Data-management and Power Quality

Energy transition (ET) will drive electrical installations to optimize their energy consumption and to add renewable energy sources (RES) and perhaps storage systems to their installation.

Most RES generation will rely on inverter-based resources (IBRs) and also most of the loads will be connected to the installation, using power electronic interfaces. This could increase the possibility of controlling their behaviour, but could also be a source of problems related to electromagnetic compatibility.

To get a better insight in the electrical installations and their behaviour, customers are adding power quality meters to their installation and also additional sensors to measure the most important parameters needed to optimize the usage of the installation.

However, the gained data is not always used in a smart way and a algorithms to build new applications and to add additional intelligence to the installations should be developed.

Research Question

  1. Which applications and additional intelligence could be added in software and measurement equipment to optimize the usage of electrical installations.
  2. How can the data be compressed, communicated, visualised for the most optimal usage?

Students task description

The research is part of a project in which the company HyTEPS is involved with several industries in the Netherlands. The student will work and be supervised within this company in combination with the TU/e supervisors. Practical cases will be used for the research.

Earlier studies identified several topics where more in-depth analysis is required. There are several activities for the graduation project. The task descriptions for this goal can be detailed as follows:

Graduation project

  1. Overview of recent activities on this subject
  2. Conduct a literature survey on applications to optimize the usage of an installation
  3. Define the most important (future) changes in installations, related to a more sustainable infrastructure.
  4. Define/select one or two case studies where these changes are foreseen to be in place.
  5. Build or use models in PowerFactory/Vision for the scenarios/areas of interest.
  6. Quantify the economic profits/costs of the new applications.

Requirements

  • The student should have followed the related power system courses.
  • The thesis should be in MS Word and IEEE journal paper template.

 

For more information

  • TU/e graduation professor: J.F.G. (Sjef) Cobben (F.G.Cobben@tue.nl)
  • TU/e supervisor: Vladimir Ćuk (cuk@tue.nl)
  • External supervisors:
    • Christan van Dorst (HyTEPS)
    • Anil Kumar (HyTEPS))

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