1. Visualization of CONCERTO Data Dan Gutu Prof. Andreas Wagner Workshop on data status and first CONCERTO Premium results Brussels, October 23 rd 2012 Karlsruhe Institute of Technology (KIT) 1

2. Software Components Overview TMD Concerto Data TMD Concerto Data Semantic Layer Concerto Knowledge Base General facts & rules Customized facts & rules Data Monitor Data Monitor Visualization Reasoner Interactive sandbox

3. Objectives of Visualization  Provide visual support for the decision making processes regarding energy efficiency measures  Realization through a user-friendly visualization approach of data and indicators related to Buildings and Energy Supply Units 3

4. Visualization Workflow Concept 4 Filtered by metadata Filtered by map 1 Select ion of buildings and ESUs Suitable to sel. indicators selected buildings and ESUs selected indicators Results CSV-Export table / graphics change selection Filtered by occasion 2 Filtered by role Filtered by topic Selection of indicators suitable to sel. objects

5. Selection of Objects by Map 5 Selection of buildings and Energy Supply Units (ESUs) from CONCERTO cities by map Simultaneous pre-checking of calculability regarding selected indicators

6. Selection of Objects by Filtered List 6 Selection of buildings and ESUs from lists Metadata-based filtering of listed buildings and ESUs Simultaneous pre- checking of calculability with respect to selected indicators

7. Selection of Indicators 7 Selection of indicators for buildings and ESUs from lists Metadata-based filtering of listed indicators Simultaneous pre- checking of calculability with respect to selected buildings and ESUs

8. Filtering 8 Metadata-based filtering of listed buildings, ESUs and indicators Aggregation of filters for buildings, ESUs and indicators

9. Building filtering criteria 9 Building status –new –refurbished Building type –industrial –municipal –residential –tertiary Year of construction Area Features and measures –Thermal bridges –Improvement of air tightness –Special building materials –Shading –Ventilation –… Technology used before and after refurbishment –Boiler –Condensing boiler –District heating/cooling network –Compression/absorption/adsorption pump –Solar thermal collectors –Solar air collectors –Night storage heater –Electric heating –Stove –Continuous flow water heater –Compression refrigerator machine –Conventional HVAC machine –Reversible heat pump –Absorption/adsorbtion pump –Micro CHP –Connection to electricity grid –…

10. ESU filtering criteria 10 ESU type –Boiler –Solar-thermal –Heat pump –Micro CHP –Photovoltaic –Chiller –Biomass –Geothermal –Wind power –Hydro power –District heating –Thermal storage –Biogas –… ESU energy carrier –Light/heavy oil –Domestic gas – grid bound/from tank –Liquefied petroleum gas –Hard coal –Lignite –Wood chips –Pellets –Bio waste –Energy crops –Biogas –District heat/cold –Solar radiation –Ambient air –Geothermal heat –Wind energy –Potential energy –Electricity/’Green’ electricity –…

11. Indicator filtering criteria 11 By target group –Building owner or developer –Utiltiy or energy service –Authority and legislation –Grants, funding, insurance –Energy consultancy –Building services –Public By topic –Economic –Environmental –Economic-environmental –Indicators for grant providers By occasion –New construction of building –Refurbishment of building –Sale or purchase of building –Implementation of large-scale energy supply –Sale or purchase of land –Set-up of masterplan –Set-up of legislation –Design of information campaign –Design of grant scheme –Set-up of municipal targets

12. Representation of results – buildings 12 demand = consumption demand = consumption/2 demand = 2*consumption

13. Representation of results – buildings 13

14. Representation of results - ESUs 14

15. Representation of results - ESUs 15 Building integrated photovoltaics

16. Demonstration – Scenario 16