CSTPR Noontime Seminar: The Human Dimensions of Plug-In Hybrid Electric Vehicles in Boulder

I will be in the air, so can’t see this.. a bit off our usual topics but related, and sounded very interesting…
Here’s the link. It’s at 12 MT.

Abstract: This research explores the effect of feedback from the smart grid, smart plugs, and dashboard displays on driving, vehicle charging, and household energy-use behaviors. Toyota Motor Sales, Inc., sponsored the study and provided the University of Colorado with 28 plug-in hybrid electric vehicles (PHVs) for a 2-year field-test in a smart-grid environment. In Boulder, Colorado, 23,000 households have smart meters; a stratified random sample of 142 of households volunteering for the smart-grid drove 2010 Prius PHVs for 9-week field tests. The utility partnered with the study by installing smart plugs in participant garages. Toyota’s interest was exploring the effects of real-world driving on PHV performance in extreme climatic conditions at high altitudes with mountainous terrain in a smart-grid environment. The utility’s interest was the potential impacts of PHV charging on the electricity grid. Using households and drivers as units of analysis, the University’s investigation addresses a range of topics, including the role of three types of feedback on driving and charging behavior: (1) the utility’s web portal that provided data on overall household electricity usage in 15-minute increments 15 minutes ago; (2) a garage smart plug that provided real-time data in 5-minute increments on a web portal, indicating timing, electricity usage, and frequency of vehicle charging; and (3) the vehicle’s dashboard displays which provided real-time feedback on mpg and on whether the vehicle is in battery-only or hybrid mode, among other information.
In addition to interview and questionnaire data, high-resolution data were collected from 27 vehicles and smart plugs for a period of about 1.5 years. Charging behavior and management are examined from various angles. Data analysis results include distributions of fuel economy, energy consumption, trip lengths, distance between charging events, and spatial and temporal distributions of charging events.

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