Intelligent Energy Management of Electric Vehicles in Distribution Systems
Student thesis: Master Thesis and HD Thesis
- Alberto Palomar Lozano
4. term, Energy Engineering, Master (Master Programme)
In this short master thesis an optimal charging and discharging
algorithm for Electric Vehicles and a later verification
of the results in a distribution system are presented.
A first algorithm without EVs is run to determine the ordinary
cost and the normal loading conditions of the distribution
system. The second algorithm includes the electric
vehicles and minimises the total cost of the system attending
to economic criteria. Both algorithms were programmed
using GAMS software. Three different caseswere
created and three hourly prices from different days were
used along the project for running all the simulations.
Optimal 24 hours charging and discharging plans are obtained
respecting all the technical constraints from the
EVs. These results are later validated in DIgSILENT PowerFactory
using four different EVs distribution to check the
technical constraints of the system.
An economic analysis is also performed to determine if the
system cost is reduced by the intelligent management of
the energy and the use of the V2G technology.
algorithm for Electric Vehicles and a later verification
of the results in a distribution system are presented.
A first algorithm without EVs is run to determine the ordinary
cost and the normal loading conditions of the distribution
system. The second algorithm includes the electric
vehicles and minimises the total cost of the system attending
to economic criteria. Both algorithms were programmed
using GAMS software. Three different caseswere
created and three hourly prices from different days were
used along the project for running all the simulations.
Optimal 24 hours charging and discharging plans are obtained
respecting all the technical constraints from the
EVs. These results are later validated in DIgSILENT PowerFactory
using four different EVs distribution to check the
technical constraints of the system.
An economic analysis is also performed to determine if the
system cost is reduced by the intelligent management of
the energy and the use of the V2G technology.
Language | English |
---|---|
Publication date | 31 Dec 2012 |
Number of pages | 76 |
Publishing institution | AAU - Study of Energy Engineering |