Research on the Charging Load Calculation Method for Electric Vehicle Cluster

[Introduction] The widespread adoption of electric vehicles (EVs) enhances environmental sustainability during travel, yet it simultaneously elevates strain on the mains supply. To assess the impact of EV charging on the power grid, a specialized charging load calculation method is developed for large EV cluster on the basis of the Monte Carlo method. [Method] In this approach, EVs were categorized into six groups based on their usage: private EVs, electric buses, electric taxis, online ride-hailing EVs, official EVs, and logistics EVs. Typical battery performance parameters for each group were identified, and probability models were established to characterize the variability in their travel and charging patterns. By integrating group scale forecasts, daily charging schedules for each group were simulated through random sampling. Subsequently, the daily charging load for each group was calculated, culminating in the total charging load for the EV cluster through an aggregation method. [Result] The EV cluster in a southern province in 2030 was taken as the simulation case. [Conclusion] The case analysis reveals that the proposed approach can provide the daily charging load of various EV groups and the entire EV cluster. Furthermore, among all types of EVs, electric buses have the highest peak charging load at 4 639.5 MW, followed by that of private EVs (not higher than 70% of the electric buses' peak load), and electric taxis have the lowest peak charging load. The charging peak of the entire EV cluster occurs between 19:00 and 23:00 at night, and the peak load can reach 10.0927 GW.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.16516/j.ceec.2024.5.17
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Charging Load Calculation Method for Electric Vehicle Cluster

1 citations
SHILAP Revista de lepidopterología
Electric Vehicles and Infrastructure
0.21
article

Research on the Charging Load Calculation Method for Electric Vehicle Cluster

article en
1 citations

Abstract

[Introduction] The widespread adoption of electric vehicles (EVs) enhances environmental sustainability during travel, yet it simultaneously elevates strain on the mains supply. To assess the impact of EV charging on the power grid, a specialized charging load calculation method is developed for large EV cluster on the basis of the Monte Carlo method. [Method] In this approach, EVs were categorized into six groups based on their usage: private EVs, electric buses, electric taxis, online ride-hailing EVs, official EVs, and logistics EVs. Typical battery performance parameters for each group were identified, and probability models were established to characterize the variability in their travel and charging patterns. By integrating group scale forecasts, daily charging schedules for each group were simulated through random sampling. Subsequently, the daily charging load for each group was calculated, culminating in the total charging load for the EV cluster through an aggregation method. [Result] The EV cluster in a southern province in 2030 was taken as the simulation case. [Conclusion] The case analysis reveals that the proposed approach can provide the daily charging load of various EV groups and the entire EV cluster. Furthermore, among all types of EVs, electric buses have the highest peak charging load at 4 639.5 MW, followed by that of private EVs (not higher than 70% of the electric buses' peak load), and electric taxis have the lowest peak charging load. The charging peak of the entire EV cluster occurs between 19:00 and 23:00 at night, and the peak load can reach 10.0927 GW.

SHILAP Revista de lepidopterología
Guangdong Hydropower Planning & Design Institute (CN)
Responsible consumption and production
Openalex Percentile: Top 43%
Electric Vehicles and Infrastructure
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.