Open AccessAn intelligent control strategy for vehicle-to-grid and grid-to-vehicle energy transfer
Author(s) -
Vinayak Laxman Patil,
M R Sindhu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/561/1/012123
Subject(s) - electric vehicle , grid , automotive engineering , control (management) , fuzzy logic , state of charge , transfer (computing) , work (physics) , charging station , parking lot , computer science , transport engineering , engineering , power (physics) , battery (electricity) , mechanical engineering , physics , geometry , mathematics , civil engineering , quantum mechanics , artificial intelligence , parallel computing
In this work a Fuzzy logic based control strategy for Vehicle to Grid and Grid to Vehicle energy transfer with pricing strategy for EV(Electric vehicle) and PHEV(Plug-in Hybrid Electric Vehicles) is proposed. The method proposed allows the vehicles in the public charging station or in home to intelligently charge/discharge based on the preferences of owner also taking care of grid safe operational conditions. The system discussed in this work will charge or discharge the vehicles by assigning priorities among the vehicles at the public parking infrastructure based on information of initial State of Charge of vehicle, State of Charge to be achieved at the end of charging/discharging, duration for which vehicle stays in parking infrastructure, and also proposes pricing strategy based on prediction technique to maintain uniform energy consumption of EV or PHEV on day-to-day basis. By the proposed method these charging and discharging mechanics of EV or PHEV can be leveled, scheduled, and managed intelligently.