Below we list a number of suggested projects for DAT300. Of course we would be open to hear your suggestions too -- but the projects must relate to Energy and ICT. The suggestions below are just a seed idea. It is then up to you to work out the details and the work plan with the project demonstration at the end of the course.
How can data from the smart grid best be visualized and what patterns can be determined? Use tools such as Spotfire, Gephi, and your programming skills.
For most applications, such as energy consumption measurements in the smart grid, it is important to monitor the network connectivity in real time. The monitor results can be used as an indication of the health of the sensors and the network, e.g. whether they behave in the expected way. Visualizing the network dynamics and highlighting irregularities help the network administrator to quickly locate and pinpoint problems and make the appropriate decisions. Tools as Gephi or JUNG can be useful.
How can a de facto IDS such as snort be adapted for protocols found in the smart grid. This project is about understanding snort rules and how these can be adapted to DLMS/COSEM or MBUS traffic.
Many government agencies and other organizations provide open datasets. How can such datasets be used to extend our understanding of enery consumption, or other patterns in the smart grid datasets? One source for open data is found at the hack for Sweden site.
What services would be useful for consumers and companies to have in the smart grid? Are the data available sufficient to create such services? See for example the following service from E.On to save energy.