DocumentCode
1614758
Title
Vehicle to Grid — Monte Carlo simulations for optimal Aggregator strategies
Author
Sandels, Claes ; Franke, Ulrik ; Ingvar, Niklas ; Nordstrom, Lars ; Hamren, Roberth
Author_Institution
Dept. of Ind. Inf. & Control Syst., R. Inst. of Technol., Stockholm, Sweden
fYear
2010
Firstpage
1
Lastpage
8
Abstract
Previous work has shown that it could be profitable on some control markets to use Plug-in Hybrid Electric Vehicles (PHEV) as control power resources. This concept, where battery driven vehicles such as PHEVs provide ancillary service to the grid is commonly referred to as Vehicle to Grid (V2G). The idea is to sell the capacity and energy of the parked PHEVs on the control market. Due to the fact that cars on average are parked 92% of the day, the availability of this capacity could be very high, even though it will be highly dependent on commuting patterns in peak hours. However, as each PHEV has a very small capacity from a grid perspective, it is necessary to implement an aggregating control system, managing a large number of vehicles. This paper presents strategies for an Aggregator to fulfill control bids on the German control markets. These strategies are tested with respect to reliability, efficiency and profitability in a Monte Carlo simulation model. The model is based on available data on the distributions of commuting departure times and travel distances, as well as average driving power consumption, PHEV battery capacities and the market constraints of the secondary control market in Germany.
Keywords
Monte Carlo methods; battery powered vehicles; hybrid electric vehicles; Germany; PHEV; battery driven vehicles; optimal aggregator strategies; plug-in hybrid electric vehicles; vehicle to grid - Monte Carlo simulations; Aggregates; Aggregator; Control Market; Monte Carlo simulations; Plug-in Hybrid Electric Vehicles; Vehicle to Grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology (POWERCON), 2010 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-5938-4
Type
conf
DOI
10.1109/POWERCON.2010.5666607
Filename
5666607
Link To Document