Developing an Artificial Neural Network (ANN) to Forecast EVs' Trip Destinations and Charging Behavior

Electric vehicle (EV) adoption rates are rising in California as a result of successful state air pollution mitigation regulations such as the Zero Emission Vehicle mandate. While this is a great feat for reducing local air pollution throughout the state, improperly managed EV charging can lead to peak electricity demand loads that can strain local distribution networks and potentially increase point source emissions from power plants. This problem can be solved if a straight forward algorithm can handle this uncertainty by estimating the accurate rate of load demand that is needed. Smart charging is one of the most promising approaches to prevent sub-optimal EV charging as it enables utility operators to control EV charging to reduce load spikes and take full advantage of renewable power. The researchers aim to develop an Artificial Neural Network (ANN) to forecast EVs’ trip destinations and charging behavior–information that is essential for electricity load aggregators to effectively manage charging loads.

• Record URL:
  https://ncst.ucdavis.edu/project/developing-artificial-neural-network-ann-forecast-evs-trip-destinations-and-charging

Language

• English

Project

• Status: Active
• Funding: $61000
• Contract Numbers:

  DOT 69A3551747114

• Sponsor Organizations:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Davis

  1 Shields Ave
  Davis, California  United States  95616

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Davis

  1 Shields Ave
  Davis, California  United States  95616
• Project Managers:

  Iacobucci, Lauren

• Performing Organizations:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Davis

  1 Shields Ave
  Davis, California  United States  95616
• Principal Investigators:

  Tayarani, Hanif

  Tal, Gil

• Start Date: 20201001
• Expected Completion Date: 20230930
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Electric automobiles; Electric vehicle charging; Forecasting; Neural networks
• Subject Areas: Energy; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01778680
• Record Type: Research project
• Source Agency: National Center for Sustainable Transportation
• Contract Numbers: DOT 69A3551747114
• Files: UTC, RIP
• Created Date: Aug 4 2021 8:21PM