Abstract
This paper presents a new approach to Vehicle-to-Grid (V2G) scheduling. V2G technology has drawn great interest in the recent years. It can efficiently manage load fluctuation, peak load; however, it increases spinning reserves and reliability. V2G can reduce dependencies on small expensive units in the existing power systems as energy storage that can decrease running costs. Success of the V2G research depends on efficient scheduling of grid able vehicles in limited parking lots. as number of grid able 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, 2 versions of PSO are used in the same model to optimize the on/off states of power generating units and grid able 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 grid able vehicles in constrained parking lots.
Recommended Citation
A. Y. Saber and G. K. Venayagamoorthy, "V2G Scheduling - a Modern Approach to Unit Commitment with Vehicle-to-Grid using Particle Swarm Optimization," IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 42, no. 9, pp. 261 - 266, Institute of Electrical and Electronics Engineers, Jan 2009.
The definitive version is available at https://doi.org/10.3182/20090705-4-SF-2005.00047
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Generating units; Gridable vehicles; Parking lots; Particle swarm optimization; Unit commitment; V2G
International Standard Serial Number (ISSN)
1474-6670
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2009
Comments
National Science Foundation, Grant 0348221