Estimating Potential Demand for Electric Vehicles (EVs) Michael K. Hidrue and George R. Parsons Camp Resources XVII Wrightsville Beach, NC June 24-25, 2010 Sponsored by: US Department of Energy, Office of Electricity Delivery and Reliability

Outline Objective Study design Estimation results WTP estimates Conclusion 1

Estimate potential market demand for EVs Assess the value of adding V2G on demand for EVs V2G vehicles are special type of EVs that allow people to sell power from their batteries back to electric companies. 2 Objectives

Study Design Web based choice experiment National Survey, N=3029 Sample resembles national census data Latent class random utility model 3

Sample EV Choice Set 4

Results: Number of Latent Classes BIC identified two latent classes The EV class has positive EV constant, high value for fuel saving and tend to be green The GV class has negative EV constant, low value for fuel cost saving and tend not to be green 5 EV class GV class

Results: Class Membership Model Variable CoefficientT-statOdds ratio Constant Young (25-35yrs old) Middle age ( yrs old) Expected gas price in 5 years Change in life style & shopping habit : Major Change in life style & shopping habit: Minor Having access for installing charger Expected next vehicle: Hybrid Multicar household College (>=B.A) Male Four more variables… 6

Results: Vehicle Choice Model Attributes Parameters Prob. Weighted Implicit Prices GV classEV class Coef.T-stat.Coef.T-stat. EV constant $9,337* Yea saying Price-1.8E E Pr *pr on GV4.1E E Fuel cost $2,764 7 *=value of yea saying is subtracted from the constants

Results: Vehicle Choice Model Continued Attributes Parameters Probability weighted Implicit Prices GV classEV class Coef.T-stat.Coef.T-stat. Driving range (Ref=75 mi) 150 mi $5, mi $8, mi $11,391 Charging time for 50 mi (Ref=10 hrs) 5 hours $2,136 1 hour $5, minutes $8,567 8

Results: Vehicle Choice Model Continued Attributes Parameters Probability weighted Implicit Prices GV classEV class Coef.T-stat.Coef.T-stat. Acceleration relative to respondent’s next car (Ref=20% slower) 5% slower $1,957 5% faster $4,372 20% faster $6,521 Pollution relative to respondent’s next car (Ref=25% lower) 50% lower $636 75% lower $1,428 95% lower $3,333 9

Top 10% WTP Estimates 10 Assumptions: Fuel cost=$1.00/gal equivalent Acceleration=5% slower Pollution=75% lower

Comparing WTP Estimates with Battery Cost Estimates 11

Comparing WTP and Battery Cost Estimates 12

Comparing WTP and Battery Cost Estimates in the Presence of Subsidy 13

Conclusion Driving range, charging time and performance are significant drivers of EV choice Green life style, hybrid buyer, outlet access, expected gas price and age are significant predictors of EV choice Multicar household, college education and regions are not significant predictors of EV choice People will pay premium for some EV designs For EVs to compete on the market, battery cost has to decline substantially. 14