Pev consumer behavior study plug in 2012 haddow v3 panel
Upcoming SlideShare
Loading in...5
×
 

Pev consumer behavior study plug in 2012 haddow v3 panel

on

  • 639 views

 

Statistics

Views

Total Views
639
Views on SlideShare
639
Embed Views
0

Actions

Likes
0
Downloads
1
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Pev consumer behavior study plug in 2012 haddow v3 panel Pev consumer behavior study plug in 2012 haddow v3 panel Presentation Transcript

  • Designing PEV InfrastructureDo PEV TOU Rates Impact PEV Charging Time Decisions? Gregory W. Haddow
  • SDG&E GoalsCreate an excellent customer experience and support thegrowth of electric transportation while ensuring thesafe, reliable & efficient integration of PEV loads with the grid Charging Technology & Infrastructure Widespread & convenient Charging Pricing Attractive to charge off-peak Utility System Integration Efficient & smart Market Development Educate & support2
  • EV Rate Participation & Ownership are Growing1,8001,600 ~1,600 Total PEVs through June 121,4001,200 701 PEV Rate Customers1,000 (Premises Metered and/or Submetered) 800 600 400 200 394 Experimental Rate Customers (Submetered PEV usage) 0 Jan11 Mar11 May11 Jul11 Sep11 Nov11 Jan12 Mar12 May12 Total Vehicles PEV Rate customers Experimental Rate Customers
  • What Drives Charging Time Decisions? PEV Rates & Technology Study – CPUC approved experimental PEV rates for EV Project & Nissan deployment• Price – Fuel Savings? AM PM Low Super Off-peak rates• Technology & Information – “Set & Forget”? On-board Leaf technology• Convenience & Lifestyle – Do Travel Needs Rule? Schedule4
  • Research Advisory Panel• San Diego Gas & Electric• UC Davis, Tom Turrentine, PHEV Research Center• EPRI, Bernie Neenan, Electric Transportation Program• University of San Diego-EPIC, Scott Anders & Nilmini Silva-Send• UC San Diego, Professor Graff Zivin & Ben Gilbert• CEC, Phil Misemer• U.S. EPA, Zoltan Jung• CCSE, Mike Ferry• SCE, Russ Garwacki• SMUD, Bill Boyce• EV Project / ECOtality, Don Karner• Coulomb Technologies, Richard Lowenthal• Boulder Energy Group, Bill Le Blanc• EEI, Rick Tempchin• CPUC Staff
  • Study ObjectiveTo examine PEV consumer charging time preferences, use of technology, and other relevant factors in a controlled study of CPUC-approved time-differentiated rates coincident with the EV Project and Nissan Leaf launch in San Diego. Working Hypotheses• Time variant pricing and technology use will influence consumer charging behavior• Greater price variations will drive more charging activity to off- peak periods• Enabling technology will facilitate charging behavior that is convenient and economic to the consumer
  • Study DesignDependent VariableTime-of-use ChargingRatio of on-peak charging kWh tooff-peak and super off-peakcharging kWh per day Independent Variable Leaf Customers Randomly Assigned to 3 Time Variant Priced Rates Each rate differing in super off-peak to on- peak price spread Conditioning Variables • Use of Enabling Technology • Driver Profile • Use of Charging Facilities
  • PEV Experimental Rates – Summer 40 35 30Cents per kWh 25 20 15 10 5 0 EV-TOU Rate 2 Rate 3 On-peak Off-peak Super Off-peak Noon to 8pm 8pm to midnight Midnight to 5am 5am to Noon
  • Separate PEV MeteringSDG&E determines House Meterlocation of the separatePEV meter (inseries), with flexibilityregarding the PEV Meterdisconnect breaker Garage Panel EVSE
  • EV TOU Rate is Effective Regardless of Price 90% 82% 83% 80% 78% 70%% of Total Consumption 60% 50% 40% 30% 20% 13% 9% 11% 10% 10% 7% 7% 0% On-Peak Off-Peak Super Off-Peak EPEV-L (N=110) EPEV-M (N=146) EPEV-H (N=138) Three Experimental EV Rate Customer Groups
  • Super Off-Peak Charging at Home is Encouraged by TOU rates 7% • Usage: 3 experimental PEV rate 11% groups kWh usage combined • Data: January 2011 to June 2012 • Super Off-Peak: Midnight to 5 am • Off-Peak: 5 am to Noon & 8 pm to Midnight 82% • On-Peak: Noon to 8 pmOn-Peak Off-Peak Super Off-Peak
  • Charging Behavior Similar Across the 3 Experimental Rate Groups Separately metered data isolates the charging use Super Off-peak usage Midnight to 5 am indicates the use of EVSE or PEV timers Hour 12 = Noon Hour 24 = Midnight
  • Slightly Less Charging on Weekends Indicates a routine driving & charging pattern, regardle ss of day of week
  • TOU Rates Influence PEV Charging TOU rates encourage off-peak charging vs. a flat rate Nashville Electric Svc, TN • 260 residential EVSE • Charge: $13.43 / month • Summer: $0.0936 / kWh • Winter: $0.0898 / kWh $ SDG&E, CA • 539 residential EVSE • TOU rates • Super off-peak: midnight to 5amSource: INL http://avt.inl.gov/pdf/EVProj/EVProjInfrastructureQ42011.pdf 14
  • PEV Driving Maturation in ~ 6 months “Charge Month” is the month after initial charge, regardless of calendar month of the PEV purchase Line denotes 3 month moving average
  • Implications • Too soon to tell if charging patterns are stable • Is fueling cost so low that charging will shift to off peak and on-peak periods over time? • It doesn’t take much pricing incentive to change behavior – 1 to 2 pricing difference between super off- peak and on-peak as effective as the 1 to 6 differential • Convenience technology works – implies smart grid technology must be simple “set and forget” in nature • If PEV rate structures becomes more complex (e.g., weekday-weekend, summer- winter, tiers), simpler technologies may be less effective16
  • Designing PEV Infrastructure Gregory W. Haddow GHaddow@SempraUtilities.com SDGE.COM/EV EV@SDGE.COM