Title :
Analysis of multi-location PEV charging behaviors based on trip chain generation
Author :
Dai Wang ; Xiaohong Guan ; Jiang Wu ; Junyu Gao
Author_Institution :
Key Lab. for Intell. Networks & Network Security (MOE KLINNS), Xi´an Jiaotong Univ., Xi´an, China
Abstract :
In this paper, we focus on analyzing multi-location charging behaviors of plug-in electric vehicles (PEVs) under the Time-of-Use (TOU) pricing scheme. Trip chain model incorporating the information on start time, end time, driving distance, start location and end location of each trip is used to depict the sequence of daily driving missions. Statistical distributions of travel patterns are fitted from a real-world driving dataset. Then a method is developed to generate the complete trip chain of each individual PEV. Simulation results show that due to the TOU price, people prefer the overnight charging at home, although workplace charging can support PEVs with smaller battery capacities and long-distance commute trips. Furthermore, with a large enough battery capacity, charging at workplaces will not be necessary if vehicle-to-grid (V2G) technology is not considered. Although high charging power accelerates PEV´s charging processes during price-valley periods, it imposes higher requirements on the charging facilities and distribution grid.
Keywords :
battery powered vehicles; power distribution economics; power grids; secondary cells; statistical distributions; PEV charging process; TOU pricing scheme; V2G technology; long distance commute trip chain model; multilocation PEV charging behavior analysis; overnight charging; plug-in electric vehicle driving dataset; price valley period; smaller battery capacity; time-of-use pricing scheme; travel pattern statistical distribution grid; vehicle-to-grid technology; workplace charging; Batteries; Educational institutions; Electricity; Employment; Load modeling; Statistical distributions; Vehicles; PEV; charging load; multi-location charging; travel pattern; trip chain;
Conference_Titel :
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
Conference_Location :
Taipei
DOI :
10.1109/CoASE.2014.6899319