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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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 |
work_keys_str_mv |
AT martinakajanova definitionofdiscretechoicemodelsofevownersbasedondifferentsociodemographicaspects AT peterbracinik definitionofdiscretechoicemodelsofevownersbasedondifferentsociodemographicaspects |
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