Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Architectural Engineering
Advisor Information
Associate Professor
Location
CEC RM #201/205/209
Presentation Type
Poster
Poster Size
48 x 36
Start Date
22-3-2024 2:30 PM
End Date
22-3-2024 3:45 PM
Abstract
While the rapid expansion in the number of Plug-in Electric Vehicles (PEVs) signifies important progress in the implementation of green technology, the accompanying increase in energy demand presents severe challenges to the electric grid. Previous research has found that the majority of PEV users with household charging stations connect their vehicles after returning home from work. As PEV penetration increases, this simultaneous charging has the potential to deteriorate voltage profiles and overload distribution transformers. Measures which shift PEV charging to off-peak hours for different users can greatly benefit the grid through peak reduction and load factor maximization. In this study, a framework for the development of optimal scheduling models for household PEV charging is proposed, with the goal of minimizing peak load and electricity cost while satisfying user demand. Results are presented for a case study based on historical data from 480 existing household charging stations located in a midwestern U.S. city.
A Framework for Scheduling Household Charging of Electric Vehicles
CEC RM #201/205/209
While the rapid expansion in the number of Plug-in Electric Vehicles (PEVs) signifies important progress in the implementation of green technology, the accompanying increase in energy demand presents severe challenges to the electric grid. Previous research has found that the majority of PEV users with household charging stations connect their vehicles after returning home from work. As PEV penetration increases, this simultaneous charging has the potential to deteriorate voltage profiles and overload distribution transformers. Measures which shift PEV charging to off-peak hours for different users can greatly benefit the grid through peak reduction and load factor maximization. In this study, a framework for the development of optimal scheduling models for household PEV charging is proposed, with the goal of minimizing peak load and electricity cost while satisfying user demand. Results are presented for a case study based on historical data from 480 existing household charging stations located in a midwestern U.S. city.