Analyzing Coincident Factors of Public Electric Vehicles in Ho Chi Minh City: A Monte Carlo Approach

This study presents the method of calculating the coincident factor (CF) for public electric vehicles (PEVs) using Monte Carlo Simulation (MCS). The paper focuses on predicting future charging demand for electric buses (EBs) and electric taxis (ETs) in the greater Ho Chi Minh City (HCMC) metropolitan area, which, since July 1, 2025, has officially expanded to include Binh Duong and Ba Ria–Vung Tau provinces. The projection is based on population growth and public electric vehicle (PEV) penetration scenarios. It builds three scenarios for the years 2030, 2035, and 2040 to estimate the number of PEVs and their charging behaviours. The simulation runs 1,000 times for each vehicle type and scenario to calculate the CF. Results show that while the total number of PEVs increases over time, the CF slightly decreases, indicating that charging loads become more distributed across the day. For example, the CF for ETs changes from 0.26 in 2030 to 0.24 in 2040, while for EBs it stays around 0.35. These findings highlight the need for better charging management strategies and infrastructure planning to reduce grid overload risks and improve power system stability, especially for the newly enlarged urban area.

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Publication Details

Journal
Technical Education Science/Giáo dục Kỹ thuật
Published
2025-09-09
DOI
https://doi.org/10.54644/jte.2025.1967
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00

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article

Analyzing Coincident Factors of Public Electric Vehicles in Ho Chi Minh City: A Monte Carlo Approach

Tien Khai Nguyen, Trong Nghia Le
Technical Education Science/Giáo dục Kỹ thuật
Electric Vehicles and Infrastructure
article

Analyzing Coincident Factors of Public Electric Vehicles in Ho Chi Minh City: A Monte Carlo Approach

Tien Khai Nguyen, Trong Nghia Le
article en

Abstract

This study presents the method of calculating the coincident factor (CF) for public electric vehicles (PEVs) using Monte Carlo Simulation (MCS). The paper focuses on predicting future charging demand for electric buses (EBs) and electric taxis (ETs) in the greater Ho Chi Minh City (HCMC) metropolitan area, which, since July 1, 2025, has officially expanded to include Binh Duong and Ba Ria–Vung Tau provinces. The projection is based on population growth and public electric vehicle (PEV) penetration scenarios. It builds three scenarios for the years 2030, 2035, and 2040 to estimate the number of PEVs and their charging behaviours. The simulation runs 1,000 times for each vehicle type and scenario to calculate the CF. Results show that while the total number of PEVs increases over time, the CF slightly decreases, indicating that charging loads become more distributed across the day. For example, the CF for ETs changes from 0.26 in 2030 to 0.24 in 2040, while for EBs it stays around 0.35. These findings highlight the need for better charging management strategies and infrastructure planning to reduce grid overload risks and improve power system stability, especially for the newly enlarged urban area.

Technical Education Science/Giáo dục Kỹ thuật
Ho Chi Minh City University of Technology and Engineering (VN)
Ho Chi Minh City University of Technology and Education
Openalex Percentile: Top 76%
Electric Vehicles and Infrastructure
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