ExemplaryResultsoftheGerman Eneff:StadtResearch Program: Strategies, Technologies and Tools IEA-EBC Annex 73. Dr.-Ing.

Transcription

1 ExemplaryResultsoftheGerman Eneff:StadtResearch Program: Strategies, Technologies and Tools IEA-EBC Annex 73 Dr.-Ing. Rita Streblow

2 Initial Situation Goals Greenhouse gas Greenhouse gas emission in comparison to 1990 Increase the share of RE in energy consumption ShareofRE in gross energy consumption Atleast-40 % Atleast -55 % Atleast -80 to 95 % 18 % 30 % 60 % Reduction of energy consumption and increase in energy efficiency Reduction of primary energy consumption compared to % -50 % 2

3 Necessary Primary Energy Factor Primary energy consumption in TWh [WERT] 967 District heating Primärenergieverbrauch PEF bei 0,5 % Sanierungsquote Frankfurt Hamburg, Berlin Hannover München Münster Heatpump withspf = 3, PEF bei 1 % PEF bei 1,5 % PEF bei 2 % Sanierungsquote Sanierungsquote Sanierungsquote 243 1,6 1,4 1,2 1 0,8 0,6 0,4 0,2 0 Primary energy factor PEF bei 3 % Sanierungsquote 3

4 Planning Structure for Germany ClimateAction Program2020 Federal spatial planning National Action Plan on Energy Efficiency (NAPE) Conferences of Ministers of Spatial Planning Public agencies ADJUSTMENT State spatial planning Regional planning Local planning MUTUAL FEEDBACK Sectoral planning 4

5 Federal Ministries in the field of urban and energy planning Federal Ministry for the Environment, Nature Conservation and Nuclear Safety(BMUB) Create the framework conditions for good living standards and intact cities Promote the high level of construction technology and building materials in Germany Federal Ministry for Economic Affairs and Energy Demonstration and pilot processes Systemic approaches to energetic optimization at city district level Development of new technologies and planning tools 5

6 Master Plan Communities 6

7 Distribution of the Research Projects Methods and concepts 129 Buildings 100 City quarters 44 Tools and software 81 Supply grids 42 Specification in number of projects Multiple choice considered New technologies 204 7

8 From Research to Practice 2050 Network solutions Network solutions ENERGIEWENDE 2018 Isolated consideration Coupled consideration 8

9 From Research to Practice 2050 City district City district ENERGIEWENDE 2018 A Static planning B A B Dynamic planning 9

10 From Research to Practice 2050 Communication Communication ENERGIEWENDE 2018 Everyone alone Smart City 10

11 Research Fields Simulation Evaluations Web application Interfaces 11

12 Simulations with Physical Models GIS-Data Database model Building simulation Load curves: - Room heat - Electricity - Hot water Additional infos Building data: - Year of construction - Type - Floor space - Number of floors - Building models 12

13 Web Services Intergration of the user 13

14 Database Database (PostgreSQL, Influx) Static data = Year of construction = Floor space =. Dynamic time series = Heat demand = Electricity demand =. PostgreSQL 14

15 Building Models

16 Optimization of Energy Concepts for Different Settlements 1. Terraced houses with 35 single family houses Heatdemand: 847 MWh Electricitydemand: 129 MWh 2. Block structure with 16 multi family houses Heatdemand: MWh Electricitydemand: 214 MWh 3. Block development with 36 multi family houses Heatdemand: MWh Electricitydemand: 582 MWh 16

17 Optimization of Energy Concepts for Different Settlements 400 Costs in 1000 /a Typ 1 Typ 2 Typ 3 Conventional Konventionelle supply Versorgung Optimized Opt. Dezentrale decentral Versorgung supply Optimized Opt. Zentrale central Versorgung supply 17

18 Virtual Property as Planing Instrument Virtual property Feedback Dynamic model Analysis, optimization 18

19 Cloud-Services: Optimization City district solutions Invest building energy systems Operating costs building energy systems Subsidies Construction costs grid Energy losses grid 19

20 Cloud-Services: Physical Model Simulation of alternative solutions/ retrofit Boiler 20

21 Cloud-Services: Physical Model Simulation of alternative solutions/ retrofit Insulation Window change Window change Insulation Boiler 21

22 Cloud-Services: Physical Model Simulation of alternative solutions/ retrofit Insulation Window change unrenovated renovated Window change Insulation Boiler 22

23 Cloud-Services: Optimization Usecasewitha citydistrictof50 buildings Boiler +TES CHP+boiler+ TES Boiler +TES CHP+boiler+ TES + district heating Boiler +TES Annuity 23

24 Research Fields Simulation Evaluations Cloud energy management Control of BES Control of heating/ cooling grid B B B B E- vehicle HP Heat Wärme Cold Kälte Power Strom CHP Web application Interfaces 24

25 Towards Near Zero Energy Resilient Neighborhoods Energy System stability management systems Missing evaluation methods and control signals Data- and service platforms Missing operator models, legal framework and data security Thermal electrical plants Classical business models and missing qualified personnel Static procedures for single buildings Evaluation methods Static signals and missing correlation between costs and emissions Control signals Classical concepts for dimensioning Storage systems Data security and classical concepts for dimensioning User behaviour 25

26 Kontakt E.ON Energy Research Center Mathieustraße Aachen Germany Rita Streblow T F rstreblow@eonerc.rwth-aachen.de 26