Title
Indirect Customer-to-Customer Energy Trading with Reinforcement Learning
Abstract
In this paper, we explore the role of emerging energy brokers (middlemen) in a localized event-driven market (LEM) at the distribution level for facilitating indirect customer-tocustomer energy trading. This proposed LEM does not aim to replace any existing energy service or become the best market model; but instead to diversify the energy ecosystem at the edge of distribution networks. In light o...
Year
DOI
Venue
2019
10.1109/TSG.2018.2857449
IEEE Transactions on Smart Grid
Keywords
Field
DocType
Electricity supply industry,Business,Ecosystems,Markov processes,Learning (artificial intelligence),Peer-to-peer computing,Buildings
Market mechanism,Markov process,Customer to customer,Markov decision process,Control engineering,Search cost,Engineering,Industrial organization,Power Balance,Electricity retailing,Reinforcement learning
Journal
Volume
Issue
ISSN
10
4
1949-3053
Citations 
PageRank 
References 
3
0.39
0
Authors
2
Name
Order
Citations
PageRank
Tao Chen1163.09
Wencong Su225427.89