Building Thermal Energy Simulations Supported by the CityGML Energy ADE

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1 Building Thermal Energy Simulations Supported by the CityGML Energy ADE INSTITUT FÜR AUTOMATION UND ANGEWANDTE INFORMATIK KIT Die Forschungsuniversität in der Helmholtz-Gemeinschaft

2 Agenda General remarks on the status of the Energy ADE development and corresponding KIT activities Workflows for building energy simulations based on 3D building models Standard workflow (without Energy ADE) KIT workflow using the Energy ADE KIT implementations CityGML LoD 2/LoD 3 Energy ADE Energy ADE Simulation system Summary and outlook 2

3 Claim of the CityGML Energy ADE The Energy ADE is a 3D geometric / semantic data format for building and urban energy related data, supporting Multiple use cases Multiple simulation systems Multiple stakeholders Interoperable data exchange between different IT systems It allows for multi-scale urban-energy modelling, going from single buildings up to whole districts or cities Simulations are based on available data from virtual 3D city models, esp. CityGML data 3

4 Evaluation of the Energy ADE This can only be proven by using the Energy ADE to solve real, energy simulation related problems What's needed are Energy ADE sample data, supporting different types of simulations Interfaces of the Energy ADE to different simulation systems on Building level (e. g. EnergyPlus, TRNSYS, MatLab, ) City level (e. g. TEASER, SimStadt, CitySIM, ) 4

5 KIT activities concerning Energy ADE The general goals are to develop a software-tool for easily generating Energy ADE sample data to evaluate the Energy ADE on base of real building models The activities are currently restricted to the use case "Dynamic simulation of the annual heating / cooling demand"; a well defined subset "KIT-Profile" of the Energy ADE ( processing of file-based, XML-encoded data; single-zone thermal models; two specific energy simulation systems EnergyPlus (Open Source) Gebäudesimulation 3D-Plus (Commercial, Hottgenroth Software) 5

6 Workflow for building energy simulations based on 3D building models Building typologies Statistics Other information Default values Building model Trans formation Simulation model Simulation Results Standard workflow 6

7 Workflow for building energy simulations based on 3D building models Building typologies Statistics Other information Default values Default values CityGML model Enrichment Energy ADE model Trans formation Simulation model Simulation Results KIT workflow 7

8 Workflow for building energy simulations based on 3D building models Building typologies Statistics Other information Default values Default values CityGML model Enrichment Energy ADE model Trans formation Simulation model Simulation Results KIT workflow 8

9 Implementation of the workflow Workflow is implemented in the GML-Toolbox software Stand-alone Windows application written in C++ and MS.NET Generation, reading/writing, checking and semantic transformation of GML-based data Not open source, but a freeware version (actually without Energy ADE functionality) is available 9

10 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) window to façade ratios to all building elements Step 4: User controlled assignment of occupancy models/parameters and schedules Output: Energy ADE model 10

11 LoD 2 LoD 3 11

12 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) window to façade ratios to all building elements Step 4: User controlled assignment of usage parameters and schedules Output: Energy ADE model 12

13 Geometric checking and correction Detection of severe geometrical errors Detection of shared walls between buildings and building parts 6 Building objects Up to 5 BuildingPart objects Source: Stadt Karlsruhe 13

14 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) window to façade ratios to all building elements Step 4: User controlled assignment of usage parameters and schedules Output: Energy ADE model 14

15 Central building parameters Location of the building Is heated / is cooled Functional classification of building Architectural classification of building Construction weight Year of construction Year of last renovation Number of storeys Building height Gross/net volume Gross/net floor area Available in CityGML data (eventually) Not represented in CityGML 15

16 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) window to facade ratios to all building elements Step 4: User controlled assignment of usage parameters and schedules Output: Energy ADE model 16

17 Building physics Simple construction model Advanced construction model Physical and optical parameters for groups of building elements (roof, outer wall ground slab, window, door): U-value, density, specific heat, thickness, transparency, glazing ratio Window to facade ratios for roof and outer wall (only LoD2) Detailed, multi-layered constructions for individual building elements Window to facade ratios for individual roof and outer wall elements 17

18 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) opening-ratios to all building elements Step 4: User controlled assignment of usage parameters and schedules Output: Energy ADE model 18

19 Usage parameters and schedules Heating and cooling set-point temperature schedules Heat gains from occupants Floor area per person / maximal number of persons in the building Heat emission per person Occupancy schedules Heat gains due to electrical devices and lighting Thermal energy emission per floor area Operational schedules Heat losses due to ventilation Ventilation schedules 19

20 4 types of schedules for yearly values Constant value schedule Dual value schedule Daily pattern schedule Time series schedule 1 average value 1 usage value 1 idle value Usage hours per day Usage days per year Different time periods in a year Different daily schedules in a period Daily schedules are characterized by daytype and a time series of day values Arbitrary time series of year values 20

21 User controlled enrichment of CityGML models Input: Single CityGML LoD2 or LoD3 building model Step 1: Automatic geometry checking and (if possible) correction Step 2: User controlled checking and (if necessary) addition/correction of basic building parameters Step 3: User controlled assignment of physical parameters and (for LoD2) opening-ratios to all building elements Step 4: User controlled assignment of usage parameters and schedules Output: Energy ADE model 21

22 LoD 2 LoD 3 22

23 LoD 2 LoD 3 23

24 LoD 2 LoD 3 24

25 LoD 2 LoD 3 25

26 Automatic enrichment of CityGML models Input: Multiple CityGML LoD2 or LoD3 models Step 1: Checking whether the building is heated Check is based on building function No cooling is assumed as default Step 2: Geometry checking and (if possible) correction Step 3: Assignment of physical parameters and (for LoD2) window to facade ratios to all building elements (work in progress) Step 4: Assignment of usage parameters and schedules (work in progress) Step 5: Save data as Energy ADE model 26

27 CityGML Energy ADE Simulation (IFCExplorer) GML-Toolbox Transformation EnergyPlus Explicit geometry of thermal boundaries and thermal openings Energy ADE Transformation GebSim IFCExplorer Gebäude-Simulation 3D Plus Thermal boundaries and thermal openings are represented by parameters 27

28 Sample model: KIT Campus Nord, Building 445 EnergyPlus GebSim Energy demand heating Energy gains occupants Energy gains lighting Energy gains devices Energy losses ventilation , , , , , , , , , ,5 28

29 Energy ADE file with simulation results ADE model, based on CityGML LoD2, before simulation ADE model, based on CityGML LoD2, after simulation 29

30 Summary At KIT are available: A tool (GML-Toolbox) for enriching CityGML LoD 2 and LoD 3 building models with energy related information, and storing the result in Energy ADE format; Software modules to transform Energy ADE data into input data models for two specific simulation systems EnergyPlus (GML-Toolbox, IFCExplorer) ETU Gebäude-Simulation 3D Plus (IFCExplorer) It could be proved that the Energy ADE can principally support building energy related simulations. The developed software modules only support single zone models and use a proper subset to the Energy ADE data model. In particular, classes of the Energy Systems module are not used at all. 30

31 Outlook Next steps Automatic enhancement of CityGML models based on building typologies and functional classifications Cooperation with Institut für Wohnen und Umwelt (IWU) Darmstadt Implementation of the "KIT-workflow" with other simulation systems Cooperation with RWTH Aachen Improvement of the transformation Energy ADE EnergyPlus Cooperation partners are welcome Improvement of the Energy ADE data model, esp. harmonization with gbxml gbxml + Energy ADE gbgml?? 31

32 Are there any questions? 32