Royal HaskoningDHVs office in the city of Amersfoort, the Netherlands, is the first location in the world where electric vehicles are smart charged using machine learning. The charging stations are managed by the charging point operator Eneco eMobility, with smart charging technology provided by the GreenFlux platform.
With the number of electric vehicles ever increasing, so is the pressure to increase the number of charging stations on office premises. This comes at a cost; electric vehicles require a significant amount of power, which can lead to high investments in the electrical installation. With smart charging these costs can be significantly reduced, by ensuring that not all vehicles charge at the same time.
With the innovation, developed by GreenFlux, deployed by Eneco eMobility and applied at Royal HaskoningDHVs Living Lab Charging Plaza in Amersfoort, the Netherlands, smart charging is now taken to the next level, allowing up to three times more charging stations on a site than with regular smart charging.
The novelty in this solution is that machine learning is used to determine or estimate how charge station sites are wired physicallydata that commonly is incomplete and unreliable. At Royal HaskoningDHV, the algorithm determines over time the topology of how all the three-phase electricity cables are connected to each individual charge station.
Using this topology, the algorithm can optimize between single and three phase charging electric vehicles. Though this may seem like a technicality, it allows up to three times as many charging stations to be installed on the same electrical infrastructure.
Now that this part has been tested and proven, there is so much more we can add. We can use the same technology to, for instance, predict a drivers departure time or how much energy they will need. With these kinds of inputs, we can optimize the charging experience even further.
Lennart Verheijen, head of innovation at GreenFlux
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