Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems
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Abstract (arXiv)
The rapidly changing architecture and functionality of electrical networks and the increasing penetration of renewable and distributed energy resources have resulted in various technological and managerial challenges. These have rendered traditional centralized energy-market paradigms insufficient due to their inability to support the dynamic and evolving nature of the network. This survey explores how multi-agent reinforcement learning (MARL) can support the decentralization and decarbonization of energy networks and mitigate the associated challenges. This is achieved by specifying key computational challenges in managing energy networks, reviewing recent research progress on addressing them, and highlighting open challenges that may be addressed using MARL.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 11 of its 46 references that are in the map. First posted on arXiv 24 Apr 2024.
Builds on
11 of 46 references.
References · 11
- 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
- 2013The Complexity of Decentralized Control of Markov Decision Processescited by 225
- 2021Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networkscited by 52
- 2020Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networkscited by 16
- 2020Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Controlcited by 15
- 2021GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Managementcited by 12
- 2022Scalable multi-agent reinforcement learning for distributed control of residential energy flexibilitycited by 11
- 2022Coordination of resources at the edge of the electricity grid: systematic review and taxonomycited by 4
- 2020Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Gridscited by 2
- 2022Efficient Methods for Approximating the Shapley Value for Asset Sharing in Energy Communitiescited by 1
- 2023What may future electricity markets look like?cited by 1
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Citing papers per year: 2026: 2.
2 papers.