Smart Charge of an Electric Vehicles Station: A Model Predictive Control Approach

Cesar Eduardo Diaz Londono1, Fredy Ruiz, Diego Patino1

  • 1Pontificia Universidad Javeriana



Regular Session


10:00 - 12:00 | Wed 22 Aug | Christiansborg | WeA2

Smart Grids

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The increasing use of Electric Vehicles (EVs) connected to the electrical power grid generates challenges in the EV charging coordination and operation cost management. An EV Charging Station (EVCS), with time-variant prices and customers who have different charging time preferences, presents challenges for scheduling all requests. In this article, an aggregator based on a Model Predictive Control (MPC) strategy is proposed. It reduces the operating costs in the EVCS through managing EVs as flexible loads, i.e., the power delivered to each EV and its charging time can be modified. The MPC approach is analyzed by two scenarios. First, with full information, such as, EVs arrival State of Charge (SoC), arrival and departure times. Second, with uncertainty in the arrival SoC. Results show possible cost savings about 21.5% with full information and 21.0% with uncertainty in the arrival SoC. This MPC strategy might provide a new tool for reducing the EVCS operation costs fulfilling EV owners requirements.

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