Deep Reinforcement Learning for an Incentive-based Demand Response Model
Author:
Affiliation:
1. Guangxi University,School of Electrical Engineering,Nanning,China
Funder
Research and Development
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10115460/10115466/10117409.pdf?arnumber=10117409
Reference18 articles.
1. Real-time Incentive-based Demand Response for a Virtual Power Plant: a Rolling-window Multistage Stochastic Programming Approach
2. Deep reinforcement learning based bi-layer optimal scheduling for microgrid considering flexible load control;zhang;CSEE Journal of Power and Energy Systems,0
3. Playing atari with deep reinforcement learning;mnih,2013
4. Energy Management in Microgrids Using Demand Response and Distributed Storage—A Multiagent Approach
5. Optimal Demand Response Programs for improving the efficiency of day-ahead electricity markets using a multi attribute decision making approach
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