mlsanityData to 7 Oct 2026

Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks

arXiv 2007.02991 ↗First posted 6 Jul 2020eess.SY cs.LG cs.SYcited by 16

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Abstract (arXiv)

Volt-VAR control (VVC) is a critical application in active distribution network management system to reduce network losses and improve voltage profile. To remove dependency on inaccurate and incomplete network models and enhance resiliency against communication or controller failure, we propose consensus multi-agent deep reinforcement learning algorithm to solve the VVC problem. The VVC problem is formulated as a networked multi-agent Markov decision process, which is solved using the maximum entropy reinforcement learning framework and a novel communication-efficient consensus strategy. The proposed algorithm allows individual agents to learn a group control policy using local rewards. Numerical studies on IEEE distribution test feeders show that our proposed algorithm matches the performance of single-agent reinforcement learning benchmark. In addition, the proposed algorithm is shown to be communication efficient and resilient.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jul 2020.

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Citing papers per year: 2021: 3; 2022: 5; 2023: 2; 2024: 3; 2025: 0; 2026: 3.

16 papers.

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  1. 2021Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challengescited by 40
  2. 2021PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systemscited by 15
  3. 2024Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Taskscited by 12
  4. 2021A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systemscited by 5
  5. 2024Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problemscited by 2
  6. 2024Safety Constrained Multi-Agent Reinforcement Learning for Active Voltage Controlcited by 2
  7. 2022An Optimization Method-Assisted Ensemble Deep Reinforcement Learning Algorithm to Solve Unit Commitment Problemscited by 1
  8. 2023An Efficient Distributed Multi-Agent Reinforcement Learning for EV Charging Network Controlcited by 1
  9. 2023Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Networkcited by 1
  10. 2022Reducing Learning Difficulties: One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Controlcited by 0
  11. 2022A Reinforcement Learning-based Volt-VAR Control Dataset and Testing Environmentcited by 0
  12. 2022RACA: Relation-Aware Credit Assignment for Ad-Hoc Cooperation in Multi-Agent Deep Reinforcement Learningcited by 0
4 more
  1. 2022Reducing Action Space: Reference-Model-Assisted Deep Reinforcement Learning for Inverter-based Volt-Var Controlcited by 0
  2. 2026Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorizationcited by 0
  3. 2026Decentralized Stochastic Subgradient-type Methods with Communication Compression for Nonsmooth Nonconvex Optimizationcited by 0
  4. 2026Safety Screening for Voltage Control in Active Distribution Grids via Distributionally Robust Conformal Screeningcited by 0