Title :
Real-Time Modeling and Control of Electric Vehicles Charging Processes
Author :
Benetti, Guido ; Delfanti, Maurizio ; Facchinetti, Tullio ; Falabretti, Davide ; Merlo, Marco
Author_Institution :
Dept. of Electr., Comput. & Biomed. Eng., Univ. of Pavia, Pavia, Italy
Abstract :
This paper presents a method for the real-time management of electric vehicles (EVs) charging processes. The proposed method aims to limit the peak load and to increase the number of rechargeable EVs with respect to the scenario in which no coordination action is performed, while achieving given constraints on the power distribution system. The approach is based on a tight interaction between a scheduling algorithm and a power-flow evaluation procedure. The scheduling algorithm finds the best charging periods for each EV. The power flow procedure checks the achievement of electrical constraints and evaluates the operational parameters of the grid. Simulations are carried out on a real electricity distribution system of a medium-sized Italian city. The results show that the proposed approach increases the number of rechargeable EVs up to 33%. At the same time, the peak load is reduced by 25%. The scheduling algorithm requires an average of 50 ms to evaluate each charge request on an ordinary computer, therefore allowing its use in real-time conditions.
Keywords :
distribution networks; electric vehicles; load flow control; scheduling; EV charging process; electric vehicle charging processes control; electricity distribution system; medium-sized Italian city; power distribution system; power flow evaluation procedure; real-time management; real-time modeling; rechargeable EV; scheduling algorithm; Batteries; Cascading style sheets; Load modeling; Optimization; Power systems; Schedules; System-on-chip; Centralized control; load flow analysis; power distribution; road vehicles; scheduling;
Journal_Title :
Smart Grid, IEEE Transactions on
DOI :
10.1109/TSG.2014.2376573