Dynamic Pricing Strategy for Electromobility using Markov Decision Processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00322131" target="_blank" >RIV/68407700:21230/18:00322131 - isvavai.cz</a>
Result on the web
<a href="https://electrific.eu/wp-content/uploads/2018/04/ICAART_2018_88.pdf" target="_blank" >https://electrific.eu/wp-content/uploads/2018/04/ICAART_2018_88.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Dynamic Pricing Strategy for Electromobility using Markov Decision Processes
Original language description
Efficient allocation of charging capacity to electric vehicle (EV) users is a key prerequisite for large-scale adaption of electric vehicles. Dynamic pricing represents a flexible framework for balancing the supply and demand for limited resources. In this paper, we show how dynamic pricing can be employed for allocation of EV charging capacity. Our approach uses Markov Decision Process (MDP) to implement demand-response pricing which can take into account both revenue maximization at the side of the charging station provider and the minimization of cost of charging on the side of the EV driver. We experimentally evaluate our method on a real-world data set. We compare our dynamic pricing method with the flat rate time-of-use pricing that is used today by most paid charging stations and show significant benefits of dynamically allocating charging station capacity through dynamic pricing.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
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
Proceedings of the 10th International Conference on Agents and Artificial Intelligence
ISBN
978-989-758-275-2
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
507-514
Publisher name
SciTePress
Place of publication
Madeira
Event location
Funchal, Medeira, Portugal
Event date
Jan 16, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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