Dexter Energy optimizes energy-related assets and reduces emissions. As more renewables come, it becomes more difficult to connect supply and demand to the electricity network.
eShift is a control software that derives value from the flexibility of energy-related assets. With the help of forecasting, Dexter predicts the electricity prices in the market. Data for the forecasting is extracted from various data sources. Next, 140 features in trends over time are analyzed with different machine learning tools, which make an accurate statements about the prices based on links between these variables.
On the basis of these predictions, advice can be given when which asset can best be used.
1: Energy suppliers, who can thus better offer their capacity on the APX market and become more efficient there by not offering too much power.
2: Industries that consume a lot of electricity and can save money and electricity through better demand response management by optimally using batteries or heat pumps.
in February 2018 a pilot started with AI. Within 2 weeks, the model could better predict how the energy sets could be used more efficiently on the basis of the predictions, which resulted in lower costs and low power consumption.