The Metroscope methodology uses Modelica based digital twins of power units as a basis. Such component-based models need to be calibrated to find the value of the component parameters (heat exchange coefficients, efficiencies…), to fit the process best. Such a calibration is extremely dependant on the total power produced by the installation : at 100% or at 30% results are extremely different. Our method today focuses on full load.

The goal of the internship is to extend Metroscope’s solution to a new perimeter : improving Metroscope’s solution for partial load. The goal being to study the effect of load variation on parameter calibration, then design a multi-load calibration, suitable for a broad range of operating conditions.

Once introduced to Metroscope’s solution for modeling industrial installations, you will :

• Calibrate a similar project for an installation running at partial load
• Evaluate the difference it generates as compared to a full load project
• Put in place a way to take into account load dependency in the calibration of the end model
• If necessary, propose ways to refine our models to make them more suited for working at partial load

You will work on a real usecase from one of our clients. If time allows it, you will also explore the effect of other boundary conditions (for instance external air temperature) on the calibration.

The tools that you will use for this work include Modelica (and the use of our internal modeling library) and Python (for calibration and result analysis).

• You are currently in an engineer school and are looking for a 6 month end-of-study internship
• You have some prior experience with modeling, ideally with Modelica or Python
• You have some basis in data science and statistics
• You are interested in the energy sector, and in studying in details industrial processes
• You are dynamic, autonomous and want to work in a small team