Abstract
Micro-grids have become the building block of modern energy systems, where distributed resources are the characterizing feature. The charging operation of electric vehicles can be exploited as a flexible load to achieve operational goals of the micro-grid. In the particular case of car-sharing fleets, the degrees of freedom in the charging procedures are reduced when compared to private users. In this work, we illustrate how a car sharing fleet can be incorporated as a flexible load in the micro-grid management system. A linear optimization problem is formulated, where the cost function makes a trade-off between the gain in flexibility in the micro-grid and the loss incurred by the car-sharing service for delaying the recharging procedure of the EV. The proposed approach is evaluated on a data set of charging events generated by a real car-sharing fleet showing that the EMS allows reducing the daily peak demand requested to the public grid and diminishes the operational costs.
Highlights
Today, nano and micro-grids play a strategic role in the development of the electricity system [1,2]
A linear optimization problem is formulated, where the cost function makes a trade-off between the gain in flexibility in the micro-grid and the loss incurred by the car-sharing service for delaying the recharging procedure of the Electric Vehicles (EV)
Most of the works assume that the electric vehicles are autonomous and an important effort is made in forecasting the arrival time of each EV and other uncertain variables, such as the arrival State of Charge (SoC) [13,14], or in developing robust scheduling techniques that can guarantee an adequate power flow to/from the public grid, in front of any feasible realization of arrival time and SoC [15]
Summary
Nano and micro-grids play a strategic role in the development of the electricity system [1,2]. Micro-grid architectures have different configurations, but in most cases the high use of renewable sources, such as solar, make these networks, on the one hand to behave with low inertia and on the other hand to count on generation resources, whose actual production is not predictable compared to the needs of the loads It is, essential to have energy storage systems capable of promoting an optimal use of the resources. In [12], a different approach is presented, where the main element of the model is the charging station and the arrival of EVs are handled as events that modify the state of the station This configuration, limits the size of the problems to the number of stations handled by the management system.
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