Παρακολούθηση
Haotian Liu
Haotian Liu
Ph.D. Candidate, Tsinghua University
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα mails.tsinghua.edu.cn - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Online multi-agent reinforcement learning for decentralized inverter-based volt-var control
H Liu, W Wu
IEEE Transactions on Smart Grid 12 (4), 2980-2990, 2021
1322021
Two-stage deep reinforcement learning for inverter-based volt-var control in active distribution networks
H Liu, W Wu
IEEE Transactions on Smart Grid 12 (3), 2037-2047, 2020
1322020
Federated reinforcement learning for decentralized voltage control in distribution networks
H Liu, W Wu
IEEE Transactions on Smart Grid 13 (5), 3840-3843, 2022
642022
Bi-level off-policy reinforcement learning for two-timescale Volt/VAR control in active distribution networks
H Liu, W Wu, Y Wang
IEEE Transactions on Power Systems 38 (1), 385-395, 2022
372022
Exploiting the flexibility inside park-level commercial buildings considering heat transfer time delay: A memory-augmented deep reinforcement learning approach
H Zhao, B Wang, H Liu, H Sun, Z Pan, Q Guo
IEEE Transactions on Sustainable Energy 13 (1), 207-219, 2021
282021
Model-free voltage control for inverter-based energy resources: Algorithm, simulation and field test verification
H Liu, W Wu, A Bose
IEEE Transactions on Energy Conversion 36 (2), 1207-1215, 2020
92020
Data-driven wind farm Volt/Var control based on deep reinforcement learning
B Zhang, H Liu, G Zhuang, L Liu, W Wu
2020 IEEE 4th Conference on Energy Internet and Energy System Integration …, 2020
82020
Bi-level off-policy reinforcement learning for volt/var control involving continuous and discrete devices
H Liu, W Wu
arXiv preprint arXiv:2104.05902, 2021
72021
Reinforcement Learning with Enhanced Safety for Optimal Dispatch of Distributed Energy Resources in Active Distribution Networks
X Yang, H Liu, W Wu, Q Wang, P Yu, J Xing, Y Wang
Journal of Modern Power Systems and Clean Energy, 2024
52024
Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control in Active Distribution Networks
Q Liu, Y Guo, L Deng, H Liu, D Li, H Sun, W Huang
IEEE Transactions on Sustainable Energy, 2024
52024
Attention-Enhanced Multi-Agent Reinforcement Learning Against Observation Perturbations for Distributed Volt-VAR Control
X Yang, H Liu, W Wu
IEEE Transactions on Smart Grid, 2024
42024
Reducing learning difficulties: One-step two-critic deep reinforcement learning for inverter-based Volt-Var control
Q Liu, Y Guo, L Deng, H Liu, D Li, H Sun, W Huang
arXiv preprint arXiv:2203.16289, 2022
42022
Coordinated real-time power dispatch for integrated transmission and distribution networks based on model-based optimization and deep reinforcement learning
X Yang, Y Sun, W Wu, H Liu, Y Wang
Energy Reports 9, 1011-1020, 2023
22023
Active and reactive power coordinated control of active distribution networks based on prioritized reinforcement learning
X Wang, H Liu, X Cao, W Wu, S Li, X Jia
2021 Power System and Green Energy Conference (PSGEC), 91-96, 2021
22021
Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Control
Q Liu, Y Guo, L Deng, H Liu, D Li, H Sun
arXiv preprint arXiv:2210.07360, 2022
12022
One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control in Active Distribution Networks.
Q Liu, Y Guo, L Deng, H Liu, D Li, H Sun, W Huang
arXiv preprint arXiv:2203.16289, 2022
12022
A Two-stage Optimal Scheduling Approach for Networked Distributed Energy Resources in Power Distribution Systems
H Liu, C Zheng, Y Leng, Z Lin, J Chen, J Zhang, L Che
EMIE 2022; The 2nd International Conference on Electronic Materials and …, 2022
2022
Direct Thermal Load Control in Active Distribution Networks Based on Deep Reinforcement Learning
Z Chen, H Liu, W Wu, Y Li, J Jing, T Da
2021 IEEE 5th Conference on Energy Internet and Energy System Integration …, 2021
2021
Critical nodes identification based on comprehensive topological importance in complex networks
P Li, L Xie, Y Wu, H Liu, Y Wang, J Zhou, X Wu, L Qiao, Q An, S Yang
Proceedings of the 2021 2nd International Conference on Computing, Networks …, 2021
2021
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