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Authors: Jan Mrkos ; Antonín Komenda and Michal Jakob

Affiliation: Czech Technical University in Prague, Czech Republic

Keyword(s): Electric Vehicles, Demand-response, Dynamic Pricing, Charging, MDP, Markov Decision Process.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Industrial Applications of AI ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Model-Based Reasoning ; Multi-Agent Systems ; Soft Computing ; Software Engineering ; Symbolic Systems

Abstract: 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.

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Paper citation in several formats:
Mrkos, J.; Komenda, A. and Jakob, M. (2018). Dynamic Pricing Strategy for Electromobility using Markov Decision Processes. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-275-2; ISSN 2184-433X, SciTePress, pages 507-514. DOI: 10.5220/0006601505070514

@conference{icaart18,
author={Jan Mrkos. and Antonín Komenda. and Michal Jakob.},
title={Dynamic Pricing Strategy for Electromobility using Markov Decision Processes},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2018},
pages={507-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006601505070514},
isbn={978-989-758-275-2},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Dynamic Pricing Strategy for Electromobility using Markov Decision Processes
SN - 978-989-758-275-2
IS - 2184-433X
AU - Mrkos, J.
AU - Komenda, A.
AU - Jakob, M.
PY - 2018
SP - 507
EP - 514
DO - 10.5220/0006601505070514
PB - SciTePress

- Science and Technology Publications, Lda.
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