Title :
Cost optimization of energy purchase for EV fleets based on a Markovian EV charging model
Author :
Schmutzler, Johannes ; Rietfort, Carsten ; Wietfeld, Christian
Author_Institution :
Commun. Networks Inst., Dortmund Univ. of Technol., Dortmund, Germany
Abstract :
This work analyses potential energy purchase strategies for an ICT-enabled and active charge management of a large fleet of electric vehicles in order to minimize applicable costs for the purchase of energy at Day-Ahead or Intraday spot markets. The optimization potential for energy purchase is leveraged through a Markovian electric vehicle charging model and on the basis of empirical data for mobility patterns of vehicles as well as actual spot market data. Two scenarios with different charging characteristics of the EV fleet are investigated. In a commuter scenario, where the fleet of EVs charges during daytime (7:00AM-3:30PM), we found that volatility in spot market prices from Q4/2011-Q3/2012 may have allowed for cost optimization of up to 13% compared to entirely unmanaged charging. In a parcel delivery service scenario, the fleet of EVs charges during nighttime (6:00PM-6:00AM), which allows for cost optimization of up to 34% based on the same period for spot market data.
Keywords :
Markov processes; battery management systems; costing; electric vehicles; information technology; optimisation; power engineering computing; power markets; purchasing; secondary cells; EV fleets; ICT-enabled charge management; Markovian EV charging model; Markovian electric vehicle charging model; active charge management; cost optimization; day-ahead spot markets; electric vehicles; energy purchase strategies; intraday spot markets; mobility patterns; spot market prices; Analytical models; Batteries; Indexes; Optimization; Quality of service; Schedules; System-on-chip; EV Charging Model; EV Fleet Management; Energy Purchase; Markov;
Conference_Titel :
Electric Vehicle Symposium and Exhibition (EVS27), 2013 World
Conference_Location :
Barcelona
DOI :
10.1109/EVS.2013.6914750