Aug 4, Determining Metrics for Success

Transcription

1 Aug 4, pm EDT Determining Metrics for Success Moderators: Joel Rogers, Director of fcenter on Wisconsin Strategy (COWS) Satya Rhodes-Conway, Administrator of Efficiency Cities Network (ECN)

2 Agenda Welcome and intro (5 min) Presenters (30 min) Anne Evens, Center for Neighborhood Technology Jeff Perlman, Bright Power John Picard, Zero Plus Jim Meacham, CTG Energetics, Inc. Ron Herbst, Deutsche Bank AG London Questions and discussion (50 min) Next call Tuesday August 18, 3PM EDT, Certifying auditors and contractors -TENTATIVE 2

3 Energy Consumption in Chicago s Buildings Anne Evens Director, CNT Energy

4 Goals to establish a baseline of energy consumption for Chicago s buildings by building type to identify buildings to target for energy efficiency programs that will be developed as part of a large scale energy efficiency initiative in Chicago

5 Methodology Matching of Gas, Electricity and Tax Assessor Data Calculate Energy Consumption per Square Foot Energy Use Intensity (EUI) (kbtu/sq.ft./year)

6 Benchmarking

7 Benchmarking Metric is Energy Use Intensity (EUI) Kbtu/Sqft/Year Single two to four > 5 units family units Energy Use Varies by dwelling unit type & size, household size, weather and behavior 1 1 Residential Energy Consumption Survey, 2001, Energy Information Agency

8 Visualization of Energy Use Data 1 Residential Energy Consumption Survey, 2001, Energy Information Agency

9 Background on Chicago s Housing Stock 5-24 Unit Buildings 18% Distribution of Residential Housing Stock in Chicago 25+ Unit Buildings 15% Two-Four Unit Buildings 35% Single Family 32% 1.1 million housing units, located in 600,000 structures 67% are in single family and 2-4 flats About half of Chicagoans are renters About 45% of homes were built prior to 1940

10 Single Family Homes

11 Single Family Energy Use and Costs Building Type Energy Use Intensity (Kbtu/sqft/yr) Average Annual Costs for Utilities Single Family Overall Single Family Natural Gas Single Family Electricity $3,300 $1,800 $1,500

12 Where are the most energy intensive single family homes?

13 Target Neighborhoods for Single Family 22 Communities where the average EUI was greater than the city-wide average 106,000 single family homes in these communities (about 1/3 of the city s single family homes) Median HH Income = $35,000 (ranges from $13K to $53K) 53% are owners and 47% are renters 34% was built pre-1940

14 Overlap with Funding Opportunities LISC New Communities & TIF Districts

15 Summary of Energy Analysis in Single Family Homes Chicago s single family homes are less efficient than regional average. Energy Use Intensity in single family homes is highest in lower and moderate income communities. Older homes have the highest total energy consumption and natural gas consumption per square foot. (Electricity consumption per square foot does not vary significantly with age of housing) Energy consumption varies greatly within neighborhoods

16 Two to Four Unit Buildings Multi-family Housing

17 Commercial and Industrial Buildings

18 Advantages & Disadvantages This type of analysis helps understand energy consumption in your building stock Provides benchmarks that help building owners understand how they compare Highest users may not always be the best or most cost-effective opportunities for efficiency EUI does not separate behavior from building technology

19 Measuring Success of EE Programs Energy Savings (energy and dollars), verified by a third party Program Costs (by type of expenditure e.g. cost of recruitment, technical assistance, administration, capital costs, leverage) Participation Rates Customer Satisfaction Resident Comfort (by type of resident and owner)

20 EECBG & Local Metrics for Success Jobs created or retained Energy savings per $ invested Renewable capacity installed Greenhouse gas emissions reductions Leverage? Housing Units Preserved?

21 Thank you for your time Comments & Questions? Anne Evens CNT Energy

22 Energy Efficiency Metrics Multifamily Examples Efficiency Cities Network August 4, 2009 Jeff Perlman, CEM, LEED, BPIMFBA

23 Greening Existing Buildings 1. Benchmark Evaluate the building's current performance using historical utility bills 2. Audit Assess the building's systems for greening and efficiency opportunities on site visit + audit report 3. Finance Figure out how to pay for energy and green retrofits 4. Retrofit Make improvements to the building 5. Verify Monitor the building's post-retrofit performance to evaluate success 4

24 Data Needs and Wants Required Utility Bills And to which spaces they provide energy Weather Data Property Information Size and occupancy Production information (if manufacturing) Potentially Helpful Energy Management System Smart Meters 5

25 1. Benchmark From Utility Bills Common Area Electric Acct #: Date # of Days Usage (kwh) Demand (kw) Amount Jan $5,056 Dec $3,897 Nov $3,248 Oct $2,796 Sep $2,538 Aug $2,887 Jul $2,928 Jun $2,399 May $2,476 Apr $2,789 Mar $3,713 Feb $3,853 1 Year Total $38,581 Electric Average Usage Per Month Gas Acct #: End Date # of Days CCF Amount* Jan $5,633* Dec $4,785* Nov $3,617* Oct $2,583* Sep $633* Aug $577* Jul $648* Jun $725* May $2,861* Apr $3,753* Mar $5,464* Feb $5,747* 1 Year Total $37,025* ,000 Average Gas Usage Per Month Jan-06 Feb-06 Mar-06 Apr-06 May-06 Jun-06 Jul-06 Aug-06 Elec Use (kwh) Sep-06 Oct-06 Nov-06 Dec-06 Baseline 25,000 20,000 15,000 10,000 5,000 0 (kwh) Average Usage Jan-06 Feb-06 Mar Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06 Usage (Therms) Baseline Oct-06 Nov-06 Dec-06 6, ,000 4,000 3,000 2,000 1,000 0 Average Usage (Th herms) 6

26 Building Benchmarks Total Energy Usage Index (kbtu/sf/yr) Heating Index (BTU/sf/HDD) Weather-normalized Cooling Index (BTU/sf/CDD) Weather-normalized Hot Water Index (mmbtu/bedroom/yr) Electricity Index (kwh/unit/yr) Baseload usage only Baseload = non-seasonal consumption 7

27 YEAR BUILT 2004 CITY Albuque MOST RECENT RENO/REHAB n/a STATE NM TOTAL CONDITIONED SQFT 17,300 CLIMATE ZONE 3 COMMON AREA SQFT 2600 (estimated)* OCCUPANCY TYPE Elderly UNITS 60 BEDROOMS 61 PAYMENT TYPE OOO Owner pays cooling, heating and hot water FUEL TYPE EEG Electricity used for cooling and heating, gas used for hot water Energy Score Card: Metric name Units Notes Percent Owner Energy Spend / sqft $2.35 $/sqft/yr Calculated for total sqft Owner Energy Spend / unit $677 $/unit/yr Owner Energy Index 96 kbtu/sf/yr Only includes bills paid by owner Baseload Electric Index 4576 kwh/unit/yr Cooling Index 4.2 BTU/sf/CDD Heating Index 47BTU/sf/HDD 4.7 Domestic hot water 4.3 mmbtu/bedroom/yr Energy Use and Cost: Most Recent 12 months * Projected Annual Consumption ** Date Range 06/01/ /31/2009 n/a Electricity it Usage 378,452 kwh 388,459 kwh Electricity Cost $37,300 $37,555 Natural Gas Usage 3,140 therms 3,269 therms Natural Gas Cost $2,593 $3,051 Total Cost $39,893 $40,606 Carbon Footprint 540,829 lbs of CO2 555,684 lbs of CO2 8

28 Fuel Usage by Cost Electric 92% Gas 8% Electric Usage by End Use Baseload 70% Gas Usage by End Use Baseload 81% Cooling 7% Heating 23% Heating 19% kwh/m month May- 08 Jun- 08 Jul-08 Aug- 08 Monthly Electric Usage Sep- 08 Oct- 08 Nov- 08 Dec- 08 Jan- 09 Feb- 09 Mar- 09 Apr- 09 May- 09 Therms/m onth Apr- 08 May- 08 Jun- 08 Monthly Gas Usage Jul-08 Aug- 08 Sep- 08 Oct- 08 Nov- 08 Dec- 08 Jan- 09 Feb- 09 Mar- 09 Apr- 09 Model Baseload Model Heating Model Cooling Billed Usage Model Baseload Model Heating Billed Usage 9

29 Comparing Across a Portfolio Total Energy Usage (kbtu/sq ft/year) 10

30 Compare by Energy End Use 11

31 Energy Payment Profiles (sample) Who Pays for Cooling, Heating and Hot Water (number of sites) "O"=Owner O pays "T"=Tenant pays Owner pays "N"=None only heating and hot water (TOO), 106 Tenant pays all (TTT), 177 Order: Cooling Heating Hot Water Owner pays only hot water (TTO), 123 Owner pays all (OOO), 159 Other,

32 Fuel Use Profiles (sample) Fuel for cooling, heating, hot water (number of sites) "E"=Electricity Gas for "G"=Gas hot water (EEG), 100 Only electricity used onsite (EEE), 167 Other, 11 EPP,NPP, 6 Gas for heating and hot water (EGG), 236 "O"=Oil "P"=Propane "N"=None Gas for cooling, heating hot water EGE, 13 (GGG), 32 EOO,NOO, 9 Order: Cooling Heating Hot Water 13

33 5. Verify Weather-normalized comparison (new boiler) 20 BTU/SF/HDD Year Month Average Monthly Heating Index (BTU/ft2/HDD) Average Annual HDD Building SF Total Heating Therms Before Upgrades ,880 18,877 14,366 After Upgrades ,880 18,877 11,345 21% Annual Savings 3,

34 Thank you! Jeff Perlman, CEM, LEED, BPI MFBA Bright Power, Inc. 11 Hanover Square 15 th Floor New York, NY biz 15

35 DETERMINING METRICS FOR SUCCESS LOCAL GOVERNMENT NEEDS FOR EFFECTIVE ENERGY AND CLIMATE ACTION PLANNING August 4, 2009 CTG Energetics, Inc. Solutions for a Sustainable Built Environment

36 Transition to a new normal: how do we know we are on track? BAU Source: CARB Proposed Scoping Plan

37 Local government opportunity: spatial energy and emissions data Land Use Layers Density Housing Land cover Zoning Brownfields Parcels Planning units Public Service Layers Fire Public Health Schools Community Services Public Offices Recreational facilities Infrastructure Layers Electricity grid Water supply Water treatment Telecommunications Waste processing and landfills Environment Layers Parks Open space Critical habitat Rivers Water bodies Energy and Emissions Layers Energy demand and consumption Water consumption Transportation data Energy supply

38 Privacy vs. Spatial Resolution Decreasing Usefulness of Data Increasing Privacy Concern Individual id Parcels

39 Spatial Resolution and Relevancy Overall policy and goals Tracking and programs Project review Individual Parcels Parcel impact Bottom line data are needed at a spatial scale relevant to p local government planning units

40 Spatial Resolution and Land Use City of Irvine Planning Area 14 Residential buildings (orange, beige, g, brown) Commercial (red) Transportation (white) Public assembly (blue) Parks (green) Public infrastructure (white) Bottom line consumption data need to be related to land p use for effective monitoring, program design, and review

41 Collecting and maintaining good data: varying levels of influence Municipal buildings Energy Star Projects direct M&V requirements (IPMVP) Metering Energy Star Standard reporting: efficiency, renewables, water, and GHG emissions Community at large coordinate with energy and water utilities N d t lf h f dt bt Need a protocol for exchange of data between utilities and local governments

42 Projects: How to determine the baseline? International Performance Measurement and Verification Protocol (IPMVP, 2007) Retrofit isolation (e.g. chiller before and after) Whole building (e.g. multiple upgrades/ envelope) Calibrated simulation not preferred Other resources: ASHRAE Guideline M&V for Federal Energy Projects v2.2 (FEMP)

43 What about City wide baselines? Leverage utility data Choose a representative year Correlate energy and emissions with key factors: Population, number of buildings, etc Track spatially and by land use type Absolute and normalized tracking Use data to develop targeted programs and regulations

44 Potential protocol for utility local government interaction Use census block group geographic boundaries as the basis for providing spatially explicit consumption data from utilities to local governments Within the block groups, provide rate schedule/ land use classification information to enable land use correlations.

45 The role of building labeling and disclosure EU Directive on the Energy Performance of Buildings CA AB1103 Waxman Markey Harness market forces and help target local government programs and policies i

46 Discussion i and Next Steps Jim Meacham, P.E. CTG Energetics, Inc. jmeacham@ctgenergetics.com John Picard Zero Plus Johnpicard@me.com Ron Herbst, P.E. Deutsche Bank kag London ron.herbst@db.com

47 Potential ECN topics: Certifying auditors and contractors Overcoming the split incentive e and reaching renters Working with utilities Efficiency Labeling - disclosing energy costs at sale or lease Opportunities in nonresidential properties Contracts Determining measures and payback times Structure of municipal bonds Point of Sale ordinances Aggregating g g properties p to achieve scale Model training programs and curriculum Coordinating purchasing, and applying technology

48 Contact Information ECN: ADMINISTRATOR: LISTSERV: WEBSITE: Presenters: Anne Evens, Center for Neighborhood Technology John Picard, Zero Plus Jeff Perlman, Bright Power - Jim Meacham, CTG Energetics, Inc. Ron Herbst, Deutsche Bank AG London