Abstract. This paper focuses on the importance of Geographical Digital Twins to increase renewable energy production in urban areas and cities for decarbonization and reduction of climate change impacts. The study demonstrates the role of interoperable geographical digital twins based on Free and Open-Source software and geospatial software technologies in the simulation, monitoring, and management of renewable-based energy systems. We simulated the potential for building-integrated and building-attached solar photovoltaic (PV) electricity generation for the use case in cities to allow at a later stage for scale up to a nationwide level. The platform provides a tool for estimating PV power generation at high resolution across entire neighbourhoods and districts. Tools for the identification of cost-efficient PV placement or integration in buildings on roof-tops and facades were implemented to allow for interactive selection of optimal PV placement. The developed platform serves multiple beneficiaries, including municipalities, urban planners, developers, citizens, investors, and energy communities. Overall, the study highlights the advantage of an interoperable geographical urban digital twin, which provides the flexibility necessary to simulate and test scenarios for rapid, integrated urban planning for decarbonization under climate change. The platform is based on open-source, open standards and APIs, using open 3D city models, and allowing seamless integration of simulation and assessment methods and tools to provide a 3D real-world environment to assess and develop energy transition approaches.
[1]
J. Stoter,et al.
Challenges of urban digital twins: A systematic review and a Delphi expert survey
,
2023,
Automation in Construction.
[2]
M. Casals,et al.
The adoption of urban digital twins
,
2022,
Cities.
[3]
C. Braun,et al.
A SCALABLE APPROACH FOR SPATIO-TEMPORAL ASSESSMENT OF PHOTOVOLTAIC ELECTRICITY POTENTIALS FOR BUILDING FAÇADES OF ENTIRE CITIES
,
2019,
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
[4]
Ina Wagner,et al.
Supporting community engagement in the city: urban planning in the MR-tent
,
2009,
C&T.
[5]
Eduard Petlenkov,et al.
Uses of the digital twins concept for energy services, intelligent recommendation systems, and demand side management: A review
,
2021
.
[6]
Ron Janssen,et al.
Effectiveness of collaborative map-based decision support tools: Results of an experiment
,
2013,
Environ. Model. Softw..
[7]
Ulrich Leopold,et al.
iGUESS - A web based system integrating Urban Energy Planning and Assessment Modelling for multi-scale spatial decision making
,
2012
.
[8]
COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS
,
2009
.
[9]
Thomas H. Kolbe,et al.
Spatio-semantic coherence in the integration of 3D city models
,
2007
.