Project management overall project: Johannes Weninger, Bartenbach GmbH
Project consortium:
Bartenbach GmbH
Zumtobel Lighting GmbH
Hella Sonnen- und Wetterschutztechnik GmbH
University of Innsbruck, Department of Computer Science
University of Innsbruck, Energy Efficient Building Unit
Funding organisation: Federal Ministry for Climate Protection, Environment, Energy, Mobility, Innovation and Technology (BMK) represented by Österreichische Forschungsförderungsgesellschaft mbH (FFG)
Funding programme: AI for Green
Funding amount: 319,175 euros (UIBK-EEB)
Duration: 01.07.2024 until 30.06.2027
Summary of the programme
Despite pioneering successes such as the introduction of LEDs and sensor-based control systems, an increase in efficiency in the lighting sector (15% to 20% of global electrical energy demand in the building sector) is urgently needed for climate protection and sustainability. Improvements in the area of integral artificial lighting and daylight control systems offer great potential for this, but this can only be fully exploited if application-specific characteristics such as individual room usage behaviour are taken into account. As this information is not normally available during the planning phase, artificial lighting and daylight control systems today are primarily based on generalised assumptions about user characteristics and behaviour without taking real individualities into account.
These incorrect assumptions made in the early planning and simulation phase often result in large deviations from reality (so-called performance gaps) and prevent the full realisation of the desired energy and health potential of modern lighting systems. In addition, the resulting discrepancy remains largely unrecognised due to a lack of extended commissioning or leads to resource-intensive and costly subsequent adjustments to control systems during operation in order to compensate for the incorrect assumptions made during the planning phase. However, improved mapping of application-specific properties in the planning process will continue to prove difficult in the future and in some cases (e.g. new buildings) is simply impossible due to a lack of user information. To ensure the optimal operation of integral control systems, it is therefore essential to adapt them to the respective application during operation. In addition, systems should also be able to efficiently map changes in utilisation (e.g. seasonal effects or when users change) in order to ensure that the energy and health potential is utilised in the long term over the entire lifetime of the building. However, there are currently no applicable control concepts available for this.
