Carbon Free Boston Buildings Sector

Transcription

1 Carbon Free Boston Buildings Sector Technical Advisory Group Meeting #3 1

2 Agenda Breakfast 8:30-9:00am 30 minutes 1. Project Update 2. Model Calibration & Typology Studies 3. Growth in the Building Sector 4. Adoption Rates & Policy 5. Next Steps 9:00-9:15am 9:15-9:45am 9:45-10:05am 10:05-10:50am 10:50-11:00am 15 minutes 30 minutes 20 minutes 45 minutes 5 minutes 2

3 Model Calibration & Typology Studies 4

4 Data Process Modeling Methodology Generate Archetype Energy Models 15 Buildings 4 Age Groups Segment Boston Building Stock into Categories + Age Groups Estimate All Buildings Energy Consumption and Carbon Emissions Identify ECMs and Impact/ Penetration, Simulate Impact with Calibrated Models Identify Best Suite of Policies to Meet Carbon Target Calibrate Energy Models from Actual Building Data CBECS, RECS, ResStock, Boston Building Data Building Energy Data (EverSource, National Grid, Veolia) GIS-Based Parcel Data for City of Boston Precedent Policies, Adoption Rates, and Impacts CBECS, RECS, ResStock, Boston Building Data 5

5 Utility Data BU/Arup from Parcel Database EverSource, Veolia & National Grid Building Types Single Family Triple Decker Multifamily Office Fire/Police Convention Hotel Medical/Lab Restaurant Retail School Supermarket Warehouse Worship Pre-1950* * * Post-2000* Building 1 Building 50 + Building 1 Building 50 + Building 1 Building 50 + Building 1 Building per segment Pre-1950 Anonymized Monthly EUI Anonymized Monthly EUI Anonymized Monthly EUI Post-2000 Anonymized Monthly EUI *Age ranges related to major changes in ASHRAE code for commercial buildings. Residential age groups are Pre-1945, , , and Post-1990

6 Utility Data Processing Remove outliers based on high and low means Remove outliers based on high and low means Remove outliers by month based on distance to sample mean Average monthly profile for each building type, vintage 7

7 EUI (kbtu/sf/year) Results: Means are Low Relative to BERDO Utility BERDO 8

8 Solution: Filter by Monthly EUI Bounds 9

9 Solution: Filter by Monthly EUI Bounds Utility revised BERDO 10

10 Calibration Methodology 60 EnergyPlus Models Simulate for and Extract Monthly Use Retail Pre Monthly Utility Data Compare to Normalized Monthly Utility Profiles Calibrate to monthly profiles based on two metrics: Normalized One Mean Year Bias Error (NMBE) Compares Hourly difference Utility in sample mean and true mean Profiles (utility data) Coefficient of Variation of Root Mean Squared Error (CV[RMSE]) Compares difference in variability of data points between sample and true data Both tests are recommended by ASHRAE for energy model calibration Monthly calibration: NMBE < 5% CV[RMSE] < 10% Hourly calibration: NMBE < 15% CV[RMSE] < 30% 11 Utility Model

11 Calibration Methodology 60 EnergyPlus Models Monthly Utility Data One Year Hourly Utility Profiles Simulate for and Extract Monthly Use Compare to Normalized Monthly Utility Profiles Second calibration based on hourly profiles 1E+10 9E+09 8E+09 7E+09 6E+09 5E+09 4E+09 3E+09 2E+09 1E+09 0 Post-2000 Office Gas Updated Original 12

12 Large Multi-Family (In Progress) (5+ family) Pre Post-2000 Electricity (18.5% NMBE, 23.2% CV[RMSE]) Electricity (26.0% NMBE, 29.5% CV[RMSE]) Electricity (34.5% NMBE, 37.2% CV[RMSE]) Electricity (20.2% NMBE, 29.8% CV[RMSE]) Utility Model Utility Model Utility Model Utility Model Gas (7.2% NMBE, 29.5% CV[RMSE]) Gas (6.7% NMBE, 28.1% CV[RMSE]) Gas (32.8% NMBE, 42.4% CV[RMSE]) Gas (-20.8% NMBE, 50.3% CV[RMSE]) Utility Model Utility Model Utility Model Utility Model 13 ASHRAE recommendation: Monthly calibration: NMBE < 5% & CV[RMSE] < 10% Hourly calibration: NMBE < 15% & CV[RMSE] < 30%

13 Office (In Progress) Pre Post-2000 Electricity (-8.4% NMBE, 15.8% CV[RMSE]) Electricity (-2.9% NMBE, 15.5% CV[RMSE]) Electricity (-1.3% NMBE, 13.5% CV[RMSE]) Electricity (-5.5% NMBE, 15.1% CV[RMSE]) Utility Model Utility Model Utility Model Utility Model Gas (-0.7% NMBE, 30.2% CV[RMSE]) Gas (3.1% NMBE, 28.4% CV[RMSE]) Gas (4.0% NMBE, 29.3% CV[RMSE]) Gas (-4.0% NMBE, 34.3% CV[RMSE]) Utility Model Utility Model Utility Model Utility Model 14 ASHRAE recommendation: Monthly calibration: NMBE < 5% & CV[RMSE] < 10% Hourly calibration: NMBE < 15% & CV[RMSE] < 30%

14 Data Process Modeling Methodology: Next Steps Generate Archetype Energy Models 15 Buildings 4 Age Groups Segment Boston Building Stock into Categories + Age Groups Estimate All Buildings Energy Consumption and Carbon Emissions Identify ECMs and Impact/ Penetration, Simulate Impact with Calibrated Models Identify Best Suite of Policies to Meet Carbon Target Calibrate Energy Models from Actual Building Data CBECS, RECS, ResStock, Boston Building Data Building Energy Data (EverSource, National Grid, Veolia) GIS-Based Parcel Data for City of Boston Precedent Policies, Adoption Rates, and Impacts CBECS, RECS, ResStock, Boston Building Data 15

15 Modeling Methodology: Strategies Stretch building code Passive House standard Energy Use (EUI) Cap Emissions Cap Fuel switching (gas to electric) Fossil fuel free new construction ZNE new construction Increased lighting efficiency standards Increased HVAC efficiency standards Increased envelope requirements Required PV on rooftop Energy performance disclosure Mandate performance relative to BERDO Expanded BERDO reporting requirement Passive House retrofits Lighting efficiency retrofit program HVAC efficiency retrofit program Envelope efficiency retrofit program Deep energy retrofits Enhanced commissioning/ RCx Demand response On-bill saving suggestions EV charging Energy storage Incentives for more efficient appliances Cool roofs District energy 16

16 Modeling Methodology: Next Steps 17

17 Growth in the Building Sector 18

18 19 Source: Imagine Boston 2030

19 Boston Building Stock Using City s Tax Parcel ID database, segmented the data by Typologies: 1. Single family residential 2. Small multi-family (triple decker) 3. Multifamily residential 4. Office 5. Fire/police 6. Convention/Assembly 7. Hotel 8. Medical/Lab/Production 9. Restaurant 10. Retail 11. School 12. Supermarket 13. Warehouse 14. Worship 15. Garage 20

20 Boston Building Stock Source: Tax Parcel ID database 1% 4% 0.2% 3% 3.5% 0.5% 1.5% 1% 0.3% 5% 6.5% 8.5% 18% 22.5% 24.5% = 55.5% = 44.5% Residential Commercial Total 633,000,000 SF 21

21 million square feet Boston Building Stock Source: Tax Parcel ID database % Residential Commercial % % 13% % 7% 7% 6% 20 Single family Small Large Multi-family Residential 2-4 family < 20,000 20,000 to <100, ,000 to <500, ,000 to <1M quantity 30,565 38,905 7,500 7,000 1, M + 22

22 Boston Building Stock Source: Tax Parcel ID database 23 square feet 4% 0.2% 3% 3.5% 0.5% 1.5% 1% 0.3% 5% 6.5% 8.5% 18% 22.5% 24.5% 1% Commercial Residential Boston GHG Emissions Transportation Small Residential 24% 21% Wastewater Source: 2015 GHG inventory 54% Commercial, Industrial + Large Residential

23 How will Boston s Building Stock Grow Predicted growth utilized Imagine Boston 2030 as the primary source for projections. Residential methodology Commercial methodology 24

24 Predicted Growth Methodology existing turnover growth 2017 Area (SF) Demolition Replacement New Construction Future building stock at 2030 &

25 Boston Building Stock: Residential Growth Source: Imagine Boston

26 Boston Building Stock: Residential Growth Source: Tax Parcel ID database square feet demolition rate = 0.020% replacement rate = 0.35% new construction = 900 SF/unit post-2000 allocation of typology Single family Small residential Large residential 6% 27% 67% Starting date

27 Boston Building Stock: Residential Growth + 3,575, ,540, ,850,000 square feet Total growth 66,965,000 square feet : + 29,585,000 (44%) : + 37,380,000 (56%) 28

28 Boston Building Stock: Commercial Growth Source: Imagine Boston 2030 Starting date

29 Boston Building Stock: Commercial Growth Source: Tax Parcel ID database demolition rate = 0.020% replacement rate = 0.35% new construction = BPDA pipeline report square feet Starting date

30 Boston Building Stock: Commercial Growth BPDA Current Post-2000 pipeline allocation allocation Commercial Office 59% 46% 38% Convention/Assembly 8% 13% 18% Hotel 7% 4% 6% Medical/Lab/Production 12% 17% 25% Restaurant 0% 1% 0% Retail 12% 9% 6% Supermarket 3% 1% 1% Warehouse 0 10% 6% Starting date

31 Boston Building Stock: Commercial Growth Total growth 33,685,000 square feet : + 13,685,000 (40%) : + 20,000,000 (60%) square feet 32

32 Boston Building Stock: Non-Commercial Growth Source: Tax Parcel ID database million square feet demolition rate = 0.020% replacement rate = 0.35% new construction = proportional to existing residential garage = no growth for stand alone. accounted for within buildings 33

33 Boston Building Stock: Non-Commercial Growth million square feet Total growth 5,525,000 square feet : + 2,520,000 (46%) : + 3,005,000 (54%) 34

34 Boston Building Stock: Growth Total growth 106,175,000 SF Residential: 66,965,000 SF Non-commercial: 5,525,000 SF Commercial: 33,685,000 SF 35

35 square feet Boston Building Stock: Growth Total growth 106,175,000 SF Residential: 66,965,000 SF Non-commercial: 5,525,000 SF Commercial: 33,685,000 SF 15% growth residential commercial 36

36 Boston Building Stock % existing Total growth 106,175,000 SF 15% growth Residential: 66,965,000 SF Non-commercial: 5,525,000 SF Commercial: 33,685,000 SF square feet 37

37 Adoption Rates 38

38 Who is adopting? Commercial Public entities Institutions Developers Property owners Owner occupiers Tenants Residential Owners Condo Associations Landlords Tenants 39

39 Who is adopting? 12% 15% 3% 6% 4% 3% 9% 17% 31% square feet 40

40 Adoption Rate Methodology Four (4) to be developed; Hierarchy of data; Mandate Incentive Performance Prescriptive Boston Massachusetts National International 41

41 Building Energy Reporting Disclosure Ordinance Mandated disclosure 1 st reporting year was 2014 for calendar year st reporting year was 2016 for calendar year 2015 Non-residential buildings > 50,000 SF and Set of non-residential buildings on 1 tax parcel id > 100,000 square feet Non-residential buildings > 35,000 SF 1 st reporting year was 2015 for calendar year st reporting year was 2017 for calendar year 2016 Residential buildings > 50,000 SF or 50 units Residential buildings > 35,000 SF or 35 units 42

42 Building Energy Reporting Disclosure Ordinance Mandated disclosure and buildings to complete an energy action or assessment every five years beginning in 2019 Owner or tenant shall be subject to enforcement or penalties for failure to comply with the requirements of this ordinance during the first year of their required compliance set forth in subsection (d). Violations range from $ $ per violation, up to $3,000 per calendar year. 43

43 Building Energy Reporting Disclosure Ordinance 73% 82% data year

44 NYC Local Law 84 90% 45 Source:

45 San Francisco 90% Existing Commercial Buildings (ECB) Energy Performance Ordinance Commercial buildings > 10,000 sf conditioned space 1,847 private sector buildings applicable municipal facilities and schools Source: 46

46 What does this tell us for the future programs we need to design? What may we expect from more stringent mandates? 47

47 Renew Boston Incentive Average annual participation = 16,900 households Doubled participation from 3% to 6.8% Source: STRATEGIC-PLAN_2013_%20Updated_tcm pdf 48

48 Renew Boston Incentive Average annual participation = 16,900 households Doubled participation from 3% to 6.8% Source: 49

49 Renew Boston Home energy audits & actions 12,000 10,000 8,000 6, Family Targets On average, 41% of energy audits result in upgrades 4,000 2, Audits Upgrades Source: City of Boston 50

50 National Examples NYC 80x50 Plan 100% implementation of performance-based energy code 100% of full technical potential for solar PV 50-60% buildings pursue strategies 51

51 National Examples Boulder CO: SmartRegs SmartRegs requires all licensed rental housing, about half of Boulder s housing stock, to meet a basic energy efficiency standard by Dec. 31, 2018 Source: 52

52 Discussion What does this tell us for the future programs we need to design? How should Carbon Free Boston be categorizing various owner classes? What strategies will be best driven by incentives, what strategies will be best driven by mandates? How can we leverage limited data on adoption from those existing programs and policies in Boston and in other cities to inform our forecasts and policy design? Neutrality will require a large scale technology transition on existing buildings that has not yet been experienced. How does Carbon Free Boston forecast behavior? What barriers to deep adoption will Boston experience? How can these barriers be overcome? 53

53 Next steps 54