13 December 2024

The energy transition, shifting from fossil fuels to renewable and low-carbon sources, requires smarter decision-making. A new PhD thesis from Linköping University demonstrates how data-driven tools can aid this process and help decision-makers navigate complex choices in the energy field.

A young women looking at her computer.
Qianyun Wen successfully defended her thesis. Photographer: Teiksma Buseva

The thesis written by Qianyun Wen, PhD student at the Department of Management and Engineering, investigates how large datasets from smart grids and digital technologies can be used to develop models and tools to support various stages of the energy transition.

"Data-driven tools can not only improve decision-making but also make it more accessible and user-friendly. For these tools to have a real impact, it is crucial that they provide reliable results and are adapted to the users' needs," says Qianyun Wen, a PhD candidate at the division of Environmental Technology and Management at Linköping University.

The study analyses three key areas: choosing heating technologies for buildings, forecasting energy usage and generation, and establishing energy-sharing communities. The results show that a combination of techniques, such as machine learning and optimization models, can help decision-makers find more sustainable and efficient solutions.
Qianyun Wen emphasizes that transparency and user-friendliness are key.

To create a sustainable energy transition, we need tools that are not only technologically advanced but also practical and easy to use for various stakeholders.

The thesis provides guidelines on how data-driven decision techniques can be implemented and adapted to different challenges. The research is an important step in helping decision-makers manage the complexities of the energy transition in a more informed and sustainable way.

Effective guidelines for implementing data-driven decision techniques in the energy transition

User adaptability

Tools should be transparent, user-friendly, and accessible to different types of decision-makers.

Flexible design

Integrate methods like multi-criteria decision-making (MCDM), machine learning, and optimization to handle complex decisions.

Data coordination

Use open and accessible data sources, such as meteorological and historical data, to create accurate forecasts and scenarios.

Scenario planning

Develop semi-dynamic models that incorporate future technological and economic changes.

Decentralization and collaboration

Promote energy sharing in communities by optimizing resources and balancing interests between stakeholders.

Systems thinking

Use a holistic approach to identify connections between different parts of the energy system and avoid unintended consequences.

Contact

Organisation

Latest news from LiU

Eiko Yasui.

Japan meets Sweden in linguistic research

Eiko Yasui is from Japan. For a year, she has been researching language, grammar, and movements at Linköping University. Her work has provided new insights into how we communicate and interact, and she has thoroughly enjoyed the Swedish work culture.

Two men in a boat taking samples from the seabed.

Radioactive legacy at the bottom of the Baltic Sea

Researchers have mapped radioactivity in the marine environment at a nuclear research facility. The research has resulted in maps, that can be used to assess the risks in connection with releases of radioactive substances into the environment.

A tree branch in bloom in front of a building

LiU new on World Reputation Rankings list

For the first time, Linköping University has made it onto the British Times Higher Education magazine’s World Reputation Rankings list.