WP6 –
Building Stock Module

The building module (WP6) work package of ETH, Chalmers University and TEP Energy consists of three main objectives: (a) research and development, (b) integration and (c) implementation.

 

Research and Development

The building stock of urban settings has a decisive impact on its overall performance in all pillars of sustainability. The building stock model assesses the consequences of the existing parameters by applying a bottom up approach of construction components and energy systems for different scenarios. The model includes different energy services, energy supply systems, building technologies as well as energy-efficiency measures. Model specific options on embodied energy and usage spatially differentiated potentials of renewable energies are to be added in 2012. The model so far is able to describe the environmental impact as a result of development scenarios in the building sector. The environmental impact can be read out on numerous levels including CO2eq and other established indicators (figure below), including GIS-based representation.

Furthermore the data structure will be adapted to include techno-economic characteristica, economic potentials and investor preferences, depending on building types and categories of building owners and users (agent initialisation) in order to be compatible with the agent-based transport model.

The combination of multiple models, the demands for interactivity and the resulting increase in data sets directly results in an increase in related calculation processes. The current version of the BSM was not intended to cover such amounts of processing and therefore has to be redesigned. Within this WP6 the BSM will be set up as a module that will be able to meet the computation requirements. Further the BSM will be tightly coupled with the GIS/data-warehouse.

The data interface Model/ Warehouse will be designed to be in line with the other modules to allow for easy design of the warehouse itself. Special care will be taken on the intellectual property as well as on the application of methods for census data anonymization data security that has been defined in WP 1 and WP 2.

 

Integration

The integration within the project happens mainly through the GIS/data-warehouse. The research of the building module needs various geographically assigned synthesized first stage data such as spatial distribution of building types, ownership structure, condition of building stock, accessibility, historical development of the building stock, neighbourhood characteristics, availability of renewable energy sources and energy infrastructure etc. Following the research procedure it provides second stage data such as CO2eq Emissions resulting from the building stock to the GIS/data-warehouse.

 

Implementation

The building module will be supplemented with the interface to the GIS/data-warehouse.

The interface transfers model results to the warehouse, and, vice versa, operates the building module. For the case studies, a simplified APP of the existing model is transferred to the data warehouse and cloud servers. The warehouse is supplemented with the necessary data for the case studies and linked with the software, depending on the cloud system. The results of existing spatial regression models are implemented as default values in the data warehouse.

 

Fig. up: Model input: Example Retrofit rate of wall insulation by construction periode  –(MFH, efficiency scenario). Fig. down: Model result: Example of total energy demand per person.

Besides the application of the newly developed cloud system on the city level in Switzerland a second application will be carried out for London. This case study allows us to gain further insights into the future transferability of the developed software solutions to other European regions.