Energy companies are always looking for ways to reduce their reliance on traditional energy grids while exploiting the full potential of renewable energy sources.


Energy companies have a higher demand for clean and efficient energy solutions. One way to address this would be to be able to optimize electrical energy mix from different power sources (E.g. solar, wind, grid).


  • Energy Mix optimizer tool is a software solution that analyses real-time data from solar panels, wind turbines and the power grid to optimize energy mix and minimize costs.
  • The tool uses an advanced ML model to gather data from various sources, including electricity demand, energy prices and weather conditions. Regular monitoring of these factors determines the most cost-effective energy mix in real-time.
  • The ML model is trained on a large dataset of historical energy data and is updated regularly with new data.
  • For instance, depending on the day (E.g. sunny day), the tool can increase the usage of solar energy and reduce on the grid. When the sun set arrives, the tool integrates wind power into the mix.
  • When data shows high electricity price days, the tool can increase the use of renewable sources.

How an Energy company uses an energy mix optimizer tool (EMO) to not just reduce costs but optimize its energy consumption.

energy mix optimizer


  • Although the tool, including the ML model, is still under implementation, it has shown interesting preliminary results.

  • By having the most cost-effective energy mix, this tool have reported cost savings of up to 15% on their energy bills.
  • Also, the tool helps to enhance grid resilience (I.e. ensuring uninterrupted power supply) and optimizes energy demand scheduling.

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ML model also makes a recommendation on how to operate the equipment to increases up-time, lifetime and minimizes unplanned downtime.

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