[Journal Papers]
[91] D. Shi, R. Hu, Y. Wu, et al., “Towards AI-Empowered Smart Power Grid: Forecasting, Dispatch and Control,” IEEE Power & Energy Magazine, vol. 22, no. 6, Nov/Dec 2024. DOI: 10.1109/MPE.2024.3408111.
[90] H. Davoudi, F. Wang, Y. Chen, D. Shi, and A. Xavier, and F. Qiu, “Market Implications of Alternative Operating Reserve Modeling in Wholesale Electricity Markets,” IEEE Trans. Energy Markets, Policy and Regulation, 2024.
[89] Y. Zhou, L. Zhou, Z. Yi, D. Shi, and M. Guo, “Leveraging AI for Enhanced Power Systems Control: An Introductory Study of Model-Free DRL Approaches,” IEEE Access, 2024.
[88] S. Nematshahi, D. Shi, F. Wang, and B. Yan, “Deep Reinforcement Learning Based Voltage Control Revisited,” IET Generation, Transmission & Distribution, 2023.
[87] Y. Lin, X. Zhang, J. Wang, D. Shi, and D. Bian, “Voltage Stability Constrained Optimal Power Flow for Unbalanced Distribution System Based on Semidefinite Programming,” Journal of Modern Power Systems and Clean Energy, 2022.
[86] R. Ma, Z. Yi, Y. Xiang, D. Shi, C. Xu, H. Wu, “A Blockchain-Enabled Demand Management and Control Framework Driven by Deep Reinforcement Learning,” IEEE Transactions on Industrial Electronics, 2022.
[J85] Z. Liang, D. Bian, X. Zhang, and D. Shi, “Risk-constrained Energy Management Strategy for a Commercial Campus Considering Comprehensive Reserves Against Islanding Conditions,” CSEE Journal of Power and Energy Systems, 2021.
[J84] M. Kamruzzaman, J. Duan, D. Shi, and M. Benidris, “A Deep Reinforcement Learning-based Multi-agent Framework to Enhance Power System Resilience using Shunt Resources,” IEEE Transactions on Power Systems, 2021.
[J83] M. Kamruzzaman, X. Zhang, M. Abdelmalak, D. Shi, and M. Benidris, “A Data-driven Accurate Battery Model to Use in Probabilistic Analysis of Power Systems,” Journal of Energy Storage, 2021.
[J82] Y. Zhou, W. Lee, R. Diao, and D. Shi, “Deep Reinforcement Learning Based Real-time AC Optimal Power Flow Considering Uncertainties,” Journal of Modern Power Systems and Clean Energy, 2021.
[J81] Z. Zhou, Y. Xiang, H. Xu, Y. Wang, and D. Shi, “Unsupervised Learning for Non-intrusive Load Monitoring in Smart Grid Based on Spiking Deep Neural Network,” Journal of Modern Power Systems and Clean Energy, 2021.
[J80] Y. Lin, Y. Wang, J. Wang, D. Shi, “Tensor-based Parameter Reduction of Dynamic Load Models with Variable Frequency Drive,” IEEE Transactions on Power Systems, 2021.
[J79] M. Cui, F. Li, H. Cui, S. Bu, D. Shi, “Data-driven Joint Voltage Stability Assessment Considering Load Uncertainty: A Variational Bayes Inference Integrated with Multi-CNNs,” IEEE Transactions on Power Systems, 2021.
[J78] Y. Xiang, Z. Yi, X. Lu, Z. Yu, D. Shi, C. Xu, “Distributed Frequency Emergency Control with Coordinated Edge Intelligence,” Electric Power Systems Research, 2021.
[J77] G. Tian, Y. Gu, Z. Yu, Q. Zhang, D. Shi, Q. Zhou, Z. Wang, “Enhanced Denoising Autoencoder Aided Bad Data Filtering for Synchrophasor-based State Estimation,” CSEE Journal of Power and Energy Systems, 2021.
[J76] P. Xu, J. Duan, J. Zhang, Y. Pei, D. Shi, Z. Wang, X. Dong, and Y. Sun, “Active Power Correction Strategies Based on Deep Reinforcement Learning-Part I: A Simulation-driven Solution for Robustness,” CSEE Journal of Power and Energy Systems, 2021.
[J75] S. Chen, J. Duan, Y. Bai, J. Zhang, D. Shi, Z. Wang, X. Dong, and Y. Sun, “Active Power Correction Strategies Based on Deep Reinforcement Learning-Part II: A Distributed Solution for Adaptability,” CSEE Journal of Power and Energy Systems, 2021.
[J74] S. Li, D. Tylavsky, D. Shi, and Z. Wang, “Implications of Stahl’s Theorems to Holomorphic Embedding Pt. I: Theoretical Convergence,” CSEE Journal of Power and Energy Systems, 2021.
[J73] A. Dronamraju, S. Li, Q. Li, Y. Li, D. Tylavsky, D. Shi, and Z. Wang, “Implications of Stahl’s Theorems to Holomorphic Embedding Pt. II: Numerical Convergence,” CSEE Journal of Power and Energy Systems, 2021.
[J72] G. Tian, Y. Gu, D. Shi, J. Fu, Z. Yu, and Q. Zhou, “Neural Network-based Power System State Estimation with Extended Observability,” Journal of Modern Power Systems and Clean Energy, 2021.
[J71] Y. Gu, Z. Yu, R. Diao, and D. Shi, “Doubly-fed Deep Learning Method for Bad Data Identification in Linear State Estimation,” Journal of Modern Power Systems and Clean Energy, 2020.
[J70] Y. Zhou, B. Zhang, C. Xu, T. Lan, R. Diao, D. Shi, Z. Wang, W. Lee, “A Data-driven Method for Fast AC OPF Solutions via Deep Reinforcement Learning,” Journal of Modern Power Systems and Clean Energy, 2020. [Best Paper]
[J69] Y. Meng, Z. Yu, N. Lu and D. Shi, “Time Series Classification for Locating Forced Oscillation Sources,” IEEE Transactions on Smart Grid, 2020.
[J68] M. AlAshery, Z. Yi , D. Shi, X. Lu, C. Xu, Z. Wang and W. Qiao, “A Blockchain-Enabled Multi-Settlement Quasi-Ideal Peer-to-Peer Trading Framework,” IEEE Transactions on Smart Grid, 2020.
[J67] W. Li, M. Yi, M. Wang, Y. Wang, D. Shi, and Z. Wang, “Real-time Energy Disaggregation at Substations with Behind-the-Meter Solar Generation,” IEEE Trans. Power Syst., 2020.
[J66] S. Wang, R. Diao, C. Xu, D. Shi and Z. Wang, “On Multi-Event Co-Calibration of Dynamic Model Parameters Using Soft Actor-Critic,” IEEE Transactions on Power Systems, 2020.
[J65] Y. Wang, W. Zhang, H. Sun, Y. Xiang, D. Shi, and Z. Wang, “Research on Fast Response Criterion of Power Grid Distributed Loads after HVDC Block Fault,” IET Generation, Transmission & Distribution, 2020.
[J64] Z. Zhou, Y. Xiang, H. Xu, Z. Yi, D. Shi and Z. Wang, “A Novel Transfer Learning based Intelligent Non-intrusive Load Monitoring with Limited Measurements,” IEEE Transactions on Instrumentation & Measurement, 2020.
[J63] Z. Zhou, Y. Xiang, H. Xu, Y. Wang, D. Shi and Z. Wang, “Self-organizing Probability Neural Network Based Intelligent Non-Intrusive Load Monitoring with Applications to Low-cost Residential Measuring Devices,” Transactions of the Institute of Measurement and Control, 2020.
[J62] Y. Hashmy, Z. Yu, D. Shi and Y. Weng, “Wide-area Measurement System-based Low Frequency Oscillation Damping Control through Reinforcement Learning,” IEEE Transactions on Smart Grid, 2020.
[J61] Y. Xiang, X. Zhang, D. Shi, R. Diao and Z. Wang, “Robust Optimization for Transmission Defense against Multi-Period Attacks with Uncertainties,” International Journal of Electrical Power and Energy Systems, 2020.
[J60] K. Yu, W. Guo, X. Chen, D. Shi, J. Wang, L. Gan, “Research on Dynamic Control of Low-voltage Distribution Network with High Penetration of Electric Heat Pumps based on uPMU Measurements and Data-driven Approach,” IET Generation, Transmission & Distribution, 2020.
[J59] S. Wang, J. Duan, D. Shi, C. Xu, H. Li, R. Diao and Z. Wang, “A Data-driven Multi-agent Autonomous Voltage Control Framework Using Deep Reinforcement Learning,” IEEE Transactions on Power Systems, 2020.
[J58] X. Wang, Y. Wang, D. Shi, J. Wang and Z. Wang, “Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach,” IEEE Transactions on Smart Grid, 2020.
[J57] X. Wang, Y. Wang, J. Wang and D. Shi, “Residential Customer Baseline Load Estimation Using Stacked Autoencoder With Pseudo-Load Selection,” IEEE Journal on Selected Areas in Communications, vol. 38, no. 1, pp. 61-70, Jan. 2020.
[J56] Y. Lin, Y. Wang, J. Wang, S. Wang and D. Shi, “Global Sensitivity Analysis in Load Modeling via Low-rank Tensor,” IEEE Transactions on Smart Grid, 2020.
[J55] J. Duan, D. Shi, R. Diao, H. Li, Z. Wang, B. Zhang, D. Bian and Z. Yi, “Deep-Reinforcement-Learning-Based Autonomous Voltage Control for Power Grid Operations,” IEEE Transactions on Power Systems, vol. 35, no. 1, pp. 814-817, Jan. 2020.
[J54] Z. Ma, Z. Wang, Y. Wang, R. Diao and D. Shi, “Mathematical representation of the WECC composite load model,” Journal of Modern Power Systems and Clean Energy, vol. 8, no. 5, pp. 1015-1023, Sept. 2020.
[J53] J. Xie, Z. Ma, K. Dehghanpour, Z. Wang, Y. Wang, R. Diao and D. Shi, “Imitation and Transfer Q-learning-Based Parameter Identification for Composite Load Modeling”, IEEE Transactions on Smart Grid, 2020.
[J52] Y. Fu, L. Chen, Z. Yu, Y. Wang and D. Shi, “Data-Driven Low Frequency Oscillation Mode Identification and Preventive Control Strategy Based on Gradient Descent,” Electric Power System Research, 2020.
[J51] X. Deng, D. Bian, W. Wang, Z. Jiang, W. Yao, W. Qiu, N. Tong, D. Shi and Y. Liu, “A Novel Deep Learning Model to Detect Various Synchrophasor Data Anomalies,” IET Generation, Transmission & Distribution, 2020.
[J50] M. Khan, H. Sun, Y. Xiang and D. Shi, “Electric Vehicles Participation in Load Frequency Control based on mixed H2/H∞,” International Journal of Electrical Power & Energy Systems, 2020.
[J49] C. Fu, C. Wang, L. Y. Wang, and D. Shi, “An Alternative Method for Mitigating Impacts of Communication Delay on Load Frequency Control,” International Journal of Electrical Power & Energy Systems, 2020.
[J48] L. Zhang, J. Qin, D. Shi, and Z. Wang, “Improved Equivalent Circuit Model of MMC and Influence Analysis of Simulation Time Step,” IET Power Electronics, 2020.
[J47] J. Duan, D. Shi, R. Diao, Z. Wang, D. Bian, Z. Yi, “Deep-Reinforcement-Learning-Based Autonomous Voltage Control for Power Grid Operations,” IEEE Trans. Power Systems, 2019.
[J46] X. Wang, Y. Wang, J. Wang, and D. Shi, “Residential Customer Baseline Load Estimation Using Stacked Autoencoder with Pseudo-load Selection,” IEEE Journal on Selected Areas in Communications (J-SAC) Issue on Communications and Data Analytics in Smart Grid, 2019.
[J45] X. Deng, D. Bian, D. Shi, W. Yao, L. Wu, and Y. Liu, “Impact of Low Data Quality on Disturbance Triangulation Application Using High-density PMU Measurements,” IEEE Access, 2019.
[J44] C. Liu, F. Hu, D. Shi, X. Zhang, K. Sun, and Z. Wang, “Measurement-based Voltage Stability Assessment Considering Generator VAR Limits,” IEEE Trans. Smart Grid, 2019.
[J43] M. Cui, J. Wang, Y. Wang, R. Diao, and D. Shi, “Robust Time-Varying Synthesis Load Modeling in Distribution Networks Considering Anomalies,” IEEE Trans. Power Systems, 2019.
[J42] Z. Yi, X. Zhao, D. Shi, J. Duan, Y. Xiang, and Z. Wang, “Accurate Power Sharing and Synthetic Inertia Control for DC Building Microgrids with Guaranteed Performance,” IEEE Access, 2019.
[J41] H. Li, Q. Chen, C. Fu, Z. Yu, D. Shi, and Z. Wang, “Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model,” Energies, vol. 12, no. 3, pp. 547-562, 2019.
[J40] D. Bian, M. Kuzlu, M. Pipattanasomporn, S. Rahman, and D. Shi, “Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications,” IET Communications, 2019.
[J39] J. Duan, Z. Yi, D. Shi, Z. Wang, “Reinforcement-Learning-Based Optimal Control for Hybrid Energy Storage System”, IEEE Transactions on Industrial Informatics, 2019.
[J38] K. Lai, Y. Wang, D. Shi, M. S. Illindala, Y. Jin, and Z. Wang, “Sizing Battery Storage for Islanded Microgrid Systems to Enhance the Robustness against Attacks on Energy Sources,” Journal of Modern Power Systems and Clean Energy, 2019. [Best Paper]
[J37] X. Wang, D. Shi, J. Wang, and Z. Wang, “Online Identification and Data Recover for PMU Data Manipulation Attack,” IEEE Trans. Smart Grid, 2019.
[J36] D. Bian, Z. Yu, D. Shi, R. Diao, Z. Wang, “A Real-time Robust Low-Frequency Oscillation Detection and Analysis (LFODA) System with Innovative Ensemble Filtering,” CSEE Journal of Power and Energy Systems, 2019.
[J35] H. Li, R. Diao, X. Zhang, X. Lin, X. Lu, D. Shi, Z. Wang, and L. Wang, “An Integrated Online Dynamic Security Assessment System for Improved Situational Awareness and Economic Operation,” IEEE Access, 2019.
[J34] Z. Liang, D. Bian, X. Zhang, D. Shi, R. Diao, and Z. Wang, “Optimal Energy Management for Commercial Buildings Considering Comprehensive Comfort Levels in a Retail Electricity Market,” Applied Energy, 2018.
[J33] L. Yu, D. Shi, G. Xu, X. Guo, Z. Jiang, C. Jing, “Consensus Control of Distributed Energy Resources in a Multi-bus Microgrid for Reactive Power Sharing and Voltage Control,” Energies, 2018.
[J32] D. Bian, D. Shi, M. Pipattanasomporn, M. Kuzlu and S. Rahman, “Mitigating the Impact of Renewable Variability with Demand-Side Resources Considering Communication and Cyber Security Limitations,” IEEE Access, 2018.
[J31] L Yu, D. Shi, X. Guo, Z. Jiang, G. Xu, G. Jian, J. Lei, C. Jing, “An Efficient Substation Placement and Sizing Strategy Based on GIS Using Semi-supervised Learning,” CSEE Journal of Power and Energy Systems, 2018.
[J30] Y. Yan, D. Shi, D. Bian, B. Huang, Z. Yi, Z. Wang, “Small-signal Stability Analysis and Performance Evaluation of Microgrids under Distributed Control,” IEEE Trans. Smart Grid, 2018.
[J29] X. Zhang, D. Shi, Z. Wang, X. Wang, K. Tomsovic, Y. Jin, “Optimal Allocation of Series FACTS Devices Under High Penetration of Wind Power Within a Market Environment,” IEEE Transactions on Power Systems, 2018.
[J28] R. Yao, K. Sun, D. Shi, and X. Zhang, “Voltage Stability Analysis of Power Systems with Induction Motors Based on Holomorphic Embedding,” IEEE Transactions on Power Systems, 2018.
[J27] K. Lai, Y. Wang, D. Shi, M. Illindala, X. Zhang, Z. Wang, “A Resilient Power System Operation Strategy Considering Transmission Line Attacks,” IEEE Access, 2018.
[J26] L. Mang, D. Shi, Z. Yu, W. Zhu, Z. Wang, Y. Xiang, “An Alternating Direction Method of Multipliers Based Approach for Phasor Measurement Unit Data Recovery,” IEEE Trans. Smart Grid, 2018.
[J25] H. Banna, Z. Yu, D. Shi, Z. Wang, D. Su, C. Xu, S. Solanki, J. Solanki, “Online Coherence Identification Using Dynamic Time Warping for Controlled Islanding,” Journal of Modern Power Systems and Clean Energy, 2018.
[J24] T. Zhang, X. Chen, Z. Yu, X. Zhu, and D. Shi, “A Monte-Carlo Simulation Approach to Evaluate Service Capacities of EV Charging and Battery Swapping Stations,” IEEE Trans. Industrial Informatics, 2018.
[J23] Z. Yu, D. Shi, Z. Wang, Q. Zhang, J. Huang, and S. Pan, “Distributed Estimation of Oscillations in Power Systems: an Extended Kalman Filtering Approach,” CSEE Journal of Power and Energy Systems, 2018.
[J22] H. Yuan, F. Li, H. Cui, D. Shi, and Z. Wang, “A Measurement-based VSI for Voltage Dependent Loads Using Angle Difference between Tangent Lines of Load and PV Curves,” Electric Power Systems Research, 2018.
[J21] Y. Zhu, C. Liu, K. Sun, D. Shi, and Z. Wang, “Optimization of Battery Energy Storage to Improve Power System Oscillation Damping,” IEEE Transactions on Sustainable Energy, 2018.
[J20] Z. Jiang, D. Shi, X. Guo, G. Xu, L. Yu, and C. Jing, “Robust Smart Meter Data Analytics Using Smoothed ALS and Dynamic Time Warping,” Energies, 2018.
[J19] C. Liu, B. Wang, X. Xu, K. Sun, D. Shi, and C. L. Bak, “A Multi-Dimensional Holomorphic Embedding Method for Analytical Power Flow Solutions,” IEEE Access, 2017.
[J18] L. Zhang, J. Yu, J. Qin, D. Shi, and Z. Wang, “Modeling, Control, and Protection of Multi-terminal Modular Multilevel Converters-based HVDC Systems,” CSEE Journal of Power and Energy Systems, Invited Paper, 2017.
[J17] X. Zhang, C. Xu, D. Shi, Z. Wang, Q. Zhang, G. Liu, K. Tomsovic, A. Dimitrovski, “The Allocation of Variable Series Reactor Considering AC Constraints and Contingencies,” CSEE Journal of Power and Energy Systems, 2017.
[J16] F. Hu, K. Sun, D. Shi, and Z. Wang, “Measurement-based Voltage Stability Assessment for Load Areas Addressing n-1 Contingencies,” IET Generation, Transmission & Distribution, 2017.
[J15] X. Wang, D. Shi, Z. Wang, C. Xu, Q. Zhang, X. Zhang, and Z. Yu, “Online Calibration of Phasor Measurement Unit Using Density-Based Spatial Clustering,” IEEE Transactions on Power Delivery, 2017.
[J14] B. Kan, W. Zhu, G. Liu, X. Chen, and D. Shi. “Topology Modeling and Analysis in Power Grid Network based on Graph Database,” International Journal of Computational Intelligence Systems, 2017.
[J13] Y. Li, D. Shi, X. Guo, et al., “An Efficient GIS-based Substation Placement and Sizing Strategy Using Semi-Supervised Learning,” CSEE Journal of Power and Energy Systems, 2017.
[J12] D. Bian, M. Kuzlu, M. Pipattanasomporn, S. Rahman, D. Shi, “Performance Evaluation of Communication Network Supporting Various Smart Grid Applications,” IET Communications, 2018.
[J11] D. Shi, X. Chen, Z. Wang, J. Chai, X. Zhang, and X. Wang, “A Distributed Cooperative Control Framework for Synchronized Reconnection of a Multi-Bus Microgrid,” IEEE Trans. Smart Grid, 2017.
[J10] F. Hu, K. Sun, D. Shi, and Z. Wang, “Measurement-based Voltage Stability Assessment for Load Areas Addressing n-1 Contingencies,” IET Generation, Transmission & Distribution, 2017.
[J9] X. Zhang, C. Xu, D. Shi, Z. Wang, Q. Zhang, G. Liu, K. Tomsovic, A. Dimitrovski, “The Allocation of Variable Series Reactor Considering AC Constraints and Contingencies,” CSEE Journal of Power and Energy Systems, 2017.
[J8] Z. Yu, D. Shi, Z. Wang, Q. Zhang, J. Huang, and S. Pan, “Distributed Estimation of Oscillations in Power Systems: an Extended Kalman Filtering Approach,” CSEE Journal of Power and Energy Systems, 2017.
[J7] X. Wang, D. Shi, Z. Wang, et al., “Online Calibration of Phasor Measurement Unit Using Density-based Spatial Clustering,” IEEE Trans. Power Delivery, 2017.
[J6] G. Liu, D. Shi, W. Zhu, X. Chen, and J. Chen, “Clouds and Fog Computation Based Optimal Control and Software-defined Application Techniques,” Power Information and Communication Technology, vol. 14, no. 3, 2016.
[J5] H. Zhou, X. Zhao, D. Shi, H. Zhao, and C. Jing, “Transmission Line Sequence Impedances Identification Using PMU Measurements,” Journal of Energy and Power Engineering, no. 9, pp. 214-221, 2015.
[J4] D. Shawhan, J. Taber, D. Shi, R. Zimmerman, et al., “Does a Detailed Model of the Electricity Grid Matter? Estimating the Impacts of the Regional Greenhouse Gas Initiative,” Resource and Energy Economics, vol. 36, no. 1, pp. 191-207, Jan. 2014.
[J3] D. Shi, and D. J. Tylavsky, “A Novel Bus-Aggregation-Based Structure-Preserving Network Equivalent Method,” IEEE Trans. Power Syst., Oct. 2014.
[J2] D. Shi, D. J. Tylavsky and N. Logic, “An Adaptive Method for Detection and Correction of Errors in PMU Measurements,” IEEE Trans. on Smart Grid, vol. 3, no. 4, Dec. 2012.
[J1] D. Shi, D. J. Tylavsky, K. M. Koellner, N. Logic and D. E. Wheeler, “Transmission Line Parameter Identification using PMU Measurements,” Euro. Trans. Electr. Power, vol. 21, no. 4, pp. 1574-1588, Nov. 2010.
[Conference Papers]
[C89] J. Ansu, F. Wang, and D. Shi, “Analysis of Unit Commitment Considering Demand Response and Synthetic Inertia in Electricity Markets,” The 56th North American Power Symposium (NAPS), 2024.
[C88] D. Shi, Q. Zhang, M. Hong, F. Wang, S. Maslennikov, X. Luo, and Y. Chen, “Implementing Deep Reinforcement Learning-Based Grid Voltage Control in Real-World Power Systems: Challenges and Insights,” 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT - Europe), 2024.
[C87] L. Zhou, Y. Zhou, Z. Yi, D. Shi, and Z. Huang, “Optimizing Grid Services: A Deep Deterministic Policy Gradient Approach for Demand-Side Resource Aggregation,” 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT - Europe), 2024.
[C86] Y. Zhang, J. Zhao, D. Shi, and S. Chung, “Deep Reinforcement Learning-Enabled Adaptive Forecasting-Aided State Estimation in Distribution Systems with Multi-source Multi-rate Data,” IEEE PES Innovative Smart Grid Technologies Conference (ISGT), 2024.
[C85] M. Arif, F. Wang, D. Shi, L. Sun, and Z. Wang, “Analysis of the Impacts of Reserve Requirements on Marginal Emission Rate,” IEEE PES Innovative Smart Grid Technologies (ISGT) North America, 2024.
[C84] H. Davoudi, F. Wang, A. Xavier, F. Qiu, and D. Shi, “Market Pricing and Settlements Analysis Considering Capacity Sharing and Reserve Substitutions of Operating Reserve Products,” North American Power Symposium, 2023.
[C83] X. Wang, D. Shi, G. Xu, and F. Wang, “Edge-Computing Based Dynamic Anomaly Detection for Transmission Lines,” 2023 IEEE PES Innovative Smart Grid Technologies Conference, Jan. 2023
[C82] H. Davoudi, F. Wang, A. Xavier, F. Qiu, and D. Shi, “Market Pricing and Settlements Analysis Considering Capacity Sharing and Reserve Substitutions of Operating Reserve Products,” North American Power Symposium (NAPS), 2023.
[C81] Y. Zhou, L. Zhou, D. Shi, X. Zhao, “Coordinated Frequency Control through Safe Reinforcement Learning,” IEEE PES General Meeting, 2022.
[C80] H. Li, Y. Xiang, T. Jin, S. Wang, Z. Yi, and D. Shi, “A DRL-Based Approach for System Frequency Response Model Calibration,” 52nd North American Power Symposium (NAPS), 2021.
[C79] Z. Liang, D. Bian, C. Xu, X. Zhang, D. Shi, and Z. Wang, “Deep Reinforcement Learning based Energy Management Strategy for Commercial Building Considering Comprehensive Comfort Levels,” 52nd North American Power Symposium (NAPS), 2021.
[C78] R. Diao, D. Shi, B. Zhang, S. Wang, H. Li, C. Xu, et al., “On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control,” NeurIPS 2020.
[C77] X. Zhou, S. Wang, R. Diao, D. Bian, J. Duan, D. Shi, et al., “Rethink AI-based Power Grid Control: Diving Into Algorithm Design,” NeurIPS 2020.
[C76] Z. Wang, X. Lu, R. Diao, H. Li, C. Xu, J. Duan, N. Zhang, and D. Shi, “Deep-Reinforcement-Learning-Based Autonomous Control and Decision Making for Power Systems,” Electric Power Engineering Technology, vol. 39, no. 6, Nov. 2020. (In Chinese)
[C75] X. Wang, Y. Wang, D. Shi, J. Wang, S.Wang, R. Diao and Z. Wang, “Evaluating Load Models and Their Impacts on Power Transfer Limits,” IEEE ICCA, Oct. 2020.
[C74] Z. Liang, D. Bian, C. Xu, X. Zhang, D. Shi, and Z. Wang, “Deep Reinforcement Learning based Energy Management Strategy for Commercial Buildings Considering Comprehensive Comfort Levels,” North American Power Symposium, Tempe, AZ, USA, 2020.
[C73] T. Xia, Z. Yu, K. Sun, D. Shi and Z. Wang, “Extended Prony Analysis on Power System Oscillation Under a Near-Resonance Condition,” IEEE PES General Meeting, Montreal, Canada, 2020. [Best Paper]
[C72] Z. Yu, D. Shi, J. Li, Y. Wang, X. Zhao, Z. Wang and J. Li, “Using Transfer Learning to Distinguish between Natural and Forced Oscillations,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C71] Z. Xu, Y. Zan, C. Xu, J. Li, D. Shi, Z. Wang, B. Zhang and J. Duan, “Accelerated DRL Agent for Autonomous Voltage Control Using Asynchronous Advantage Actor-critic,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C70] Y. Lin, X. Zhang, S. Yin, J. Wang and D. Shi, “Real-Time Economic Dispatch for Integrated Energy Microgrid Considering Ancillary Services,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C69] G. Tian, Y. Gu, X. Lu, D. Shi, Q. Zhou, Z. Wang and J. Li, “Estimation Matrix Calibration of PMU Data-driven State Estimation Using Neural Network,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C68] B. Zhang, X. Lu, R. Diao, H. Li, T. Lan, D. Shi and Z. Wang, “Real-time Autonomous Line Flow Control Using Proximal Policy Optimization,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C67] S. Wang, R. Diao, T. Lan, Z. Wang, D. Shi, H. Li and X. Lu, “A DRL-Aided Multi-Layer Stability Model Calibration Platform Considering Multiple Events,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C66] T. Lan, J. Duan, B. Zhang, D. Shi, Z. Wang, R. Diao and X. Zhang, “AI-Based Autonomous Line Flow Control via Topology Adjustment for Maximizing Time-Series ATCs,” IEEE PES General Meeting, Montreal, Canada, 2020.
[C65] MD Kamruzzaman, X. Zhang, M. Abdelmalak, M. Benidris and D. Shi, “A Method to Evaluate the Maximum Hosting Capacity of Power Systems to Electric Vehicles,” IEEE PMAPS, 2020.
[C64] H. Li, Y. Xiang, T. Jin, S. Wang, Z. Yi and D. Shi, “A DRL-Based Approach for System Frequency Response Model Calibration,” North American Power Symposium, Tempe, AZ, USA, 2020.
[C63] J. Duan, H. Li, X. Zhang, R. Diao, B. Zhang, D. Shi, X. Lu, Z. Wang, and S. Wang, “A Deep Reinforcement Learning Based Approach for Optimal Active Power Dispatch,” IEEE Sustainable Power and Energy Conference, Beijing, 2019.
[C62] X. Zhang, D. Bian, D. Shi, Z. Wang, and G. Liu., “Community Microgrid Planning Considering Building Thermal Dynamics”, IEEE Sustainable Power and Energy Conference, 2019. [Best Paper]
[C61] S. Wang, X. Zhao, F. Xue, W. Li, H. Peng, D. Shi, S. Wang, and Z. Wang, “Electromechanical Transient Modeling of Modular Multilevel Converter based HVDC Network,” IEEE Sustainable Power and Energy Conference, Beijing, 2019. [Best Paper]
[C60] X. Gao, G. Li, X. Zhang, D. Shi, X. Wang, and Z. Bie, “An Iteration Method for Optimal Energy Flow of Combined Heating and Electricity System,” IEEE International Conference on Energy Internet, 2019.
[C59] Q. Qiu, G. Li, X. Zhang, D. Shi, T. Gao, and Z. Bie, “Analysis of Heating and Electrical Loads Based on Auto-encoder for Integrated Park,” IEEE International Conference on Advanced Power System Automation and Protection, Xi’an, China, 2019.
[C58] X. Deng, D. Bian, D. Shi, W. Yao, Z. Jiang, and Y. Liu, “Line Outage Detection and Localization via Synchrophasor Measurement,” IEEE PES Innovative Smart Grid Technologies (ISGT) Asia, Chengdu, China, 2019.
[C57] Q. Chang, Y. Wang, X. Lu, D. Shi, H. Li, J. Duan, and Z. Wang, “Probabilistic Load Forecasting via Point Forecast Feature Integration,” IEEE PES Innovative Smart Grid Technologies (ISGT) Asia, Chengdu, China, 2019.
[C56] Y. Peng, Y. Wang, X. Lu, H. Li, D. Shi, Z. Wang, and J. Li, “Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis,” IEEE PES Innovative Smart Grid Technologies (ISGT) Asia, Chengdu, China, 2019.
[C55] K. Li, L. Chen, Z. Yu, Y. Wang, D. Shi, “Improvement of Electromechanical Mode Identification from Ambient Data with Stochastic Subspace Method,” IEEE PES APPEEC, 2019. [Best Paper]
[C54] Z. Nie, X. Zhang, X. Zhao, Y. Xu, D. Shi, J. Duan, Z. Wang , “Adaptive Online Learning with Momentum for Contingency-based Voltage Stability Assessment,” IEEE PES General Meeting, 2019.
[C53] R. Diao, Z. Wang, D. Shi, Q. Chang, J. Duan, X. Zhang, “Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning,” IEEE PES General Meeting, 2019. [Best Paper]
[C52] Y. Wang, X. Lu, Y. Xu, D. Shi, Z. Yi, J. Duan, Z. Wang, “Submodular Load Clustering with Robust Principal Component Analysis,” IEEE PES General Meeting, 2019.
[C51] X. Wang, Y. Wang, D. Shi, J. Wang, “A Deep Stacked Autoencoder Application for Residential Load Curve Forecast and Peak Shaving,” IEEE PES General Meeting, 2019.
[C50] Y. Xiang, X. Lu, Z. Yu, D. Shi, H. Li, Z. Wang, “IoT and Edge Computing Based Direct Load Control for Fast Adaptive Frequency Regulation”, 2019 IEEE PES General Meeting, 2019.
[C49] Chang Fu, Zhe Yu, D. Shi, Haifeng Li, Caisheng Wang, and Zhiwei Wang, “Bayesian Estimation Based Parameter Estimation for Composite Load,” IEEE PES General Meeting, 2019.
[C48] Z. Liang, D. Bian, D. Su, R. Diao, D. Shi, Z. Wang, W. Su, “Adaptive Robust Energy Management Strategy for Campus-Based Commercial Buildings Considering Comprehensive Comfort Levels,” 2019 IEEE PES General Meeting, 2019.
[C47] X. Deng, D. Shi, D. Bian, W. Yao, L. Wu, Y. Liu, “Impact of Low Data Quality on Disturbance Triangulation Application using High-Density PMU Measurements,” IEEE PES ISGT Asia, 2019.
[C46] Y. Peng, Y. Wang, X. Lu, H. Li, D. Shi, Z. Wang, J. Li, “Short-term Load Forecasting at Different Aggregation Levels,” IEEE PES ISGT Asia, 2019.
[C45] J. Duan, Z. Yi, D. Shi, H. Xu, and Z. Wang, “A Neural-Network-Based Optimal Control of Ultra-Capacitors with System Uncertainties,” 2019 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington, DC, USA, 2019.
[C44] Y. Cui, Z. Yi, J. Duan, D. Shi, and Z. Wang, “A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation,” 2019 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington, DC, USA, 2019.
[C43] Z. Yu, D. Shi, H. Li, Y. Wang, Z. Yi, Z. Wang, “An Extended Kalman Filter Enhanced Hilbert-Huang Transform in Oscillation Detection,” ISGT Europe 2018, Sarajevo, Bosnia and Herzegovina, Oct. 2018.
[C42] A. Babqi, Z. Yi, D. Shi, and X. Zhao, “Model Predictive Control of H5 Inverter for Transformerless PV Systems with Maximum Power Point Tracking and Leakage Current Reduction”, 44th Annual Conference of the IEEE Industrial Electronics Society (IECON 2018), 2018.
[C41] Y. Meng, Z. Yu, D. Shi, et al., “Forced Oscillation Source Location via Multivariate Time Series Classification,” IEEE PES Transmission and Distribution (T&D) Conference and Exposition, 2018.
[C40] Y. Wang, Z. Yi, D. Shi, Z. Yu, D. Bian, and Z. Wang, “Optimal Distributed Energy Resources Sizing for Commercial Building Hybrid Microgrids,” 2018 IEEE PES General Meeting, 2018.
[C39] X. Wang, J. Wang, D. Shi, M. Khodayar, “A Factorial Hidden Markov Model for Energy Disaggregation Based on Human Behavior Analysis,” 2018 IEEE PES General Meeting, 2018.
[C38] Z. Yi, A. Babqi, Y. Wang, D. Shi, A. H. Etemadi, Z. Wang, and Bibin Huang, “Finite-Control-Set Model Predictive Control for Hybrid Microgrids,” 2018 IEEE PES General Meeting, 2018.
[C37] Y. Xiang, X. Zhang, D. Shi, Y. Jin, Z. Wang and L. Wang, “A Robust Power Grid Defense Model Considering Load Demand and Wind Generation Uncertainties,” 2018 IEEE PES General Meeting, 2018.
[C36] X. Zhang, D. Shi, X. Lu, Z. Yi, Q. Zhang, and Z. Wang, “Sensitivity Based Thevenin Index for Voltage Stability Assessment Considering N-1 Contingency,” 2018 IEEE PES General Meeting, 2018.
[C35] S. Rao, D. Tylavsky, W. Yi, V. Vittal, D. Shi, and Z. Wang, “Fast Weak-bus and Bifurcation Point Determination Using Holomorphic Embedding Method,” 2018 IEEE PES General Meeting, 2018.
[C34] M. Liao, D. Shi, Z. Yu, W. Zhu, Z. Wang, Y. Xiang, “Recover the lost Phasor Measurement Unit Data using Alternating Direction Multipliers Method,” 2018 IEEE PES Transmission & Distribution Conference and Exposition, Denver, CO, 2018.
[C33] Y. Meng, Z. Yu, D. Shi, D. Bian, and Z. Wang, “Forced Oscillation Source Location via Multivariate Time Series Classification,” 2018 IEEE PES Transmission & Distribution Conference and Exposition, Denver, CO, 2018.
[C32] X. Zhang, D. Shi, Z. Wang, Z. Yu, X. Wang, D. Bian, and K. Tomsovic, “Bilevel Optimization Based Transmission Expansion Planning Considering Phase Shifting Transformer,” 2017 North American Power Symposium, Morgantown, WV, 2017.
[C31] G. Liu, K. Liu, D. Shi, W. Zhu, Z. Wang, and X. Chen, “Graph Computation and Its Applications in Smart Grid,” 2017 International Congress on Big Data, Honolulu, HI, 2017.
[C30] X. Lu, D. Shi, B. Zhu, et al., “PMU Assisted Power System Parameter Calibration at Jiangsu Electric Power Company,” 2017 IEEE PES General Meeting, Chicago, 2017. [Best Paper]
[C29] L. Yu, D. Shi, X. Guo, et al., “GIS-based Optimal Siting and Sizing of Substation Using Semi-Supervised Learning,” IEEE Green Energy and Smart Systems Conference, Long Beach, CA, 2017.
[C28] L. Zhao, D. Shi, C. Wang, et al., “A Distributed Control Framework for Microgrid with Renewables and Energy Storage Systems,” IEEE Green Energy and Smart Systems Conference, Long Beach, CA, 2017.
[C27] C. Wang, L. Zhao, D. Shi, C. Hong, et al., “Modeling and Control of Energy Storage System in a Microgrid using Electromagnetic Simulation Program (ESP),” IEEE Green Energy and Systems Conference, 2016.
[C26] X. Zhang, D. Shi, Z. Wang, et al., “Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming,” 2017 IEEE PES General Meeting, 2017.
[C25] D. Shi, J. Luo, W. Zhu, X. Chen, and G. Xu, “Distributed Control for Microgrid with Renewables and Energy Storage Systems,” 2016 International Conference on Global Energy Interconnection, Beijing, 2016.
[C24] G. Liu, K. Liu, D. Shi, W. Zhu, X. Chen, X. Chang, and Y. Xu, “Graph Computation and its Applications in Global Energy Interconnection,” 2016 International Conference on Global Energy Interconnection, Beijing, 2016.
[C23] F. Gao, G. Liu, C. Saunders, D. Shi and W. Zhu, “Energy Disaggregation Based on Mixed Integer Programming and Collocation Method,” IEEE PES General Meeting, 2016.
[C22] B. Ansari, D. Shi, R. Sharma, and M. G. Simoes, “Economic Analysis, Optimal Sizing and Management of Energy Storage for PV Grid Integration,” IEEE PES T&D Conference & Exposition, 2016.
[C21] B. Asghari, R. Patil, D. Shi, and R. Sharma, “A Mixed-mode Energy Management System for Grid Scale Energy Storage Units,” IEEE International Conference on Smart Grid Communications, Miami, FL, 2015.
[C20] Y. Zhu, R. Azim, H. A. Saleem, K. Sun, D. Shi, and R. Sharma, “Microgrid Security Assessment and Islanding Control by Support Vector Machine,” IEEE PES General Meeting, Denver, 2015.
[C19] R. Azim, Y. Zhu, H. A. Saleem, K. Sun, F. Li, D. Shi and R. Sharma, “A Decision Tree Based Approach for Microgrid Islanding Detection,” IEEE Innovative Smart Grid Technologies, Washington, D.C., 2015.
[C18] H. Zhou, X. Zhao, D. Shi, H. Zhao, C. Jing, “Calculating Sequence Impedances of Transmission Line Using PMU Measurements,” IEEE PES General Meeting, Denver, 2015.
[C17] R. Azim, K. Sun, F. Li, Y. Zhu, H. Saleem, D. Shi, and R. Sharma, “A Comparative Analysis of Intelligent Classifiers for Passive Islanding Detection in Microgrids,” Powertech Eindhoven 2015, June 2015.
[C16] D. Shawhan, J. Taber, R. Zimmerman, J. Yan, C. Marquet, W. Schulze, R. Schuler, R. Thomas, D. Tylavsky, D. Shi, N. Li, W. Jewell, T. Hardy, and Z. Hu, “A Detailed Power System Planning Model: Estimating the Long-Run Impact of Carbon-Reducing Policies,” 48th Hawaii International Conference on System Sciences (HICSS), 2015.
[C15] J. Wang, Y. Su, J. Li, C. Jing, D. Shi, and J. Liu, “Online Probabilistic Security Risk Assessment Implementation at China Southern Power Grid Towards Smart Control Center,” IEEE GreenTech, New Orleans, 2015.
[C14] D. Shi, Y. Luo and R. Sharma, “Active Synchronization Control for Microgrid Reconnection after Islanding,” IEEE PES Innovative Smart Grid Technologies (ISGT) Europe, 2014.
[C13] D. He, D. Shi and R. Sharma, “Consensus-based Distributed Cooperative Control for Microgrid Voltage Regulation and Reactive Power Sharing,” IEEE PES Innovative Smart Grid Technologies Europe, 2014.
[C12] J. Zhao, D. Shi and R. Sharma, “Microgrid Reactive Power Management During and Subsequent to Islanding Process,” IEEE PES Transmission and Distribution (T&D) Conf. and Expo., Chicago, Apr. 14-17, 2014.
[C11] R. Patil, A. Keeli, D. Shi and R. Sharma, “Zone Based Control of Building A/C Systems through Temperature Monitoring and Control,” ASME 2014 Power Conference, Baltimore, Maryland, 2014.
[C10] J. Wang, Y. Su, J. Li, C. Jing, and D. Shi, “Real Time Probabilistic Security Risk Assessment at an EMS,” IEEE PES Transmission and Distribution (T&D) Conference and Exposition, Apr. 14-17, 2014.
[C9] D. Shi, R. Sharma, and Y. Ye, “Adaptive Control of Distributed Generation for Microgrid Islanding,” IEEE Innovative Smart Grid Technologies (ISGT) Europe, Lyngby, Denmark, 2013.
[C8] D. Shi, and R. Sharma, “Adaptive Control of Energy Storage for Voltage Regulation in Distribution System,” IEEE International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, Canada, 2013.
[C7] D. Shi, D. Tylavsky, and N. Logic, “An Adaptive Method for Detection and Correction of Errors in PMU Measurements,” IEEE PES General Meeting, Vancouver, Canada, 2013.
[C6] Y. Ye, R. Sharma, and D. Shi, “Adaptive Control of Hybrid Ultracapacitor-battery Storage System for PV Output Smoothing,” Proceedings of the ASME 2013 Power Conference, Boston, Massachusetts, 2013.
[C5] D. Shi, D. L. Shawhan, N. Li, D. J. Tylavsky, J. Taber, and R. D. Zimmerman, “Optimal Generation Investment Planning: Pt. 1: Network Equivalents,” 44th North American Power Symposium, 2012.
[C4] N. Li, D. Shi, D. L. Shawhan, D. J. Tylavsky, J. Taber, and R. D. Zimmerman, “Optimal Generation Investment Planning: Pt. 2: Application to the ERCOT System,” 44th North American Power Symposium, 2012.
[C3] Y. Qi, D. Shi, and D. J. Tylavsky, “Impact of Assumptions on DC Power Flow Model Accuracy,” 44th North American Symposium, 2012.
[C2] D. Shi and D. J. Tylavsky, “An Improved Bus Aggregation Technique for Generating Network Equivalents,” IEEE PES General Meeting, San Diego, USA, 2012.
[C1] D. Shi, D. J. Tylavsky, N. Logic, and K. M. Koellner, “Identification of Short Transmission Line Impedance Parameters using Synchrophasor Measurements,” 40th North American Power Symposium, Nov. 2008.
