Title :
Anticipative charging of Plug-in Electric Vehicles and its impact on the grid
Author :
Kefayati, Mahdi ; Baldick, Ross
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA
Abstract :
Transportation electrification is deemed to have profound impacts on both transportation and electricity networks as well as our dependence on fossil fuels. Therefore, it is imperative to understand the impacts of this transition and prepare for it. Most of the literature on Plug-in Electric Vehicle (PEV) charging models treat charging sessions independently and ignore their interdependence. In this work, we argue the importance of understanding this interdependence, propose the anticipative charging model, and investigate its effect on PEV demand flexibility, PEV charging demand and the grid. We demonstrate that the anticipative behavior of the drivers, i.e. their (partial) knowledge of their transportation plan in near future, results in less overall flexibility in the PEV load. However, under certain conditions, it positively impacts the overall PEV load by moving it toward off peak hours.
Keywords :
electric vehicles; power grids; transportation; PEV anticipative charging demand; driver anticipative behavior; electricity network; plug-in electric vehicle grid; transportation electrification; Biological system modeling; Electric vehicles; Electricity; Load modeling; Optimization;
Conference_Titel :
Transportation Electrification Conference and Expo (ITEC), 2014 IEEE
Conference_Location :
Dearborn, MI
DOI :
10.1109/ITEC.2014.6861805