Title :
Impact of a large fleet of EVs on the efficiency and reliability of an electric power system
Author :
Giglioli, Romano ; Giuntoli, Marco ; Lutzemberger, Giovanni ; Poli, Davide
Author_Institution :
Dept. of Energy, Syst., Territory & Constructions Eng., Univ. of Pisa, Pisa, Italy
Abstract :
The influence of electric vehicles on the power system has been traditionally analyzed in terms of recharge infrastructures and adequacy of the electric distribution network. Nevertheless, the additional power demand due to the recharge of a large number of batteries could significantly modify the national load profile, hence the dispatching of production plants. The recent literature approaches this issue using deterministic methods or simplified probabilistic considerations. In this framework, the present paper proposes the use of a Monte Carlo probabilistic approach to assess the impact of large fleet of EVs on the efficiency and reliability of the generating park of an electric power system. A Sequential Monte Carlo simulator has been developed and applied to the hourly operation of the Italian power system. Several 2020 scenarios, diversified in terms of number of vehicles and recharge timing, have been assumed for the future fleet of EVs. The study was mainly realized within the PRIME project, funded by the Italian Ministry for the Environment.
Keywords :
Monte Carlo methods; battery powered vehicles; power generation reliability; probability; EV; Italian Ministry for the Environment; Italian electric power system; Monte Carlo probabilistic approach; PRIME project; battery electric vehicle; deterministic method; electric distribution network; production plant dispatching; reliability; sequential Monte Carlo simulator; Load modeling; Monte Carlo methods; Power generation; Power system reliability; Production; Reliability; Efficiency; Electric Vehicles; Mobility; Power Systems; Reliability;
Conference_Titel :
Electric Vehicle Conference (IEVC), 2014 IEEE International
DOI :
10.1109/IEVC.2014.7056090