An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electrici...

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Veröffentlicht in:Electronics (Basel) 2024-06, Vol.13 (12), p.2259
Hauptverfasser: Huaman-Rivera, Anny, Calloquispe-Huallpa, Ricardo, Luna Hernandez, Adriana C., Irizarry-Rivera, Agustin
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container_end_page
container_issue 12
container_start_page 2259
container_title Electronics (Basel)
container_volume 13
creator Huaman-Rivera, Anny
Calloquispe-Huallpa, Ricardo
Luna Hernandez, Adriana C.
Irizarry-Rivera, Agustin
description The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.
doi_str_mv 10.3390/electronics13122259
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source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Air quality management
Automobiles
Automobiles, Electric
Electric industries
Electric power grids
Electric vehicle charging stations
Electric vehicles
Emissions
Greenhouse gases
Machine learning
Neural networks
Public policy
Subsidies
Transportation industry
title An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies
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