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An optimization model for electrical vehicles scheduling in a smart grid
- Publication Year :
- 2018
- Publisher :
- Elsevier Ltd, 2018.
-
Abstract
- Energy Management Systems (EMSs) are recognized as essential tools for the optimal management of smart grids. However, few of them consider, in their whole complexity, the integration of electrical vehicles (EVs) in smart grids, taking into account the requirements and the time specifications characterizing the service requests. In this paper, attention is focused on the formalization of a model for the optimal scheduling of charging of EVs in a smart grid, also considering the vehicle to grid process (i.e., the possibility for the EV to inject power during the charging process). In the formalization of an optimization problem for a smart grid, a deferrable demand is considered, which is represented by the charging demand of the set of EVs. The cost to be optimized for the considered problem includes the economic cost of energy production/acquisition (from the main grid) and the cost relevant to the delay in the satisfaction of the customers’ demand (is represented as a tardiness cost). Also, the income coming from the service provided to vehicles is taken into account. The developed model is tested and applied in connection with a real case study characterized by a photovoltaic plant, two batteries, power production plants that use natural gas as primary energy, and a charging station.
- Subjects :
- Optimization
Optimization problem
Primary energy
Electric vehicles
Sustainability and the Environment
Renewable Energy, Sustainability and the Environment
Computer science
Energy management
Scheduling
020209 energy
Photovoltaic system
Energy Engineering and Power Technology
Vehicle-to-grid
02 engineering and technology
Grid
Microgrids
Control and Systems Engineering
Electrical and Electronic Engineering
Reliability engineering
Charging station
Smart grid
0202 electrical engineering, electronic engineering, information engineering
Renewable Energy
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....711c083310b1f0ab19c20b3055b41f96