Title :
Optimal charging strategy algorithm for PEVs: A Monte Carlo validation
Author :
Baccino, Francesco ; Grillo, Samuele ; Massucco, Stefano ; Silvestro, Federico
Author_Institution :
DITEN, Univ. degli Studi di Genova, Genoa, Italy
Abstract :
This paper proposes the validation of an optimal charging strategy for plug-in electric vehicles (PEVs). The algorithm is composed of two phases and is intended to be used by Distribution System Operator (DSO) to properly manage the network. The effectiveness of the optimization algorithm, described in a previous work, is tested through Monte Carlo simulations. The proposed algorithm has evaluated and compared with a dumb charging strategy. The low voltage CIGRE benchmark grid for 5 years was simulated considering 300 PEVs. In addition, a different set of Monte Carlo simulations was run with random-though reasonable-load profiles in order to test the robustness of the algorithm. The traditional and newly proposed power-systemrelated indices were calculated for all of the simulation sets.
Keywords :
Monte Carlo methods; battery powered vehicles; battery storage plants; distribution networks; optimisation; power grids; DSO; Monte Carlo simulations; Monte Carlo validation; PEV; distribution system operator; low voltage CIGRE benchmark grid; optimal charging strategy algorithm; plug-in electric vehicles; power system; random-though reasonable-load profiles; Density functional theory; Indexes; Load forecasting; Load modeling; Monte Carlo methods; Optimization; Predictive models; Plug-in electric vehicle (PEV); SAIDI; SAIFI; optimal dispatching; optimal power flow; recharge optimization;
Conference_Titel :
Electric Vehicle Conference (IEVC), 2014 IEEE International
DOI :
10.1109/IEVC.2014.7056188
