Smart Agent to Optimize Recharge of Electric Vehicles (EVs) into Smart Cities

Abstract

By 2040 it is expected that electric cars will be about 50% of the car market. The design and entry into the market of electric vehicles are constantly increasing, many authoritative car manufacturers are investing in this new type of transport systems. Currently an EV typically has a range of about 150 km (90 miles), therefore the fear remains that of remaining without charge; fundamental is the creation of charging stations and widely distributed networks, no more than 50 km (30 miles) away from each other. There are different types of recharge, slow or fast, depending on the characteristics of the system that delivers it and the vehicle that receives it. Charging services can be associated with other business ventures, such as retail, financial services, medical services, and can be easily placed near shopping centers, restaurants, cinemas, concert halls and car parks, in this way drivers they will be able to recharze their vehicles almost anywhere. Yet the charging of electric cars without a coordination mechanism will put a strain on the electricity grid, creating a real danger of power failure. The management and control system, through the charging stations, will play a key role in the development of the electric mobility network, which initially will find in sharing mobility, the starting point for the deployment of electric vehicles. It is necessary to integrate it with a hardware mounted on cars that measure use and mileage, to evaluate the movements, intended as repetitive and predictable actions, eg: home-work, going shopping, to accompany children to school, etc., to develop a targeted proposal for the introduction of electric mobility based on the effective use of resources. With this paper we want to define how in vehicle to smart grid systems (V2SG), in vehicle to smart building systems (V2SB) or finally in Vehicle to Smart Home systems (V2SH) smart agent systems can play a fundamental role in the algorithm of control for an intelligent recharge, to optimize the energy demand in order not to overload the electrical network.