An Agent-Based Model of Energy Demand and Emissions from Plug-in Hybrid Electric Vehicle Use

Energy Demand;Plug-in Hybrid Electric Vehicles;Natural Resources and Environment

Stephens, ThomasSullivan, John ;

University of Michigan

关键词: Energy Demand;    Plug-in Hybrid Electric Vehicles;    Natural Resources and Environment;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/77595/Stephens_MSthesis_final.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

An agent-based model, the Driver Vehicle Use Decision (DVUD) model, was developed that uses simple assumptions about travel demand and statistical information on travel by U.S. drivers. From these, and data on the greenhouse gas (GHG) emissions from the fuel supply network and from electric utilities, the electricity and fuel demand and the resulting GHG emissions are estimated.This model represents a population of drivers as agents, some of whom drive plug-in hybrid electric vehicles (PHEVs). Driver agents make decisions about how frequently to drive trips and when to recharge their PHEV batteries. In deciding whether to take trips, driver agents consider their schedule and travel cost. They also consider cost, location and planned length of time they will stay at a location when deciding whether to recharge their PHEV batteries. This enables the agents to respond to changes in electricity rates and gasoline prices and to constraints on when (time of day) and where (home or both home and work) they can recharge PHEV batteries.For a fleet penetration of 50% by PHEVs in Michigan, with a total fleet of 7.3 million vehicles, gasoline consumption is projected to decrease from 11.4 million gallons per day to 7.4 million gallons per day. Total fuel-cycle greenhouse gas emissions from the fleet are projected to decrease from 128,000 metric tons CO2 eq/day to 95,000 metric tons CO2 eq/day. Peak electricity demand for PHEV charging is projected to reach about 1400 MW. Most PHEV charging is projected to occur overnight, with the peak in charging demand occurring soon after most drivers get home in the evening.Model results show that PHEV drivers are less sensitive to changes in gasoline prices than drivers of less fuel-efficient conventional vehicles. Response to changes in electricity prices is more complex, with drivers showing little or no response at low electricity rates, but not charging at all at very high electricity rates, depending on the price of gasoline and the efficiency of their vehicle.Under interruptible electricity service, in which the electric utility shuts off power to PHEV chargers during peak demand hours, nearly all PHEV owners were able to fully charge their vehicles overnight, and there was very little impact on PHEV operating cost, indicating that this may be a feasible approach to managing increased electric demand for PHEV charging.