Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning

Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning

This article develops a special decomposition methodology for the traditional optimal power flow which facilitates optimal integration of stochastic distributed energy resources in power distribution systems. The resulting distributed optimal power flow algorithm reduces the computational complexity...

Full description

Bibliographic Details
Main Authors: Mohammed Al-Saffar, Petr Musilek
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Distributed architecture
distributed optimization
Monte Carlo tree search
multi-agent deep reinforcement learning
optimal power flow
Online Access:https://ieeexplore.ieee.org/document/9411856/

Internet

https://ieeexplore.ieee.org/document/9411856/

Similar Items