SMARTplug: Using smart devices for a managed charge of electric vehicles Ricardo P. Faria*, Víctor C. Ramirez**, Pedro S. Moura*, José I. Moreno**, Joaquim B. Delgado*,Aníbal T. de Almeida* * Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal ** Telematic Engineering Department, Carlos III University, Madrid, Spain Abstract Electric vehicles are seen as an option to reduce greenhouse emissions from the transportation sector and their number on the road is growing in a daily basis. However, with their widespread adoption the increase in the demand for electricity to charge these vehicles could pose significant challenges to the electrical grid in terms of additional load due to unmanaged charge strategies. In order to mitigate this problem, the charging of the electrical vehicles must be managed. This paper presents the development of a hardware and software architecture to dynamically control the charge of electric vehicles to maintain the proper operation of the local distribution grid, by reducing the possibility of power outages due to overload, in a Smart Grid context. The hardware consists in two modules, a meter and controllable plugs both with communication capabilities, while the software consists in a load forecast and scheduler module. The load forecast is calculated based on the power consumption behavior and is used to assign the best time slot to charge the vehicle. The system aims to minimize the load peaks and flatten the load profile. Based on the user preferences, system characteristics and consumption forecast, the system will assign the most suitable time slot to charge the electric vehicle. For the case of multiple electric vehicles, the system will schedule their charge based on a calculated priority level, in order to maintain a reliable operation of the local electrical grid. 1. Introduction Electric Vehicles (EVs) are expected to have a large share in the future of the transportation system in order to reduce the share of Greenhouse Gas (GHG) emissions associated to personal transport and also due to the increasing costs of fossil fuels [1] [2]. This electrification of the transport system will cause an additional load on the electric grid, since the EVs will require a connection to the grid to charge the batteries. Currently, due to the EVs low penetration rate the additional load imposed to the grid by the vehicles charging is not an issue, however in the future, with a higher penetration rate, this could bring serious consequences to the grid reliability due to overload [3] [4]. The main problem is not in the extra energy required to charge the batteries, since the grid has enough capacity, but the peak load of the charging [5] [6]. Since the majority of EVs will be charged at home, it is expected that the vehicle will be plugged in when their owners get home, at the end of the afternoon. This behavior will lead to a considerable additional load that can overload the grid. In order to mitigate these problems, the charging cycle of EVs must be managed in some way [7]. This concept of coordinate charging is being explored due to the wake of smart grids, where the exchange of information using several communication technologies can improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity [5] [8]. Coordinate charging can also be beneficial for grids with a large share of renewable energy sources by absorbing the excess energy produced [9]. Alternatives to uncoordinated charging are currently being investigated by using devices with bi- directional communication capabilities to perform a coordinated charging [10] [11] [12]. This type of coordination is intended to minimize the negative impacts on the grid, due to a large number of vehicles charging at the same time by distributing this charge over a large period of time, flattening the load peak. Efficient operation in a smart grid environment usually is focused in reducing energy losses and increasing efficiency [13] [14], in this paper the focus is in maintain the grid stability by avoiding the overload due to the uncoordinated introduction of additional loads.