sansavini, G.; Zio, E. | 2023 | 0 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Graph Neural Network-Based Power Flow Model | Tuo, M.; Li, X.; Zhao, T. | 2023 | 8 | Planningoptimization | ๐ Search |
| Distributed resource power aggregation prediction considering photovoltaic and wind power | Tang, X.; Zeng, Z.; Sibo, B.; Teng, C.; Li, H.; Cheng, J. | 2023 | 1 | Forecastingprediction | ๐ Search |
| AIGCN: Attack Intention Detection for Power System Using Graph Convolutional Networks | Tang, Q.; Chen, H.; Ge, B.; Wang, H. | 2022 | 2 | Cybersecurityprivacy | ๐ Search |
| Spatial-Temporal Wind Power Probabilistic Forecasting Based on Time-Aware Graph Convolutional Network | Tang, J.; Liu, Z.; Hu, J. | 2024 | 4 | Forecastingprediction | ๐ Search |
| Power system topological node tamper detection method based on fuzzy graph theory | Tan, H.; Guo, W.; Li, S.; Zheng, W.; Li, Q. | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Robust Graph Autoencoder-Based Detection of False Data Injection Attacks Against Data Poisoning in Smart Grids | Takiddin, A.; Ismail, M.; Atat, R.; Davis, K.R.; Serpedin, E. | 2024 | 13 | Cybersecurityprivacy | ๐ Search |
| Graph Autoencoder-Based Detection of Unseen False Data Injection Attacks in Smart Grids | Takiddin, A.; Ismail, M.; Atat, R.; Davis, K.R.; Serpedin, E. | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Generalized Graph Neural Network-Based Detection of False Data Injection Attacks in Smart Grids | Takiddin, A.; Atat, R.; Ismail, M.; Boyaci, O.; Davis, K.R.; Serpedin, E. | 2023 | 36 | Cybersecurityprivacy | ๐ Search |
| A Graph Neural Network Multi-Task Learning-Based Approach for Detection and Localization of Cyberattacks in Smart Grids | Takiddin, A.; Atat, R.; Ismail, M.; Davis, K.; Serpedin, E.; IEEE; IEEE Signal Processing Society | 2023 | 5 | Cybersecurityprivacy | ๐ Search |
| Cyber-Physical GNN-Based Intrusion Detection in Smart Power Grids | Sweeten, J.; Takiddin, A.; Ismail, M.; Refaat, S.S.; Atat, R. | 2023 | 4 | Cybersecurityprivacy | ๐ Search |
| End-to-end deep graph convolutional neural network approach for intentional islanding in power systems considering load-generation balance | Sun, Z.; Spyridis, Y.; Lagkas, T.; Sesis, A.; Efstathopoulos, G.; Sarigiannidis, P. | 2021 | 11 | Planningoptimization | ๐ Search |
| An ultra-fast optimization algorithm for unit commitment based on neural branching | Sun, Y.; Wu, J.; Zhang, G.; Zhang, L.; Li, R. | 2023 | 4 | Planningoptimization | ๐ Search |
| Battery Swapping Dispatch for Self-Sustained Highway Energy System Based on Spatiotemporal Deep-Learning Traffic Flow Prediction | Sun, Y.; Li, Y.; Borozan, S.; Wang, G.; Qiu, J.; Strbac, G. | 2024 | 3 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Research on Carbon Traceability of Power System Based on Blockchain and Power Flow Calculation under Carbon Peaking and Carbon Neutrality Goals | Sun, H.; Yang, C.; Li, T.; Song, J.; Lei, Z.; Zhang, Y.; Liu, Y.; Hou, Y.; IEEE | 2022 | 2 | Planningoptimization | ๐ Search |
| Smart grid power load type forecasting: research on optimization methods of deep learning models | Sun, H.; Ren, Y.; Wang, S.; Zhao, B.; Yin, R. | 2023 | 2 | ForecastingpredictionPlanningoptimization | ๐ Search |
| A Data Retrieval Method Based on AGCN-WGAN | Sun, G.; Peng, G.; Tian, X.; Li, L.; Zhao, Y.; Wang, Y. | 2024 | 1 | Datainfrastructuredecisionsupport | ๐ Search |
| Graph Neural Network-Based ShortโTerm Load Forecasting with Temporal Convolution | Sun, C.; Ning, Y.; Shen, D.; Nie, T. | 2023 | 15 | Forecastingprediction | ๐ Search |
| Graph Learning Empowered Situation Awareness in Internet of Energy With Graph Digital Twin | Sui, L.; Guan, X.; Cui, C.; Jiang, H.; Pan, H.; Ohtsuki, T. | 2023 | 16 | Datainfrastructuredecisionsupport | ๐ Search |
| Short-term load forecasting of regional integrated energy system based on spatio-temporal convolutional graph neural network | Su, Z.; Zheng, G.; Hu, M.; Kong, L.; Wang, G. | 2024 | 6 | Forecastingprediction | ๐ Search |
| A Short-term PV Power Forecasting Method based on NWP Correction Considering Meteorological Coupling Correlation | Su, Y.; Sun, Y.; Yang, H.; Ren, H.; Zhen, Z.; Wang, F. | 2023 | 3 | Forecastingprediction | ๐ Search |
| Multi-task Transient Contingency Screening with Temporal Graph Convolutional Network in Power Systems | Su, Y.; Huang, J.; Yao, H.; Guan, L.; Guo, M.; Zhong, Z. | 2021 | 1 | Planningoptimization | ๐ Search |
| Power System Small-signal Stability Assessment Model Based on Residual Graph Convolutional Networks | Su, Y.; Guo, M.; Yao, H.; Guan, L.; Huang, J.; Zhu, S.; Zhong, Z. | 2021 | 4 | Operationcontrol | ๐ Search |
| DAMGAT Based Interpretable Detection of False Data Injection Attacks in Smart Grids | Su, X.; Deng, C.; Yang, J.; Li, F.; Li, C.; Fu, Y.; Dong, Z.Y. | 2024 | 9 | Cybersecurityprivacy | ๐ Search |
| Application of Physics-based Graph Convolutional Network in Real-time State Estimation of Under-determined Distribution Grids | Stock, S.; Dressel, M.; Babazadeh, D.; Becker, C. | 2022 | 1 | Operationcontrol | ๐ Search |
| Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems | Sterzinger, R.; Poland, J.; Paulus, M.B.; Chรฉtelat, D.; ENEDIS; et al.; GreenAlp; Le Reseau de Transport d'electricite (RTE); Schneider Electric; Think Smartgrids | 2023 | 1 | Forecastingprediction | ๐ Search |
| Graph-based Large Scale Probabilistic PV Power Forecasting Insensitive to Space-Time Missing Data | Song, K.; Kim, M.; Kim, H. | 2024 | 3 | ForecastingpredictionDatainfrastructuredecisionsupport | ๐ Search |
| Interpretable temporal-spatial graph attention network for multi-site PV power forecasting | Simeunoviฤ, J.; Schubnel, B.; Alet, P.-J.; Carrillo, R.E.; Frossard, P. | 2022 | 42 | Forecastingprediction | ๐ Search |
| Load Forecasting of Electric Vehicle Charging Stations: Attention Based Spatiotemporal Multi-Graph Convolutional Networks | Shi, J.; Zhang, W.; Bao, Y.; Gao, D.W.; Wang, Z. | 2024 | 25 | Forecastingprediction | ๐ Search |
| Integrated advance assessment of power system transient voltage and transient angle stability based on two-stage ensemble spatio-temporal graph neural network | Shi, F.; Wu, J.; Wang, Y.; Li, L.; Zheng, Y. | 2023 | 7 | Operationcontrol | ๐ Search |
| Graph Convolutional Networks for probabilistic power system operational planning | Sheikh-Mohamed, Y.B.; Jakobsen, S.H.; Bรธdal, E.F.; Haugseth, F.M.; Kiel, E.S.; Riemer-Sรธrensen, S.; DIG Silent; EMTP; et al.; Opal-RT Technologies; RTDS Technologies; Saturn Electric | 2023 | 0 | PlanningoptimizationOperationcontrol | ๐ Search |
| Fault location estimation of power grid using graph attention networks | Shan, P.; Han, L.; Lei, M.; Pan, R.; Zhao, Y.; Li, Y.; Academic Exchange Information Centre (AEIC); Hohai University | 2024 | 0 | ReliabilityresilienceOperationcontrol | ๐ Search |
| Review and Comparative Analysis of Deep Learning Techniques for Smart Grid Load Forecasting | Shahinzadeh, H.; Sadrarhami, H.; Hayati, M.M.; Majidi-Gharehnaz, H.; Abapour, M.; Gharehpetian, G.B. | 2024 | 3 | Forecastingprediction | ๐ Search |
| Data-driven approach to form energy-resilient microgrids with identification of vulnerable nodes in active electrical distribution network | Reddy, D.M.; Dwivedi, D.; Yemula, P.K.; Pal, M. | 2023 | 6 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Hybrid LSTM-Graph Convolutional Neural Network with Wavelet Transform and Correlation Analysis for Electrical Demand Forecasting | Rawal, K.; Ahmad, A. | 2024 | 1 | Forecastingprediction | ๐ Search |
| Multi-Edge Graph Convolutional Networks for Power Systems | Ravi, A.; Bai, L.; Ding, F.; Wang, H. | 2024 | 0 | Method | ๐ Search |
| ENERGY EXCHANGE PROCESS FOR SMART GRID BASED ON INTEGRATING BLOCKCHAIN WITH GCN-LSTM | Rao, V.S.; Anjum, A.; Mary, S.S.C.; Aqeel, I.; Koteswari, S.; Khan, S.A.; Rengarajan, M. | 2023 | 0 | General | ๐ Search |
| Localization of dummy data injection attacks in power systems considering incomplete topological information: A spatio-temporal graph wavelet convolutional neural network approach | Qu, Z.; Dong, Y.; Li, Y.; Song, S.; Jiang, T.; Li, M.; Wang, Q.; Wang, L.; Bo, X.; Zang, J.; Xu, Q. | 2024 | 29 | Cybersecurityprivacy | ๐ Search |
| A Knowledge-Graph-Driven Method for Intelligent Decision Making on Power Communication Equipment Faults | Qu, H.; Zhang, Y.; Liang, K.; Li, S.; Huo, X. | 2023 | 3 | ReliabilityresilienceDatainfrastructuredecisionsupport | ๐ Search |
| Load forecasting based on dynamic adaptive and adversarial graph convolutional networks | Liu, J.; Dong, S.; Zhang, P.; Li, T.; Peng, C.; Hu, Z. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Anomalous Traffic Detection Method for Power Internet of Things Based on Graph Neural Networks | Liu, C.; Zhao, J.; Song, Z.; Dong, Y.; IEEE | 2023 | 0 | Cybersecurityprivacy | ๐ Search |
| Electric Load Forecasting for Individual Households via Spatial-temporal Knowledge Distillation | Lin, W.; Wu, D.; Jenkin, M. | 2024 | 1 | ForecastingpredictionDatainfrastructuredecisionsupport | ๐ Search |
| Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks | Lin, W.; Wu, D.; International Joint Conferences on Artifical Intelligence (IJCAI) | 2021 | 0 | Forecastingprediction | ๐ Search |
| Spatiotemporal Graph Convolutional Neural Network-Based Forecasting-Aided State Estimation Using Synchrophasors | Lin, J.; Tu, M.; Hong, H.; Lu, C.; Song, W. | 2024 | 3 | ForecastingpredictionOperationcontrol | ๐ Search |
| Transient Stability Analysis of AC-DC Hybrid Power Grid under Topology Changes Based on Deep Learning | Lin, H.; Chen, Z.; Chen, J.; Chen, W.; Guangdong University of Technology; IEEE; IEEE PES; South China University of Technology; University of Electronic Science and Technology of China | 2022 | 3 | Operationcontrol | ๐ Search |
| Emergency Control of Power Grid under Topology Changes Based on Graph Reinforcement Learning | Lin, H.; Chen, J.; Chen, W.; Chen, Z.; Guangdong University of Technology; IEEE; IEEE PES; South China University of Technology; University of Electronic Science and Technology of China | 2022 | 0 | Operationcontrol | ๐ Search |
| Electricity Theft Detection Using Euclidean and Graph Convolutional Neural Networks | Liao, W.; Yang, Z.; Liu, K.; Zhang, B.; Chen, X.; Song, R. | 2023 | 33 | Cybersecurityprivacy | ๐ Search |
| Ultra-short-term Interval Prediction of Wind Power Based on Graph Neural Network and Improved Bootstrap Technique | Liao, W.; Wang, S.; Bak-Jensen, B.; Pillai, J.R.; Yang, Z.; Liu, K. | 2023 | 31 | Forecastingprediction | ๐ Search |
| Short-term power prediction for renewable energy using hybrid graph convolutional network and long short-term memory approach | Liao, W.; Bak-Jensen, B.; Pillai, J.R.; Yang, Z.; Liu, K. | 2022 | 42 | Forecastingprediction | ๐ Search |
| A Data and Model-Driven Deep Learning Approach to Robust Downlink Beamforming Optimization | Liang, K.; Zheng, G.; Li, Z.; Wong, K.; Chae, C. | 2024 | 1 | Planningoptimization | ๐ Search |
| Graph-based detection for false data injection attacks in power grid | Li, X.; Wang, Y.; Lu, Z. | 2023 | 33 | Cybersecurityprivacy | ๐ Search |
| Detection of false data injection attack in power grid based on spatial-temporal transformer network | Li, X.; Hu, L.; Lu, Z. | 2024 | 9 | Cybersecurityprivacy | ๐ Search |
| Research on smart grid management and security guarantee of sports stadiums based on GCNN-GRU and self-attention mechanism | Li, S. | 2023 | 1 | Cybersecurityprivacy | ๐ Search |
| Triplet-aware graph neural networks for factorized multi-modal knowledge graph entity alignment | Li, Q.; Li, J.; Wu, J.; Peng, X.; Ji, C.; Peng, H.; Wang, L.; Yu, P.S. | 2024 | 5 | Datainfrastructuredecisionsupport | ๐ Search |
| Graph Convolution Networks-Based Island Partition for Energy and Information Coupled Active Distribution Systems | Li, Q.; Dai, S.; Li, X.; Li, W.; Sun, W. | 2021 | 2 | Operationcontrol | ๐ Search |
| An Entity Alignment Method Integrating Dual Entity Classification and Graph Attention Networks in Power Domain | Li, P.; Huang, W.; Liang, L.; Liang, Y.; Dai, Z.; Hou, J.; Wang, X.; Chen, X.; Chinese Society for Electrical Engineering; IEEE Power and Energy Society; State Grid Corporation of China | 2023 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| A Data-Driven Method for Power System Emergency Control to Improve Short-Term Voltage Stability | Li, M.; Lin, Z.; Lin, Y.; Tang, Y.; Jiang, C.; Liu, C.; Shao, Z. | 2023 | 1 | Operationcontrol | ๐ Search |
| Forced oscillation location based on temporal graph convolutional network | Li, L.; Wang, B.; Liu, S.; Li, J.; Teng, S.; Liu, D.; Peng, X.; Feng, S. | 2023 | 5 | Operationcontrol | ๐ Search |
| Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods | Li, J.; Liu, T.; Zhu, G.; Li, Y.; Xie, Y. | 2023 | 12 | Planningoptimization | ๐ Search |
| A Spatiotemporal Coupling Calculation-Based Short-Term Wind Farm Cluster Power Prediction Method | Li, H.; Liu, L.; He, Q. | 2023 | 3 | Forecastingprediction | ๐ Search |
| Short-Term Wind Power Forecasting for Multiple Farms with Alternating Temporal and Graph Convolutional Networks | Li, G.; Che, J.; Liu, D.; IEEE; IEEE Power and Energy Society (PES); Science and Engineering Institute (SCIEI) | 2023 | 0 | Forecastingprediction | ๐ Search |
| An adaptive spatiotemporal fusion graph neural network for short-term power forecasting of multiple wind farms | Li, D.; Yang, F.; Miao, S.; Gan, Y.; Yang, B.; Zhang, Y. | 2023 | 3 | Forecastingprediction | ๐ Search |
| Twin Data Correlation Analysis Based on GCN-LSTM model and Its Sharing with Blockchain Technology | Li, C.; Zhang, Q.; Chen, L.; Qiu, Y.; Zhao, B. | 2023 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Low Carbon Economy Optimal Dispatching Strategy for a Power System Based on GCN Classification | Li, C.; Yin, X.; Zhao, H.; Li, X.; Shen, H.; Qi, L. | 2023 | 0 | Planningoptimization | ๐ Search |
| A BROADBAND OSCILLATION SOURCE LOCATION METHOD BASED ON LSTM VARIATIONAL AUTOENCODER AND GRAPH CONVOLUTIONAL NEURAL NETWORK | Li, C.; Wang, Y.; Zheng, Z. | 2023 | 0 | Operationcontrol | ๐ Search |
| Spatio-Temporal Missing Data Imputation for Smart Power Grids | Kuppannagari, S.R.; Fu, Y.; Chueng, C.M.; Prasanna, V.K.; ACM SIGEnergy | 2021 | 26 | Datainfrastructuredecisionsupport | ๐ Search |
| Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks | Kundacina, O.; Forcan, M.; Cosovic, M.; Raca, D.; Dzaferagic, M.; Miskovic, D.; Maksimovic, M.; Vukobratovic, D. | 2022 | 5 | Operationcontrol | ๐ Search |
| Graph neural networks on factor graphs for robust, fast, and scalable linear state estimation with PMUs | Kundacina, O.; Cosovic, M.; Miskovic, D.; Vukobratovic, D. | 2023 | 7 | Operationcontrol | ๐ Search |
| Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach | Kim, S.; Heo, S.; Nam, K.; Woo, T.; Yoo, C. | 2023 | 8 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Three-Phase Inverter Dynamics Predictions Using GNN-based Regression Model | Khamis, A.K.; Agamy, M.; Comsol; Delta; et al.; Hitachi; John Deere; Oak Ridge National Laboratory | 2023 | 0 | Forecastingprediction | ๐ Search |
| Asynchronous Traveling Wave-based Distribution System Protection with Graph Neural Networks | Jimenez-Aparicio, M.; Reno, M.J.; Wilches-Bernal, F.; Burns and McDonnell; Imperix | 2022 | 5 | Reliabilityresilience | ๐ Search |
| Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks | Jimรฉnez-Aparicio, M.; Hernรกndez-Alvidrez, J.; Montoya, A.Y.; Reno, M.J. | 2022 | 6 | Reliabilityresilience | ๐ Search |
| A Graph Neural Network Based Deep Learning Predictor for Spatio-Temporal Group Solar Irradiance Forecasting | Jiao, X.; Li, X.; Lin, D.; Xiao, W. | 2022 | 59 | Forecastingprediction | ๐ Search |
| Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables | Jiang, W.; Liu, B.; Liang, Y.; Gao, H.; Lin, P.; Zhang, D.; Hu, G. | 2024 | 38 | Forecastingprediction | ๐ Search |
| Short-Term Wind Power Output Prediction Based on Temporal Graph Convolutional Networks | Ji, X.; Li, Z.; Jiang, X.; Yang, D.; Shandong University; Tsinghua University | 2022 | 1 | Forecastingprediction | ๐ Search |
| Graph Neural Network Based Prediction of Data Traffic in Cyber-Physical Smart Power Grids | Islam, M.A.; Ismail, M.; Boyaci, O.; Atat, R.; Shannigrahi, S. | 2022 | 2 | Cybersecurityprivacy | ๐ Search |
| Proactive Routing Strategy in SDN-Based Smart Power Grids Using Graph Neural Network and Reinforcement Learning | Islam, M.A.; Ismail, M.; Atat, R.; Boyaci, O.; Shannigrahi, S. | 2023 | 6 | Datainfrastructuredecisionsupport | ๐ Search |
| Anomaly detection in smart grid using a trace-based graph deep learning model | Ida Evangeline, S.; Darwin, S.; Peter Anandkumar, P.; Chithambara Thanu, M. | 2024 | 3 | Reliabilityresilience | ๐ Search |
| AWL-GCN: Branch Parameter Identification Considering Grid Spatial Structure Constraints | Huang, Z.; Xia, M.; Lu, M.; Pan, L.; Liu, J. | 2023 | 3 | Planningoptimization | ๐ Search |
| Risk-averse stochastic dynamic power dispatch based on deep reinforcement learning with risk-oriented Graph-Gan sampling | Huang, W.; Dai, Z.; Hou, J.; Liang, L.; Chen, Y.; Chen, Z.; Pan, Z. | 2023 | 0 | PlanningoptimizationReliabilityresilience | ๐ Search |
| Spatial-Temporal-Correlation Multi-Feature-based Project Engineering and Prediction in Smart Grid | Huang, S.; Peng, G.; Zhang, Y.; Zhao, J.; Zhu, K.; Zhang, H.; Wang, X.; IEEE; IEEE Computer Society | 2021 | 0 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Safety analysis of new power system based on graph convolutional neural network evaluation | Huang, J.; Wu, F.; Li, Y.; Qian, J.; Yang, Y.; Yao, W.; IEEE | 2023 | 0 | Cybersecurityprivacy | ๐ Search |
| A deep learning scheme for transient stability assessment in power system with a hierarchical dynamic graph pooling method | Huang, J.; Guan, L.; Chen, Y.; Zhu, S.; Chen, L.; Yu, J. | 2022 | 6 | Operationcontrol | ๐ Search |
| GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems | Huang, D.; Liu, H.; Bi, T.; Yang, Q. | 2022 | 11 | Forecastingprediction | ๐ Search |
| Multidimensional Feature-Based Graph Attention Networks and Dynamic Learning for Electricity Load Forecasting | Huang, C.; Du, N.; He, J.; Li, N.; Feng, Y.; Cai, W. | 2023 | 1 | Forecastingprediction | ๐ Search |
| Time Series Anomaly Detection Based on Graph Convolutional Networks | Hu, Z.; Wu, T.; Zhang, Y.; Li, J.; Jiang, L. | 2020 | 4 | Reliabilityresilience | ๐ Search |
| Wind Power Forecasting Based on Adaptive Spatio-Temporal Graph Neural Network | Hu, N.; Wang, G.; Yang, Y.; IEEE; Lanzhou Jiaotong University; School of New Energy and Power Engineering | 2023 | 0 | Forecastingprediction | ๐ Search |
| Knowledge reasoning in power grid infrastructure projects based on deep multi-view graph convolutional network | Hu, J.; Xu, G.; Qi, L.; Qie, X. | 2023 | 2 | PlanningoptimizationDatainfrastructuredecisionsupport | ๐ Search |
| Graph Convolutional Neural Networks for Optimal Load Shedding under Line Contingency | Kim, Cheolmin; Kim, Kibaek; Balaprakash, Prasanna; Anitescu, Mihai | 2019 | 43 | Planningoptimization | ๐ Search |
| Fault Detection and Isolation in Industrial Networks using Graph Convolutional Neural Networks | Khorasgani, Hamed; Hasanzadeh, Arman; Farahat, Ahmed; Gupta, Chetan | 2019 | 20 | Reliabilityresilience | ๐ Search |
| Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting | Khodayar, Mahdi; Wang, Jianhui | 2019 | 336 | Forecastingprediction | ๐ Search |
| Convolutional Graph Autoencoder: A Generative Deep Neural Network for Probabilistic Spatio-Temporal Solar Irradiance Forecasting | Khodayar, Mahdi; Mohammadi, Saeed; Khodayar, Mohammad E.; Wang, Jianhui; Liu, Guangyi | 2020 | 132 | Forecastingprediction | ๐ Search |
| Federated Learning Based Distributed Localization of False Data Injection Attacks on Smart Grids | Keรงeci, Cihat; Davis, Katherine R.; Serpedin, Erchin | 2023 | 0 | Cybersecurityprivacy | ๐ Search |
| Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems | Karimi, Ahmad Maroof; Wu, Yinghui; Koyuturk, Mehmet; French, Roger H. | 2021 | 44 | Forecastingprediction | ๐ Search |
| A Physics-Informed Graph Attention-based Approach for Power Flow Analysis | Jeddi, Ashkan B.; Shafieezadeh, Abdollah | 2021 | 15 | Planningoptimization | ๐ Search |
| High Impedance Fault Detection in Electrical Power Feeder by Wavelet and GNN | Jamil, Majid; Sharma, Rajveer Singh and S. K. | 2015 | 0 | Reliabilityresilience | ๐ Search |
| Fault Diagnostics in Shipboard Power Systems using Graph Neural Networks | Jacob, Roshni Anna; Senemmar, Soroush; Zhang, Jie | 2021 | 18 | Reliabilityresilience | ๐ Search |
| Software-Defined Networking-Based Resilient Proactive Routing in Smart Grids Using Graph Neural Networks and Deep Q-Networks | Islam, Md Aminul; Atat, Rachad; Ismail, Muhammad | 2024 | 2 | Datainfrastructuredecisionsupport | ๐ Search |
| Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand | Hรผttel, Frederik Boe; Peled, Inon; Rodrigues, Filipe; Pereira, Francisco C. | 2021 | 13 | Forecastingprediction | ๐ Search |
| Non-intrusive power load decomposition method based on message passing graph neural network | Huangfu, Hancong; Wang, Yongcai; Guan, Zhaoxiong | 2024 | 0 | General | ๐ Search |
| Gated spatial-temporal graph neural network based short-term load forecasting for wide-area multiple buses | Huang, Nantian; Wang, Shengyuan; Wang, Rijun; Cai, Guowei; Liu, Yang; Dai, Qianbin | 2023 | 57 | Forecastingprediction | ๐ Search |
| Recurrent Graph Convolutional Network-Based Multi-Task Transient Stability Assessment Framework in Power System | Huang, Jiyu; Guan, Lin; Su, Yinsheng; Yao, Haicheng; Guo, Mengxuan; Zhong, Zhi | 2020 | 76 | Operationcontrol | ๐ Search |
| GNN4GCโGraph Neural Networks for Grid Control | Hosseini, Ilia; Dietz, Thomas | 2024 | 0 | Operationcontrol | ๐ Search |
| State Estimation in Smart Grids Using Temporal Graph Convolution Networks | Hossain, Md Jakir; Rahnamay-Naeini, Mahshid | 2021 | 25 | Operationcontrol | ๐ Search |
| Graph Reinforcement Learning in Power Grids: A Survey | Hassouna, Mohamed; Holzhรผter, Clara; Lytaev, Pawel; Thomas, Josephine; Sick, Bernhard; Scholz, Christoph | 2024 | 3 | Survey | ๐ Search |
| Power Flow Balancing With Decentralized Graph Neural Networks | Hansen, Jonas Berg; Anfinsen, Stian Normann; Bianchi, Filippo Maria | 2023 | 30 | Planningoptimization | ๐ Search |
| Abnormal Electricity Consumption Behavior Identifying Method with Multiple Types of Users Based on Bo-Gcn | Han, Xiaojuan; Li, Haoyu; Xu, Minglu; He, Ziliang; Li, Bin | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Graph machine learning for predicting wake interaction losses based on SCADA data | Hammer, Florian; Helbig, Nora; Losinger, Thomas; Barber, Sarah | 2023 | 3 | Forecastingprediction | ๐ Search |
| Graph Neural Networks for Voltage Stability Margins With Topology Flexibilities | Guddanti, Kishan Prudhvi; Weng, Yang; Marot, Antoine; Donnot, Benjamin; Panciatici, Patrick | 2023 | 8 | Operationcontrol | ๐ Search |
| OPF-HGNN: Generalizable Heterogeneous Graph Neural Networks for AC Optimal Power Flow | Ghamizi, Salah; Ma, Aoxiang; Cao, Jun; Rodriguez Cortes, Pedro | 2024 | 1 | Planningoptimization | ๐ Search |
| Physics Embedded Graph Convolution Neural Network for Power Flow Calculation Considering Uncertain Injections and Topology | Gao, Maosheng; Yu, Juan; Yang, Zhifang; Zhao, Junbo | 2024 | 10 | Planningoptimization | ๐ Search |
| A Topology-Guided Learning Framework for Security-Constraint Unit Commitment | Gao, Liqian; Fang, Jiakun; Ai, Xiaomeng; Wei, Lishen; Cui, Shichang; Yao, Wei; Wen, Jinyu | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Leveraging Power Grid Topology in Machine Learning Assisted Optimal Power Flow | Falconer, Thomas; Mones, Letif | 2023 | 46 | Planningoptimization | ๐ Search |
| Neural networks for power flow: Graph neural solver | Donon, Balthazar; Clรฉment, Rรฉmy; Donnot, Benjamin; Marot, Antoine; Guyon, Isabelle; Schoenauer, Marc | 2020 | 83 | Planningoptimization | ๐ Search |
| Residential Power Forecasting Using Load Identification and Graph Spectral Clustering | Dinesh, Chinthaka; Makonin, Stephen; Bajic, Ivan V. | 2019 | 49 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Fault localization method for power distribution systems based on gated graph neural networks | de Freitas, Jonas Teixeira; Coelho, Frederico Gualberto Ferreira | 2021 | 20 | Reliabilityresilience | ๐ Search |
| Mitigating Cascading Effects in Large Adversarial Graph Environments | Cunningham, James D.; Tucker, Conrad S. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| IR-Aware ECO Timing Optimization Using Reinforcement Learning | Chhabria, Vidya A.; Jiang, Wenjing; Sapatnekar, Sachin S. | 2024 | 2 | Planningoptimization | ๐ Search |
| Nonintrusive load disaggregation by fusion of graph signal processing and CNN | Chen, Zhigang; Peng, Haotian; Su, Yongxin | 2024 | 0 | General | ๐ Search |
| Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks | Chen, Kunjin; Hu, Jun; Zhang, Yu; Yu, Zhanqing; He, Jinliang | 2020 | 220 | Reliabilityresilience | ๐ Search |
| Powerformer: A Section-Adaptive Transformer for Power Flow Adjustment | Chen, Kaixuan; Luo, Wei; Liu, Shunyu; Wei, Yaoquan; Zhou, Yihe; Qing, Yunpeng; Zhang, Quan; Wang, Yong; Song, Jie; Song, Mingli | 2024 | 0 | Planningoptimization | ๐ Search |
| A Heterogeneous Graph-Based Multi-Task Learning for Fault Event Diagnosis in Smart Grid | Chanda, Dibaloke; Soltani, Nasim Yahya | 2023 | 3 | Reliabilityresilience | ๐ Search |
| Reliability Evaluation of Park-Level Electricity-Hydrogen Systems Using Explainable Graph Neural Network | Cao, Binrui; Wu, Xiong; Wang, Xiuli | 2024 | 3 | Reliabilityresilience | ๐ Search |
| Infinite Impulse Response Graph Neural Networks for Cyberattack Localization in Smart Grids | Boyaci, Osman; Narimani, M. Rasoul; Davis, Katherine; Serpedin, Erchin | 2022 | 8 | OperationcontrolCybersecurityprivacy | ๐ Search |
| Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses | Bentsen, Lars รdegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal | 2022 | 12 | Forecastingprediction | ๐ Search |
| Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models | Al-Ibraheemi, Zainab; Al-Janabi, Samaher | 2024 | 5 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Advancing the MILP-Based Load Restoration with Graph Neural Networks | Ahmed, Shihab; Sun, Wei | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Graph Neural Network for Power Flow Considering Line and Generator Contingencies | Aboutalebi Zonouz, Mirkarim; Tarafdar Hagh, Mehrdad | 0 | Planningoptimization | ๐ Search | |
| Topology-Aware Reinforcement Learning for Tertiary Voltage Control | Donon, Balthazar; Cubelier, Franรงois; Karangelos, Efthymios; Wehenkel, Louis; Crochepierre, Laure; Pache, Camille; Saludjian, Lucas; Panciatici, Patrick | 2024 | 0 | Operationcontrol | ๐ Search |
| Forecasting Electricity Prices: An Optimize Then Predict-Based Approach | Tschora, Lรฉonard; Pierre, Erwan; Plantevit, Marc; Robardet, Cรฉline | 2023 | 1 | ForecastingpredictionPlanningoptimization | ๐ Search |
| Graph Computing Based Knowledge Reasoning in Electric Power System Considering Knowledge Graph Sparsity | Tianjiao, PU; Yuanpeng, TAN; Zhenyuan, MA; Jiannan, XU | 0 | Datainfrastructuredecisionsupport | ๐ Search | |
| Graph Neural Networks for Electric and Hydraulic Data Fusion to Enhance Short-term Forecasting of Pumped-storage Hydroelectricity | Theiler, Raffael; Fink, Olga | 2024 | 1 | Forecastingprediction | ๐ Search |
| Graphdeformer: A Spatio-Temporal Model Integrating Graph Neural Network and Transformer for Wind Power Forecasting | Teng, Jing; Jiang, Yajun; Shi, Ruifeng | 2024 | 0 | Forecastingprediction | ๐ Search |
| Spatio-temporal Graph-Based Generation and Detection of Adversarial False Data Injection Evasion Attacks in Smart Grids | Takiddin, Abdulrahman; Ismail, Muhammad; Atat, Rachad; Serpedin, Erchin | 2024 | 3 | Cybersecurityprivacy | ๐ Search |
| Multi-fidelity Graph Neural Networks for Efficient Power Flow Analysis under High-Dimensional Demand and Renewable Generation Uncertainty | Taghizadeh, Mehdi; Khayambashi, Kamiar; Hasnat, Md Abul; Alemazkoor, Negin | 2024 | 0 | Planningoptimization | ๐ Search |
| Graph Convolutional Neural Networks for Optimal Power Flow Locational Marginal Price | Surani, Adrian-Petru; Sahetiya, Rahul | 2023 | 0 | Planningoptimization | ๐ Search |
| Learning Assisted Optimal Scheduling of Integrated Gas and Electricity Networks Under High Penetration of Renewable Energy | Sun, Xianzhuo; Bai, Runze; Zhang, Wen; Qiu, Jing; Tao, Yuechuan; Lai, Shuying | 2024 | 0 | Planningoptimization | ๐ Search |
| The whole process control algorithm of inflatable dustproof shed construction in substation engineering based on graph neural network | Song, Kun; Li, Shuai; Zhang, Ou; Wu, Xuefeng; Jiang, Xue | 2024 | 0 | Operationcontrol | ๐ Search |
| Visualizing graph neural networks in order to learn general concepts in power systems | Solheim, รystein Rognes; Presthus, Gunnhild Svandal; Hรธverstad, Boye Annfelt; Korpรฅs, Magnus | 2024 | 1 | Datainfrastructuredecisionsupport | ๐ Search |
| Spatio-Temporal Graph Neural Networks for Multi-Site PV Power Forecasting | Simeunovic, Jelena; Schubnel, Baptiste; Alet, Pierre-Jean; Carrillo, Rafael E. | 2022 | 123 | Forecastingprediction | ๐ Search |
| COMBINING PHYSICS AND MACHINE LEARNING FOR NETWORK FLOW ESTIMATION | Silva, Arlei; Kocayusufoglu, Furkan; Jafarpour, Saber; Bullo, Francesco; Swami, Ananthram; Singh, Ambuj | 2021 | 0 | PlanningoptimizationOperationcontrol | ๐ Search |
| An Enhanced Fault Localization Method in Distribution Network Using Graph Neural Network | Shang, Jun; Qiu, Zhen; Gao, Mingwei; Li, Jinsheng | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Smartformer: Graph-Based Transformer Model for Energy Load Forecasting | Saeed, Faisal; Rehman, Abdul; Shah, Hasnain Ali; Diyan, Muhammad; Jie, Chen; Kang, Jae-Mo | 2024 | 0 | Forecastingprediction | ๐ Search |
| Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids | Ringsquandl, Martin; Sellami, Houssem; Hildebrandt, Marcel; Beyer, Dagmar; Henselmeyer, Sylwia; Weber, Sebastian; Joblin, Mitchell | 2021 | 16 | Survey | ๐ Search |
| Spectral Graph Analysis of the Geometry of Power Flows in Transmission Networks | Retiere, Nicolas; Ha, Dinh Truc; Caputo, Jean-Guy | 2020 | 22 | Planningoptimization | ๐ Search |
| Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment | Ramesh, Arun Venkatesh; Li, Xingpeng | 2024 | 20 | Cybersecurityprivacy | ๐ Search |
| Solve Large-scale Unit Commitment Problems by Physics-informed Graph Learning | Qin, Jingtao; Yu, Nanpeng | 2023 | 1 | Method | ๐ Search |
| Reconfigure Distribution Network with Physics-informed Graph Neural Network | Qin, Jingtao; Yu, Nanpeng | 2023 | 2 | Planningoptimization | ๐ Search |
| Dgmscl: A Dynamic Graph Mixed Supervised Contrastive Learning Approach for Class Imbalanced Multivariate Time Series Classification | Qian, Lipeng; Zuo, Qiong; Li, Dahu; Zhu, Hong | 2024 | 0 | General | ๐ Search |
| Reduced Optimal Power Flow Using Graph Neural Network | Pham, Thuan; Li, Xingpeng | 2022 | 21 | Planningoptimization | ๐ Search |
| Dynamic Fault Characteristics Evaluation in Power Grid | Pei, Hao; Lin, Si; Li, Chuanfu; Wang, Che; Chen, Haoming; Li, Sizhe | 0 | Reliabilityresilience | ๐ Search | |
| Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments | Park, Seonho; Chen, Wenbo; Han, Dahye; Tanneau, Mathieu; Van Hentenryck, Pascal | 2024 | 24 | Reliabilityresilience | ๐ Search |
| Physics-induced graph neural network: An application to wind-farm power estimation | Park, Junyoung; Park, Jinkyoo | 2019 | 0 | Operationcontrol | ๐ Search |
| M-Dcatdgn: Enhancing Load Demand Forecasting with an Adaptive Dynamic Graph Neural Network | Pan, Sheng; Jiang, He; Shu, Tong; Dong, Yao; Wang, Jianzhou | 2024 | 0 | Forecastingprediction | ๐ Search |
| Optimal Power Flow Using Graph Neural Networks | Owerko, Damian; Gama, Fernando; Ribeiro, Alejandro | 2020 | 122 | Planningoptimization | ๐ Search |
| Predicting Power Outages Using Graph Neural Networks | Owerko, Damian; Gama, Fernando; Ribeiro, Alejandro | 2018 | 56 | Reliabilityresilience | ๐ Search |
| Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems | Nguyen, Bang L. H.; Vu, Tuyen V.; Nguyen, Thai-Thanh; Panwar, Mayank; Hovsapian, Rob | 2023 | 25 | Reliabilityresilience | ๐ Search |
| Predicting basin stability of power grids using graph neural networks | Nauck, Christian; Lindner, Michael; Schรผrholt, Konstantin; Zhang, Haoming; Schultz, Paul; Kurths, Jรผrgen; Isenhardt, Ingrid; Hellmann, Frank | 2022 | 22 | Operationcontrol | ๐ Search |
| Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning | Nauck, Christian; Lindner, Michael; Molkenthin, Nora; Kurths, Jรผrgen; Schรถll, Eckehard; Raisch, Jรถrg; Hellmann, Frank | 2024 | 1 | ForecastingpredictionOperationcontrol | ๐ Search |
| Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions | Nauck, Christian; Gorantla, Rohan; Lindner, Michael; Schรผrholt, Konstantin; Mey, Antonia S. J. S.; Hellmann, Frank | 2024 | 2 | Forecastingprediction | ๐ Search |
| Time-Synchronized State Estimation Using Graph Neural Networks in Presence of Topology Changes | Moshtagh, Shiva; Sifat, Anwarul Islam; Azimian, Behrouz; Pal, Anamitra | 2023 | 3 | Operationcontrol | ๐ Search |
| Identifying critical nodes in the power grid via deep learning methods | Min, Z.; Zesan, L.; Chenghua, F.; Aijun, W.; Zhenya, W.; Wenjuan, Z. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Intelligent Auxiliary Operation and Maintenance System of Power Communication Network based on Knowledge Graph | Miao, Weiwei; Wu, Haiyang; Chen, Peng; Jing, Jiangping | 2020 | 4 | OperationcontrolDatainfrastructuredecisionsupport | ๐ Search |
| Multi-area short-term load forecasting based on spatiotemporal graph neural network | Lv, Yunlong; Wang, Li; Long, Dunhua; Hu, Qin; Hu, Ziyuan | 2024 | 2 | Forecastingprediction | ๐ Search |
| Fault Prediction and Classification of Large-Scale Substation Equipment Based on Neural Network | Luo, Chuansheng | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Graph Neural Network Power Flow Solver for Dynamical Electrical Networks | Lopez-Garcia, Tania B.; Dominguez-Navarro, Jose Antonio | 2022 | 1 | Planningoptimization | ๐ Search |
| Searching for Critical Power System Cascading Failures With Graph Convolutional Network | Liu, Yuxiao; Zhang, Ning; Wu, Dan; Botterud, Audun; Yao, Rui; Kang, Chongqing | 2021 | 38 | Reliabilityresilience | ๐ Search |
| Guiding Cascading Failure Search with Interpretable Graph Convolutional Network | Liu, Yuxiao; Zhang, Ning; Wu, Dan; Botterud, Audun; Yao, Rui; Kang, Chongqing | 2020 | 16 | Reliabilityresilience | ๐ Search |
| Topology-Aware Graph Neural Networks for Learning Feasible and Adaptive AC-OPF Solutions | Liu, Shaohui; Wu, Chengyang; Zhu, Hao | 2023 | 44 | Planningoptimization | ๐ Search |
| PowerFlowNet: Power flow approximation using message passing Graph Neural Networks | Lin, N.; Orfanoudakis, S.; Cardenas, N.O.; Giraldo, J.S.; Vergara, P.P. | 2024 | 6 | Planningoptimization | ๐ Search |
| EleGNN: Electrical-Model-Guided Graph Neural Networks for Power Distribution System State Estimation | Lin, Hui; Sun, Yan | 2022 | 1 | Operationcontrol | ๐ Search |
| FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets | Liang, Ming; Meng, Yao; Wang, Jiyu; Lubkeman, David L.; Lu, Ning | 2021 | 21 | Datainfrastructuredecisionsupport | ๐ Search |
| From Graph Theory to Graph Neural Networks (GNNs): The Opportunities of GNNs in Power Electronics | Li, Yuzhuo; Xue, Cheng; Zargari, Faraz; Li, Yunwei Ryan | 2023 | 12 | Survey | ๐ Search |
| Federated Graph Learning for EV Charging Demand Forecasting with Personalization Against Cyberattacks | Li, Yi; Xie, Renyou; Li, Chaojie; Wang, Yi; Dong, Zhaoyang | 2024 | 0 | ForecastingpredictionCybersecurityprivacy | ๐ Search |
| Missing Data Recovery for Transmission Networks Using Graph Convolutional Networks with Location Mask | Li, Lijuan; Zhang, Qingsong; Liu, Hongliang; Xing, Baixue; Liu, Hai; Chen, Qi; Wang, Jie | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation | Kundacina, Ognjen; Gojic, Gorana; Cosovic, Mirsad; Miskovic, Dragisa; Vukobratovic, Dejan | 2023 | 1 | Operationcontrol | ๐ Search |
| Graph-Based Multi-Task Learning For Fault Detection In Smart Grid | Chanda, D.; Soltani, N.Y.; ELMAN | 2023 | 5 | Reliabilityresilience | ๐ Search |
| A short-term load forecasting method for integrated community energy system based on STGCN | Cao, J.; Liu, C.; Chen, C.-L.; Qu, N.; Xi, Y.; Dong, Y.; Feng, R. | 2024 | 1 | Forecastingprediction | ๐ Search |
| Deep Learning Architecture for Processing Cyber-Physical Data in the Electric Grid | Calzada, D.; Hossain-Mckenzie, S.; Mao, Z. | 2022 | 4 | Cybersecurityprivacy | ๐ Search |
| Calculation Method of Available Transfer Capacity Based on Graph Convolutional Network | Cai, Z.; Li, Y.; Dai, S.; Men, D.; CAA; DCLOD; IEEE; IEEE Beijing Section; Qingdao University; Suzhou University of Science and Technology | 2021 | 2 | Planningoptimization | ๐ Search |
| Learning Spatio-Temporal Aggregations for Large-Scale Capacity Expansion Problems | Brenner, A.; Khorramfar, R.; Amin, S.; ACM SIGBED; IEEE TCRTS | 2023 | 5 | Planningoptimization | ๐ Search |
| Graph Neural Networks Based Detection of Stealth False Data Injection Attacks in Smart Grids | Boyaci, O.; Umunnakwe, A.; Sahu, A.; Narimani, M.R.; Ismail, M.; Davis, K.R.; Serpedin, E. | 2022 | 88 | Cybersecurityprivacy | ๐ Search |
| Cyberattack Detection in Large-Scale Smart Grids using Chebyshev Graph Convolutional Networks | Boyaci, O.; Rasoul Narimani, M.; Davis, K.; Serpedin, E. | 2022 | 14 | Cybersecurityprivacy | ๐ Search |
| Data-Driven Graph Convolutional Neural Networks for Power System Contingency Analysis | Bolz, V.; Rueร, J.; Zell, A.; IEEE; IEEE Signal Processing Society | 2023 | 3 | Planningoptimization | ๐ Search |
| Short-Term Load Forecastiong Based on Residual Graph Convolutional Neural Network | Bian, M.; Chu, X.; Ye, H.; Chinese Society for Electrical Engineering; IEEE Power and Energy Society; State Grid Corporation of China | 2023 | 1 | Forecastingprediction | ๐ Search |
| Application of Recurrent Graph Convolutional Networks to the Neural State Estimation Problem | Berezin, A.; Balduin, S.; Oberlieรen, T.; Veith, E.; Peter, S.; Lehnhoff, S. | 2023 | 2 | Operationcontrol | ๐ Search |
| Spatial-Temporal Graph Neural Network for Detecting and Localizing Anomalies in PMU Networks | Behdadnia, T.; Thoelen, K.; Zobiri, F.; Deconinck, G. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Fault Identification Method for the Whole Map of Station Area Considering Node Correlation | An, Y.; Hu, L.; Qin, Y.; Zhang, Y.; Zhong, K.; IEEE | 2023 | 0 | PlanningoptimizationReliabilityresilience | ๐ Search |
| A Graph-Based Neural Approach to Linear Sum Assignment Problems | Aironi, C.; Cornell, S.; Squartini, S. | 2024 | 2 | Method | ๐ Search |
| Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation, and Optimal Measurement Placement in Power Systems? | Afonin, A.; Chertkov, M. | 2021 | 2 | Survey | ๐ Search |
| UMGAN: multi-scale graph attention network for grid parameter identification | Zou, Gang; Xia, Min; Zhang, Liudong; Lei, Zhen; Peng, Zhiqiang; Liu, Jun | 2024 | 0 | Planningoptimization | ๐ Search |
| Graph Convolutional Network-Based Multi-harmonic Source Localization Method Without the Need for Synchronous Measurement Data | Zhu, Yuanzhe; Wang, Ling; Du, Wanlin; Lv, Hong; Wang, Jinfeng | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Multivariate Time Series Forecasting of Integrated Energy Systems Based on Fast Fourier Transform Fully Connected Space-Time Graph | Zhao, Weicheng; Lin, Xiaoyong; Xu, Jiwei | 2024 | 0 | Forecastingprediction | ๐ Search |
| Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics | Zhao, Tianqiao; Yue, Meng; Wang, Jianhui | 2022 | 30 | Forecastingprediction | ๐ Search |
| Graph neural networks for power grid operational risk assessment under evolving grid topology | Zhang, Yadong; Karve, Pranav M.; Mahadevan, Sankaran | 2024 | 0 | ReliabilityresilienceOperationcontrol | ๐ Search |
| Operational risk quantification of power grids using graph neural network surrogates of the DC OPF | Zhang, Yadong; Karve, Pranav M.; Mahadevan, Sankaran | 2024 | 0 | PlanningoptimizationReliabilityresilienceOperationcontrol | ๐ Search |
| Transformgraph: A Novel Short-Term Electricity Net Load Forecasting Model | Zhang, Qingyong; Chen, Jiahua; Xiao, Gang; He, Shangyang; Deng, Kunxiang | 2022 | 31 | Forecastingprediction | ๐ Search |
| Compound-Fault Diagnosis of Integrated Energy Systems Based on Graph Embedded Recurrent Neural Networks | Zhang, Jingfei; He, Xiao | 2024 | 12 | Reliabilityresilience | ๐ Search |
| Emergency control methods for power systems based on improved deep reinforcement learning | Zhang, Jie; Zhu, Yihua; Liang, Zhuohang; Ma, Qinfeng; Zhang, Qingqing; Liu, Mingshun; An, Su; Pu, Qingxin; Dai, Jiang | 2024 | 0 | Operationcontrol | ๐ Search |
| PIDGeuN: Graph Neural Network-Enabled Transient Dynamics Prediction of Networked Microgrids Through Full-Field Measurement | Yu, Yin; Jiang, Xinyuan; Huang, Daning; Li, Yan | 2022 | 5 | Forecastingprediction | ๐ Search |
| Learning Coarse-Grained Dynamics on Graph | Yu, Yin; Harlim, John; Huang, Daning; Li, Yan | 2024 | 0 | Method | ๐ Search |
| Enhanced neighborhood node graph neural networks for load forecasting in smart grid | Yanmei, Jiang; Mingsheng, Liu; Yangyang, Li; Yaping, Liu; Jingyun, Zhang; Yifeng, Liu; Chunyang, Liu | 2024 | 16 | Forecastingprediction | ๐ Search |
| Short-term electricity price forecasting based on graph convolution network and attention mechanism | Yang, Yuyun; Tan, Zhenfei; Yang, Haitao; Ruan, Guangchun; Zhong, Haiwang; Liu, Fengkui | 2022 | 14 | Forecastingprediction | ๐ Search |
| Long-term wind power forecasting with series decomposition and spatio-temporal graph neural network | Yang, Yujie; Chen, Junhong; Zheng, Wenbin; Zhang, Fan | 2024 | 1 | Forecastingprediction | ๐ Search |
| Probabilistic power flow based on physics-guided graph neural networks | Yang, Mei; Qiu, Gao; Liu, Tingjian; Liu, Junyong; Liu, Kai; Li, Yaping | 2024 | 1 | Planningoptimization | ๐ Search |
| AC Optimal Power Flows: Combining Lagrangian Dual and physics-Guided Graph Neutral Networks | Yang, Mei; Liu, Junyong; Qiu, Gao; Liu, Tingjian; Tang, Zhiyuan | 2022 | 1 | Planningoptimization | ๐ Search |
| MFAGCN: A new framework for identifying power grid branch parameters | Xia, Min; Wang, Zhiwei; Lu, Min; Pan, Lingling | 2022 | 23 | Planningoptimization | ๐ Search |
| Research on Intelligent Grid Fault Prediction Communication System Based on Computer Big Data | Wu, Xuan | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Missing Data Recovery in Large Power Systems Using Network Embedding | Wu, Tong; Zhang, Ying-Jun Angela; Liu, Yang; Lau, Wing Cheong; Xu, Huanle | 2021 | 13 | Datainfrastructuredecisionsupport | ๐ Search |
| Graph Learning based Generative Design for Resilience of Interdependent Network Systems | Wu, Jiaxin; Wang, Pingfeng | 2022 | 6 | Reliabilityresilience | ๐ Search |
| Efficient Residential Electric Load Forecasting via Transfer Learning and Graph Neural Networks | Wu, Di; Lin, Weixuan | 2023 | 53 | Forecastingprediction | ๐ Search |
| Non-invasive load identification method in smart grid based on graph convolutional neural network | Wei, Jie; He, Xing | 2024 | 0 | Planningoptimization | ๐ Search |
| An Adaptive Spatio-Temporal Graph Recurrent Network for Short-Term Electric Vehicle Charging Demand Prediction | Wang, Shengyou; Li, Yuan; Shao, Chunfu; Wang, Pinxi; Wang, Aixi; Zhuge, Chengxiang | 2024 | 0 | Forecastingprediction | ๐ Search |
| Research on Graph Multi-Attention Neural Network for Power System Transient Stability Assessment | Wang, Qingwen; Yu, Tenglong; Chu, Hongliang; Xiong, Xiaozhou; Huang, Kang; Qiu, Rixuan; Hu, Bing; Yan, Haoran; Wang, Fan; Bai, Yang; Wang, Song; Qi, Jun; Liu, Siyan; Shi, Danni | 2024 | 0 | Operationcontrol | ๐ Search |
| A Data-Driven Method for Probabilistic Prediction of Power Grid Critical Section Power from Probability Distributions of Renewable Energy | Wang, Heng; Wang, Xiaoru; Liu, Liu; Sun, Xieli; Tian, Fang | 2024 | 0 | Forecastingprediction | ๐ Search |
| Probabilistic Power Flow Solution with Graph Convolutional Network | Wang, Dawei; Zheng, Kedi; Chen, Qixin; Luo, Gang; Zhang, Xuan | 2020 | 27 | Planningoptimization | ๐ Search |
| Goal-Oriented Graph Generation for Transmission Expansion Planning | Varbella, Anna; Gjorgiev, Blazhe; Sartore, Federico; Zio, Enrico; Sansavini, Giovanni | 2024 | 0 | Planningoptimization | ๐ Search |
| PowerGraph: A power grid benchmark dataset for graph neural networks | Varbella, Anna; Amara, Kenza; Gjorgiev, Blazhe; El-Assady, Mennatallah; Sansavini, Giovanni | 2024 | 4 | Survey | ๐ Search |
| Multi-Agent Reinforcement Learning for Power Grid Topology Optimization | van der Sar, Erica; Zocca, Alessandro; Bhulai, Sandjai | 2023 | 0 | Planningoptimization | ๐ Search |
| Gnn Assisted Frequency Constrained Unit Commitment of Multi-Region Power Systems with High Penetration of Renewable Energy Sources | Tuo, Mingjian; Zhao, Cunzhi; Zhang, Mulan; Gao, Tao; Shang, Xuequan | 2024 | 0 | General | ๐ Search |
| Machine Learning Assisted Inertia Estimation Using Ambient Measurements | Tuo, Mingjian; Li, Xingpeng | 2023 | 11 | Operationcontrol | ๐ Search |
| A High Temporal-Spatial Resolution Power System State Estimation Method for Online DSA | Hu, J.; Wang, Q.; Ye, Y.; Wu, Z.; Tang, Y. | 2024 | 9 | Operationcontrol | ๐ Search |
| A classification model of power operation inspection defect texts based on graph convolutional network | Hu, J.; Guo, B.; Yan, W.; Lin, J.; Li, C.; Yan, Y. | 2022 | 6 | Operationcontrol | ๐ Search |
| Recommendation Method of Power Knowledge Retrieval Based on Graph Neural Network | Hou, R.; Zhang, Y.; Ou, Q.; Li, S.; He, Y.; Wang, H.; Zhou, Z. | 2023 | 1 | Datainfrastructuredecisionsupport | ๐ Search |
| Graph convolutional network-based topology embedded deep reinforcement learning for voltage stability control | Hossain, R.R.; Huang, Q.; Huang, R. | 2021 | 66 | Operationcontrol | ๐ Search |
| Voltage Control in Distribution Grids Using Topology Aware Deep Reinforcement Learning | Hossain, R.; Gautam, M.; Mansourlakouraj, M.; Livani, H.; Benidris, M. | 2023 | 1 | Operationcontrol | ๐ Search |
| A robust spatio-temporal prediction approach for wind power generation based on spectral temporal graph neural network | He, Y.; Chai, S.; Zhao, J.; Sun, Y.; Zhang, X. | 2022 | 7 | Forecastingprediction | ๐ Search |
| Power System Fault Diagnosis and Prediction System Based on Graph Neural Network | Hao, J.; Zhang, Z.; Ping, Y. | 2024 | 2 | Reliabilityresilience | ๐ Search |
| False data injection attacks detection with modified temporal multi-graph convolutional network in smart grids | Han, Y.; Feng, H.; Li, K.; Zhao, Q. | 2023 | 29 | Cybersecurityprivacy | ๐ Search |
| Impact of Topology Noise on Power Systems State Estimation Using a Temporal GCN Framework | Haghshenas, S.H.; Naeini, M. | 2023 | 4 | Operationcontrol | ๐ Search |
| Analyzing Multi-Area State Estimation in Power Systems in a Temporal Graph Convolutional Network Framework | Haghshenas, S.H.; Hossain, M.J.; Naeini, M. | 2023 | 0 | Operationcontrol | ๐ Search |
| A Temporal Graph Neural Network for Cyber Attack Detection and Localization in Smart Grids | Haghshenas, S.H.; Hasnat, M.A.; Naeini, M. | 2023 | 28 | Cybersecurityprivacy | ๐ Search |
| A Directed Acyclic Graph Neural Network for AC Optimal Power Flow | Guo, Z.; Sun, K.; Park, B.; Simunovic, S.; Kang, W. | 2023 | 0 | Planningoptimization | ๐ Search |
| Utilizing virtual power plants to support main grid for frequency regulation | Guo, J.; Dou, C.; Yue, D.; Zhang, Z. | 2024 | 2 | PlanningoptimizationOperationcontrolDatainfrastructuredecisionsupport | ๐ Search |
| Multi-task transient stability assessment of power system based on graph neural network with interpretable attribution analysis | Gu, S.; Qiao, J.; Shi, W.; Yang, F.; Zhou, X.; Zhao, Z. | 2023 | 9 | Operationcontrol | ๐ Search |
| Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks | Giamarelos, N.; Zois, E.N. | 2024 | 7 | Forecastingprediction | ๐ Search |
| A Transductive Graph Neural Network learning for Grid Resilience Analysis | Gautam, P.; Sreejith, A.; Natarajan, B. | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Dynamic adaptive spatio-temporal graph neural network for multi-node offshore wind speed forecasting | Gao, Z.; Li, Z.; Xu, L.; Yu, J. | 2023 | 17 | Forecastingprediction | ๐ Search |
| Anomaly Detection Algorithm of Power System Based on Graph Structure and Anomaly Attention | Gao, Y.; Zhang, J.; Chen, Z.; Chen, X. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Spatial-temporal learning structure for short-term load forecasting | Ganjouri, M.; Moattari, M.; Forouzantabar, A.; Azadi, M. | 2023 | 1 | Forecastingprediction | ๐ Search |
| Detection of False Data Injection Attacks in Cyber-Physical Power Systems: An Adaptive Adversarial Dual Autoencoder With Graph Representation Learning Approach | Feng, H.; Han, Y.; Si, F.; Zhao, Q. | 2024 | 9 | Cybersecurityprivacy | ๐ Search |
| STGNet: Short-term residential load forecasting with spatialโtemporal gated fusion network | Feng, D.; Li, D.; Zhou, Y.; Zhao, J.; Zhang, K. | 2024 | 2 | Forecastingprediction | ๐ Search |
| Research on Transformer Fault Prediction Based on Graph Neural Network | Fang, M.; Jiang, Y.; Li, L.; Liu, Y.; Zhang, Y.; Lv, F.; Liu, Z. | 2022 | 0 | Reliabilityresilience | ๐ Search |
| A Markov Regime Switching Model for Ultra-Short-Term Wind Power Prediction Based on Toeplitz Inverse Covariance Clustering | Fan, H.; Zhang, X.; Mei, S.; Zhang, J. | 2021 | 6 | Forecastingprediction | ๐ Search |
| M2gsnet: Multi-modal multi-task graph spatiotemporal network for ultra-short-term wind farm cluster power prediction | Fan, H.; Zhang, X.; Mei, S.; Chen, K.; Chen, X. | 2020 | 36 | Forecastingprediction | ๐ Search |
| Graph Autoencoder-Based Power Attacks Detection for Resilient Electrified Transportation Systems | Fahim, S.R.; Atat, R.; Kececi, C.; Takiddin, A.; Ismail, M.; Davis, K.R.; Serpedin, E. | 2024 | 12 | Cybersecurityprivacy | ๐ Search |
| Spatio-Temporal Graph Neural Networks for Aggregate Load Forecasting | Eandi, S.; Cini, A.; Lukovic, S.; Alippi, C. | 2022 | 5 | Forecastingprediction | ๐ Search |
| Spatio-temporal Convolutional Network Based Power Forecasting of Multiple Wind Farms | Dong, X.; Sun, Y.; Li, Y.; Wang, X.; Pu, T. | 2022 | 52 | Forecastingprediction | ๐ Search |
| Hybrid Attack Graph Generation with Graph Convolutional Deep-Q Learning | Donald, S.; Meyur, R.; Purohit, S.; Ankura; IEEE Dataport | 2023 | 0 | Cybersecurityprivacy | ๐ Search |
| Short-Long Correlation Based Graph Neural Networks forย Residential Load Forecasting | Deng, Y.; Zhou, Y.; Zhang, Z. | 2021 | 0 | Forecastingprediction | ๐ Search |
| Power Terminal Detection System Based on Graph Neural Network | Deng, H.; Zhang, L.; Li, H.; Wang, W.; Li, Z. | 2023 | 0 | Operationcontrol | ๐ Search |
| SELFIE: A Semantically-Enhanced Load Forecasting Approach with Indirect Estimate of Spatial Influences | Das, M.; Dutta, S. | 2021 | 0 | Forecastingprediction | ๐ Search |
| Boosting efficiency in state estimation of power systems by leveraging attention mechanism | Cibaku, E.; Gama, F.; Park, S. | 2024 | 3 | Operationcontrol | ๐ Search |
| Leveraging spatial information in smart grids using STGCN for short-term load forecasting | Cheung, C.M.; Kuppannagari, S.; Kannan, R.; Prasanna, V.K. | 2021 | 3 | Forecastingprediction | ๐ Search |
| Temporal-Spatial Graph Neural Network for Wind Power Forecasting Considering the Blockage Effects | Cheng, X.; Liu, X.; Ilieva, I.; Redhu, S.; IEEE Norway Section CIS Chapter | 2023 | 1 | Forecastingprediction | ๐ Search |
| Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets | Chen, Y.; Jiang, T.; Heleno, M.; Moreira, A.; Gel, Y.R.; Ankura; et al.; Hitachi; KPMG Consulting Co., Ltd.; NTT Data Intellilink Corporation; Think in Data Initiative, Association Inc | 2022 | 3 | Reliabilityresilience | ๐ Search |
| Learning Power Grid Outages With Higher-Order Topological Neural Networks | Chen, Y.; Jacob, R.A.; Gel, Y.R.; Zhang, J.; Poor, H.V. | 2024 | 7 | Reliabilityresilience | ๐ Search |
| LFGCN: Levitating over graphs with levy flights | Chen, Y.; Gel, Y.R.; Avrachenkov, K.; IEEE Computer Society | 2020 | 7 | Method | ๐ Search |
| Research on the Transformer Intelligent Operation and Maintenance System Based on the Graph Neural Network | Chen, W.; Luo, D.; Fu, F.; He, H.; Zhang, K. | 2022 | 1 | Operationcontrol | ๐ Search |
| A Multi-Channel Composite Recommendation Method in Federated Learning | Chen, S.; Li, Q.; Wang, Q.; Zhao, X.; Ge, H.; Li, N. | 2023 | 0 | Method | ๐ Search |
| Distributed Photovoltaic Real-Time Output Estimation Based on Graph Convolutional Networks | Chen, L.; Hong, D.; He, X.; Lu, D.; Zhang, Q.; Xie, N.; Xu, Y.; Ying, H. | 2024 | 1 | Operationcontrol | ๐ Search |
| Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System | Chen, K.; Liu, S.; Yu, N.; Yan, R.; Zhang, Q.; Song, J.; Feng, Z.; Song, M. | 2022 | 4 | Operationcontrol | ๐ Search |
| Stochastic Dynamic Power Dispatch with Human Knowledge Transfer Using Graph-GAN Assisted Inverse Reinforcement Learning | Chen, J.; Yu, T.; Pan, Z.; Zhang, M.; Lu, G.; Zhu, K. | 2024 | 3 | PlanningoptimizationDatainfrastructuredecisionsupport | ๐ Search |
| Research on short-term load forecasting of new-type power system based on GCN-LSTM considering multiple influencing factors | Chen, H.; Zhu, M.; Hu, X.; Wang, J.; Sun, Y.; Yang, J. | 2023 | 34 | Forecastingprediction | ๐ Search |
| Multifeature Short-Term Power Load Forecasting Based on GCN-LSTM | Chen, H.; Zhu, M.; Hu, X.; Wang, J.; Sun, Y.; Yang, J.; Li, B.; Meng, X. | 2023 | 4 | Forecastingprediction | ๐ Search |
| Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes | Chen, D.; Liu, R.; Hu, Q.; Ding, S.X. | 2023 | 87 | Reliabilityresilience | ๐ Search |
| Real-time risk assessment of cascading failure in power system with high proportion of renewable energy based on fault graph chains | Chen, B.; Sun, D.; Zhu, Y.; Liu, D.; Zhou, Y. | 2023 | 6 | Reliabilityresilience | ๐ Search |
| A Graph Motif Adversarial Attack for Fault Detection in Power Distribution Systems | Chanda, D.; Soltani, N.Y. | 2024 | 0 | ReliabilityresilienceCybersecurityprivacy | ๐ Search |
| A novel temporalโspatial graph neural network for wind power forecasting considering blockage effects | Qiu, H.; Shi, K.; Wang, R.; Zhang, L.; Liu, X.; Cheng, X. | 2024 | 14 | Forecastingprediction | ๐ Search |
| Geometric Deep-Learning-Based Spatiotemporal Forecasting for Inverter-Based Solar Power | Qin, C.; Srivastava, A.K.; Saber, A.Y.; Matthews, D.; Davies, K. | 2023 | 6 | Forecastingprediction | ๐ Search |
| Graph Neural Network Based Transient Stability Assessment Considering Topology Changes | Qiao, J.; Wang, X.; Ni, J.; Shi, M.; Ren, H.; Chen, E.; China Southern Power Grid Co., Ltd.; Chinese Society for Electrical Engineering (CSEE); IEEE Power and Energy Society (PES) | 2021 | 5 | Operationcontrol | ๐ Search |
| Fault Diagnosis Combining Power Grid and Communication System Based on Graph Neural Network | Qian, L.; Zhou, Z.; Cai, X.; Zhu, P.; China Institute of IOT (CIIOT); et al.; IEEE; IEEE Beijing Section; Wuxi Internet of Things Innovation Promotion Center; Wuxi Liangxi Sci-Tech City | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Cyber Forensic Analysis for Operational Technology Using Graph-Based Deep Learning | Presekal, A.; Stefanov, A.; Rajkumar, V.S.; Palensky, P. | 2023 | 5 | OperationcontrolCybersecurityprivacy | ๐ Search |
| Attack Graph Model for Cyber-Physical Power Systems Using Hybrid Deep Learning | Presekal, A.; Stefanov, A.; Rajkumar, V.S.; Palensky, P. | 2023 | 72 | Cybersecurityprivacy | ๐ Search |
| Dynamic Weight Enabled Physics-Aware Graph Attention Network for Power Flow Analysis | Prashal, G.; Sumathi, P.; Padhy, N.P.; ENEDIS; et al.; GreenAlp; Le Reseau de Transport d'electricite (RTE); Schneider Electric; Think Smartgrids | 2023 | 0 | Planningoptimization | ๐ Search |
| IoT-enabled EMS for grid-connected solar PV-fed DC residential buildings with hybrid HBA-DCGNN approach | Pitchai, M.K.; Narayanan, P.; Rajendiran, E.; Venkataramani, V. | 2024 | 6 | Other | ๐ Search |
| Localizing False Data Injection Attacks in Smart Grid: A Spectrum-Based Neural Network Approach | Peng, S.; Zhang, Z.; Deng, R.; Cheng, P. | 2023 | 25 | Cybersecurityprivacy | ๐ Search |
| Knowledge Graph for Power Grid Dispatching of Digital Homes based on Graph Convolutional Network | Peng, F.; An, T.; Li, D.; Wang, H.; Tian, C.; Chen, Z. | 2020 | 8 | PlanningoptimizationDatainfrastructuredecisionsupport | ๐ Search |
| Anย emergency control strategy for undervoltage load shedding of power system: A graph deep reinforcement learning method | Pei, Y.; Yang, J.; Wang, J.; Xu, P.; Zhou, T.; Wu, F. | 2023 | 12 | Operationcontrol | ๐ Search |
| Emergency Control Strategy of Power System Considering Operation Scenario Variations | Pei, Y.; Yang, J.; Ma, B.; Peng, X.; Jiang, K.; Liu, D.; Cao, K.; IEEE; IEEE Macau Section; Macau University of Science and Technology; Science and Engineering Institute; University of Electronic Science and Technology of China | 2023 | 0 | Operationcontrol | ๐ Search |
| Distributed Power System State Estimation Using Graph Convolutional Neural Networks | Park, S.; Gama, F.; Lavaei, J.; Sojoudi, S.; Association for Information Systems (AIS); Spatial Business Initiative - ESRI; University of Arkansas, Sam M. Walton College of Business, Information Systems; University of Hawai'i at Manoa, Shidler College of Business; University of Redlands, School of Business and Society | 2023 | 3 | Operationcontrol | ๐ Search |
| Increasing resilience of power systems using intentional islanding; A comparison of binary genetic algorithm and deep learning based method | Paradell, P.; Spyridis, Y.; Colet, A.; Ivanova, A.; Dominguez N Garcia, J.L.; Sesis, A.; Efstathopoulos, G.; IEEE; IEEE Systems, Man, and Cybernetics (SMC) Society; LOGOS Research and Innovation (RI) | 2021 | 2 | Reliabilityresilience | ๐ Search |
| Short-term wind speed forecasting based on spatial-temporal graph transformer networks | Pan, X.; Wang, L.; Wang, Z.; Huang, C. | 2022 | 55 | Forecastingprediction | ๐ Search |
| A Real-Time Load Forecasting Approach Based on Graph Convolution Neural Network in a Distributed IoT Energy System | Pan, L.; Gan, J.; Liu, Q.; Zhang, Y.; Liu, X. | 2023 | 0 | Forecastingprediction | ๐ Search |
| Application of improved graph convolutional networks in daily-ahead carbon emission prediction | Pan, F.; Yang, Y.; Ji, Y.; Li, J.; Zhang, J.; Zhong, L. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Forecasting Solar Energy Production using a Hybrid GCN-BiLSTM Model | Pamungkas, R.F.; Yoga Utama, I.B.K.; Faridh, M.M.; Alam, M.M.; Chung, B.; Jang, Y.M. | 2023 | 2 | Forecastingprediction | ๐ Search |
| 1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems | Nguyen, B.L.H.; Vu, T.; Nguyen, T.-T.; Panwar, M.; Hovsapian, R.; Ansys; Entuple Technologies - Wavect; OPAL-RT Technologies; Tsuyo | 2022 | 3 | Reliabilityresilience | ๐ Search |
| State Estimation for Power Distribution System Using Graph Neural Networks | Ngo, Q.-H.; Nguyen, B.L.H.; Vu, T.V.; Ngo, T. | 2023 | 4 | Operationcontrol | ๐ Search |
| GLASS: A Graph Learning Approach for Software Defined Network Based Smart Grid DDoS Security | Nagaraj, K.; Starke, A.; McNair, J.; IEEE Communications Society; IEEE Montreal Section; IEEE Ottawa Section | 2021 | 9 | Cybersecurityprivacy | ๐ Search |
| A Model Based on GCN and TCN for Malicious Code Detection in Power Information System | Na, Q.; Zhang, S.; Li, X.; Lai, J.; Yang, Y.; Zeng, J.; IEEE | 2024 | 1 | Cybersecurityprivacy | ๐ Search |
| Graph Multi-Agent Reinforcement Learning for Inverter-Based Active Voltage Control | Mu, C.; Liu, Z.; Yan, J.; Jia, H.; Zhang, X. | 2024 | 14 | Operationcontrol | ๐ Search |
| Electricity demand forecasting at distribution and household levels using explainable causal graph neural network | Miraki, A.; Parviainen, P.; Arghandeh, R. | 2024 | 7 | Forecastingprediction | ๐ Search |
| Nonparametric Probabilistic Total Transfer Capability Estimation with Deep Learning | Meng, Z.; Guo, Y.; Tang, W.; Sun, H.; Li, S.; Dai, Y. | 2022 | 0 | Operationcontrol | ๐ Search |
| Spatio-Temporal Short Term Load Forecasting Using Graph Neural Networks | Mansoor, H.; Shabbir, M.; Ali, M.Y.; Rauf, H.; Khalid, M.; Arshad, N.; Istanbul Nisantasi University; JR-East Group; NTEC; TMEiC | 2023 | 2 | Forecastingprediction | ๐ Search |
| Fast Pooling Based Multi-Scale Graph Neural Network and Its Application in Electric Power System | Ma, Z.; Tan, Y.; Li, Z.; Xu, H.; Liu, L.; He, K.; Chengdu University of Technology; IEEE; IEEE Power and Energy Society (PES); UESTC | 2022 | 0 | Method | ๐ Search |
| Cloud Computing-Based Graph Convolutional Network Power Consumption Prediction Method | Ma, Y.; Sheng, H.; Wu, S.; Gong, S.; Cheng, H. | 2021 | 0 | Forecastingprediction | ๐ Search |
| Grid-Metaverse: The Path From Digital Twins and Prototype Tests on DC Microgrids | Ma, W.; Liu, M.; Hong, G.; Yang, S.; Deng, R.; IEEE; IEEE Computer Society's Technical Community on the Internet (TCI); Kanazawa University | 2023 | 5 | Datainfrastructuredecisionsupport | ๐ Search |
| Short-Term Voltage Stability Assessment Based on Heterogeneous Edge-Integrated Graph Attention Network | Lv, Z.; Wang, B.; Guo, Q.; Zhao, H.; Wang, Z.; Sun, H. | 2024 | 1 | Operationcontrol | ๐ Search |
| An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model | Lv, Y.; Hu, Q.; Xu, H.; Lin, H.; Wu, Y. | 2024 | 7 | Forecastingprediction | ๐ Search |
| Graph Convolutional Network-Based Interpretable Machine Learning Scheme in Smart Grids | Luo, Y.; Lu, C.; Zhu, L.; Song, J. | 2023 | 23 | Operationcontrol | ๐ Search |
| Data-driven short-term voltage stability assessment based on spatial-temporal graph convolutional network | Luo, Y.; Lu, C.; Zhu, L.; Song, J. | 2021 | 56 | Operationcontrol | ๐ Search |
| A R-GCN-Based Correlation Characteristics Extraction Method for Power Grid Infrastructure Planning and Analysis | Lu, S.; Yan, J.; Zhang, Y.; Qi, L.; Wang, S.; Wu, Q.; Zhou, M.; Zhao, W. | 2022 | 4 | PlanningoptimizationDatainfrastructuredecisionsupport | ๐ Search |
| Adaptive Stability Contingency Screening for Operational Planning Based on Domain-Adversarial Graph Neural Network | Lu, G.; Bu, S. | 2024 | 5 | PlanningoptimizationOperationcontrol | ๐ Search |
| Power System Transient Stability Assessment Based on Graph Convolutional Network | Lu, D.; Ren, J.; Chen, J.; Shi, D.; China Electrotechnical Society (CES); Huazhong University of Science and Technology (HUST); Institute of Electrical and Electronics Engineers (IEEE) Beijing Section | 2021 | 1 | Operationcontrol | ๐ Search |
| Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional networks | Lonapalawong, S.; Chen, C.; Wang, C.; Chen, W. | 2022 | 5 | Reliabilityresilience | ๐ Search |
| Multi-step short-term wind power prediction based on spatio-temporal graph convolutional networks | Liu, Z.; Xiao, S.; Liu, H.; IEEE; IEEE Power and Energy (PES); Institute of Engineering Thermophysics (IET) (Chinese Academy of Sciences); Tsinghua University | 2023 | 1 | Forecastingprediction | ๐ Search |
| Capturing Spatial Influence in Wind Prediction With a Graph Convolutional Neural Network | Liu, Z.; Ware, T. | 2022 | 11 | Forecastingprediction | ๐ Search |
| An online power system transient stability assessment method based on graph neural network and central moment discrepancy | Liu, Z.; Ding, Z.; Huang, X.; Zhang, P. | 2023 | 1 | Operationcontrol | ๐ Search |
| Spatio-Temporal Graph Neural Network and Pattern Prediction Based Ultra-Short-Term Power Forecasting of Wind Farm Cluster | Liu, X.; Zhang, Y.; Zhen, Z.; Xu, F.; Wang, F.; Mi, Z. | 2024 | 14 | Forecastingprediction | ๐ Search |
| Power Grid Fault Localtion Method Based on Graph Neural Network | Liu, X.; Song, X.; Yu, Y.; Zhang, F.; Fan, S.; Chengdu Global Union Institute of Science and Technology; Chongqing Geeks Education Technology Co., Ltd; Chongqing Global Union Academy of Science and Technology; Chongqing University of Technology; Global Union Academy of Science and Technology; IEEE Beijing Section | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Progressive decision-making framework for power system topology control | Liu, S.; Zhou, Y.; Song, M.; Bu, G.; Guo, J.; Chen, C. | 2024 | 8 | Operationcontrol | ๐ Search |
| Attention based spatial-temporal graph convolutional networks for short-term load forecasting | Liu, R.; Chen, L. | 2021 | 5 | Forecastingprediction | ๐ Search |
| A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system | Liu, Q.; Pan, L.; Cao, X.; Gan, J.; Huang, X.; Liu, X. | 2024 | 0 | Forecastingprediction | ๐ Search |
| A Concurrent Fault Diagnosis Method of Transformer Based on Graph Convolutional Network and Knowledge Graph | Liu, L.; Wang, B.; Ma, F.; Zheng, Q.; Yao, L.; Zhang, C.; Mohamed, M.A. | 2022 | 26 | ReliabilityresilienceDatainfrastructuredecisionsupport | ๐ Search |
| Self-Organized Criticality Identification of Power System Based on SC-GCN Network | Liu, L.; Han, Y.; Ye, S.; Long, C.; Liu, Z.; Liu, X.; Li, T.; Yang, X.; Li, D. | 2023 | 0 | Planningoptimization | ๐ Search |
| Risk-Averse Graph Learning for Real-time Power System Emergency Load Shedding | Liu, J.; Zhang, Y.; Meng, K.; Xu, Y.; Dong, Z.Y. | 2022 | 3 | Reliabilityresilience | ๐ Search |
| Time-Adaptive Transient Stability Assessment Based on the Gating Spatiotemporal Graph Neural Network and Gated Recurrent Unit | Liu, J.; Yao, C.; Chen, L. | 2022 | 4 | Operationcontrol | ๐ Search |
| Predicting Braess's paradox of power grids using graph neural networks | Zou, Yanli; Zhang, Hai; Wang, Hongjun; Hu, Jinmei | 2024 | 4 | Forecastingprediction | ๐ Search |
| Building-Level Multi-Energy Load Forecasting: A Graph Representation Learning Convolution-Based Approach in Smart Meter-Enabled Environments | Zonouz, Mir Karim Aboutalebi; Hagh, Mehrdad Tarafdar; Ravadanegh, Sajad Najafi | 2024 | 0 | Forecastingprediction | ๐ Search |
| Scaling Graph Neural Networks for Large-Scale Power Systems Analysis: Empirical Laws for Emergent Abilities | Zhu, Yuhong; Zhou, Yongzhi; Yan, Lei; Li, Zuyi; Xin, Huanhai; Wei, Wei | 2024 | 18 | Method | ๐ Search |
| Emergent Abilities of Graph Neural Networks for Large-scale Power System Analysis | Zhu, Yuhong; Zhou, Yongzhi; Yan, Lei; Li, Zuyi; Xin, Huanhai; Wei, Wei | 0 | General | ๐ Search | |
| GNNs' Generalization Improvement for Large-scale Power System Analysis Based on Physics-informed Self-supervised Pre-training | Zhu, Yuhong; Zhou, Yongzhi; Wei, Wei | 0 | General | ๐ Search | |
| Cascading Failure Analysis Based on a Physics-Informed Graph Neural Network | Zhu, Yuhong; Zhou, Yongzhi; Wei, Wei; Wang, Ningbo | 2023 | 22 | Reliabilityresilience | ๐ Search |
| Fast Resilience Assessment for Power Systems Under Typhoons Based on Spatial Temporal Graphs | Zhu, Yuhong; Zhou, Yongzhi; Sun, Yong; Li, Wei | 2024 | 0 | Reliabilityresilience | ๐ Search |
| GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations | Zhu, Nanyang; Wang, Ying; Yuan, Kun; Yan, Jiahao; Li, Yaping; Zhang, Kaifeng | 2024 | 12 | ForecastingpredictionPlanningoptimization | ๐ Search |
| GMD-Linear: Integrating Graph Neural Networks and WaveNet for Enhanced Wind Power Forecasting | Zhang, Y.; Zhang, Z.; Hu, Y.; Wan, Y. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Power grid operational risk assessment using graph neural network surrogates | Zhang, Y.; Karve, P.M.; Mahadevan, S. | 2024 | 3 | ReliabilityresilienceOperationcontrol | ๐ Search |
| A GNN-based Day Ahead Carbon Intensity Forecasting Model for Cross-Border Power Grids | Zhang, Xiaoyang; Wang, Dan | 2023 | 7 | Forecastingprediction | ๐ Search |
| Adaptive Identification of Power System Operational States Based on Spatio-Temporal Dynamic Graph Neural Networks | Zhang, Qingqing; Ma, Qinfeng; Liu, Mingshun; Zhang, Jie; Zhu, Yihua; Liang, Zhuohang; An, Su; Pu, Qingxin; Dai, Jiang | 2024 | 0 | PlanningoptimizationOperationcontrol | ๐ Search |
| Reinforcement Learning-based Routing Optimization Model for Smart Grid Scenarios | Zhang, Peiming | 2024 | 1 | Planningoptimization | ๐ Search |
| Optimal Graph Structure Based Short-Term Solar PV Power Forecasting Method Considering Surrounding Spatio-Temporal Correlations | Zhang, Meng; Zhen, Zhao; Liu, Nian; Zhao, Hongjun; Sun, Yiqian; Feng, Changyou; Wang, Fei | 2023 | 53 | ForecastingpredictionPlanningoptimization | ๐ Search |
| A Trustworthy Framework of Artificial Intelligence for Power Grid Dispatching Systems | Zhang, Ke; Xu, Peidong; Gao, Tianlu; ZHANG, Jun | 2021 | 6 | Planningoptimization | ๐ Search |
| Physics-informed line graph neural network for power flow calculation | Zhang, Hai-Feng; Lu, Xin-Long; Ding, Xiao; Zhang, Xiao-Ming | 2024 | 0 | Planningoptimization | ๐ Search |
| KG-BGCN: A Secondary Power Equipment Classification Model Based on Knowledge Graphs | Zeng, X.; Lu, Y.; Su, Y.; Qiu, W.; Lin, X.; Chen, K. | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Superposition Graph Neural Network for offshore wind power prediction | Yu, Mei; Zhang, Zhuo; Li, Xuewei; Yu, Jian; Gao, Jie; Liu, Zhiqiang; You, Bo; Zheng, Xiaoshan; Yu, Ruiguo | 2020 | 81 | Forecastingprediction | ๐ Search |
| Synchrophasor Recovery and Prediction: A Graph-Based Deep Learning Approach | Yu, James J. Q.; Hill, David J.; Li, Victor O. K.; Hou, Yunhe | 2019 | 41 | Forecastingprediction | ๐ Search |
| A New Energy Multi-Station Short-Circuit Ratio Online Calculation Method Based on Message Passing GCNConv | Yi, Y.; Zhu, C.; Lin, J.; Zheng, L. | 2024 | 0 | General | ๐ Search |
| Towards adoption of GNNs for power flow applications in distribution systems | Yaniv, Arbel; Kumar, Parteek; Beck, Yuval | 2023 | 15 | Planningoptimization | ๐ Search |
| Power System State Estimation Using Gauss-Newton Unrolled Neural Networks with Trainable Priors | Yang, Qiuling; Sadeghi, Alireza; Wang, Gang; Giannakis, Georgios B.; Sun, Jian | 2020 | 9 | Operationcontrol | ๐ Search |
| Research on Dynamic Security Detection of New Energy Terminals Based on Graph Neural Networks | Yang, H.; Xiao, Y.; Xu, J.; Ji, Y.; Cao, H. | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| A Simulation-Constraint Graph Reinforcement Learning Method for Line Flow Control | Xu, PeiDong; Pei, YangZhou; Zheng, Xinhu; Zhang, Jun | 2020 | 8 | PlanningoptimizationOperationcontrol | ๐ Search |
| Complex-Value Spatiotemporal Graph Convolutional Neural Networks and Its Applications to Electric Power Systems AI | Wu, Tong; Scaglione, Anna; Arnold, Daniel | 2024 | 10 | Method | ๐ Search |
| Optimizing load frequency control in isolated island city microgrids: a deep graph reinforcement learning approach with data enhancement across extensive scenarios | Wu, M.; Ma, D.; Xiong, K.; Yuan, L. | 2024 | 1 | PlanningoptimizationOperationcontrol | ๐ Search |
| Fast power flow calculation method for power system based on heterogeneous edge graph convolutional neural network | Wu, G.; Liu, S.; Xie, T.; Luo, W.; Liu, J. | 2024 | 0 | Planningoptimization | ๐ Search |
| Fault Location Method of Distribution Network Based on Improved Graph Neural Network | Wei, T.; Zhang, H.; Fan, M.; Sun, J.; Wang, X. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| Short-term load forecasting using spatial-temporal embedding graph neural network | Wei, Chuyuan; Pi, Dechang; Ping, Mingtian; Zhang, Haopeng | 2023 | 14 | Forecastingprediction | ๐ Search |
| Modeling and Application of Meteorological-Transportation-Power Coupling Complex Network | Wang, Zhiwei; Jiang, Wei; Guo, Xinyun; Lin, Jiashun; Huang, Kai; Liu, Zhiyuan | 2024 | 0 | General | ๐ Search |
| Uncertainty-Aware Transient Stability-Constrained Preventive Redispatch: A Distributional Reinforcement Learning Approach | Wang, Zhengcheng; Teng, Fei; Zhou, Yanzhen; Guo, Qinglai; Sun, Hongbin | 2024 | 0 | PlanningoptimizationReliabilityresilienceOperationcontrol | ๐ Search |
| A short-term residential load forecasting scheme based on the multiple correlation-temporal graph neural networks | Wang, Yufeng; Rui, Lingxiao; Ma, Jianhua; jin, Qun | 2023 | 17 | Forecastingprediction | ๐ Search |
| A wind speed forecasting framework for multiple turbines based on adaptive gate mechanism enhanced multi-graph attention networks | Wang, Y.; Yang, Z.; Ma, J.; Jin, Q. | 2024 | 4 | Forecastingprediction | ๐ Search |
| Stealth FDIA Localization in Power Systems Using Spatio-Temporal Graph Neural Networks | Wang, X.; Tang, L.; Xie, H. | 2023 | 0 | Cybersecurityprivacy | ๐ Search |
| Power system preventive control aided by a graph neural network-based transient security assessment surrogate | Wang, Kangkang; Wei, Wei; Xiao, Tannan; Huang, Shaowei; Zhou, Bo; Diao, Han | 2022 | 2 | ReliabilityresilienceOperationcontrol | ๐ Search |
| Dynamic spatio-temporal correlation and hierarchical directed graph structure based ultra-short-term wind farm cluster power forecasting method | Wang, Fei; Chen, Peng; Zhen, Zhao; Yin, Rui; Cao, Chunmei; Zhang, Yagang; Duiฤ, Neven | 2022 | 61 | Forecastingprediction | ๐ Search |
| Geometric deep learning for online prediction of cascading failures in power grids | Varbella, Anna; Gjorgiev, Blazhe; Sansavini, Giovanni | 2023 | 34 | Reliabilityresilience | ๐ Search |
| Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow | Varbella, Anna; Briens, Damien; Gjorgiev, Blazhe; D'Inverno, Giuseppe Alessio; Sansavini, Giovanni | 2024 | 0 | Planningoptimization | ๐ Search |
| Graph neural networks for fault diagnosis of geographically nearby photovoltaic systems | Van Gompel, Jonas; Spina, Domenico; Develder, Chris | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Cost-effective fault diagnosis of nearby photovoltaic systems using graph neural networks | Van Gompel, Jonas; Spina, Domenico; Develder, Chris | 2023 | 25 | Reliabilityresilience | ๐ Search |
| Graph convolutional network-based security-constrained unit commitment leveraging power grid topology in learning | Tang, Xian; Bai, Xiaoqing; Weng, Zonglong; Wang, Rui | 2023 | 8 | Cybersecurityprivacy | ๐ Search |
| Resilience of Data-Driven Cyberattack Detection Systems in Smart Power Grids | Takiddin, Abdulrahman; Atat, Rachad; Mbayed, Hayat; Ismail, Muhammad; Serpedin, Erchin | 2024 | 0 | Cybersecurityprivacy | ๐ Search |
| Multi-fidelity graph neural networks for efficient power flow analysis under high-dimensional demand and renewable generation uncertainty | Taghizadeh, Mehdi; Khayambashi, Kamiar; Hasnat, Md Abul; Alemazkoor, Negin | 2024 | 7 | Planningoptimization | ๐ Search |
| Deep learning method based on graph neural network for performance prediction of supercritical CO2 power systems | Sun, Lei; Liu, Tianyuan; Wang, Ding; Huang, Chengming; Xie, Yonghui | 2022 | 25 | Forecastingprediction | ๐ Search |
| A Method for Fault Location in Distribution Networks Based on Graph Neural Networks and Improved Convolutional Neural Networks | Sun, G.; Liu, X.; Fu, R.; He, B.; Shang, J. | 2024 | 0 | Reliabilityresilience | ๐ Search |
| AnyCast: Efficient Graph Learning for Large-Scale PV Power Forecasting with Extreme Missing Data | Song, Keunju; Kim, Minsoo; Kim, Hongseok | 2024 | 0 | ForecastingpredictionDatainfrastructuredecisionsupport | ๐ Search |
| Using Graph Neural Networks in Reinforcement Learning With Application to Monte Carlo Simulations in Power System Reliability Analysis | Solheim, รystein Rognes; Annfelt Hรธverstad, Boye; Korpรฅs, Magnus | 2024 | 1 | Reliabilityresilience | ๐ Search |
| Short-term load forecasting study of distribution network based on FADJ-ASTGCN | Rui, Liu Jin; Sen, Wei Xiang | 2024 | 0 | Forecastingprediction | ๐ Search |
| Dynamic Generative Residual Graph Convolutional Neural Networks for Electricity Theft Detection | Zhuang, W.; Jiang, W.; Xia, M.; Liu, J. | 2024 | 7 | Cybersecurityprivacy | ๐ Search |
| A Multi-Scale Spatial-Temporal Graph Neural Network-Based Method of Multienergy Load Forecasting in Integrated Energy System | Zhuang, W.; Fan, J.; Xia, M.; Zhu, K. | 2024 | 20 | Forecastingprediction | ๐ Search |
| Real-Time Cascading Failure Risk Evaluation With High Penetration of Renewable Energy Based on a Graph Convolutional Network | Zhu, Y.; Zhou, Y.; Wei, W.; Zhang, L. | 2023 | 16 | Reliabilityresilience | ๐ Search |
| Assessing Bulk Power System Reliability by End-to-End Line Maintenance-Aware Learning | Zhu, Y.; Singh, C. | 2023 | 2 | Reliabilityresilience | ๐ Search |
| Topology-Aware Reliability Assessment by Graph Neural Networks | Zhu, Y.; Singh, C.; Burns and McDonnell; Imperix | 2022 | 2 | Reliabilityresilience | ๐ Search |
| Robust Representation Learning for Power System Short-Term Voltage Stability Assessment Under Diverse Data Loss Conditions | Zhu, L.; Wen, W.; Qu, Y.; Shen, F.; Li, J.; Song, Y.; Liu, T. | 2024 | 7 | Operationcontrol | ๐ Search |
| Structure-Aware Recurrent Learning Machine for Short-Term Voltage Trajectory Sensitivity Prediction | Zhu, L.; Wen, W.; Li, J.; Zhang, C.; Shen, Y.; Hou, Y.; Liu, T. | 2024 | 6 | Forecastingprediction | ๐ Search |
| Integrated Data-Driven Power System Transient Stability Monitoring and Enhancement | Zhu, L.; Wen, W.; Li, J.; Hu, Y. | 2024 | 23 | Operationcontrol | ๐ Search |
| Spatial-Temporal Electric Vehicle Charging Demand Forecasting: A GTrans Approach | Zhu, L.; Ge, Y.; Wang, K.; Fan, Y.; Ma, X.; Zhang, L. | 2023 | 0 | Forecastingprediction | ๐ Search |
| Deep Reinforcement Learning-Based Optimal PMU Placement Considering the Degree of Power System Observability | Zhou, X.; Wang, Y.; Shi, Y.; Jiang, Q.; Zhou, C.; Zheng, Z. | 2024 | 8 | Planningoptimization | ๐ Search |
| Transient Stability Assessment Based on Gated Graph Neural Network With Imbalanced Data in Internet of Energy | Zhou, X.; Guan, X.; Sun, D.; Jiang, H.; Peng, J.; Jin, Y.; Zhang, Y. | 2022 | 21 | Operationcontrol | ๐ Search |
| A Novel Semi-supervised Learning Method for Power Transformer Fault Diagnosis with Limited Labeled Data | Zhou, G.; Wang, D.; Tian, Y.; Wang, J.; Cao, S.; Academic Exchange Information Centre; Guangdong Polytechnic Institute | 2023 | 1 | Reliabilityresilience | ๐ Search |
| A method of multivariate short-term voltage stability assessment based on heterogeneous graph attention deep network | Zhong, Z.; Guan, L.; Su, Y.; Yu, J.; Huang, J.; Guo, M. | 2022 | 16 | Operationcontrol | ๐ Search |
| Spatiotemporal Correlation Analysis for Predicting Current Transformer Errors in Smart Grids | Zhong, Y.; Li, T.; Przystupa, K.; Lin, C.; Yang, G.; Yang, S.; Kochan, O.; Sikora, J. | 2024 | 2 | Forecastingprediction | ๐ Search |
| Graph spatiotemporal process for multivariate time series anomaly detection with missing values | Zheng, Y.; Koh, H.Y.; Jin, M.; Chi, L.; Wang, H.; Phan, K.T.; Chen, Y.-P.P.; Pan, S.; Xiang, W. | 2024 | 12 | ReliabilityresilienceDatainfrastructuredecisionsupport | ๐ Search |
| Correlation-Aware SpatialโTemporal Graph Learning for Multivariate Time-Series Anomaly Detection | Zheng, Y.; Koh, H.Y.; Jin, M.; Chi, L.; Phan, K.T.; Pan, S.; Chen, Y.P.; Xiang, W. | 2023 | 20 | Reliabilityresilience | ๐ Search |
| A hybrid physical-data approach for solving dynamic optimal power flow considering uncertainties and different topology configurations | Zheng, L.; Bai, X.; Weng, Z.; Jia, Y. | 2023 | 3 | Planningoptimization | ๐ Search |
| Transient Stability Evaluation of Independent Microgrid based on Message Passing Graph Neural Network | Zhen, J.; Huang, S.; Jia, X.; Du, H.; IEEE; Sichuan Institute of Electronics | 2023 | 1 | Operationcontrol | ๐ Search |
| Short-term Wind Power Prediction Method Based on GCN-LSTM | Zhao, Y.; Pu, H.; Dai, Y.; Cong, S. | 2023 | 5 | Forecastingprediction | ๐ Search |
| On the Use of Spatial-temporal Feature Graph Convolutional Network for Ultra-Short Term Prediction of Wind Power Generation | Zhao, W.; Chen, Y.; Ru, C.; Qian, W.; Shi, C.; Yang, Q.; Chengdu University of Technology; Chinese Society for Electrical Engineering; et al.; IEEE Power and Energy Society; Tsinghua University Dept. of Electrical Engineering; University of Electronic Science and Technology of China | 2022 | 0 | Forecastingprediction | ๐ Search |
| Learning Sequential Distribution System Restoration via Graph-Reinforcement Learning | Zhao, T.; Wang, J. | 2022 | 48 | Reliabilityresilience | ๐ Search |
| A Regional Short-term Load Forecasting Method Based on Adaptive Graph Construction and Kernel Size Selection | Zhao, J.; Dai, H.; Zhen, Z.; Wang, F. | 2024 | 0 | Forecastingprediction | ๐ Search |
| Ultra-short-term Power Forecasting of Wind Farm Cluster Based on Spatio-temporal Graph Neural Network Pattern Prediction | Zhao, H.; Li, G.; Chen, R.; Zhen, Z.; Wang, F. | 2022 | 3 | Forecastingprediction | ๐ Search |
| Spatial correlation learning based on graph neural network for medium-term wind power forecasting | Zhao, B.; He, X.; Ran, S.; Zhang, Y.; Cheng, C. | 2024 | 13 | Forecastingprediction | ๐ Search |
| Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control | Zhang, Y.; Yue, M.; Wang, J.; Yoo, S. | 2024 | 12 | PlanningoptimizationOperationcontrol | ๐ Search |
| Chinese Electric Power Equipment Fault Recognition Based on Graph Convolutional Networks | Zhang, Y.; Lu, M.; Liu, L.; Li, Z.; Jiao, F.; Xiong, Y.; Tang, Q.; Li, R.; China Computer Federation, Chinese Association for Artificial Intelligence | 2021 | 1 | Reliabilityresilience | ๐ Search |
| Graph Convolution Network for Carbon Emission Factor Forecast of Power Grid | Zhang, Y.; Guo, B.; Liu, C.; Li, H.; Xu, W.; Energy Storage and Electrotechnics Department in China Electric Power Research Institute; IEEE; IEEE Power and Energy Society (PES); North China Electric Power University; Tianjin University | 2023 | 1 | Forecastingprediction | ๐ Search |
| Modeling Long- and Short-term Project Relationships for Project Management Systems | Zhang, Y.; Bai, G.; Gao, Z.; Zhu, P.; Li, S. | 2024 | 0 | Planningoptimization | ๐ Search |
| Research on Anomaly Monitoring Algorithm of Smart Grid Based on Graph Neural Network | Zhang, Y. | 2023 | 0 | Reliabilityresilience | ๐ Search |
| Distributed PV Power Forecasting Considering Spatio-temporal Dependence | Zhang, X.; Wen, M.; Li, J.; Huang, H.; IEEE; Lanzhou Jiaotong University; School of New Energy and Power Engineering | 2023 | 0 | Forecastingprediction | ๐ Search |
| GCN-based Entity Relation Extraction Method for Power Marketing Data | Zhang, X.; Meng, Q.; Tan, Q.; Dong, Y.; Chen, Y.; Tan, Z. | 2023 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Ultra-short-term prediction of regional photovoltaic power based on dynamic graph convolutional neural network | Zhang, X.; Gao, R.; Zhu, C.; Liu, C.; Mei, S. | 2024 | 8 | Forecastingprediction | ๐ Search |
| A Method and System for Power Grid Engineering Error Diagnosis Based on Improved Graph Convolutional Networks | Zhang, S.; Gao, H.; Shan, X.; Wu, H.; Sun, S. | 2023 | 0 | Reliabilityresilience | ๐ Search |
| A graph attention networks-based model to distinguish the transient rotor angle instability and short-term voltage instability in power systems | Zhang, R.; Yao, W.; Shi, Z.; Zeng, L.; Tang, Y.; Wen, J. | 2022 | 30 | Operationcontrol | ๐ Search |
| PSGformer: A novel multivariate net load forecasting model for the smart grid | Zhang, Q.; Zhou, S.; Xu, B.; Shen, Z.; Chang, W. | 2024 | 2 | Forecastingprediction | ๐ Search |
| TransformGraph: A novel short-term electricity net load forecasting model | Zhang, Q.; Chen, J.; Xiao, G.; He, S.; Deng, K. | 2023 | 33 | Forecastingprediction | ๐ Search |
| Graph Neural Network based Short-term Solar Irradiance Forcasting Model Considering Surrounding Meteorological Factors | Zhang, M.; Sun, Y.; Feng, C.; Zhen, Z.; Wang, F.; Li, G.; Liu, D.; Wang, H. | 2022 | 3 | Forecastingprediction | ๐ Search |
| State Estimation Method for Few-Measurements Power Distribution Network Based on Improved Deep Graph Convolutional Network | Zhang, L.; Zhou, L.; Hou, Y.; Guo, T.; Wang, X. | 2023 | 1 | Operationcontrol | ๐ Search |
| MNGAN: Multi-Branch Parameter Identification Based onย Dynamic Weighting | Zhang, L.; Lei, Z.; Peng, Z.; Xia, M.; Zou, G.; Liu, J. | 2023 | 0 | Planningoptimization | ๐ Search |
| Combined Wind Speed Prediction Model Considering the Spatio-Temporal Features of Wind Farm | Zhang, J.; Yang, C.; Niu, F.; Sun, Y.; Wang, R. | 2022 | 3 | Forecastingprediction | ๐ Search |
| Interpretable Wind Power Short-Term Power Prediction Model Using Deep Graph Attention Network | Zhang, J.; Li, H.; Cheng, P.; Yan, J. | 2024 | 5 | Forecastingprediction | ๐ Search |
| Fault Diagnosis of Energy Networks Based on Improved SpatialโTemporal Graph Neural Network With Massive Missing Data | Zhang, J.; Cheng, Y.; He, X. | 2023 | 7 | ReliabilityresilienceDatainfrastructuredecisionsupport | ๐ Search |
| Fault Diagnosis of Energy Networks: A Graph Embedding Learning Approach | Zhang, J.; Cheng, Y.; He, X. | 2022 | 9 | Reliabilityresilience | ๐ Search |
| Low Frequency Oscillation Mode Estimation Using Synchrophasor Data | Zhang, J.; An, H.; Wu, N. | 2020 | 9 | Operationcontrol | ๐ Search |
| Intelligent Detection Model for Power Grids Based on Graph Neural Networks | Zhang, G.; Zhang, Y.; Du, Z.; Zhang, X.; Wang, L.; He, Z.; IEEE | 2022 | 1 | Operationcontrol | ๐ Search |
| Graph Convolution Network Considering Edge Node Feature Aggregation | Zhang, D.; Guo, H.; Wang, B.; Chu, Z.; Jia, Y.; Ye, M.; Beijing Sihuida Electric Power Technology Co., Ltd.; Electric Power Engineering Technology; Tebian Electric Apparatus Stock Co. Ltd. | 2021 | 0 | General | ๐ Search |
| An end-to-end power knowledge extraction method based on convolutional neural networks and multi-headed attention mechanisms | Zhang, B.; Zhou, Y.; Qin, L.; Li, S.; Academic Exchange Information Centre (AEIC); Universiti Malaysia Perlis | 2023 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Physics-Informed Multi-Agent deep reinforcement learning enabled distributed voltage control for active distribution network using PV inverters | Zhang, B.; Cao, D.; Hu, W.; Ghias, A.M.Y.M.; Chen, Z. | 2024 | 11 | Operationcontrol | ๐ Search |
| Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework | Zeng, L.; Yao, W.; Hu, Z.; Shuai, H.; Li, Z.; Wen, J.; Cheng, S. | 2024 | 0 | Datainfrastructuredecisionsupport | ๐ Search |
| Learning Latent Interactions for Event Classification via Graph Neural Networks and PMU Data | Yuan, Y.; Wang, Z.; Wang, Y. | 2023 | 18 | Reliabilityresilience | ๐ Search |
| Toward dynamic stability assessment of power grid topologies using graph neural networks | Nauck, Christian; Lindner, Michael; Schรผrholt, Konstantin; Hellmann, Frank | 2023 | 0 | Operationcontrol | ๐ Search |
| Power System Sparse Matrix Statistics | Safdarian, F.; Mao, Z.; Jang, W.; Overbye, T. J. | 2022 | 2 | General | ๐ Search |
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