Impact of Increased Market Penetration of Electric Vehicles on the PJM Regional Electric Grid
Open Access
- Author:
- Humenik, Dylan James
- Area of Honors:
- Energy Engineering
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Dr. Mort D Webster, Thesis Supervisor
Dr. Sarma V Pisupati, Thesis Honors Advisor - Keywords:
- Electric Vehicle
Electric Car
Economic Dispatch
unit commitment
electricity
PJM
electric grid
EV
charging
IEEE
market
market penetration
regional grid
grid
energy
power
engineering
EME
generation
generator
wind
solar
nuclear
coal
gas
biomass
control algorithm
constraint
charging window - Abstract:
- This paper analyzes an increased market penetration of electric vehicles in the Classic PJM regional electric grid, and its effect on the dispatch of generators. A unit commitment model was used to create an hour-by-hour generator dispatch schedule for a 168-hour week in PJM. The additional demand placed on the electric grid by increased usage of electric vehicles was modeled using two extreme scenarios and an intermediate scenario. Electric vehicles were assumed to charge within a 13-hour charging window during nighttime hours. Scenario 1 assumed no control algorithm to manage EV demand, and thus resulted in a large spike in demand at the onset of the charging window. Scenario 2 assumed that a perfect control algorithm was present to spread out all EV charging demand across the 13-hour charging window. In reality, a control algorithm implemented through a future smart grid would likely result in an hourly demand curve somewhere in between these two extreme scenarios, thus, an intermediate scenario (Scenario 3) where the EV demand is ramped up and down around the beginning and end of the charging window, respectively, was also analyzed. Three EV market penetrations were analyzed: 0.2, 0.5, and 1.0. When EV demand was added to existing demand in the 168-hour week, the unit commitment model produced an economic dispatch schedule that met demand but raised costs, as expected. Scenario 1 resulted in the highest costs, while significant savings were achieved in Scenario 2 and Scenario 3. As EV market penetration increased, these cost savings became even more pronounced. Scenario 3 had a slight advantage over Scenario 2 in cost savings, but both cut costs significantly from Scenario 1.