Smart Synergy Mechanism between Electric Vehicle Charging and Flexibility Markets

Descripción del proyecto

Un modelo basado en inteligencia artificial para aumentar la infraestructura de recarga de vehículos eléctricos

La adopción de vehículos eléctricos (VE) sigue siendo baja debido a la falta de infraestructuras de recarga suficientes. Aunque el despliegue de más estaciones públicas de recarga de VE puede resolver este problema en cierta medida, los retos relacionados con la rentabilidad y la presión sobre la red siguen restringiendo la disponibilidad. Los cargadores domésticos son una solución prometedora, ya que ofrecen opciones de recarga pública rentables y sostenibles. El equipo del proyecto ChargFlex, financiado con fondos europeos, se dedica a ampliar la accesibilidad de la infraestructura de recarga de VE. Se creará un mercado de recarga para que los hogares puedan vender el excedente de energía a los VE, y se empleará una estrategia de pujas basada en inteligencia artificial (IA) para maximizar los beneficios. El objetivo de ChargFlex es mejorar la accesibilidad a la recarga de VE desarrollando un modelo basado en IA que recomiende las horas y los lugares óptimos de recarga.

Objetivo

Rapid integration of Electric Vehicles (EVs) in the transport sector is the key to achieving the Green Deal decarbonization targets. However, EV adoption is still low for several reasons, mainly concerns about the lack of charging infrastructure from the EV drivers' view, known as range anxiety. Many studies believe deploying more public EV charging stations (EVCSs) can ease this anxiety among EV drivers. Still, EVCSs are not yet widely available due to profitability issues and putting more stress on the grid. While the growth of the EVCSs is moving slowly, the number of household charger installations is growing rapidly. However, scarce studies have investigated the potential of household chargers in providing public charging services. Further, many households are already equipped with renewables and sell the surplus energy to the grid through local flexibility markets. With renewables, household chargers can provide cheaper charging services while minimizing the negative grid impacts of EV charging. This project intends to alleviate the range anxiety in two ways. First, we will enhance the charging infrastructure availability by encouraging households to sell surplus energy to EVs through a market framework called the charging market, besides flexibility markets. We will design a coordinated bidding strategy model from the household viewpoint based on AI to maximize profit from the two markets (Work Package 1). Second, we will improve charging infrastructure accessibility by developing an AI-based charging recommendation model to guide EV drivers on when and where to get recharged (Work Package 2). Finally, we will conduct software implementation and real-time performance validation of the proposed AI-based models (Work Package 3). The complementarity between me, the host supervisor's profile, the environment provided by the host, and the secondment ensure the achievement of this timely and innovative project and the dissemination and exploitation of the results.