Yan Du
Cited by
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Intelligent Multi-microgrid Energy Management based on Deep Neural Network and Model-free Reinforcement Learning
Y Du, F Li
IEEE Transactions on Smart Grid, 2019
A cooperative game approach for coordinating multi-microgrid operation within distribution systems
Y Du, W Zhiwei, L Guangyi, X Chen, H Yuan, W Yanli, F Li
Applied Energy 222, 383-395, 2018
Optimal bidding strategy and intramarket mechanism of microgrid aggregator in real-time balancing market
W Pei, Y Du, W Deng, K Sheng, H Xiao, H Qu
IEEE Transactions on Industrial Informatics 12 (2), 587-596, 2016
Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning
Y Du, H Zandi, O Kotevska, K Kurte, J Munk, K Amasyali, E Mckee, F Li
Applied Energy 281, 2020
Temporal-spatial analysis and improvement measures of Chinese power system for wind power curtailment problem
W Pei, Y Chen, K Sheng, W Deng, Y Du, Z Qi, L Kong
Renewable and Sustainable Energy Reviews 49, 148-168, 2015
From AlphaGo to Power System AI: What Engineers Can Learn from Solving the Most Complex Board Game
F Li, Y Du
IEEE Power and Energy Magazine 16 (2), 76-84, 2018
Achieving 100x Acceleration for N-1 Contingency Screening with Uncertain Scenarios using Deep Convolutional Neural Network
Y Du, F Li, J Li, T Zheng
IEEE Transactions on Power Systems, 2019
A Hierarchical Real-time Balancing Market Considering Multi-microgrids with Distributed Sustainable Resources
Y Du, F Li
IEEE Transactions on Sustainable Energy, 2018
Real-time microgrid economic dispatch based on model predictive control strategy
D Yan, P Wei, N Chen, X Ge, X Hao
Journal of Modern Power Systems and Clean Energy, 2017
Emerging smart grid technology for mitigating global warming
X Zhang, W Pei, W Deng, Y Du, Z Qi, Z Dong
International Journal of Energy Research 39 (13), 1742-1756, 2015
Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control
Y Du, F Li, J Munk, K Kurte, O Kotevska, K Amasyali, H Zandi
Electric Power Systems Research 192, 106959, 2021
Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning
Y Du, F Li, H Zandi, Y Xue
Journal of Modern Power Systems and Clean Energy, 2021
Novel solution and key technology of interconnection and interaction for large scale microgrid cluster integration
PEI Wei, DU Yan, LI Hongtao, Y Yanhong, D Wei
High Voltage Engineering 41 (10), 3193-3203, 2015
Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response
X Kou, Y Du, F Li, H Pulgar-Painemal, H Zandi, J Dong, MM Olama
IEEE Open Access Journal of Power and Energy, 2021
Evaluating the adaptability of reinforcement learning based HVAC control for residential houses
K Kurte, J Munk, O Kotevska, K Amasyali, R Smith, E McKee, Y Du, B Cui, ...
Sustainability 12 (18), 7727, 2020
Fast Cascading Outage Screening based on Deep Convolutional Neural Network and Depth-First Search
Y Du, F Li, T Zheng, J Li
IEEE Transactions on Power Systems, 2020
Coordinating Multi-microgrid Operation within Distribution System: A Cooperative Game Approach
Y Du, F Li, X Kou, W Pei
Power & Energy Society General Meeting, 2017 IEEE, 1-5, 2018
Deep Reinforcement Learning from Demonstrations to Assist Service Restoration in Islanded Microgrids
Y Du, D Wu
IEEE Transactions on Sustainable Energy, 2022
Optimal operation of microgrid with photovoltaics and gas turbines in demand response
W Pei, Y Du, H Xiao, Z Shen, W Deng, Y Yang
2014 International Conference on Power System Technology, 3058-3063, 2014
Learning and fast adaptation for grid emergency control via deep meta reinforcement learning
R Huang, Y Chen, T Yin, Q Huang, J Tan, W Yu, X Li, A Li, Y Du
IEEE Transactions on Power Systems, 2022
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