Based Volt Var Control

Based Volt-Var Control (VVC) optimizes voltage and reactive power in power grids, particularly crucial with the increasing integration of renewable energy sources and inverter-based resources (IBRs). Current research heavily utilizes reinforcement learning (RL), employing various architectures like actor-critic methods and multi-agent RL, often enhanced by techniques to improve scalability and robustness in partially observable environments. These advancements aim to improve grid stability, reduce power losses, and enhance the efficiency of renewable energy integration, impacting both the development of more sophisticated control algorithms and the practical operation of power systems.

Papers

October 19, 2024

Augmented Lagrangian-Based Safe Reinforcement Learning Approach for Distribution System Volt/VAR Control
Guibin Chen
Safe Reinforcement Learning Distribution System Active Distribution Soft Actor Critic Algorithm Based Volt Var Control

September 22, 2024

A Unified Approach for Learning the Dynamics of Power System Generators and Inverter-based Resources
Shaohui Liu, Weiqian Cai, Hao Zhu, Brian Johnson
Recurrent Neural Network Unified Framework Synchronous Generator Based Volt Var Control RNN Cell Structure

August 13, 2024

Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks
Qiong Liu, Ye Guo, Tong Xu
Distribution System DRL Algorithm Robust Deep Reinforcement Learning Active Distribution Based Volt Var Control

February 24, 2024

Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach
Alaa Selim, Yanzhu Ye, Junbo Zhao, Bo Yang
Deep Reinforcement Learning Reinforcement Learning Approach Based Volt Var Control

December 7, 2023

A Scalable Network-Aware Multi-Agent Reinforcement Learning Framework for Decentralized Inverter-based Voltage Control
Han Xu, Jialin Zheng, Guannan Qu
Multi Agent Reinforcement Learning Power Grid Multi Agent Actor Critic Voltage Control Based Volt Var Control

November 7, 2023

An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network
Wenlong Liao, Benjamin Schäfer, Dalin Qin, Gonghao Zhang, Zhixian Wang, Zhe Yang
Machine Learning Framework Distribution System Based Volt Var Control

October 31, 2022

Fault diagnosis for open-circuit faults in NPC inverter based on knowledge-driven and data-driven approaches
Lei Kou, Chuang Liu, Guo-wei Cai, Jia-ning Zhou, Quan-de Yuan, Si-miao Pang
Data Driven Approach Based Volt Var Control Open Circuit Fault

October 10, 2022

Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Control
Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun
Deep Reinforcement Learning Action Space Soft Actor Critic DRL Algorithm Active Distribution Based Volt Var Control

April 20, 2022

A Reinforcement Learning-based Volt-VAR Control Dataset and Testing Environment
Yuanqi Gao, Nanpeng Yu
Reinforcement Learning Reinforcement Learning Algorithm Test Environment Based Volt Var Control

March 30, 2022

Reducing Learning Difficulties: One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control
Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu, Dongyu Li, Hongbin Sun, Wenqi Huang
Deep Reinforcement Learning Actor Critic Active Distribution Based Volt Var Control

Based Volt Var Control

Papers

Augmented Lagrangian-Based Safe Reinforcement Learning Approach for Distribution System Volt/VAR Control

A Unified Approach for Learning the Dynamics of Power System Generators and Inverter-based Resources

Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks

Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach

A Scalable Network-Aware Multi-Agent Reinforcement Learning Framework for Decentralized Inverter-based Voltage Control

An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network

Fault diagnosis for open-circuit faults in NPC inverter based on knowledge-driven and data-driven approaches

Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Control

A Reinforcement Learning-based Volt-VAR Control Dataset and Testing Environment

Reducing Learning Difficulties: One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control