Resilient Load Restoration in Microgrids Considering Mobile Energy Storage Fleets: A Deep Reinforcement Learning Approach.
Shuhan YaoJiuxiang GuPeng WangTianyang ZhaoHuajun ZhangXiaochuan LiuPublished in: CoRR (2019)
Keyphrases
- reinforcement learning
- mobile devices
- image restoration
- load balancing
- function approximation
- remote server
- total energy
- energy consumption
- machine learning
- state space
- mobile phone
- reinforcement learning algorithms
- storage requirements
- mobile applications
- mobile learning
- multi agent
- energy minimization
- mobile networks
- energy efficiency
- storage and retrieval
- model free
- energy saving
- minimum energy
- learning algorithm
- action selection
- mobile communication
- electrical power
- file system
- computing environments
- markov decision processes
- power system
- context aware
- learning process
- image processing
- mobile environments
- routing protocol
- mobile nodes
- storage devices
- load forecasting
- wireless sensor networks
- air force