[J46] Zuzhao Ye, Yuanqi Gao, and Nanpeng Yu, "Learning to Operate an Electric Vehicle Charging Station Considering Vehicle-grid Integration," under review, https://arxiv.org/abs/2111.01294 , 2021.
[J45] Md. Zahidul Islam, Yuzhang Lin, Vinod. M. Vokkarane, and Nanpeng Yu, "Robust Real-Time Load Estimation Using Sparsely Selected Smart Meters with High Reporting Rates," under review, 2021.
[J44] Yuanqi Gao, Xian Wang, Nanpeng Yu, and Bryan Wong, "Harnessing Deep Reinforcement Learning to Discover Time-Dependent Optimal Fields for Quantum Control Dynamics," under preparation, 2021.
[J43] Yuanbin Cheng, Nanpeng Yu, Brandon Foggo, and Koji Yamashita, "Online Power System Event Detection via Bidirectional Generative Adversarial Networks," under review, 2021.
[J42] Ali Jahanshahi, Daniel Wong, and Nanpeng Yu, "PowerMorph: QoS-aware Server Power Reshaping for Data Center Regulation Service," under review, 2021.
[J41] Yuanqi Gao and Nanpeng Yu, "Model-Augmented Safe Reinforcement Learning for Volt-VAR Control in Power Distribution Networks," under review, 2021.
[J37] Mohammad Ostadijafari, Juan Carlos Bedoya, Wei Wang, Anamika Dubey, Chen-Ching Liu, and Nanpeng Yu, "Economical and Engineering Aspects of Proactive Demand-side Participation: Centralized versus Bilateral Control Structure," under review, 2020.
[J36] Wenyu Wang and Nanpeng Yu, "Estimate Three-phase Distribution Line Parameters with Physics-informed Graphical Learning Method," under review, http://arxiv.org/abs/2102.09023, 2021.
[J35] Xianghao Kong, Brandon Foggo, Koji Yamashita, and Nanpeng Yu, "Power System Event Detection Using Optimiztion with Structured Sparsity-Inducing Norms," under reivew, 2021.
[J33] Yinglun Li, Nanpeng Yu, and Wei Wang, "Machine Learning-Driven Virtual Bidding with Electricity Market Efficiency Analsysis," to appear in IEEE Transactions on Power Systems, https://arxiv.org/abs/2104.02754, 2021.
[J32] Jie Shi, Brandon Foggo, and Nanpeng Yu, "Power System Event Identification based on Deep Neural Network with Information Loading," IEEE Transactions on Power Systems, vol. 36, no. 6, pp. 5622-5632, https://arxiv.org/abs/2011.06718, Nov. 2021.
[J31] Yuanqi Gao, Wei Wang, and Nanpeng Yu, "Consensus Multi-agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks," IEEE Transactions on Smart Grid, vol. 12, no. 4, pp. 3594-3604, July, 2021. https://arxiv.org/abs/2007.02991, Digital Object Identifier: 10.1109/TSG.2021.3058996.
[J17] Ke Wang, Haiwang Zhong, Nanpeng Yu, and Qing Xia, "Nonintrusive Load Monitoring based on Sequence-to-Sequence Model and Attention Mechanism," Proceedigns of the CSEE, vol. 39, no. 1, pp. 75-83, 2018.
[J2] Liu Yingshang, Wu Wenchuan, Feng Yongqing, Zhang Boming, and Nanpeng Yu, "Black-start Zone Partitioning Based on Ordered Binary Decision Diagram Method," Proceedings of the CSEE, Vol. 28, No. 10, pp. 26-31, 2008.
[C53] Xianghao Kong, Koji Yamashita, Brandon Foggo, and Nanepng Yu, "Dynamic Parameter Estimation with Physics-based Neural Ordinary Differential Equations" under review.
[C52] Wenyu Wang, Nanpeng Yu, Farnoosh Rahmatian, and Shikhar Pandey, "Where to Install Distribution Phasor Measurement Units to Obtain Accurate State Estimation Results?" under review, 2021.
[C51] Yuanqi and Nanpeng Yu, "A Reinforcement Learning-based Volt-VAR Control Dataset and Testing Environment," under review, 2021.
[C50] Brandon Foggo and Nanpeng Yu, "On the Maximum Mutual Information Capacity of Neural Architectures," under review, https://arxiv.org/abs/2006.06037, 2022.
[C49] Jie Shi, Koji Yamashita, and Nanpeng Yu, "Power System Event Identification with Transfer Learning Using Large-scale Real-world Synchrophasor Data in the United States," to appear in IEEE ISGT North America 2022.
[C48] Brandon Foggo and Nanpeng Yu, "Analyzing Data Selection Techniques with Tools from the Theory of Information Losses," under review, https://arxiv.org/abs/1902.09602, to appear in IEEE International Conference on Big Data, 2021. (19.9% regular paper acceptance rate).
[C47] Jingtao Qin, Nanpeng Yu, and Yuanqi Gao, "Solving Unit Commitment Problems with Deep Reinforcement Learning," in 2021 IEEE SmartGridComm.
[C46] Zuzhao Ye, Ran Wei, and Nanpeng Yu, "Short-term Forecasting for Utilization Rates of Electric Vehile Charging Stations," in 7th IEEE International Smart Cities Conference, 2021.
[C45] Yinglun Li and Nanpeng Yu, "Learning to Arbitrage Congestion in Electricity Market with Virtual Bids," 2021 IEEE ISGT Europe.
[C29] Mohammad Ostadijafari, Anamika Dubey, Yang Liu, Jie Shi, and Nanpeng Yu, "Smart Building Energy Management Using Nonlinear Economic Model Predictive Control," IEEE Power and Energy Society General Meeting, pp. 1-5, 2019.
[C9] Xiaoyang Zhou, Nanpeng Yu, Weixin Yao and Raymond Johnson, "Forecast Load Impact from Demand Response Resources," IEEE Proceedings, Power and Energy Society General Meeting, pp. 1-5, Boston, USA, 2016. Nominated for Best Paper Award in Electric vehicles, energy storage, microgrids, and demand response operations and market economics.
[C6] Nanpeng Yu, Hongyan Sheng, and Raymond Johnson, "Economic Valuation of Wind Curtailment Rights," IEEE Proceedings, Power and Energy Society General Meeting, Vancouver, British Columbia, Canada, July 2013. Nominated for Best Paper Award in system operations and market economics.
[B2] Ke Wang, Haiwang Zhong, Nanpeng Yu, and Qing Xia, " Nonintrusive Load Monitoring based on Deep Learning," In: Woon W., Aung Z., Catalina Feliú A., Madnick S. (eds) Data Analytics for Renewable Energy Integration. Technologies, Systems and Society. DARE 2018. Lecture Notes in Computer Science, vol 11325. Springer, Cham
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