Probabilistic estimation of aggregated power capacity of EVs for vehicle-to-grid application

Abstract

Probabilistic estimation of aggregated power capacity of EVs for vehicle-to-grid application. 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS),

Schedulable capacity forecasting for electric vehicles based on big data analysis

“…From (11), it can be seen that the PGBDT algorithm is a combined algorithm. It approximates the expected model by iterating a series of regression trees to improve the model accuracy and provides a strong predictive performance and generalization ability.…”

“…In current literature, EVSC is generally obtained using probabilistic EV models [10][11][12][13][14][15], including plug-in time probability models based on binomial distributions [10], plug-in location probability models [11] and the aggregated queuing network model [12]. In [13][14][15], a Monte Carlo method is used to simulate the behavior of different types of EVs operating under realistic conditions, including startstop time, charging rate, charging time, etc.…”

Stochastic energy storage capacity model of EV parking lots

“…It was already shown that the travelled distances of EVs and internal combustion engine (ICE) vehicles prior to the arrival at the PL were almost similar [3,13,25]. The distance travelled prior to arriving the PL was generally assumed to follow the normal distribution in the earlier studies [10,25,26]. Several researchers used the travel pattern data provided by 2009 National Household Travel Survey [25,[27][28][29].…”

“…Due to high population density of the metropolitan cities like Istanbul, there are several challenging grid management tasks for the peak-load periods of a day [10]. Distributed energy storage capacity of PLs can be utilised as cost-effective storage sources instead of installing new generation plants with high installation costs.…”

Stochastic modelling of electric vehicle behaviour to estimate available energy storage in parking lots

“…The impact of arrival and departure patterns was analysed to determine the storage capacity of public and private company's WPLs [13]. Estimation of the aggregated storage capacity of EVs using a stochastic modelling approach was developed in [15, 16]. In [17], a stochastic model was developed to estimate the occupancy behaviour and arrival/departure pattern of EVs in WPLs using Markov chain analysis.…”