# Presentation: 645119

## Benchmarking:What’s Your Building’s Energy IQ?

- Evan Mills, Ph.D.
- Lawrence Berkeley National Lab
- EMills@lbl.gov
- Presentation at *Sustaining the Future*
- Hawaiian Electric Co., Sept. 26, 2003

## Talk Outline

-  What’s Energy Benchmarking Anyway?
-  Techniques
-  Complications
-  Applications
-  Tools
- For list, see: http://poet.lbl.gov/cal-arch/links/

## Familiar Benchmarks: IQ

## Benchmarks are Everywhere

## Huggies: Diaper Size as “logit” Function of Child Weight

- Nice chart; dubious value in real world

## Why Benchmark?

- Establish baseline and track performance
- Validate design
- Identify maintenance and control problems
- Identify best practices; set goals or standards
- Identify savings potential
- Prioritize efforts
- Educate; Inspire!

## Familiar Energy Benchmarks ...

- ...Fundamental differences in approach

## Benchmarking Can Be Done at Any Scale

-  Global CO2/Capita

-  Chiller efficiency

## Choice of Benchmark Determines Conclusions

-  Important to isolate sub-groups of interest

-  Many ways to benchmark a given system

- Source: NHTSA

## Choice of Benchmark Determines “Results” & Actions

- ENERGY STAR
- Score
- (75 = “passing”)

- Average Index ofVarious Indicators
- (energy/student,
- energy/sf, etc.)

- Source: Norford,
- Palomera-Arias, and Ramsey (2003)

## Approaches to Benchmarking 

-  Point-estimates (vs. population avg.)
-  Statistical (bell curve; vs. population)
-  Point-based (vs. best practice)
-  Model-based (actual vs. efficient)
-  Standardized (vs. test procedure)
- _Scope:_* *self-referential; enterprise; stock
- _Timeframe:_ historic trends vs. current

## Lateral & Longitudinal:e.g. Canadian Oil Refineries

- Comparing “peers” at one point in time

- Following “fleet-wide” trends over time

## Decide What is Important Before Benchmarking

- Source: DOE/EIA

- Average US fuel economy increasing, then flat

- Average US vehicle fuel use declining then rising

## Benchmarks Can Provide a “Reality Check”: Data Centers

- California Data Center owners claim a need of 250 W/ft2
- Real data benchmarks the actual need between 10 and 100.

## Caveats & Pitfalls

-  Intensity does not equal efficiency
-  Hard to avoid apples-and-oranges comparisons (want energy per unit of service)
-  Normalization
- weather
- floor area
- schedule
- plug loads
- indoorconditions
- energy price

## Examples from Hawaii

- Schools
- 32 Schools
- Average EUI: 5.9 kWh/ft2-year
- Range: 3.05 - 11.52 kWh/ft2-year
- Banks
- 49 Branches
- Average EUI: 20.07 kWh/ft2-year
- Range: 7.96 - 36.40 kWh/ft2-year

- Source: HECO, Thomas D. Van Liew

## Hawaii Commercial Buildings Benchmarking Study

- Health Care: **24.83 kWh/ft****2****-y**
- Retail: **25.50 kWh/ft****2****-y**
- Apartments: 10.11 kWh/ **kWh/ft****2****-y**** **
- Warehouse: **6.76 kWh/ kWh/ft****2****-y**** **
- Miscellaneous:**12.09 kWh/ kWh/ft****2****-y**

- Offices: **22.82 kWh/ft****2****-y**** **
- Lodging: **16.14 kWh/ft****2****-y**
- Restaurants: **52.88 kWh/ft****2****-y**** **
- Grocery Store: **53.05 kWh/ft****2****-y**
- Education: **9.00 kWh/ft****2****-y**
- University of Hawaii:**13.82 kWh/ft****2****-y**

- Source: HECO, Thomas D. Van Liew

## Fast Food Restaurant EUIs:Hawaii

- Source: HECO, Thomas D. Van Liew

## Grocery Store Energy Intensities Hawaii Average = 70.9 kWh/ft2-year 

- Source: HECO, Thomas D. Van Liew

## Energy Intensities

**Energy per meal for 36 hotels, France**

- Source: Le Strat et al., (1999)

- Std. Dev. 34%              27%                       19%                            32%

## Choice of Indicator is Key

- Source: 1996 California Commercial End Use Survey
- (Restaurant energy)

- Energy per unit floor area

- Energy per meal

- N=9

- N=21

- N=34

## Choice of Indicator is Key

- Source: The Energy Data and Modeling Center, 2001

- Energy per unit floor area

- Energy per meal

## Beyond “Apples & Oranges”:Pippins and Granny Smiths

- Data for Switzerland.  Source: Balmer and Hintermann, 2000

## Cleanroom Energy Metrics

| Recirculation air handler efficiency | cfm/kW |
| --- | --- |
| Makeup air handler efficiency | cfm/kW |
| Annual energy cost per cleanroom square foot | $/ft2 |
| Annual fuel usage | MBtu/ft2-yr |
| Annual electricity usage | kWh/ft2-yr |
| Annual energy usage | MBtu/ft2-yr |
| Makeup air  | cfm/ft2 |
| Recirculation air | cfm/ft2 or ach |
| Chiller efficiency | kW/ton |
| Tower efficiency | kW/ton |
| Condenser water pump efficiency | kW/ton |
| Chilled water pump efficiency | kW/ton |
| Total chilled-water plant efficiency | kW/ton |
| Hot water pumping efficiency | kW/MBtu |
| Cooling load density | ft2/ton |

- Tschudi and Xu, *ASHRAE Transactions*, KC-03-9-4 (2003)

## Delivery of Service Levels

## Some “Energy” Benchmarks Don’t Even Include Energy

- Tschudi and Xu, *ASHRAE Transactions*, KC-03-9-4 (2003)

## Cleanroom Chiller Efficiencies

- Tschudi and Xu, *ASHRAE Transactions*, KC-03-9-4 (2003)

## From Benchmarking to Best Practices

- Laboratory Ventilation W/cfm

***standard***

***good***

***better***

- Standard, good, better benchmarks as defined in
- “How-low Can You go: Low-Pressure Drop Laboratory Design”
- by Dale Sartor and John Weale, ASHRAE Journal

## Benchmarks as Screening Tool

- Source: Lee & Norford (2001)

## ENERGY STAR Building Label

## Labs21 Benchmarking Tool

- Data Input

## Labs21 Benchmarking Tool

- Analysis

## Cal-ARCH: Web-based Benchmarking

## Capturing Benchmarks with Design Intent Documentation

## Approach

-  Decide how benchmark is to be used
- Choose type(s) of benchmarks
- Define “indicators”
- Be creative
-  Measurement plan
-  Clear definitions (e.g. “floor area”)
-  Collect data (privacy issues)
-  Establish filters & normalization methods
-  Learn from “outliers”

## Needs

-  Considerable unmet need for benchmarking presentations that bridge the “physical” and “financial”
-  More focus on component or end-use benchmarking
-  Growing importance of peak demand

## Moral of the Story

-  “To define an energy efficiency indicator is not only a technical challenge, but also a pre-structuring of the subsequent policy choice.”
- Aebischer, et al. (2003)

## Correlation is Not Causation!

- Advice for Traders: “moon-trading is by no means a stand-alone approach”