In this paper an optimization approach to devise efficient management strategies for Electric Vehicles parking lots is proposed. A Monte Carlo approach is used to evaluate the load consumption profile for groups of Electric Vehicles showing different features. The Monte Carlo approach allows to combine the different social and economical features affecting the commercial penetration of Electric Vehicles with the technical aspects. The basic feature to be assessed is the initial State Of Charge, which in turn depends on the distance travelled by the vehicle since the last recharge and thus by the usage of the vehicle (private, professional). The model is then used to optimize some objective function such as the losses minimization or the cost of purchased energy minimization. Finally, a Simulated Annealing algorithm is used to identify the time intervals, along the day, in which the Electric Vehicles should be put in charge to minimize technical or economical objectives. The objective function is evaluated using a probabilistic model based on Monte Carlo simulations. © 2013 Springer-Verlag Berlin Heidelberg.
|Pages (from-to)||641 - 649|
|Number of pages||9|
|Journal||Journal of Ambient Intelligence and Humanized Computing|
|Publication status||Published - Dec 2013|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
Di Silvestre, M. L., Riva Sanseverino, E., Zizzo, G., & Graditi, G. (2013). An optimization approach for efficient management of EV parking lots with batteries recharging facilities. Journal of Ambient Intelligence and Humanized Computing, 4(6), 641 - 649. https://doi.org/10.1007/s12652-013-0174-y