BEHAVIOR-BASED ENERGY SAVINGS OPPORTUNITIES IN COMMERCIAL BUILDINGS:

Transcription

1 BEHAVIOR-BASED ENERGY SAVINGS OPPORTUNITIES IN COMMERCIAL BUILDINGS: ESTIMATES FOR FOUR U.S. CITIES AUGUST 24,

2 TABLE OF CONTENTS 1. Sneak Peak 2. The Whys and How tos 3. Estimates of Behavior-based Energy Savings Potential across Cities, Building Types, and End Uses 4. The Take Aways 2

3 THE BEGINNING Who? What? How? Where? A set of sustainability directors An interest in the scale of potential energy savings from behavior A low-cost estimation method Cities in the United States 3

4 THE MIDDLE cities 91 4

5 THE BEGINNING OF THE END Average achievable energy savings from actions of commercial building occupants and operators based on estimates from 4 U.S. cities 5 *Assuming a 25% participation rate.

6 TABLE OF CONTENTS 1. Sneak Peak 2. The Whys and How tos 3. Estimates of Behavior-based Energy Savings Potential across Cities, Building Types, and End Uses 4. The Take Aways 6

7 THE MOTIVATION Connecting People. Fostering Innovation. Funders: The Urban Sustainability Directors Network (USDN) is a peer-to-peer network of local government professionals from cities across the United States and Canada dedicated to creating a healthier environment, economic prosperity, and increased social equity. Our dynamic network enables sustainability directors and staff to share best practices and accelerate the application of good ideas across North America. 7

8 GOALS AND CHALLANGES Goals: develop a low cost means of: Estimating the scale of savings opportunities from behavior at the city level. Identifying the commercial building types and end uses that over the largest savings opportunities. Determining the behaviors that offer the largest savings opportunities. Challenge Utility data were not available. Primary data collection was too expensive. 8

9 PARTICIPANT CITIES Population Park City, UT Boston, MA Baltimore, MD Charlotte, NC Miami, FL 667, , , ,000 Combined population = 2.5 million people Total commercial building count* 65,000 Total square footage 1 billion sq ft Total annual commercial energy demand 90 tbtu * for selected building types 9

10 THE ESTIMATION METHOD Nine Building Types: Office Retail Education Lodging Healthcare Services Public Food Food Order Sales Service Represent: 65% of all commercial buildings, 68% of all commercial floor space, and 75% to 81% of commercial energy consumption in the four cities Excludes: public assembly, religious worship, warehouse and storage, vacant, other. 10

11 THE ESTIMATION METHOD Energy Consumption across Ten Energy End Uses Ventilation 10% Space Cooling 9% Space Heating 25% Water Heating 7% Source: EIA, Lighting 10% Cooking 7% Refrigeration 10% Office Equip 3% Other 13% Computers 6% 91 Behaviors No. of End Use Behaviors Space Heating 15 Space Cooling 10 Ventilation 5 Water Heating 8 Lighting 12 Cooking 3 Refrigeration 11 Office Equip 8 Computers 7 Other 12 TOTAL 91 11

12 THE ESTIMATION METHOD Data Inputs: Existing Data Sources 12

13 ESTIMATION METHOD Model Development and Data Inputs Model Development Process Estimation of current energy consumption patterns by building type and by end use for the city in question Identification of list of operator and tenant behaviors across building types (final list = 91 behaviors) Creation of algorithms to estimate achievable savings opportunities for each behavior (eligibility x participation rate x savings rate) Plug in city-level building stock data and run estimates Inputs/Resources National and regional CBECS data (floor space, energy intensity, end use data), EIA data Review of commercial building literature (especially ASHRAE and NREL studies) Review of commercial building literature (especially ASHRAE and NREL studies) 13

14 THE ESTIMATION METHOD Two Stages: Estimate energy consumption by energy end use and building type for each city. Estimate energy savings potential by energy end use, building type and behavior for each city. Achievable Savings = Energy Consumption (Btu) Eligibility to Participate Likelihood of Participation Action-Specific Energy Savings 14

15 THE ESTIMATION METHOD Two Approaches for estimating savings: top-down and bottom-up Top-Down: generally used for estimates of building-related technologies such as space heating, space cooling, ventilation, hot water, and lighting. Example: estimating achievable energy savings in office buildings from reduced heat settings.. = Heating-related demand Total floor space for office buildings (sqft) x Heatingrelated energy consumption per sqft by building type x Eligibility % of office buildings that are heated during unoccupied periods x Hours of potential heating reductions Savings variables x % savings per hour x participation rate (%) 15

16 THE ESTIMATION METHOD Two Approaches for estimating savings: top-down and bottom-up Bottom-up: the bottom-up approach is used for plug-load related technologies such as cooking equipment, refrigeration equipment, office equipment, and computers. Example: estimating achievable energy savings in office buildings from turning off computers on evenings and weekends.. Computer-related demand Eligibility Savings variables = Total floor space for office buildings (sqft) x Computers per square foot x Energy demand per computer per day (btu) x % of computers that remain on 24/7 x Potential reduction in computer hours / 24 hours x participation rate (%) 16

17 TABLE OF CONTENTS 1. Sneak Peak 2. The Whys and How tos 3. Estimates of Behavior-based Energy Savings Potential across Cities, Building Types and End Uses 4. The Take Aways 17

18 CITY-LEVEL ESTIMATES: BALTIMORE OFFICE BUILDINGS 4,133 bbtus OF ENERGY are used in office buildings annually. This is 19% of Baltimore s total commercial energy demand. 10.0% REDUCTION of current energy use in office buildings is possible through the behavior related actions and choices identified in the following pages. Annual Energy Demand by Energy End Use Annual Savings Opportunity by Energy End Use (bbtu) (%) (bbtu) (%) Space Heating % % Space Cooling % % Ventilation % % Water Heating % % Lighting 1, % % Cooking % 2 0.5% Refrigeration % 2 0.5% Office Equipment % % Computers % % Other % 8 2.0% Total 4, % % 18

19 CITY-LEVEL ESTIMATES: BALTIMORE TOP 24 BEHAVIORS Office Buildings % of End Use Savings % of Total Savings Opportunity Estimated Annual Savings (mmbtu) 1 Replace desktops with laptops 26.2% 6.8% Employ lighting "sweeps" at closing to ensure lights are off at night and on weekends 19.4% 6.1% Ensure proper maintenance and operation of heating system 41.7% 5.8% Ensure proper operation of Economizer 51.3% 5.0% Turn off computers (evenings and weekends) and use EE computer settings 18.6% 4.8% Purchase EE computers 17.1% 4.4% Use EE task lighting and reduce ambient lighting 14.2% 4.4% Turn off monitors and use EE monitor settings 16.3% 4.2% Minimize exterior lighting 4.2% 1.3% 5.4 TOTAL 82.4%

20 CITY-LEVEL ESTIMATES: BALTIMORE Estimated Savings Potential by Building Type # Building Type bbtu Savings As % of Use Top 3 Areas of Savings Opportunities 1 Office % Lighting, computers, air conditioning 2 Retail % Lighting, air conditioning, ventilation 3 Education % Lighting, computers, space heating 4 Hotels/Lodging % Water heating, lighting, space heating 5 Healthcare % Water heating, lighting, space heating 6 Food Service % Water heating, lighting, other 7 Service % Lighting, space heating, ventilation 8 Public Order % Space heating, lighting, ventilation 9 Food Sales % Lighting, refrigeration Total 1, % (5.7% of comm. building energy demand) 20

21 CITY-LEVEL ESTIMATES: BALTIMORE Estimated Savings Potential by End Use # End Use Office Education Retail 1 Space Heating 13.9% 17.6% 11.8% 2 Space Cooling 7.3% 7.3% 10.2% 3 Ventilation 9.7% 12.6% 10.9% 4 Water Heating 2.6% 9.1% 9.2% Subtotal 33.5% 46.6% 42.1% 5 Lighting 31.2% 28.9% 41.9% 8 Office Equipment 6.2% 4.1% 3.7% 9 Computers 26.0% 16.2% 5.3% 10 Other 2.0% 3.6% 6.2% Subtotal 34.2% 23.9% 15.2% Total bbtu

22 ACHIEVABLE ENERGY SAVINGS POTENTIAL FROM BEHAVIOR Achievable savings 7% of commercial building energy consumption Energy Use and Energy Savings Potential by City Baltimore MD Boston MA Charlotte NC Miami FL No. of Buildings 16,280 17,450 20,200 10,540 Square Feet (million) Energy Use (bbtu) 21,940 26,500 27,210 14,400 Est. Savings Opp. (bbtu) 1,272 1,423 1, Savings Equiv. 32,000 HHs 35,575 HHs 39,375 HHs 21,560 HHs HDD CDD

23 ACHIEVABLE ENERGY SAVINGS POTENTIAL FROM BEHAVIOR Energy Savings Potential by Building Type and City 23

24 ACHIEVABLE ENERGY SAVINGS POTENTIAL FROM BEHAVIOR Range of Savings Opportunity for Top Three Building Types Building Type % of City-level Savings Opportunity Offices 28-33% Education 22-24% Retail 16-20% SUM 68-75% 24

25 ACHIEVABLE ENERGY SAVINGS POTENTIAL FROM BEHAVIOR Energy Savings Potential by End Use and City 25

26 ACHIEVABLE ENERGY SAVINGS POTENTIAL FROM BEHAVIOR Energy Savings Potential by End Use and Building Type 26

27 TABLE OF CONTENTS 1. Sneak Peak 2. The Whys and How tos 3. Estimates of Behavior-based Energy Savings Potential across Cities, Building Types, and End Uses 4. The Take Aways 27

28 TAKE AWAYS Conservative estimate = 7 percent achievable savings potential* Most important building types: offices, schools, retail healthcare, lodging Most important end uses: lighting, HVAC, hot water, computers Most important behaviors vary across building types and climates The Tip of the Iceberg Green leases Benchmarking Commercial energy feedback Strategic energy management programs Envision Charlotte type programs Challenges, competitions, gamification *Assuming a 25% participation rate which could be higher if you use the 20/80 rule. 28

29 VALUE TO CITY SUSTAINABILITY EFFORTS Enhanced Ability to 1. Assess where behavior-based efforts might fit within larger sustainability efforts or carbon action plans 2. Thoughtfully select between behavioral approaches and more technology-focused approaches 3. Determine which types of buildings, end uses, and behaviors should be targeted 4. Make the case to funders, collaborators, and other stakeholders 29

30 DISCLAIMER Notice Regarding Presentation This presentation was prepared by Navigant Consulting, Inc. (Navigant) for informational purposes only. Navigant makes no claim to any government data and other data obtained from public sources found in this publication (whether or not the owners of such data are noted in this publication). Navigant does not make any express or implied warranty or representation concerning the information contained in this presentation, or as to merchantability or fitness for a particular purpose or function. This presentation is incomplete without reference to, and should be viewed solely in conjunction with the oral briefing provided by Navigant. No part of it may be circulated, quoted, or reproduced for distribution without prior written approval from Navigant. 30

31 CONTACTS KAREN EHRHARDT-MARTINEZ Associate Director navigant.com 31