Van-Hai Bui
Orcid: 0009-0002-4565-4780
According to our database1,
Van-Hai Bui
authored at least 33 papers
between 2016 and 2025.
Collaborative distances:
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Bibliography
2025
CoRR, July, 2025
ANN-Based Grid Impedance Estimation for Adaptive Gain Scheduling in VSG Under Dynamic Grid Conditions.
CoRR, June, 2025
FairMarket-RL: LLM-Guided Fairness Shaping for Multi-Agent Reinforcement Learning in Peer-to-Peer Markets.
CoRR, June, 2025
Optimal Parameter Design for Power Electronic Converters Using a Probabilistic Learning-Based Stochastic Surrogate Model.
CoRR, June, 2025
Enhancing Forecasting Accuracy in Dynamic Environments via PELT-Driven Drift Detection and Model Adaptation.
CoRR, June, 2025
CoRR, February, 2025
Deep Reinforcement Learning-Based Optimization of Second-Life Battery Utilization in Electric Vehicles Charging Stations.
CoRR, February, 2025
CoRR, January, 2025
A critical review of safe reinforcement learning strategies in power and energy systems.
Eng. Appl. Artif. Intell., 2025
2024
Reinforcement Learning-Based Integrated Control to Improve the Efficiency of DC Microgrids.
IEEE Trans. Smart Grid, January, 2024
A Critical Review of Safe Reinforcement Learning Techniques in Smart Grid Applications.
CoRR, 2024
Optimizing the Transaction Latency in the Blockchain-Integrated Energy-Trading Platform in the Standalone Renewable Distributed Generation Arena.
IEEE Access, 2024
Proceedings of the 18th IEEE International Conference on Control & Automation, 2024
2023
Emerging 6G/B6G Wireless Communication for the Power Infrastructure in Smart Cities: Innovations, Challenges, and Future Perspectives.
Algorithms, 2023
IEEE Access, 2023
Proceedings of the International Conference on Computing, Networking and Communications, 2023
2022
A Dynamic Internal Trading Price Strategy for Networked Microgrids: A Deep Reinforcement Learning-Based Game-Theoretic Approach.
IEEE Trans. Smart Grid, 2022
Optimal Design Parameters for Hybrid DC Circuit Breakers Using a Multi-Objective Genetic Algorithm.
Algorithms, 2022
Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning.
IEEE Access, 2022
2020
Double Deep Q-Learning-Based Distributed Operation of Battery Energy Storage System Considering Uncertainties.
IEEE Trans. Smart Grid, 2020
An Effort-Based Reward Approach for Allocating Load Shedding Amount in Networked Microgrids Using Multiagent System.
IEEE Trans. Ind. Informatics, 2020
Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach.
IEEE Access, 2020
Consensus Algorithm-Based Distributed Operation of Microgrids During Grid-Connected and Islanded Modes.
IEEE Access, 2020
2019
IEEE Trans. Smart Grid, 2019
Optimal Operation of Wind Farm for Reducing Power Deviation Considering Grid-Code Constraints and Events.
IEEE Access, 2019
2018
A Resilient and Privacy-Preserving Energy Management Strategy for Networked Microgrids.
IEEE Trans. Smart Grid, 2018
A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response.
IEEE Trans. Smart Grid, 2018
A Proactive and Survivability-Constrained Operation Strategy for Enhancing Resilience of Microgrids Using Energy Storage System.
IEEE Access, 2018
Robust Optimal Operation of AC/DC Hybrid Microgrids Under Market Price Uncertainties.
IEEE Access, 2018
Proceedings of the TENCON 2018, 2018
Diffusion Strategy-Based Distributed Optimization for Operation of Multi-Microgrid System.
Proceedings of the TENCON 2018, 2018
2016
Impact Quantification of Demand Response Uncertainty on Unit Commitment of Microgrids.
Proceedings of the International Conference on Frontiers of Information Technology, 2016