Deep Reinforcement Learning-Based Operation of Distribution Systems Using Surrogate Model
Author:
Affiliation:
1. State University of New York (SUNY), Maritime College,Department of Electrical Engineering,New York,USA
2. University of Michigan-Dearborn,Department of Electrical and Computer Engineering,Michigan,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10252165/10252088/10253401.pdf?arnumber=10253401
Reference14 articles.
1. Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more;lapan;Packt Publishing Ltd,2018
2. An Enhanced IEEE 33 Bus Benchmark Test System for Distribution System Studies
3. Bridging the gap between value and policy based reinforcement learning;nachum;Advances in neural information processing systems,2017
4. Surrogate-Assisted Multi-Objective Probabilistic Optimal Power Flow for Distribution Network With Photovoltaic Generation and Electric Vehicles
5. Fundamentals of Data-Driven Surrogate Modeling
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