Análise do carregamento de veículos elétricos na curva de carga do transformador de distribuição - Sausen, Jordan Passinato (2017)
The objective of this dissertation is to evaluate the insertion of Electric Vehicles (EVs) on the distribution system. Motivated by the shortage of deterministic data regarding the process of charging EVs batteries, a probabilistic methodology is proposed to estimate the requested system’s power demand. For that, energy consumption and urban mobility patterns from a pilot region are used to compose the distribution transformer load curve. The period in which the energy is requested to the system is based on the analysis of two EVs charging strategies, dumb charging and economic charging, both represented by Poisson distributions in the proposed model. While the first corresponds to the grid connection according to the driver’s usual trip recurrence time, the second is based on the hourly tariff analysis, motivating the charging at lower tariff charges, when available. The driver’s distance traveled regarding to the pilot city is estimated statistically based on the Inspection and Maintenance Program of the city of São Paulo, configured by a Normal Probability Distribution. Aggregated with charging characteristics, these distributions are intended to represent the energy demand required by electric vehicles over time, which is then added to a distribution transformer charging model. This model integrates typical load curves to the transformer, described by a probability distribution that relates the proportion of customers of each class with the average number of consumers connected to the equipment. Both demand for electric vehicles and typical consumer demand take into account the probabilistic nature of load. Therefore, the Monte Carlo method is used for both situations, which uses random variables described by probabilistic functions to estimate the EVs insertion impact. The distribution transformer load curve is evaluated based on the model’s results, regarding to the influence of different technology penetration levels, as a support tool for the decision to prioritize the investments of energy distributors.