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Electricity Trading Agent for EV-enabled Parking Lots

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Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets (AMEC/TADA 2015, AMEC/TADA 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 271))

Abstract

The reduction of greenhouse gas emissions is seen as an important step towards environmental sustainability. Perhaps not surprising, many governments all around the world are providing incentives for consumers to buy electric vehicles (EVs). A positive response from consumers means that the demand for the charging infrastructure increases as well. We investigate how an existing traditional parking lot, upgraded with chargers, can suit the present demand for charging stations. In particular, a resulting EV-enabled parking lot is an electricity trading agent (i.e., broker) which acts as an energy retailer and as a player on a target electricity market. In this paper, we use agent-based simulation to present the EV-enabled parking lot ecosystem in order to model the underlying dynamics and uncertainties regarding parking lots with electricity trading agent functionalities. We instantiate our agent-based simulations using real-life data in order to perform the what-if analysis. Several key performance indicators (KPIs), including parking utilization, charging utilization and electricity utilization, are proposed. We also illustrate how those KPIs can be used to choose the effective investment strategy with respect to the number and speed of chargers.

This paper extends the paper “Extending Parking Lots with Electricity Trading Agent Functionalities” presented at the “Workshop on Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis (AMEC/TADA 2015) @ AAMAS 2015”.

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Notes

  1. 1.

    Available at: www.nordpoolspot.com/historical-market-data.

  2. 2.

    Our simulation is implemented using R, a free software environment for statistical computing and graphics. It takes around three minutes to simulate one year scenario on a system with 4-core CPU and 8 GB RAM. Please note R does not utilize multi-threading and therefore a computer with less CPU cores will produce similar running times.

  3. 3.

    Available at: http://www.greenbiz.com/blog/2014/05/07/rmi-whats-true-cost-ev-charging-stations.

References

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Acknowledgements

The authors acknowledge the support of the research project “Managing Trust and Coordinating Interactions in Smart Networks of People, Machines and Organizations”, funded by the Croatian Science Foundation under the project UIP-11-2013-8813 and COST Action IC1404 on Multi-Paradigm Modelling for Cyber-Physical Systems, funded by European Union.

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

    Jurica Babic & Vedran Podobnik

  2. Farmer School of Business, Miami University, Oxford, Ohio, USA

    Arthur Carvalho

  3. Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, Netherlands

    Wolfgang Ketter

Authors
  1. Jurica Babic
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  2. Arthur Carvalho
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  3. Wolfgang Ketter
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  4. Vedran Podobnik
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Corresponding author

Correspondence to Jurica Babic .

Editor information

Editors and Affiliations

  1. School of Informatics, University of Edinburgh , Cambridge, United Kingdom

    Sofia Ceppi

  2. Department of Computer Science, Ashkelon Academic College , Ashkelon, Israel

    Esther David

  3. Department of EE and CS, Vanderbilt University , Nashville, Tennessee, USA

    Chen Hajaj

  4. Smart Systems Group, Heriot-Watt University , Edinburgh, United Kingdom

    Valentin Robu

  5. Information Technology, The American College of Greece , Agia Paraskevi, Athens, Greece

    Ioannis A. Vetsikas

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Babic, J., Carvalho, A., Ketter, W., Podobnik, V. (2017). Electricity Trading Agent for EV-enabled Parking Lots. In: Ceppi, S., David, E., Hajaj, C., Robu, V., Vetsikas, I. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC/TADA AMEC/TADA 2015 2016. Lecture Notes in Business Information Processing, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-319-54229-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-54229-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54228-7

  • Online ISBN: 978-3-319-54229-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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