Developing a spatial database for energy planning in Sweden
There are multiple interesting spatial and non-spatial datasets relevant for energy available in the Nordics, but these are scattered among various official and unofficial data providers. The objective of this thesis is to develop a workflow which creates an updatable, unified and coherent spatial database containing all the relevant data sources for energy planning research. Harmonising spatial datasets would help drive forward new branches of energy research that combine location and place, demand and supply.
This is one of a series of linked Masters theses on the topic of spatial energy research.
Background
The latest research shows that it is essential to better incorporate spatial information into the planning of modern energy systems. To reach net zero, we seek to integrate high levels of variable renewable energy, a flexible demand side and co-locate supply technologies alongside demand centres to operate the energy system more efficiently.
There are multiple interesting spatial and non-spatial datasets relevant for energy available in the Nordics, but these are scattered among numerous official institutions and agencies such as, for Sweden, SMHI, Lantmäteriat, Svensk Statistikmyndigheten, and other data providers, such as Open Street Map, Open Power System Data and the Global Wind Atlas.
A unified and coherent spatial database containing all the relevant data sources for energy planning research would greatly improve the capabilities of Nordic energy researchers.
Task description
The thesis will be divided into several stages:
- Familiarisation and Planning – the student will determine the scope of the project with the supervisor team, review, select and conduct training on required software tools, data, supplemented with a short, targeted literature review.
- Implementation – the student will identify spatial and non-spatial datasets across multiple categories, develop the workflow and spatial database, and investigate the potential for insights through a small number of case-studies.
- Writing Up and Examination – the student will finalise and present the written report.
Learning outcomes
After completing the thesis work, the student will be able to:
- Implement computational solutions by applying state-of-the-art knowledge engineering and Python libraries to large datasets and public APIs
- Conduct a research project independently from developing the overall research design through to the delivery of a final report
- Communicate results coherently and in a scientific manner
If the work is of good quality and the student is interested, the research project will be designed to be suitable for a peer-reviewed publication in a high-quality journal.
Prerequisites
Students should be familiar with the Python programming language, ideally have familiarity with workflow tools such as snakemake, graphical information systems and databases such as postgreSQL and PostGIS, have an enthusiasm for sustainability/climate action, and have the ability to work independently to lead a research project by identifying key problems and delivering a solution.
Track Specialization
Transformation of Energy System (TES)
Division/Department
– Department of Energy Technology
Research areas
Duration
20 weeks, starting January 2024.
How to apply
Send an email expressing your interest in the topic and your CV to the supervisor.
Supervision
