Big data for EnBop

Project description

The aim of the project is to develop and evaluate methods for applying big data analysis methods to building automation data in order to identify potential for optimizing the energy efficiency of existing buildings.

The innovative focus is on the application of analysis methods for large and complex data volumes (big data) to the enormous amount of operating data from building and component automation in modern buildings. Today, this data is generally only used for the direct operational management of buildings and systems. Only a minimal proportion of the data is used for visual inspections, alarms or the most basic analyses and reports. Most of the data is not stored or evaluated.

The approach pursued here aims to systematically apply powerful big data methods, in particular through visualization/mapping and algorithms for data analysis, to historicized and real-time data from building automation systems and individual building services components such as heat pumps, boilers, ventilation units or pumps in order to analyse the potential of this data and develop utilization concepts.

Possible application scenarios include

Component-specific analyses
for operational optimization
for cost-optimized and preventive maintenance management
to identify quality deficits in individual batches or installation companies
System-specific analyses of building and system data
to identify and correct operating errors
for the optimization of operating errors
Neighborhood-specific analyses
for the energetically and economically optimized operation of systems in the urban and grid context
In the project, typical data is analyzed and evaluated both via simulations and in practice in order to develop identification methods from this data for the applications described above. The methods will then be tested in practice on real buildings and their systems.

The intended methods will enable a comprehensive and largely automated identification of optimization potential in existing buildings and thus form the basis for a simpler, accelerated and more economical use of this potential. In particular, component manufacturers will be involved in the project to identify services and business models.