Unit Commitment Considering Multiple Charging and Discharging Scenarios of Plug-in Electric Vehicles

被引:0
|
作者
Yang, Zhile [1 ]
Li, Kang [1 ]
Niu, Qun [2 ]
Foley, Aoife [3 ]
机构
[1] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT9 5AH, Antrim, North Ireland
[2] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China
[3] Queens Univ Belfast, Sch Mech & Aerosp Engn, Belfast BT9 5AH, Antrim, North Ireland
关键词
RENEWABLE ENERGY-SOURCES; EVOLUTIONARY ALGORITHM; HARMONY SEARCH; HYBRID; POWER; UNCERTAINTY; IMPACT; COST;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Electric vehicles provide an opportunity to reduce fossil fuel consumptions and to decrease the emissions of greenhouse gas and air pollutants from the transport sector. The adoption of a large number of plug-in electric vehicles however imposes significant impacts on the power system operation due to uncertain charging and discharging patterns. In this paper, multiple charging and discharging scenarios of electric vehicles together with the grid integration of renewable energy sources are examined and evaluated within the unit commitment problem. A quantum-inspired binary particle swarm optimization method is employed to determine the on/off status of each unit. Comparative studies show that the off-peak charging and peak discharging scenario is a viable option to significantly reduce the economic cost and to complement the renewable energy generation.
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页数:8
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