Nazario-Mattei, Arnaldo L.

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    Coordinated integration of battery electric vehicles to a power system and its effect on the load curve
    (2019-05-14) Nazario-Mattei, Arnaldo L.; Cedeño-Maldonado, José R.; College of Engineering; Aponte Bezares, Erick; Orama Exclusa, Lionel R.; Department of Electrical and Computer Engineering; De La Rosa Ricciardi, Evi
    The proliferation of electric vehicles poses new challenges to the safe and economic operation of electric power systems. If electric vehicles are integrated without proper control strategies, load demand peaks will increase, and the grid may be overloaded. Coordinated methods are expected to introduce potential solutions to mitigate these negative impacts. To that end, this thesis presents a conceptual framework to effectively integrate plug-in electric vehicles into the grid. The proposed method is based on a two-stage optimization process that aims to reduce the overall load variance considering a discrete charge/discharge rate, which is largely unexplored. The first stage consists on solving a quadratic programming (QP) optimization problem, while the second stage aims at solving a mixed-integer quadratic programming (MIQP) optimization problem that uses binary variables to schedule the on/off states of the charging/discharging process. With this formulation, two approaches, vehicle-to-grid (V2G) and charging methods, were considered to evaluate the impact on the demand curve and generating costs due to the integration of electric vehicles within the system. Case studies for a typical islanded power system and the Institute of Electrical and Electronics Engineers (IEEE) 10-unit system were conducted to demonstrate that the proposed algorithms perform as expected. Traditional unit commitment problem was used to address the variations of generating costs with and without the addition of plug-in electric vehicles. Numerical results reported for the different case studies and scenarios showed that V2G and charging operations can help flatten the overall load curves and reduce generating costs by performing appropriate schedules of the charge and discharge process of electric vehicles.