DocumentCode
648057
Title
Reliability assessment of integrated residential distribution and PHEV systems using Monte Carlo simulation
Author
Zhu Wang ; Rui Yang ; Lingfeng Wang ; Jun Tan
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, Toledo, OH, USA
fYear
2013
fDate
21-25 July 2013
Firstpage
1
Lastpage
5
Abstract
Plug-in hybrid electric vehicles (PHEVs) are an increasingly attractive response to the future transportation challenges because of their potential economic and environmental benefits. When integrating PHEVs into the distribution system, it is necessary to evaluate the impact of PHEVs on distribution system reliability from the perspective of system adequacy. This paper develops a probabilistic reliability model for integrated distribution and PHEV systems. A comprehensive and time sequential Monte Carlo simulation method is applied to generate the artificial operation history for each component of a residential distribution system, and a complete simulation procedure considering the PHEVs integration is proposed. The IEEE-34 feeder system is utilized as the residential distribution network in case studies, and simulation results are presented and discussed.
Keywords
IEEE standards; Monte Carlo methods; distribution networks; electric vehicles; probability; reliability; transportation; IEEE-34 feeder system; Monte Carlo simulation; PHEV systems; artificial operation history; distribution system reliability; environmental benefits; integrated distribution; integrated residential distribution; plug-in hybrid electric vehicles; probabilistic reliability model; reliability assessment; residential distribution network; residential distribution system; time sequential Monte Carlo simulation method; transportation; History; Hybrid electric vehicles; Indexes; Interrupters; Monte Carlo methods; Power system reliability; Reliability; Distribution system; Monte Carlo simulation; Plug-in hybrid electric vehicle; Reliability assessment;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location
Vancouver, BC
ISSN
1944-9925
Type
conf
DOI
10.1109/PESMG.2013.6672618
Filename
6672618
Link To Document