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Open AccessFeature PaperArticle

Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems

1
Honda Research Institute Europe GmbH, 63073 Offenbach am Main, Germany
2
EA Systems Dresden GmbH, 01187 Dresden, Germany
*
Author to whom correspondence should be addressed.
Energies 2019, 12(15), 2858; https://doi.org/10.3390/en12152858
Received: 19 June 2019 / Revised: 16 July 2019 / Accepted: 19 July 2019 / Published: 25 July 2019
(This article belongs to the Special Issue Multi-Agent Energy Systems Simulation)
The development of efficient electric vehicle (EV) charging infrastructure requires a modeling of customer behavior at an appropriate level of detail. Since only limited information about real customers is available, most simulation approaches employ a stochastic approach by combining known or estimated customer features with random variations. A typical example is to model EV charging customers by an arrival and a targeted departure time, plus the requested amount of energy or increased state of charge (SoC), where values are drawn from normal (Gaussian) distributions with mean and variance values derived from user studies of obviously limited sample size. In this work, we compare this basic approach with a more detailed customer model employing a multi-agent simulation (MAS) framework in order to investigate how a customer behavior that responds to external factors (like weather) or historical data (like satisfaction in past charging sessions) impacts the essential key performance indicators of the charging system. Our findings show that small changes in the way customers are modeled can lead to quantitative and qualitative differences in the simulated performance of EV charging systems. View Full-Text
Keywords: EV charging; multi-agent system; digital twin; customer satisfaction indicator EV charging; multi-agent system; digital twin; customer satisfaction indicator
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MDPI and ACS Style

Rodemann, T.; Eckhardt, T.; Unger, R.; Schwan, T. Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems. Energies 2019, 12, 2858. https://doi.org/10.3390/en12152858

AMA Style

Rodemann T, Eckhardt T, Unger R, Schwan T. Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems. Energies. 2019; 12(15):2858. https://doi.org/10.3390/en12152858

Chicago/Turabian Style

Rodemann, Tobias; Eckhardt, Tom; Unger, René; Schwan, Torsten. 2019. "Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems" Energies 12, no. 15: 2858. https://doi.org/10.3390/en12152858

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