Title :
Management and coordination charging of smart park and V2G strategy based on Monte Carlo algorithm
Author :
Aryanezhad, Majid ; Ostadaghaee, Elahe ; Joorabian, Mahmood
Author_Institution :
Electr. Eng. Dept., Shahid Chamran Univ., Ahvaz, Iran
Abstract :
Charging of plug-in-hybrid-electric vehicles (PHEVs) may adversely affect electric grid reliability because a large amount of additional electrical energy is required to charge the PHEVs. In this paper, a comprehensive method to evaluate the system reliability concerning the stochastic modeling of PHEVs, renewable resources, availability of devices, etc. is proposed. This method, which consists of managed charging and vehicle-to-grid (V2G) scenarios, can be practically implemented in smart grids because the bidirectional-power-conversion technologies and two-way of both the power and data are applicable. The results showed that the smart grid´s adequacy was jeopardized by using the PHEVs without any managed charging schedule. The sensitivity analyses results illustrated that by using the management scenarios, not only did the PHEVs not compromise the system reliability, but also in the V2G scenario acted as storage systems and improved the well-being criteria and adequacy indices.
Keywords :
Monte Carlo methods; hybrid electric vehicles; power system management; reliability; sensitivity analysis; smart power grids; stochastic processes; Monte Carlo algorithm; PHEV; V2G strategy; bidirectional power conversion technologies; plug-in hybrid electric vehicles; sensitivity analyses; smart electric grid reliability; smart park coordination charging; smart park management; stochastic modeling; vehicle-to-grid scenarios; Batteries; Load modeling; Power generation; Reliability; Schedules; Smart grids; System-on-chip; Management Charging; Monte Carlo Algorithm; PHEV; Reliability; V2G;
Conference_Titel :
Smart Grid Conference (SGC), 2014
Print_ISBN :
978-1-4799-8313-1
DOI :
10.1109/SGC.2014.7090887