Challenges and Opportunities for Electric Vehicle Charging Detection Using Utility Energy Consumption Data

Partly in response to ongoing environmental and energy security concerns, and with supportive government policies, the total number of electric vehicles (EVs) has been rapidly increasing in the last years worldwide. The growing EV penetration into the electric power system changes the electricity consumption profiles and leads to challenges for different stakeholders such as transmission system operators and electric utilities. Electric utilities benefit from having information of EV charging to forecast any additional load and peaks, to understand temporal and spatial aspects, and to schedule or avoid distribution network upgrades. However, as for now, in most cases, customers do not report to their utility their EV purchase; as a result, utilities have no information about any additional load. This paper explores and evaluates the ability to detect EV charging events using only electricity consumption data from utilities. Pacific Gas and Electric (PG&E) energy consumption data from approximately 144 households located in PG&E service area in California are analyzed and used to remove EV charging load. These PG&E customers are EV owners of BMW battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Telematics event data from these vehicles are used for evaluation. From the data mining and processing of this analysis, EV load disaggregation appears to be very challenging with several limitations. Future work ideas towards the successful charging detection are described.

  • Order URL:
  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC70 Standing Committee on Transportation Energy.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Apostolaki-Iosifidou, Elpiniki
    • Woo, Soomin
    • Lipman, Timothy
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01698021
  • Record Type: Publication
  • Report/Paper Numbers: 19-05695
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:44AM