DC-Microgrid Operation Planning for an Electric Vehicle Supply Infrastructure

The integration of electric vehicles (EVs) in power systems can be encouraged by charging station diffusion. These stations can perform smart charging processes, and can take advantage of the involvement of distributed generation sources in a microgrid framework. Furthermore, since photovoltaic batt...

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Bibliographic Details
Published in:Applied sciences 2019-07, Vol.9 (13), p.2687
Main Authors: Aluisio, Benedetto, Bruno, Sergio, De Bellis, Luca, Dicorato, Maria, Forte, Giuseppe, Trovato, Michele
Format: Article
Language:English
Subjects:
Air conditioning
Controllability
Costs
DC microgrid features
Distributed generation
Electric industries
Electric power grids
Electric power systems
electric vehicle integration
Electric vehicles
Energy management
Energy storage
Genetic algorithms
Integer programming
Linear programming
mixed integer linear programming
Optimization
Power
Random variables
Reactive power
Real time
Risk management
Synchronism
Synchronization
Vehicle-to-grid
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Summary:The integration of electric vehicles (EVs) in power systems can be encouraged by charging station diffusion. These stations can perform smart charging processes, and can take advantage of the involvement of distributed generation sources in a microgrid framework. Furthermore, since photovoltaic batteries and EVs are sources based on direct current (DC), the realization of a DC microgrid structure is promising, though challenging. In this paper, a mixed-integer linear procedure for determining optimal operation planning of a DC-based electric vehicle supply infrastructure is proposed. The procedure aims at optimizing daily operational costs, based on forecast of photovoltaic production and EV exploitation. Peculiar aspects of energy storage devices and of the DC microgrid framework are accounted for through a non-linear iterative procedure. The proposed approach is applied to a test DC microgrid on different operation days and its effectiveness is compared to non-linear formulation solved by means of a genetic algorithm.
ISSN:2076-3417
2076-3417
DOI:10.3390/app9132687