Industrial asset management : decision-support with simulation in OpenModelica

MSc student work, Master Thesis, or full-time internship (remunerated) Fall 2024 or Spring 2025

Context

The design and operation of the next generation of waste management and energy supply systems should ensure industrial Global Warming Potential (GWP) reduction targets agreed internationally and enable transition towards a circular economy of materials whilst being financially viable. Related challenges stem from the range and complexity of involved technologies and engineering domains, variety of possibly conflicting performance criteria, and interaction potential within the system as well as with external interfaces, in the context of uncertain energy supply markets.

This project is part of the development of a simulation and optimization platform for decision-support in industrial decarbonization and value recovery pathways, focusing primarily on risk management in industrial waste treatment projects. This work is a collaboration of IPESE and R&D at Kanadevia Inova AG (KVI), an Engineering, Procurement and Construction company active in the waste treatment sector (>600 plants built), based in Zürich (Switzerland).

Objective

This project supports the risk assessment of industrial decision-makers through the simulation of a multi-energy system in OpenModelica. The following aspects will be covered:

  1. Definition & review of the specific industrial waste treatment system to study: KPIs of interest, risk assessment basics

  2. Introduction & training into the simulation platform environment

  3. System simulation, scenario analysis and report generation

This project will contribute to increase accuracy in the analysis of the financial viability of studied waste treatment technologies, thereby increasing industrial stakeholders’ trust in the decision-support tool.

Skills and Background

  • Understanding of energy systems (the following courses may be of advantage, but not regarded as strict requirements): ME-454 (Modelling and Optimisation of Energy systems), ME-451 (Advanced Energetics), ME-409 (Energy Conversion and Renewable Energy)
  • Knowledge in industrial asset management and/or risk assessment for industrial projects is of advantage
  • Coding skills in Python or Modelica are of advantage
  • Willingness to work independently and interest for modeling tasks

Location & Organization

The project is done remotely, either on EPFL campus, IPESE laboratory (located in Sion - train fare Lausanne-Sion is reimbursed by EPFL) or as home office. Regular meetings with the supervisor are ensured (exact schedule to be determined, but typically 1-2x/week), and discussions with Professor Maréchal, Fachhochschule OST or industrial research colleagues may be organized in the current of the semester.

Contact

The work is supervised by Julie Dutoit, PhD candidate and R&D process engineer at KVI. If interested, please send your CV with a short description of your specific interest to julie.dutoit@hz-inova.com.

References