Controlling the Charging of Electric Vehicles with Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10388389" target="_blank" >RIV/00216208:11320/18:10388389 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8489027" target="_blank" >https://ieeexplore.ieee.org/document/8489027</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2018.8489027" target="_blank" >10.1109/IJCNN.2018.8489027</a>
Alternative languages
Result language
angličtina
Original language name
Controlling the Charging of Electric Vehicles with Neural Networks
Original language description
We propose and evaluate controllers for the coordination of the charging of electric vehicles. The controllers are based on neural networks and are completely de-centralized, in the sense that the charging current is completely decided by the controller itself. One of the versions of the controllers does not require any outside communication at all. We test controllers based on two different architectures of neural networks-the feed-forward networks and the echo state networks. The networks are optimized by either an evolutionary algorithm (CMA-ES) or by a gradient-based method. The results of the different architectures and the different optimization algorithms are compared in a realistic scenario. We show that the controllers are able to charge the cars while keeping the peak consumptions almost the same as when no charging is performed. Moreover, the controllers fill the valleys of the consumption thus reducing the difference between the maximum and minimum consumption in the grid.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GJ17-10090Y" target="_blank" >GJ17-10090Y: Network Optimization</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 International Joint Conference on Neural Networks (IJCNN)
ISBN
978-1-5090-6014-6
ISSN
2161-4407
e-ISSN
neuvedeno
Number of pages
8
Pages from-to
1-8
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Neuveden
Event location
Rio de Janeiro, Brazílie
Event date
Jul 8, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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