Abstract
The transition in the transport sector towards
battery-electric public transport (bus fleets) will present
challenges to distribution system operator with regard to
estimating and serving the demand peak with the present grid
infrastructure. An understanding of the expected charging
profile can provide knowledge about the peak load and its time
of occurrence. This paper presents a generic mathematical
formulation for a tool to generate the charging profile for
battery-electric vehicle fleet operators, which uses information
about the bus fleet's characteristics to generate different
scenarios concerning the charging demand profile, peak
demand, and region of flexibility for the minimum and
maximum number of chargers needed. The paper then uses city
bus operator AtB in Trondheim, Norway as a real-life test case
for this tool. Results show that the peak demand varies from 300
kW to 1050 kW, and the bus fleet operator can provide
flexibility between 40 % and 231 % of their daily energy
demand.
battery-electric public transport (bus fleets) will present
challenges to distribution system operator with regard to
estimating and serving the demand peak with the present grid
infrastructure. An understanding of the expected charging
profile can provide knowledge about the peak load and its time
of occurrence. This paper presents a generic mathematical
formulation for a tool to generate the charging profile for
battery-electric vehicle fleet operators, which uses information
about the bus fleet's characteristics to generate different
scenarios concerning the charging demand profile, peak
demand, and region of flexibility for the minimum and
maximum number of chargers needed. The paper then uses city
bus operator AtB in Trondheim, Norway as a real-life test case
for this tool. Results show that the peak demand varies from 300
kW to 1050 kW, and the bus fleet operator can provide
flexibility between 40 % and 231 % of their daily energy
demand.
