Survey on AI and Machine Learning Techniques for Microgrid Energy Management Systems
Author:
Affiliation:
1. North Carolina State University,Department of Electrical and Computer Engineering,Raleigh,NC,USA,27695
2. UM-SJTU Joint Institute, Shanghai Jiao Tong University,Shanghai,China,200240
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Information Systems,Control and Systems Engineering,Control and Optimization
Link
http://xplorestaging.ieee.org/ielx7/6570654/10153596/10153723.pdf?arnumber=10153723
Reference84 articles.
1. Price-Based Residential Demand Response Management in Smart Grids: A Reinforcement Learning-Based Approach
2. Microgrid Energy Management by ANFIS Supported by an ESN Based Prediction Algorithm
3. Incremental Welfare Consensus Algorithm for Cooperative Distributed Generation/Demand Response in Smart Grid
4. ANFIS: adaptive-network-based fuzzy inference system
5. Representation Learning: A Review and New Perspectives
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