Pon Power – Microgrid Optimization

In May 2022, Pon Digital Solutions and the Pon Datalab organized the Pon Hackathon, with a focus on sustainability. One of the cases presented during the event was the optimization of microgrids. Over the course of two days, teams of data and digital experts worked together to develop a configuration tool to determine the most suitable installation for end clients.

What is a Microgrid?

Microgrids are small-scale versions of traditional electrical grids, capable of functioning independently or interconnectedly with the main grid. They provide a reliable and secure source of electricity to a specific area or facility, and enhance energy efficiency through precise management of energy consumption and generation. By integrating storage systems like batteries, microgrids can optimize the utilization of renewable energy sources such as solar power, thereby reducing dependence on fossil fuels and decreasing greenhouse gas emissions.

In addition to their environmental advantages, microgrids can offer economic benefits to communities as well. By generating and distributing power locally, microgrids can lower the cost of electricity and even generate revenue by feeding excess energy back into the main grid.

Although microgrids are still a relatively new technology, they have the potential to play a significant role in the energy industry’s future. As more communities and organizations seek ways to increase energy reliability and minimize their ecological footprint, microgrids present a promising solution.

What is our solution?

In collaboration with Digital Solutions, we developed a tool that allows Pon Power to input specific customer details, such as their load and solar profile, and various types of batteries and generators. The tool uses the input values and available solar, grid, batteries, and generators to calculate and display the load distribution among the components in several visuals. Based on the KIP’s and visuals, Pon Power employees can adapt the configuration to find the best suitable configuration for the end-customer.

  • Ellen Mik

    Senior Data Scientist

  • Job Deleij

    DataOps Engineer

  • Tom Klaver

    Data Scientist