Power, space heat and refurbishment: Tools and methods to include energy in urban planning. Thomas Hamacher

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1 Power, space heat and refurbishment: Tools and methods to include energy in urban planning Thomas Hamacher

2 Problem Statement 2

3 New developments Urban planning Smaller scale units in the infrastructure gain more control City operation Big Data 3

4 Urban Planning r o v g i f u lä 4

5 Urban planning and energy 5

6 Two steps in urban planning Spatial planning Zonal planning Regional planning 6

7 Energy utilisation plan as new vector in spatial planning 7

8 New tools for the energy utilisation plan Analysis of Heating Technologies Building Data Base Solar Potentials City-GIS Metrological and Geological Data Infrastructure planning Infrastructure Data 8

9 Energy Use Plan Ingolstadt Wind potential Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 9

10 Energy Use Plan Ingolstadt Photovoltaic potential Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 10

11 Energy Use Plan Ingolstadt Geothermal potential Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 11

12 Energy Use Plan Ingolstadt Heat map Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 12

13 Energy Use Plan Ingolstadt Potential of refurbishment Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 13

14 Energy Use Plan Ingolstadt Potential combined heat and power Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 14

15 Energy Use Plan Ingolstadt Potential heat pumps (collectors) Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 15

16 Energy Use Plan Ingolstadt Summary Die Ergebnisse wurden im Rahmen eines Forschungsprojektes ermittelt. Ohne Gewähr auf Richtigkeit. TUM IfE B14 Source: Wagner et al. 16

17 Energy use plan: path to automation Potential of shallow geothermal heat Quelle: Eder, LfU 17

18 Tools and methods to plan energy infrastructures and concepts Numerous energy models exist on national and international level, how can they be modified to be adequate for the urban scale? 18

19 Combination supply and demand Supply Side (DH-Network, ) Demand Side (Building stock) 19

20 City and heat supply

21 City and heat supply

22 City and heat supply W ärmenachfrage (2008 = 100% ) 110% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Extern vorgegebene Zielwerte (80% der Endenergieeinsparung) TIEF_BAU TIEF_E20 TIEF_R07 HOCH_BAU HOCH_E20 HOCH_R07 Vollsan_NEH Vollsan_PH 100 % = Startwert 2008 = GWh/a Darstellung: Daniel Reiter, Salzburg AG

23 City and heat supply

24 City and heat supply

25 City and heat supply

26 City and heat supply

27 City and heat supply

28 City and heat supply

29 City and heat supply

30 City and heat supply

31 City and heat supply Hoch-E20: Deckung Wärmenachfrage GWh/a 1,800 1,600 1,400 1,200 1, Solar Sonstige Pellets Holz Wärmepumpe Strom Heizöl Erdgas Fernwärme Rückgang der Ölheizungssysteme und Trägheit leitungsgebundener Versorgung Darstellung: Daniel Reiter, Salzburg AG

32 Combination supply and demand Heat (DH-Network) Gas Electricity 32

33 Interdisciplinary planning of target networks for electricity, gas and heat Objective: Investigation of effects on energy infrastructures in cities caused by energy policies in Germany ( Energiewende ) Methods: Variants calculation Definition of scenarios for load and generation Optimization of networks considering synergies Electricity Gas District heating Target network Target network Target network Assessment of results Special focus: Interdisciplinary planning of networks for electricity, gas and district heating Source: Schönsteiner et al. IfE B-13 33

34 Exemplary optimization of a district heating network in Frankfurt Result: Optimized heat flow for different scenarios Example: N Heat flow (scaled with quantity) Generation facilities Basemap: OpenStreetMap (and) contributors, CC-BY-SA Conclusions: Identification of areas with long-term potential for district heating networks Source: Schönsteiner et al. 34

35 Definition of scenarios for load and generation Variants calculation Optimization of networks considering synergies Electricity Gas District heating Target network Target network Target network Assessment of results IfE B-13 Source: Schönsteiner et al. 35

36 Combination supply and demand Heat (DH-Network) Electricity 36

37 Coupling heat and electricity sector Source: Heilek 37

38 Combination supply and demand Flexible demand Electricity 38

39 Football heat map: guess who played? Quelle: 39

40 Time budgets micro view Watch TV Dinner Sleep Breakfast Drive to work Drive home Go to cinema Work Go shopping

41 Time budgets 41

42 Model predictive control of building automation C electricity price, weather data self-adapting model MPC electrical HVAC system building Source: Jungwirth

43 Public participation 43

44 Summary Building design, construction, refurbishment and maintenance can optimally only been planned in the context of the whole urban system and partially beyond Area and zonal planning needs to include energy right from the beginning, new methods and tools need to be developed and more urgently be implemented in daily processes Planning the energy infrastructure becomes more complex with the advent of new possibilities like power-to-heat, flexible demand and area wide refurbishment New actors are necessary to catalyse the planning and manage the complex projects including private and public actors 44

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