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Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning Journal article
Peipei Yu, Hongcai Zhang, Yonghua Song. Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning[J]. IEEE Transactions on Power Systems, 2024, 39(6), 6819-6832.
Authors:  Peipei Yu;  Hongcai Zhang;  Yonghua Song
Favorite | TC[WOS]:2 TC[Scopus]:5  IF:6.5/7.4 | Submit date：2024/04/24
Tie-line Power Smoothing  Demand Response  Renewable Generation  Risk-aware Reinforcement Learning  
Offline DRL for Price-Based Demand Response: Learning From Suboptimal Data and Beyond Journal article
Tao Qian, Zeyu Liang, Chengcheng Shao, Hongcai Zhang, Qinran Hu, Zaijun Wu. Offline DRL for Price-Based Demand Response: Learning From Suboptimal Data and Beyond[J]. IEEE Transactions on Smart Grid, 2024, 15(5), 4618-4635.
Authors:  Tao Qian;  Zeyu Liang;  Chengcheng Shao;  Hongcai Zhang;  Qinran Hu; et al.
Favorite | TC[WOS]:7 TC[Scopus]:9  IF:8.6/9.6 | Submit date：2024/04/24
Demand Response  Deep Reinforcement Learning  Offline Learning  Suboptimal Data  Uncertainty  
A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning Journal article
Li, Kai, Chen, Hong, Hou, Shengyan, Eriksson, Lars, Zhao, Jing, Ding, Shihong, Gao, Jinwu. A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning[J]. IEEE Transactions on Transportation Electrification, 2024.
Authors:  Li, Kai;  Chen, Hong;  Hou, Shengyan;  Eriksson, Lars;  Zhao, Jing; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.2/7.9 | Submit date：2024/09/03
Energy Management System  Cabin Heat Demand  Hybrid Electric Vehicles (Hevs)  Deep Reinforcement Learning  Real-time  Low Temperature Environment  
Constraint learning-based optimal power dispatch for active distribution networks with extremely imbalanced data Journal article
Yonghua Song, Ge Chen, Hongcai Zhang. Constraint learning-based optimal power dispatch for active distribution networks with extremely imbalanced data[J]. CSEE Journal of Power and Energy Systems, 2024, 10(1), 51-65.
Authors:  Yonghua Song;  Ge Chen;  Hongcai Zhang
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:6.9/6.9 | Submit date：2024/04/24
Deep Learning  Demand Response  Distribution Networks  Imbalanced Data  Optimal Power Flow  
实时电价机制下基于复合两端采样强化学习的区域供冷系统需求响应运行控制 Journal article
宋永華, 餘佩佩, 張洪財. 实时电价机制下基于复合两端采样强化学习的区域供冷系统需求响应运行控制[J]. 中國科學技術科學 SCIENTIA SINICA Technologica, 2023, 53(10), 1699-1712.
Authors:  宋永華;  餘佩佩;  張洪財
Favorite | TC[Scopus]:0 | Submit date：2023/07/12
Compound Secondary Sampling Experience Reply  Demand Response Control  District Cooling System  Ice Storage  Real-time Price  Reinforcement Learning  
Privacy-Preserving Regulation Capacity Evaluation for HVAC Systems in Heterogeneous Buildings based on Federated Learning and Transfer Learning Journal article
Zhenyi Wang, Peipei Yu, Hongcai Zhang. Privacy-Preserving Regulation Capacity Evaluation for HVAC Systems in Heterogeneous Buildings based on Federated Learning and Transfer Learning[J]. IEEE Transactions on Smart Grid, 2023, 14(5), 3535 - 3549.
Authors:  Zhenyi Wang;  Peipei Yu;  Hongcai Zhang
Favorite | TC[WOS]:9 TC[Scopus]:11  IF:8.6/9.6 | Submit date：2023/07/12
Demand Response  Federated Learning  Hvac System  Privacy-preserving  Regulation Capacity  Transfer Learning  
A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method Journal article
Dong, Yunxuan, Zhou, Binggui, Yang, Guanghua, Hou, Fen, Hu, Zheng, Ma, Shaodan. A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method[J]. NEUROCOMPUTING, 2023, 556, 126663.
Authors:  Dong, Yunxuan;  Zhou, Binggui;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:5.5/5.5 | Submit date：2023/08/30
Deep Learning  Feature Enhancement  Spatial Series To Image Series  Spatial–temporal Learning  Tourism Demand Forecasting  
A graph-attention based spatial-temporal learning framework for tourism demand forecasting Journal article
Zhou, Binggui, Dong, Yunxuan, Yang, Guanghua, Hou, Fen, Hu, Zheng, Xu, Suxiu, Ma, Shaodan. A graph-attention based spatial-temporal learning framework for tourism demand forecasting[J]. Knowledge-Based Systems, 2023, 263, 110275.
Authors:  Zhou, Binggui;  Dong, Yunxuan;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:14 TC[Scopus]:12  IF:7.2/7.4 | Submit date：2023/04/03
Tourism Demand Forecasting  Dynamic Spatial Connections  Spatial-temporal Learning  Graph Neural Network  Attention Mechanism  
Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach Journal article
Hongliang Ding, Yuhuan Lu, N. N. Sze, Haojie Li. Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach[J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2022, 166, 150-163.
Authors:  Hongliang Ding;  Yuhuan Lu;  N. N. Sze;  Haojie Li
Favorite | TC[WOS]:9 TC[Scopus]:11  IF:6.3/6.9 | Submit date：2023/01/30
Bicycle Demand  Bike Sharing  Deep Learning  Graph Neural Network  Intervention Response Module  
Frequency Regulation Capacity Offering of District Cooling System: An Intrinsic-motivated Reinforcement Learning Method Journal article
Yu, Peipei, Zhang, Hongcai, Song, Yonghua, Hui, Hongxun, Huang, Chao. Frequency Regulation Capacity Offering of District Cooling System: An Intrinsic-motivated Reinforcement Learning Method[J]. IEEE Transactions on Smart Grid, 2022, 14(4), 2762-2773.
Authors:  Yu, Peipei;  Zhang, Hongcai;  Song, Yonghua;  Hui, Hongxun;  Huang, Chao
Favorite | TC[WOS]:4 TC[Scopus]:4  IF:8.6/9.6 | Submit date：2023/01/30
Demand Response  Capacity Offering  District Cooling System  Reinforcement Learning  Intrinsic-motivation