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Huge savings with AI, Smart Charging and variable electricity prices

Huge savings with AI, Smart Charging and variable electricity prices -

With the increase of renewable energy sources, the Dutch energy market is becoming more variable, and so are electricity prices. Recoy uses machine learning technology to predict those prices, enabling fleet managers to save electricity costs. Last Mile Solutions organizes the backend that connects the various parties.

Normally, a vehicle arrives at a charging station, plugs in and starts charging until the battery is full. Recoy adjusts the charging process to developments in the electricity market. This form of smart charging will first be applied to the electric trucks of Rotterdam transport company BREYTNER.

Imbalance market

Though it’s barely noticeable to the average consumer, the actual price of electricity on the (day-ahead) market fluctuates per hour, and on the imbalance market even every fifteen minutes.

The imbalance market, created by grid operator Tennet, ensures that the supply and demand of electricity are always in balance. The large producers and consumers of electricity must indicate a day in advance how much electricity they expect to produce or use the next day. Deviating from this will create an imbalance. If there is a shortage, you pay the (higher) imbalance price. If you are on the right side of the balance sheet, and you produce a surplus at a time when there is an electricity shortage – by producing more or consuming less than expected – you can earn money. Basically, what happens on the imbalance market is shifting electricity deficits and surpluses back and forth, with associated rates.

Last year there were more than 2000 hours with negative prices on the imbalance market. Recoy’s solution makes it possible for fleet owners to take advantage of this and get paid for charging their vehicles at these times.

Machine Learning

Together with Belgian company N-SIDE, Recoy has developed algorithms that can predict the imbalance price on the basis of machine learning. If there is too much power on the grid, the forecast can be that the price of electricity will be lower in the next half hour. Then that is the moment when the trucks and buses start loading.

Solar panels

In addition, using Alliander’s Solar Forecaster, Recoy predicts how much power solar panels will generate at a particular location. When solar panels produce more power than necessary, they feed the power back to the grid. If that power is needed later on, a consumer pays tax and storage of sustainable energy (ODE) and transport costs again. Therefore, it is more economical to use that power yourself.

Last Mile Solutions

These smart charging processes are made possible with the help of the Last Mile Solutions platform, which functions as the spider in the web.

The charging stations are connected to the Last Mile Solutions platform. As soon as a vehicle arrives and docks, a signal is passed on to Recoy with an API. The charge card number corresponds to a truck whose route schedule – and thus its available charging time – is known. Recoy reads remotely how full the battery is.

Based on this information, linked to the price predictions calculated per minute, a charging schedule is made. The vehicle is plugged in, but charges at different speeds and at different times. Regardless of the price fluctuations, the vehicle will be fully charged before continuing its route; that is the priority for the customer.

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