Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects

With an increasing number of electric vehicles (EVs), their owners’ involvement in the control of electric power systems and their market seems to be the only option for stable operation of future power networks. However, these people usually have little knowledge about power systems’ operation and...

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Main Authors: Martina Kajanova, Peter Bracinik
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/8/3679
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spelling doaj-e46da4f2f49f4f7381c7a61979b8b4562021-04-19T23:04:09ZengMDPI AGApplied Sciences2076-34172021-04-01113679367910.3390/app11083679Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic AspectsMartina Kajanova0Peter Bracinik1Faculty of Electrical Engineering and Information Technology, University of Zilina, 010 26 Žilina, SlovakiaFaculty of Electrical Engineering and Information Technology, University of Zilina, 010 26 Žilina, SlovakiaWith an increasing number of electric vehicles (EVs), their owners’ involvement in the control of electric power systems and their market seems to be the only option for stable operation of future power networks. However, these people usually have little knowledge about power systems’ operation and follow just their interests. Therefore, this paper deals with the decision-making process of EV drivers at the charging station. The paper presents the stated preference survey used to collect the responses to hypothetical scenarios, where respondents chose between three alternatives, namely slow charging, fast charging, and vehicle-to-grid services. The survey also contained questions about respondents’ socio-demographic characteristics, as gender, age, etc. The decision-making prediction models for each socio-demographic characteristic were created using the acquired data. The paper presents the estimated parameters of the attributes affecting the respondents’ choices for the models that allow models’ simple implementation. Knowing these models and the customers’ composition, the operators of the charging stations or the distribution networks could better estimate EV owners’ behavior and so their expected power demand. Moreover, operators could more effectively implement incentives for their customers and affect the customers’ behavior in a way that is suitable for better operation of their power systems.https://www.mdpi.com/2076-3417/11/8/3679electric vehiclechargingdecision-making processsocio-demographic characteristicsvehicle to grid concept
collection DOAJ
language English
format Article
sources DOAJ
author Martina Kajanova
Peter Bracinik
spellingShingle Martina Kajanova
Peter Bracinik
Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
Applied Sciences
electric vehicle
charging
decision-making process
socio-demographic characteristics
vehicle to grid concept
author_facet Martina Kajanova
Peter Bracinik
author_sort Martina Kajanova
title Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
title_short Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
title_full Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
title_fullStr Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
title_full_unstemmed Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
title_sort definition of discrete choice models of ev owners based on different socio-demographic aspects
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-04-01
description With an increasing number of electric vehicles (EVs), their owners’ involvement in the control of electric power systems and their market seems to be the only option for stable operation of future power networks. However, these people usually have little knowledge about power systems’ operation and follow just their interests. Therefore, this paper deals with the decision-making process of EV drivers at the charging station. The paper presents the stated preference survey used to collect the responses to hypothetical scenarios, where respondents chose between three alternatives, namely slow charging, fast charging, and vehicle-to-grid services. The survey also contained questions about respondents’ socio-demographic characteristics, as gender, age, etc. The decision-making prediction models for each socio-demographic characteristic were created using the acquired data. The paper presents the estimated parameters of the attributes affecting the respondents’ choices for the models that allow models’ simple implementation. Knowing these models and the customers’ composition, the operators of the charging stations or the distribution networks could better estimate EV owners’ behavior and so their expected power demand. Moreover, operators could more effectively implement incentives for their customers and affect the customers’ behavior in a way that is suitable for better operation of their power systems.
topic electric vehicle
charging
decision-making process
socio-demographic characteristics
vehicle to grid concept
url https://www.mdpi.com/2076-3417/11/8/3679
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