1
Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
Abstract
Estimation of aggregated electric vehicle charging demand is essential for better design of future distribution networks. Given that the penetration level of electric vehicles is currently very low, Hence, the precise statistical data are not available to determine the initial state of charge related to electric vehicles. this paper proposes a new model for calculating the initial state of charge in electric vehicles. The proposed model is a function of fuel consumption of the conventional gasoline vehicles and all driving behaviors such as the use of air conditioning, vehicle speed, road slope etc. have been considered. Also, unlike most of the papers that have specific outputs for the distribution network parameters, in this paper, the mentioned parameters are presented as probability functions. Finally, the proposed method is applied to the IEEE-37 node test feeder and simulation results are presented to illustrate its performance.
Pouladi, J., Bannae Sharifian, M. B., & Soleymani, S. (2018). Probabilistic Modeling of Aggregated Electric Vehicle Charging Demand in Residential Distribution Network. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47(4), 1357-1369.
MLA
J. Pouladi; M. B. Bannae Sharifian; S. Soleymani. "Probabilistic Modeling of Aggregated Electric Vehicle Charging Demand in Residential Distribution Network". TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47, 4, 2018, 1357-1369.
HARVARD
Pouladi, J., Bannae Sharifian, M. B., Soleymani, S. (2018). 'Probabilistic Modeling of Aggregated Electric Vehicle Charging Demand in Residential Distribution Network', TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47(4), pp. 1357-1369.
VANCOUVER
Pouladi, J., Bannae Sharifian, M. B., Soleymani, S. Probabilistic Modeling of Aggregated Electric Vehicle Charging Demand in Residential Distribution Network. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 2018; 47(4): 1357-1369.