As electricity grids become increasingly complex due to electrification and the growing integration of renewable energy, predictive analytics is being promoted as a tool to improve monitoring, planning and decision-making. Despite its considerable potential, however, adoption has been slower than expected.
In the thesis Predictive Analytics in Smart Grids: Examining the Interplay Between Expectations and Thoughts on Adoption, Theodore Kindong explores how policymakers, grid operators, market actors and energy users perceive predictive analytics, and how their expectations influence its adoption in practice.
Based on a Swedish case study, the research shows that different stakeholders often have diverging expectations of the role predictive analytics should play in the smart grid. At the same time, adoption is shaped by policy priorities, vendor visions and organisational goals. The findings suggest that realising the potential of predictive analytics requires not only technological solutions, but also a shared understanding and coordination among the actors involved.
The thesis contributes new knowledge on how digital innovation can be introduced in complex socio-technical systems and highlights the importance of collaboration in the development of future smart grids.
