DocumentCode :
1725194
Title :
Unit commitment with vehicle-to-Grid using particle swarm optimization
Author :
Saber, Ahmed Yousuf ; Venayagamoorthy, Ganesh Kumar
Author_Institution :
Real-Time Power & Intell. Syst. Lab., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear :
2009
Firstpage :
1
Lastpage :
8
Abstract :
Vehicle-to-Grid (V2G) technology has drawn great interest in the recent years. Success of the V2G research depends on efficient scheduling of gridable vehicles in limited parking lots. V2G can reduce dependencies on small expensive units in the existing power systems as energy storage that can decrease running costs. It can efficiently manage load fluctuation, peak load; however, it increases spinning reserves and reliability. As number of gridable vehicles in V2G is much higher than small units of existing systems, unit commitment (UC) with V2G is more complex than basic UC for thermal units. Particle swarm optimization (PSO) is used to solve the UC with V2G, as PSO can reliably and accurately solve complex constrained optimization problems easily and quickly without any dimension limitation and physical computer memory limit. In the proposed model, binary PSO is used to optimize the on/off states of power generating units and in the same model, discrete version of PSO is used to optimize the scheduling of the gridable vehicles in the parking lots to reduce the dimension of the problem. Finally, simulation results show a considerable amount of profit for using V2G after proper UC with V2G scheduling of gridable vehicles in constrained parking lots.
Keywords :
particle swarm optimisation; power generation dispatch; power generation scheduling; V2G technology; binary PSO; complex constrained optimization problems; energy storage; gridable vehicles; limited parking lots; load fluctuation; particle swarm optimization; power generating units; power systems; thermal units; unit commitment; vehicle-to-grid technology; Constraint optimization; Costs; Energy storage; Fluctuations; Load management; Particle swarm optimization; Power system management; Power system reliability; Spinning; Vehicles; Unit commitment; V2G; generating units; gridable vehicles; parking lots; particle swarm optimization; profit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
Type :
conf
DOI :
10.1109/PTC.2009.5282201
Filename :
5282201
Link To Document :
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