The GIEDION project (Gestione Intelligente e sicura di sEnsoristica Distribuita e della sua Interazione uOmo-macchiNa: possibili scenari futuri) concerns the generation of distributed electricity that requires the development of management models that are complementary and/or additional to those currently used. In particular, in order to make a correct and efficient management of both energy produced from renewable energy sources and loads, it is necessary to develop distributed energy storage systems. This requirement, together with the obligation to implement a consumption of energy from renewable sources in the transport sector accounting for 10% of the total by 2020, leads to believe the electrical urban transport system one of the possible solutions to the problems mentioned above.
In addition, the progressive development of distributed generation combined with the use of non-programmable renewable energy sources suggests that the distribution of electricity can not be managed exclusively through the network management, but it necessarily must use methods of accumulation and redistribution linked to other infrastructure networks insistent on the same territory. In this perspective, the “Vehicle to Grid”, i.e. the possibility that electrical or hybrid vehicles can bidirectionally exchange energy with the grid, is an example of synergy between the generation / electrical distribution and transport network.
The management of the vehicle to grid (V2G) system is not possible without an effective communication system that enables the exchange of information between moving vehicles and management and monitoring positions. In particular, the above scenario requires, in the first analysis, the transmission of the following types of information from the vehicle: the state of charge of the battery; distance traveled; destination (if available); consumption of the charge depending on the route; speed of the vehicle along the various routes. In contrast, the vehicle will receive information about the suggested route in order to reduce consumption and optimize the use of the storage system as well as the location of the free to park stations and their listing charge.
Funding: RAS
Duration: 2013-2016
Research Area: Internet of Things
Principal Investigator: Luigi Atzori