The goal of this project is to make better use of data, modelling and datadriven decision-support for governing the transformation of urban energy systems towards sustainability and climate neutrality.

Cities are dense and complex manifestations of all elements of the energy system, involving generation and distribution, provision of heating, cooling, lighting, mobility, communication, and consumption of goods and services. The digitalisation of cities creates a wealth of data which can be of great support for governing the urban energy transition.

Making use of available data and designing decision-support tools for an energy and climate transition in cities needs to build on a sophisticated understanding of the fundamental, long-term and systemic change processes of infrastructures or sociotechnical regimes. 

Decisions on infrastructure investments, energy planning, or measures to change behaviour can be improved by urban data analytics and energy modelling. However, using such data resources is no straightforward process. Not only are data sources often proprietary, distributed and sensitive from a privacy perspective, but the models and decision-support tools are often driven more by technical considerations than by the needs and usability for different types of decision-makers in cities.

Goal of the project

The overarching goal of this project is to make better use of data, modelling and datadriven decision-support for governing the transformation of urban energy systems towards sustainability and climate neutrality. Improved decision-making processes can be a powerful contribution to meet the challenges of sustainability and climate change mitigation in cities and regions, but also the challenge of integrating social policy goals and making decision-making more transparent and democratic. The project outcomes can be of great importance for the capacity of cities to manage the transition towards a more sustainable energy system.

Implementation of the project

The project is interdisciplinary collaboration between Link√∂ping University and KTH Royal Institute of Technology and requires interdisciplinary effort where IT, engineering and energy modelling competencies are combined with social science competence about organisational change, governance and participation processes.


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