A generalized multi-agent deep reinforcement learning framework for enhancing resilience and energy management in smart grids

Key Points

• Enhanced resilience in smart grids improves overall energy management capabilities, leading to increased efficiency.
• Energy management optimization was assessed using a multi-agent reinforcement learning framework, yielding significant performance improvements.
• Model validation included various operational scenarios across diverse grid configurations, demonstrating adaptability and effectiveness.
• Potential implications of this framework highlight enhanced efficiency in energy distribution, especially in dynamic environments.