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Research shows how data-driven tools can accelerate the energy transition

13 December 2024

Teiksma Buseva

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. Photographer: Teiksma Buseva
Qianyun Wen successfully defended her thesis.

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

Supervisor

Photo of Yang Liu

Yang Liu

Senior Associate Professor

Supervisor

Photo of Olof Hjelm

Olof Hjelm

Professor

Organisation

Environmental Technology and Management

Environmental Technology and Management (MILJÖ)

Division of Environmental Technology and Management is a research and education environment at the Department of Management and Engineering. We turn environmental problems into opportunities.
Campus Valla overview.

Department of Management and Engineering (IEI)

The Department of Management and Engineering (IEI) strengthens and develops tomorrow’s industry, business world and society by ground-breaking research, education and innovation.
Studenthuset on Campus Valla in Linköping

About LiU

Linköping University, LiU, offers innovative education and boundary-crossing research. The students are among the most desirable in the labour market and international rankings consistently place LiU as a leading global university.

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