Energy Model Southtyrol Appendix 2 Refurbishment of residential buildings

Transcription

1 Energy Model Southtyrol Appendix 2 Refurbishment of residential buildings W. Sparber, D. Moser, M. Prina, U. F. Oberegger, R. Pernetti, G. Garegnani, R. Vaccaro, M. Cozzini

2 Objectives Establish cost effective refurbishment scenario until 2050 for the residential building stock of South Tyrol Estimate investment cost and energy savings for different energy efficiency measures, building categories and years of construction Base the calculation on monitored or statistical data whenever possible 2

3 Buildings, surfaces, occupancy level ISTAT statistics

4 Surfaces dwellings occupied by residents ISTAT census 2011 Municipality Surface [m 2 ] Bolzano Merano Bressanone Brunico Appiano sulla Strada del Vino Laives Lana Caldaro sulla Strada del Vino Renon Sarentino Vipiteno Castelrotto Silandro Valle Aurina Naturno Campo Tures Millions 4 3,5 3 2,5 2 1,5 1 0,5 0 Surface in square meters % of total surface 50% 40% 30% 20% 10% 0% Total residential surface in South Tyrol: 18,390,738 m 2 Source: popolazione/censimento popolazione 2011: superficie delle abitazioni occupate da persone residenti 4

5 Occupancy level of residential buildings ISTAT census 2011 Number of residential buildings broken down by percentage of occupied dwellings % occupied % occupied 50 75% occupied 25 50% occupied 0 25% occupied empty Share of total number of buildings 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percentage of residential buildings with a certain occupancy level 79% 100% occupied 4% 7% % occupied 50 75% occupied 2% 1% 25 50% occupied 0 25% occupied 8% empty Number of residential buildings in South Tyrol: 85,644 Source: popolazione/censimento popolazione 2011: edifici residenziali per classe percentuale di abitazioni occupate 5

6 Monitored thermal consumptions EU project Sinfonia

7 Bolzano district data from Sinfonia project 1384 records Gross surface: 2,251,199 m 2 12% of residential surface in South Tyrol Net surface: 1,868,495 m 2 * District does not contain historic center and industrial zone * Estimated at 83% of total gross surface Source: Sinfonia project, smartcities.eu/en/project 7

8 Monitored residential heating + DHW consumption Bolzano district data from Sinfonia project Eurac analysis 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% Partially unheated dwellings 10% 9% Specific consumption distribution 5% 8% 15% 15% 14% 14% 3% 1% 2% 0% 0% 3% kwh/m 2 a * * All consumptions in kwh/m 2 a are based on the net surface Reference year:

9 Monitored residential heating + DHW consumption Bolzano district data from Sinfonia project Eurac analysis 30% 20% 10% 0% 5% 5% 6% 10%14% Before % 16%12% 4% 2% 1% 0% 0% 3% 9 < >300 kwh/m 2 a buildings 850 buildings 20% 13% 14% 13% 14%15% 15% 11% 10% 4% 8% 3% 5% 1% 2% 0% 1% 2% 0% < >300 kwh/m 2 a 30% 20% 10% 0% 10% 5% 10% 6% % 14% 7% 15% 2% 1% 1% 0% 0% 1% < >300 kwh/m 2 a After buildings 9% 9% 11%15%17% 11% 7% 54 buildings 20% 17% 15% 10% 5% 2% 0% 0% 2% 0% 0% 0% < >300 kwh/m 2 a Reference year: 2010

10 Monitored average residential heating + DHW consumption* Bolzano district data from Sinfonia project Eurac analysis FH: single or two family house MFH: multi family house (small 10 apt, big > 10 apt) Block: apartment block (> 10 apt, > 4 floors) kwh/m 2 a FH SMALL MFH BIG MFH BLOCK Before After 2005 * After exclusion of outliers Reference year:

11 Uncertainty: specific heating + DHW consumption if 20% of the residential surface in Bolzano were unheated Annual kwh/(m 2 heated surface) Increase by 25% FH SMALL MFH BIG MFH BLOCK Before After 2005 Reference year:

12 Surfaces per building category and construction year EU projects Sinfonia and AlpBC

13 Residential surface distribution urban area Example of Bolzano district data from Sinfonia project Eurac analysis 60% 50% 40% 30% 3,4% 4,1% 3,7% 2,6% 20% 10% 0% 39,0% 24,1% 0,5% 0,8% 5,9% 0.4% 8,8% 3,1% 3,6% 1 2 FH Small MFH Big MFH Block Before After 2005 Reference year:

14 Residential surface distribution rural area Example of municipalities St. Leonhard, St. Martin and Moos in Passeier valley Data from AlpBC project Eurac analysis 60% 50% 40% 30% 20% 10% 0% Source: AlpBC project, 2% 9% 29% 12% No apartment blocks 5% 1% 3% 16% 10% 4% 7% 1 2 FH Small MFH Big MFH Before After % Reference year:

15 Residential heating and domestic hot water consumption at Province level Eurac calculation

16 Computation of residential heating + DHW consumption at Province level assumptions Bolzano and Merano: surface distribution of Bolzano district from Sinfonia project All other municipalities: surface distribution of Passeier valley from AlpBC project Consumption per municipality scaled based on HDD (heating degree days) ,10 5,21 Number of apartments per building Computation based on ISTAT census ,15 2,94 2,81 2,78 2,75 2,70 2,61 2,59 Source: popolazione/censimento popolazione 2011: numero di abitazioni; numero di edifici residenziali 16

17 Residential surface distribution in South Tyrol Data from Sinfonia and AlpBC project Eurac analysis 40% 35% 30% 25% 20% 15% 10% 5% 0% 0.10% in Bolzano and Merano 6,3% 20,9% 9,0% 1,6% 2.80% in Bolzano and Merano 2,5% 9,1% 4,0% 0,8% 11.0% in Bolzano and Merano 1,8% 4,7% 18,6% 7,6% 13.3% in Bolzano and Merano 1,0% 0,7% 10,6% 1,0% 1 2 FH Small MFH Big MFH Block Before After 2005 Reference year:

18 Residential heating and DHW consumption in South Tyrol Eurac analysis from ISTAT, Sinfonia and AlpBC data GWh/a Before After FH Small MFH Big MFH Block Total: 2.74 TWh/a Average: 149 kwh/m 2 a Reference year:

19 Residential heating and DHW consumption in South Tyrol Eurac analysis from ISTAT, Sinfonia and AlpBC data GWh/a Total: 2.74 TWh/a Average: 149 kwh/m 2 a FH Small MFH Big MFH Block Before After 2005 Reference year:

20 Modelled retrofit cost and energy savings Eurac calculation

21 Modelled retrofit cost and energy savings Starting from past experiences in building stock analysis in South Tyrol [1, 2]: Definition of a set of building archetypes Focus on one construction period: (highest renovation potential) typical technical features of that period Four building base models in PHPP (Passive House Planning Package) for evaluating the potential retrofit savings Building features before renovation FH Small MFH Big MFH Block Surface (m 2 ) S/V Ratio H[kWh/(m 2 a)] Building features before renovation 2 Wall U [W/(m²K)] Floor/ceiling U [W/(m²K)] Roof U [W/(m²K)] Basement U [W/(m²K)] g value [%] Windows U g [W/(m²K)] U f [W/(m²K)] [1] D.Exner, V. D Alonzo, G. Paoletti, R. Pascual, R. Pernetti. Building Stock Analysis for the Definition of Energy Renovation Scenarios at Urban Scale Green Energy and Technology 2016 [2] Giulia Paoletti Analisi del patrimonio edilizio residenziale del Comune di Merano Project Open Energy 21

22 Modelled retrofit cost and energy savings Type of renovation measures: Wall insulation Roof insulation Insulation of the basement and of the ceiling Installation of new windows 20 simulations for each building typology with two levels of renovation: 10 Standard: minimum requirements for climate zone E (D.M ) 10 Advanced: towards NZEB (Net Zero Energy Building) Evaluation of: Yearly heating demand [kwh/(m 2 a)] Amount of yearly saving [%] Renovation cost for each kwh saved [ /kwh] Renovation cost for surface unit [ /m 2 ] 22

23 Modelled retrofit cost and energy savings Improvement of thermal transmittance single layer of insulation (no technical detail) λ insul = 0.04 W/(m K) Retrofit cost is total cost for energy efficiency measure including scaffolding, installation, plaster, painting etc. U [W/(m 2 K)] Standard Advanced S insul [cm] U Cost [ /m 2 ] [W/(m 2 K)] S insul [cm] Cost [ /m 2 ] Wall Floor/ceiling Roof Basement Windows U f 1.60 U g U f 1.00 U g n 50 = 1.50 n 50 = 1.00 Source for renovation costs: Intelligent Energy Europe Passive house retrofit kit (ITALY) 23

24 Simulations performed in PHPP Standard retrofit Advanced retrofit ID F B R W F B R W 0 1 x 2 x x 3 x x x 4 x x x x 5 x 6 x x 7 x x x 8 x x x x 9 x 10 x x 11 x x x 12 x 13 x x 14 x x x 15 x 16 x x 17 x 18 x x 19 x 20 x F: façade insulation; B: basement insulation; R: roof insulation; W: window replacement 24

25 Modelled total renovation cost Standard retrofit Advanced retrofit ID 1 2 FH Small MFH Big MFH Block 1 2 FH Small MFH Big MFH Block F B R W F B R W 1 25,900 52, , , ,700 64, , , ,015 91, , , , , , , ,488 61, , , ,288 76, , , , , , , , , , , ,800 12,296 31,320 24, ,115 38,902 99,090 76, ,510 61, , , ,800 14,416 36,720 28, ,545 43, ,430 85, ,059 73, , , ,315 26,606 67,770 52, ,710 49, , , ,745 28,938 73,710 56, ,259 58, , , ,395 22,950 69,570 66, ,514 29,835 90,441 86,990 F: façade insulation; B: basement insulation; R: roof insulation; W: window replacement 25

26 Modelled retrofit costs and energy savings 1 2 FH Small MFH Big MFH Block ID Q Hnd % sav /kwh /m 2 Q Hnd % sav /kwh /m 2 Q Hnd % sav /kwh /m 2 Q Hnd % sav /kwh /m % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %

27 Modelled retrofit costs and energy savings Window replacement Basement insulation 27

28 Key messages from PHPP simulation results Retrofit measure Investment cost ( /m 2 ) Cost per kwh saved per year Standard window replacement in 1 2 FH Standard roof insulation in 1 2 FH Retrofit measures with low investment cost may not always be convenient in terms of /kwh saved per year. In most cases, advanced retrofits are more cost effective in terms of /kwh saved per year than standard retrofits. Retrofit measure Investment cost ( /m 2 ) Cost per kwh saved per year Standard window replacement in 1 2 FH Advanced window replacement in 1 2 FH

29 Development of the cost energy saving curve Assumptions Modelled DHW consumption is 25 kwh/m 2 a * independent of building type, construction period and municipality. A retrofit does not change this amount. Energy saving percentage and retrofit cost are independent of construction period and municipality (but varies according to building type and retrofit measures). The residential building stock in South Tyrol is retrofitted based on /kwh saved per year (from lowest to highest) Only the direct economic benefit from energy savings is considered. The buildings are retrofitted gradually: Facade insulation Roof insulation Basement insulation Window replacement * Source: data provided by SEL. Monitored DHW consumption in the Casanova district in Bolzano in

30 Retrofit scenario: table of 4200 rows = retrofit steps Retrofit step Construction period Building type Municipality Retrofit action /per annual kwh saved Surface in m 2 Total annual kwh saved Total cost in 1 Before FH Corvara in Badia AR ,238 2 Before FH Selva di Val Gardena AR ,193, Before 1946 Small MFH Ponte Gardena AFBR , After 2005 Big MFH Rio di Pusteria AF , Big MFH Falzes AFBR , After 2005 Big MFH Appiano sulla Strada del Vino AFBR , Before 1946 Small MFH Chiusa AFBRW , After 2005 Big MFH Salorno AFBRW , After 2005 Big MFH Cortina sulla Strada del Vino AFBRW ,268 AR: advanced roof insulation AF: advanced facade insulation AFBR: advanced envelope (facade, basement and roof) insulation AFBRW: advanced envelope insulation and window replacement 30

31 7 Retrofit implementation costs versus annual energy savings 2,5 Cost in billion (cumulative) Cost Annual consumption 2,0 1,5 1,0 0,5 Annual consumption in TWh 0 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 1,8 Annual energy savings in TWh 0,0 31

32 25 Investment cost per additional kwh saved 20 per kwh saved ,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 Annual savings in TWh 32

33 Share of total surface 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Retrofit actions by building type 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 1,8 Annual savings in TWh 1 2 FH Small MFH Big MFH Block 33

34 Share of total surface 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Retrofit actions by construction period 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 1,8 Annual savings in TWh Before After

35 Retrofit scenarios until 2050 Scenario 1, Business as usual : 56 million invested/year in building stock refurbishment in South Tyrol total investments in 2013 reported by ENEA and Ufficio risparmio energetico of Province of Bolzano [1, 2] Scenario 2: 180 million invested/year necessary for covering 90% of heat demand with renewable energy sources (RES) if heat production from RES stays constant annual heat production from RES in South Tyrol is 1.3 TWh [1] ENEA report on granted tax reliefs for energy conservation measures: [2] Data shared by the Ufficio risparmio energetico. 35

36 ,5 2,0 1,5 1,0 0,5 0,0 36 Cost in billion (cumulative) Annual consumption in TWh Scenario 1 Business as usual versus Scenario 2 Annual consumption Cost Implementation year Business as usual cost Scenario 2 cost Business as usual consumption Scenario 2 consumption

37 Key findings Scenario 1 Business as usual ( 56 million invested/year) is insufficient to reach the Klimaplan target of 90% of the energy need covered by renewables by Scenario 2 ( 180 million invested/year) reaches the Klimaplan target. It is possible to lower investment cost by combining the accelerated retrofitting program with a further development of the energy generation from renewable energy sources. [1] ENEA report on granted tax reliefs for energy conservation measures: [2] Data shared by the Ufficio risparmio energetico. 37

38 Sources Sinfonia project: smartcities.eu/en/project AlpBC project: ASTAT: census, popolazione/ ISTAT: census 2001 and popolazione/censimento popolazione popolazione/censimento popolazione 2001 ENEA: report on granted tax reliefs for energy conservation measures 38

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