Power flow adjustment for smart microgrid based on edge computing and multi-agent deep reinforcement learning.
Tianjiao PuXinying WangYifan CaoZhicheng LiuChao QiuJi QiaoShuhua ZhangPublished in: J. Cloud Comput. (2021)
Keyphrases
- reinforcement learning
- multi agent
- power flow
- power system
- multi agent systems
- function approximation
- multi agent environments
- dynamic programming
- state space
- simulated annealing
- communication networks
- artificial neural networks
- machine learning
- differential evolution
- independent component analysis
- reinforcement learning agents
- objective function
- power transmission