Volume 16, Issue 1 (JIAEEE Vol.16 No.1 2019)
Journal of Iranian Association of Electrical and Electronics Engineers 2019, 16(1): 31-39 |
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Varshosaz F, Moazzami M, Fani B. Scheduling and Stochastic Capacity Estimation of an EV Charging Station with PV Rooftop Using Queuing Theory and Random Forest. Journal of Iranian Association of Electrical and Electronics Engineers 2019; 16 (1) :31-39
URL: http://jiaeee.com/article-1-864-en.html
URL: http://jiaeee.com/article-1-864-en.html
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najaf Abad, Iran
Abstract: (4278 Views)
Power capacity of EV charging stations could be increased by installing PV arrays on their rooftops. In these charging stations, power transmission can be two-sided when needed. In this paper a new method based on queuing theory and random forest algorithm proposed to calculate net power of charging station considering random SOC of EV’s. Due to estimation time constraints, a queuing model with limited input and capacity used to model arrival and departure of EV’ and a relationship proportional to SOC of EV’s in which they arrive to the charging station has been suggested. To demonstrate impact of photovoltaic rooftop, a model based on Random Forest suggested for estimation of maximum output power of PV array. In simulation process, charge and discharge operations for Nissan and Tesla EV’s is done by writing a priority list and real efficiency of charger/inverter in AC level II operation conditions. Simulation results show that proposed method is a precise and efficient model for scheduling and capacity estimation of V2G parking lots with PV rooftop.
Keywords: Charging station, PV array, distribution grid, service time, queuing theory, finite source queue model, finite capacity queue model, random forest.
Type of Article: Research |
Subject:
Power
Received: 2019/04/28 | Accepted: 2019/04/28 | Published: 2019/04/28
Received: 2019/04/28 | Accepted: 2019/04/28 | Published: 2019/04/28
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