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The objective of this paper is to present a double-layer charging control model which can be utilized by an Electric Vehicle Supplier/Aggregator (EVS/A) for scheduling and managing the electric vehicle (EV) charging demand. The first layer is a cost-minimization load scheduling algorithm considering the EV demand forecast and wholesale prices. EVS/A can be incentivized by the DSOs to offer load management...
For a large-scale introduction of electric vehicles (EVs) intelligent charging strategies are needed to adjust their energy demand to the production of renewable energy and the current load in the distribution grids. This paper presents an approach that puts the intelligence needed into the EVs, where most of the crucial information arise, thus minimizing the need of communication throughout the grid...
The paper presents an agent-based scheduling and energy management system for a smart distribution feeder which is installed on a test site and includes an electric car sharing fleet. Distributed Energy storage systems provide flexibility in the operation of the test site, where the integration of multiple power sources including Renewable Energy Sources and Distributed Generators is implemented....
There is much interest regarding the future possibilities - and risks - arising from integrating increasing numbers of plug-in vehicles with power system network operations, in particular demand-side management. There has been comparatively less enthusiasm directed towards addressing the question of what can and cannot be done with existing technology. This paper discusses what could be achieved and...
Huge investigations have to be made by car and power companies to realize the electro-mobility and the corresponding infrastructure. One of the critical challenges with respect to the infrastructure is the setup and deployment of a future-proof common standard for smart grids. The charging process requires a smooth communication between electrical vehicles, the power supply equipment and the smart...
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