Application and progress of artificial intelligence technology in the field of distribution network voltage Control: A review

X Zhang, Z Wu, Q Sun, W Gu, S Zheng… - … and Sustainable Energy …, 2024 - Elsevier
The increasing integration of distributed energy resources has led to heightened complexity
in distribution network models, posing challenges of uncertainty and volatility to the …

Deep reinforcement learning for smart grid operations: Algorithms, applications, and prospects

Y Li, C Yu, M Shahidehpour, T Yang… - Proceedings of the …, 2023 - ieeexplore.ieee.org
With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …

[HTML][HTML] Advancements in data-driven voltage control in active distribution networks: A Comprehensive review

SM Abdelkader, S Kinga, E Ebinyu, J Amissah… - Results in …, 2024 - Elsevier
Distribution systems are integrating a growing number of distributed energy resources and
converter-interfaced generators to form active distribution networks (ADNs). Numerous …

Electrical model-free voltage calculations using neural networks and smart meter data

V Bassi, LF Ochoa, T Alpcan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The proliferation of residential technologies such as photovoltaic (PV) systems and electric
vehicles can cause voltage issues in low voltage (LV) networks. During operation, voltage …

Model-augmented safe reinforcement learning for Volt-VAR control in power distribution networks

Y Gao, N Yu - Applied Energy, 2022 - Elsevier
Volt-VAR control (VVC) is a critical tool to manage voltage profiles and reactive power flow
in power distribution networks by setting voltage regulating and reactive power …

Novel Data-Driven decentralized coordination model for electric vehicle aggregator and energy hub entities in multi-energy system using an improved multi-agent …

B Zhang, W Hu, D Cao, AMYM Ghias, Z Chen - Applied Energy, 2023 - Elsevier
Energy hub (EH) is an independent entity that benefits to the efficiency, flexibility, and
reliability of integrated energy systems (IESs). On the other hand, the rapid emerging of …

Impact of demand side management approaches for the enhancement of voltage stability loadability and customer satisfaction index

A Kumar, Y Deng, X He, AR Singh, P Kumar… - Applied Energy, 2023 - Elsevier
This research work presents the tri-level optimization framework for the optimal scheduling
of grid-connected and autonomous microgrids to diminish power losses and maximize …

Artificial emotional deep Q learning for real-time smart voltage control of cyber-physical social power systems

L Yin, X He - Energy, 2023 - Elsevier
The volatility of renewable energy leads to numerous voltage changes in a short period, thus
affecting the quality of the power supply. A real-time smart voltage control framework of …

Multi-task reinforcement learning for distribution system voltage control with topology changes

Y Pei, J Zhao, Y Yao, F Ding - IEEE Transactions on Smart Grid, 2023 - ieeexplore.ieee.org
This letter proposes a multi-task deep reinforcement learning (DRL) approach for distribution
system voltage regulation considering topology changes via PV smart inverter control. The …

Meta-learning based voltage control strategy for emergency faults of active distribution networks

Y Zhao, G Zhang, W Hu, Q Huang, Z Chen, F Blaabjerg - Applied Energy, 2023 - Elsevier
With the increase of energy demand and the continuous development of renewable energy
technology, active distribution networks have become increasingly important. However, the …