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SynENERGY - Energy optimised settlement development by making use of synergies of energy efficiency, spatial planning and building culture
SynENERGY aims at an innovative, holistic approach to urban district optimization. The project targets a comprehensive analysis of the framework and urban development concept which includes not only optimisation of sustainable energy supply and use but also increased material flows (construction and disposal) at urban district level.
Syn[En]ergy: Development of Potential Synergy Effects between the Interdependency of Urban Planning goals and Photovoltaic Usage on Open Urban Landscapes
Open spaces such as parking lots, brownfields and some categories of recreation areas offer an underutilised potential for photovoltaics in urban regions. In the course of Syn[En]ergy an inter- and transdisciplinary approach potential synergies and conflicts with other use demands were investigated, a typology and practical solutions for selected areas with regard to requirements from economy, urban planning and design, legal as well social aspects developed, and then evaluated by stakeholders from enterprises, administration and the general public.
VITALITY District - Optimized energy concepts in the early planning phase of resilient, energy-efficient neighbourhoods
The aim of the VITALITY District project is to coordinate the total (electrical and thermal) load and generation profile in the design phase of urban areas and neighbourhoods in order to optimize the energy concept of energy-efficient districts. Hence smart city indicators in detailed level (buildings, individual technologies, public spaces) as well as models, principles and catalogs of criteria for energy-optimized urban neighbourhoods were created. The results were presented in compact form on the district level in order to serve as input for future urban planning projects.
KityVR - Artificial intelligence techniques to implement CityGML models and VR visualization
The KityVR project deals with key research aspects at the interface between 3D city models and virtual reality. It addresses questions such as how virtual reality can be used for visualization in the field of 3D city models and how machine learning and statistical methods can be used to enrich or complete energy-related data sets.