Forecasting Electric Vehicle Adaption Using System Dynamics: A Case Study of Regina, Saskatchewan †

S. M. Rafew; Niamat Ullah Ibne Hossain; Golam Kabir

doi:10.3390/engproc2024076027

Forecasting Electric Vehicle Adaption Using System Dynamics: A Case Study of Regina, Saskatchewan †

S. M. Rafew^*
, Niamat Ullah Ibne Hossain
, Golam Kabir

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The Zero Emission Vehicle (ZEV) mandate by Canada’s federal government is a significant initiative towards achieving net zero emissions by 2050. In this context, to quantify the evolution scale of ZEVs alongside charging pile, a system dynamics (SD)-based policy simulation has been adopted for the city of Regina, Saskatchewan. The vector autoregressive model (VAR) equation is used as an input equation in the SD model for predicting ZEV sales. For model validity, calibration of the data with an available historical dataset alongside a sensitivity analysis has been performed. The SD model with two consecutive scenarios has been simulated until 2036, and “policy 2” has been found to be adequate.

Original language	English
Article number	27
Journal	Engineering Proceedings
Volume	76
Issue number	1
DOIs	https://doi.org/10.3390/engproc2024076027
State	Published - 2024
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

Regina
electric vehicle
policy simulation
sensitivity analysis
system dynamics
vector autoregressive model

ASJC Scopus subject areas

Biomedical Engineering
Mechanical Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3390/engproc2024076027

Cite this

@article{8bee80426db84257904cd30e8f33fc0e,

title = "Forecasting Electric Vehicle Adaption Using System Dynamics: A Case Study of Regina, Saskatchewan †",

abstract = "The Zero Emission Vehicle (ZEV) mandate by Canada{\textquoteright}s federal government is a significant initiative towards achieving net zero emissions by 2050. In this context, to quantify the evolution scale of ZEVs alongside charging pile, a system dynamics (SD)-based policy simulation has been adopted for the city of Regina, Saskatchewan. The vector autoregressive model (VAR) equation is used as an input equation in the SD model for predicting ZEV sales. For model validity, calibration of the data with an available historical dataset alongside a sensitivity analysis has been performed. The SD model with two consecutive scenarios has been simulated until 2036, and “policy 2” has been found to be adequate.",

keywords = "Regina, electric vehicle, policy simulation, sensitivity analysis, system dynamics, vector autoregressive model",

author = "Rafew, \{S. M.\} and Hossain, \{Niamat Ullah Ibne\} and Golam Kabir",

note = "Publisher Copyright: {\textcopyright} 2024 by the authors.",

year = "2024",

doi = "10.3390/engproc2024076027",

language = "English",

volume = "76",

journal = "Engineering Proceedings",

issn = "2673-4591",

publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",

number = "1",

}

TY - JOUR

T1 - Forecasting Electric Vehicle Adaption Using System Dynamics

T2 - A Case Study of Regina, Saskatchewan †

AU - Rafew, S. M.

AU - Hossain, Niamat Ullah Ibne

AU - Kabir, Golam

PY - 2024

Y1 - 2024

N2 - The Zero Emission Vehicle (ZEV) mandate by Canada’s federal government is a significant initiative towards achieving net zero emissions by 2050. In this context, to quantify the evolution scale of ZEVs alongside charging pile, a system dynamics (SD)-based policy simulation has been adopted for the city of Regina, Saskatchewan. The vector autoregressive model (VAR) equation is used as an input equation in the SD model for predicting ZEV sales. For model validity, calibration of the data with an available historical dataset alongside a sensitivity analysis has been performed. The SD model with two consecutive scenarios has been simulated until 2036, and “policy 2” has been found to be adequate.

AB - The Zero Emission Vehicle (ZEV) mandate by Canada’s federal government is a significant initiative towards achieving net zero emissions by 2050. In this context, to quantify the evolution scale of ZEVs alongside charging pile, a system dynamics (SD)-based policy simulation has been adopted for the city of Regina, Saskatchewan. The vector autoregressive model (VAR) equation is used as an input equation in the SD model for predicting ZEV sales. For model validity, calibration of the data with an available historical dataset alongside a sensitivity analysis has been performed. The SD model with two consecutive scenarios has been simulated until 2036, and “policy 2” has been found to be adequate.

KW - Regina

KW - electric vehicle

KW - policy simulation

KW - sensitivity analysis

KW - system dynamics

KW - vector autoregressive model

UR - https://www.scopus.com/pages/publications/105000135205

U2 - 10.3390/engproc2024076027

DO - 10.3390/engproc2024076027

M3 - Article

AN - SCOPUS:105000135205

SN - 2673-4591

VL - 76

JO - Engineering Proceedings

JF - Engineering Proceedings

IS - 1

M1 - 27

ER -

Forecasting Electric Vehicle Adaption Using System Dynamics: A Case Study of Regina, Saskatchewan †

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this