Discussion of Mexican Adaptation of ENERGY STAR Methodology

CEC WorkshopMexico CityMarch 2013

Michael Zatz and Alexandra SullivanENERGY STAR Commercial Buildings Program

U.S. Environmental Protection Agency

2

ENERGY STAR Score Objectives

Help businesses protect the environment through superior energy efficiency

Motivate organizations to develop a strategic approach to energy management

Convey information about energy performance in a simple metric that can be understood by all levels of the organization

Be accessible through a simple and easy to use tool

Agenda

Analytical Overview Analytical Interpretation & Example Site & Source Energy Reference Data Requirements Review of Mexican Office Model

Reference Data Set Analytical Approach

Conclusions & Next Steps

3

4

ENERGY STAR score Analytical Requirements

Monitor actual as-billed energy data Create a whole building indicator

Include all fuel types Capture the interactions of building systems not

individual equipment efficiency Track energy use accounting for weather and

operational changes over time Provide a peer group comparison

Compare a building’s energy performance to its national peer group

Track how changes at a building level alter the building’s standing relative to its peer group

5

ENERGY STAR Score Analytical Development Process

Analyze national survey data Develop regression models to predict energy

use for specific space types based on operation Compare actual energy use with prediction from

the model More efficient: Actual < Predicted Less efficient: Actual > Predicted

Create scoring lookup table Scores are based on the distribution of energy

performance across commercial buildings One point on the ENERGY STAR scale represents

one percentile of buildings

6

ENERGY STAR Score Statistical Methodology

Develop the regression model

Coefficients represent average responses Coefficients provide adjustments for each operational

characteristic• Does not add the energy use of each piece of equipment• Does adjust energy based on correlation between operating

characteristic and energy use

Energy Intensity = Co + C1*Operating Hours + C2*Workers per Square Foot + C3*Computer per Square Foot + C4*HDD + C5*CDD + …

ENERGY STAR ScoreCriteria for Characteristics

7

Characteristics Included Characteristics Excluded Describe how a building operates Explain physical conditions and

parameters Are determined by the business

activity and needs

Examples: Hours, Workers, Floor Area, Computers, Weather

Describe why a building performs a certain way

Specify technologies used Reflect market conditions that may

motivate behavior are not related to thermodynamic performance

Examples: Lighting Technology, Window Type, Energy Price

8

ENERGY STAR Score Interpretation and Application

The Score DoesEvaluate actual billed energy useNormalize for operational characteristics (e.g., size, number

of employees, computers, climate)Express the performance of a building compared to its

peers, as described by a nationally representative survey

The Score Does NotSum the energy use of each piece of equipmentEvaluate buildings relative to others in Portfolio ManagerNormalize for technology choices or market conditions (e.g.,

type of lighting, energy price)Explain why a building operates as it does

9

ENERGY STAR Score Example

Two example office buildings Same size and climate (200,000 square foot; Philadelphia) Different Hours, Workers, Computers Same Actual Energy

Office A Office B

Number of Workers 700 400

Weekly Hours of Operation 112 60

Number of Computers 750 475

Predicted Energy Intensity (kBtu/ft2)

353 289

Actual Energy Intensity (kBtu/ft2) 200 200

Score 81 67

10

ENERGY STAR ScoreSite and Source Energy

Primary Energy Base fuel combusted to produce a useful

product Natural Gas, Fuel Oil

Secondary Energy Product of a raw fuel in a form that can be

used by a building Electricity, Heat, Steam

118 Mbtu Natural Gas

100 MbtuDistrict Steam

100 Mbtu Steam

Building AHeat for Occupants:

100 Mbtu

Purchase:

Natural Gas

Type:

Primary

Site Energy:

118

Source Factor:

1.047

Source Energy:

123.5

Boiler

Building AHeat for Occupants:

100 Mbtu

Purchase:

District Steam

Type:

Secondary

Site Energy:

100

Source Factor:

1.21

Source Energy:

121

Buildings can operate the same but use different amounts of primary and secondary energy

12

ENERGY STAR ScoreSource and Site Energy

Because ENERGY STAR rates the whole building, the score must account for any mix of fuels Primary and secondary

Site Energy Energy consumption expressed on utility bills Includes combination of primary and secondary energy, which

are not directly comparable Source Energy

Traces on-site consumption back to energy content of primary fuels

Accounts for the losses in conversion from primary to secondary energy (which can occur either on-site or at a utility)

Accounts for losses in distribution to buildings

ENERGY STAR ScoreData Sources

Commercial Building Energy Consumption Survey (CBECS) Conducted by Energy Information Administration every 4 years Bank/Financial Center, Courthouse, Hotel, House of Worship, K-12

School, Medical Office, Office, Residence Hall/Dormitory, Retail, Supermarket, Warehouse (refrigerated/unrefrigerated)

Industry Surveys Data Center – Conducted by EPA Hospital – Conducted by American Society for Healthcare Engineering

(ASHE) Senior Care – Conducted by Assisted Living Federation of America

(ALFA), American Association of Homes and Services for the Aging (AAHSA), American Health Care Association (AHCA), and National Center on Assisted Living (NCAL)

Wastewater Treatment Plant – Conducted by American Waterworks Association Research Foundation

13

ENERGY STAR ScoreReference Data Requirements

Sample must: Be random Be nationally representative

• Diverse in size• Diverse in geography• Diverse in ownership/management

Be sufficiently large to represent the population• Given a total restaurant population of about 900,000, a sample of at least

400 buildings would be desirable

Include measured whole building energy use data for all fuel

types Include data on numerous operational characteristics that are

potentially important• Data on more characteristics than will ultimately be included in the model 14

Overview Comments on Mexican Office Model

Follows general ENERGY STAR methodology Several significant differences

Reference data set Fuels included Site vs source energy Variables analyzed and included in final model

15

Reference Data Set Comparison

Aspect EPA ENERGY STAR Mexico

Number of Buildings 755 556

Type of Buildings Mixed public and private Public (government) only

# of Variables More than 100 9

Fuels Included All Electricity only

16

Analysis Comparison

Aspect EPA ENERGY STAR Mexico

Filters Applied to Data Set

Yes ???

Number of Buildings Eliminated by Filters

257 ???

Location Variable No – Actual heating and cooling degree days used

Yes – Adjustment based on one of three regions

Technology Variables None Cooling System Capacity

Site or Source Energy Source Energy Site Energy

17

Observations on Mexican Office Model

Not a whole building measure – electricity only Use of site energy does not present accurate

picture of total energy use in buildings – may

present challenges in consistency when

expanding to other building types Inclusion of technology variable may reward

wasteful oversizing Sample likely not representative of entire market Limited variables analyzed due to survey

limitations18

Conclusions and Recommended Next Steps

EPA review identified several key differences in the technical approach

Though similar, the Mexican methodology is not fully consistent with EPA’s Methodology

Differences in our approaches may be appropriate given our respective programs

If Mexico proceeds with the current approach, then documentation must clearly state that it is different from that of EPA

19