Project description
AI-powered model to increase EV charging infrastructure
Electric vehicle (EV) adoption remains low due to a lack of sufficient charging infrastructure. While the deployment of more public EV charging stations (EVCSs) can address this issue to some extent, challenges related to profitability and strain on the grid continue to restrict availability. Household chargers present a promising solution, offering cost-effective and sustainable public charging options. The EU-funded ChargFlex project is dedicated to expanding the accessibility of EV-charging infrastructure. A charging market will be established to enable households to sell surplus energy to EVs, and an AI-based bidding strategy will be employed to maximise profits. ChargFlex aims to improve EV charging accessibility by developing an AI-powered model that recommends optimal times and locations for recharging.
Objective
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.
Fields of science (EuroSciVoc)
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
8000 Aarhus C
Denmark