Topic 3: Managing the urban energy transition: data management and decision support systems

Challenge Description

The energy transition requires new ways of urban data management and a sensible use of digital tools for both decision-making and operation. In this regard, this topic focuses on exploring and advancing innovations that enhance the planning, monitoring and optimization of PED that, at the same time, are integrated into city-wide decision-making tools and strategies for energy planning. The key challenge within the PED context is to support situation awareness and decision support to various stakeholders, which has to adequately handle an ensemble of distributed data sources (e.g. from various renewable energy appliances) and dynamic and multidirectional data streams (e.g. in the case of V2G). To account for the systemic character of this challenge, novel approaches beyond energy technology development are required that also enable efficient resource and capacity management, and which allow for the adequate management of data protection.



Decision-making in the context of positive energy districts needs to rely on valid and comprehensive data on different aggregation levels (from household level upwards) from both the digital and the physical infrastructure. The investigation and demonstration of novel digital urban data management solutions that account for heterogenous data sources and data processing requirements, decentralized data governance and multifaceted stakeholder interests of PED is therefore of central importance. In order to enable more strategic decision-making by urban authorities on both the neighborhood and city level, approaches based on micro-level data available at city-scale as well as data harmonization efforts are necessary to better integrate energy planning and spatial planning. Digital tools for the energy transition not only need to effectively cover cross-sector data collection, data management and monitoring, but they should also enable the modelling of impact. A major requirement for succeeding with this is to interweave technology-related data with socio-economic and behavioral data of end-users, as well as administrative data in order to ensure people-oriented solutions in any given urban setting. Investigations towards this objective should identify the potentials and reflect on the constraints of emerging technology, such as artificial intelligence, in order to provide guidelines for their application for PED data management and decision support.


Project proposals submitted under this topic should address one or several of the following issues:


  • What are the needs and gaps in terms of data availability for PED for different stakeholder groups? What are the needs and gaps in terms of city-wide data availability?


  • What are the needs and gaps in terms of data management and processes (e.g. access, updating, quality management, harmonization, interoperability, linkage etc.) for PED on neighborhood/district levels and city-level? Which principles and approaches should be considered for data governance of PED, including data privacy management and data security?


  • How should data management approaches be made transparent, aligned and linked between PED and to other parts of urban energy systems, on a local, regional, national and international scale?


  • How can data be exchanged and shared across different institutional boundaries, such as end-user communities, utilities, city governments, businesses and other actors?


  • How can cross-sectoral data collection and management (energy, resource flows, mobility, etc.) be organised?


  • How should the human interface of PED data management, monitoring and optimization systems be designed to support various types of users?


  • What are the potentials and constraints of novel technology trends, such as artificial intelligence, as a means for improving decision support in the planning, operation and adaptation of PED?


Expected Outputs and Outcomes

Rather than focusing on isolated technology solutions, projects are expected to address this topic in a systemic way. Project outcomes should be impact-oriented and process-oriented, and therefore as concrete and user-centred as possible. Expected outcomes include, but are not limited to:


  • Identification of gaps, key challenges, barriers and success factors regarding data collection and data access related in and around PED


  • Modelling and prototyping of PED data management systems, tools and decision support systems for urban energy and spatial planning that allow for a holistic analysis of urban transitions, also taking account of the mobility system, resource flows, and other aspects


  • Modelling and prototyping of data management systems, tools and decision support systems for urban energy and spatial planning, including but not limited to solutions linking PEDs with city-wide processes and instruments, approaches for continuous updating and quality management as well as considerations of legal and regulatory challenges and potentials of data availability and data use


  • Demonstration of the viability and applicability of PED data management models and approaches (especially in terms of scalability, technology openness and flexible integration)


  • Evaluation of the added value and impact of PED data management models and approaches, regarding the facilitation of decision-making processes, in terms of acceptance, usability, and quality of achieved decisions


  • Recommendations and guidelines for mainstreaming and replication, considering geographical and cultural context, as well as social and regulatory aspects