Load Profile Modeling of Plug-In Electric Vehicles: Realistic and Ready-to-Use Benchmark Test Data
Abdulaziz Almutairi, Saeed Alyami
Majmaah University
IEEE Access
Abstract
This study develops realistic and ready-to-use benchmark load profiles for plug-in electric vehicles (PEVs) by considering vehicle mobility, charging infrastructure, and PEV market share. The methodology uses filtered U.S. National Household Travel Survey (NHTS) data to estimate arrival time, departure time, and daily mileage. Commercially available PEVs are grouped into four clusters using the K-means algorithm, and per-unit load profiles are developed considering residential charging levels and vehicle characteristics. The resulting profiles provide reusable benchmark data for researchers, policymakers, and planners and are applied to analyze PEV loads in countries with high EV penetration.
Keywords
Load Profile; Peak Demand Estimation; PEV Demand Estimation; PEV Load; PEV Policymakers; Plug-In Electric Vehicles; Test Data