Power flow adjustment for smart microgrid based on edge computing and multi-agent deep reinforcement learning

Power flow adjustment for smart microgrid based on edge computing and multi-agent deep reinforcement learning

Abstract In current power grids, a massive amount of power equipment raises various emerging requirements, e.g., data perception, information transmission, and real-time control. The existing cloud computing paradigm is stubborn to address issues and challenges such as rapid response and local auton...

Full description

Bibliographic Details
Main Authors: Tianjiao Pu, Xinying Wang, Yifan Cao, Zhicheng Liu, Chao Qiu, Ji Qiao, Shuhua Zhang
Format: Article
Language:English
Published: SpringerOpen 2021-09-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Power flow adjustment
Edge intelligence
Microgrid management
Machine learning
Edge computing
Online Access:https://doi.org/10.1186/s13677-021-00259-1

Internet

https://doi.org/10.1186/s13677-021-00259-1

Similar Items