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 …

[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 …

A tri-level demand response framework for EVCS flexibility enhancement in coupled power and transportation networks

T Qian, Z Liang, S Chen, Q Hu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The increasing penetration of electric vehicles (EVs) presents an opportunity for demand
response (DR) programs in the power network to improve overall operation efficiency …

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 …

A coordinated active and reactive power optimization approach for multi-microgrids connected to distribution networks with multi-actor-attention-critic deep …

L Dong, H Lin, J Qiao, T Zhang, S Zhang, T Pu - Applied Energy, 2024 - Elsevier
As a promising approach to managing distributed energy, the use of microgrids has attracted
significant attention among those managing continuous connections to distribution networks …

Physical-assisted multi-agent graph reinforcement learning enabled fast voltage regulation for PV-rich active distribution network

Y Chen, Y Liu, J Zhao, G Qiu, H Yin, Z Li - Applied Energy, 2023 - Elsevier
Active distribution network is encountering serious voltage violations associated with the
proliferation of distributed photovoltaic. Cutting-edge research has confirmed that voltage …

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 - ieeexplore.ieee.org
The cloud-edge collaboration architecture has been widely adopted for distributed Volt-VAR
control (VVC) problems in active distribution networks (ADNs). To alleviate the computation …

Deep reinforcement learning for charging scheduling of electric vehicles considering distribution network voltage stability

D Liu, P Zeng, S Cui, C Song - Sensors, 2023 - mdpi.com
The rapid development of electric vehicle (EV) technology and the consequent charging
demand have brought challenges to the stable operation of distribution networks (DNs). The …

[HTML][HTML] Safe multi-agent deep reinforcement learning for real-time decentralized control of inverter based renewable energy resources considering communication …

G Guo, M Zhang, Y Gong, Q Xu - Applied Energy, 2023 - Elsevier
The increasing penetration of distributed renewable energy resources brings a great
challenge for real-time voltage security of distribution grids. The paper proposes a safe multi …

Graph learning-based voltage regulation in distribution networks with multi-microgrids

Y Wang, D Qiu, Y Wang, M Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Microgrids (MGs), as localized small power systems, can effectively provide voltage
regulation services for distribution networks by integrating and managing various distributed …