DocumentCode :
648026
Title :
Optimal dispatch of plug-in hybrid electric vehicles to reduce the load fluctuations on distribution networks
Author :
Guibin Wang ; Fushuan Wen ; Zhao Xu ; Kit Po Wong
Author_Institution :
Dept. of Electr. Eng., Zhejiang Univ., Hangzhou, China
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
5
Abstract :
Rapid development of plug-in hybrid electric vehicles brings new challenges to the security and economy of power systems. As a clean and environmental friendly technology, the electric vehicle presents the future solution of transportation with high potentials. Currently rapid deployment of electric vehicles is taking place in many countries. However, uncoordinated charging of many plug-in hybrid electric vehicles (PHEVs) may cause serious impacts on the security and economy of power system operation. The paper proposes a new dispatch model to reduce the fluctuations of PHEV charging loads, based on the probabilistic analysis of charging behaviors of PHEVs and other demands in power systems. Genetic algorithm method is adopted to solve this optimization problem. The feasibility and efficiency of the developed stochastic dispatch model is demonstrated with a 33-bus distribution network.
Keywords :
genetic algorithms; hybrid electric vehicles; power distribution economics; power generation dispatch; power system security; 33-bus distribution network; PHEV charging loads; genetic algorithm; load fluctuations; optimal dispatch; optimization problem; plug-in hybrid electric vehicles; power system economy; power system operation; power system security; probabilistic analysis; stochastic dispatch model; transportation; Fluctuations; Genetic algorithms; Load flow; Load modeling; Power system stability; Vehicles; Wind power generation; distribution network; genetic algorithm; optimal dispatch; plug-in hybrid electric vehicles;
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.2013.6672583
Filename :
6672583
Link To Document :
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