# Presentation: 050017

## Rating Laboratories 

***Rating Laboratories ***

*Results from the Labs21 Program*

- Paul Mathew, Dale Sartor 	Lawrence Berkeley National Laboratory
- Otto van Geet 	National Renewable Energy Laboratory
- Sue Reilly	Enermodal Engineering, Inc.

**Notes:**
My talk today is rating energy efficiency and sustainability in laboratory buildings. 
Based on work we’ve done in the labs21 program – along with Dale sartor, etc.

## Outline

- Why Laboratories?
- Energy Benchmarking
- Methods and Metrics
- Database tool
- Environmental Performance Criteria
- “LEED for Labs”
- Lessons Learned

## Why Laboratories?

- Laboratories are very energy intensive
- 4 to 6 times as energy intensive as office buildings
- Substantial efficiency opportunities
- 30%-50% savings over standard practice
- Owner demands to reduce utility costs
- Typically not speculative – lifecycle incentive
*	**	**	**	**	**	**	**	**But...*

**Notes:**
Labs are a niche – not a significant part of the overall energy pie, but there are several reasons to look at them.

They are also a growing segment

So just like other sectors, they too can benefit from benchmarking tools, and other resources. 

## Challenges

- Complex functional requirements
- Health and safety
- Research requirements
- What is a lab?
- Chemical vs. biological vs. physical
- Research vs. teaching vs. manufacturing
- % lab area

**Notes:**
These are not insurmountable, they just add some interesting twists to the whole process.

% area – 
A lab building has a lot more than just lab – office, etc. sometimes these may be more in sqft than just lab.

## Benchmarking 101

- Metric Selection
- Site
- Building
- System
- Component
- Metric Normalization
- Programmatic parameters (e.g. area)
- Contextual parameters (e.g. climate)

## Labs21 Metrics

- Developed by expert group
- Tradeoff in scope vs. ease of data collection

| Whole Building | kWh/gsf-yr (elec) 	BTU/gsf-yr (site) 
Peak W/gsf (elec)	$/gsf-yr (site)   |
| --- | --- |
| Ventilation | kWh/gsf-yr 	 Peak supply cfm/sf(lab) 
Peak W/cfm 	 Avg cfm/peak cfm |
| Cooling
 | kWh/gsf-yr 	 Peak gsf/ton 
Peak W/gsf 	 Installed gsf/ton |
| Heating | BTU/gsf-yr  |
| Lighting | kWh/gsf-yr 	Installed W/sf(lab)
Peak W/gsf 		 |
| Process/Plug | kWh/gsf-yr 	Peak W/sf(lab) 
Peak W/gsf  |

**Notes:**
Original set was tweaked as we began data collection. 

Consumption as well as system efficiency

## Normalization

- Some obvious parameters
- Weather
- Gross area
- Lab area
- Some less obvious parameters
- Ventilation rates
- Equipment loads
- Operation schedules

**Notes:**
Elaborate ventilation rates

## Benchmarking Methods...1

- Simple data filtering - provides crude normalization
- May be adequate for coarse screening, opportunity assessment, goal setting

*Facilities located in cool-humid climate zone; standard occupancy hours (<= 14 hrs/day)*

**Site energy use intensity**

**Notes:**
This is a sub set of the data from the database – 
Climate, occ hours

One sticks out. It would suggest it’s worth a further look. 
Maybe it has high equipment loads or unusual ventilation requirements. 

Course screening is itself very useful. We’ve gotten some good albeit anecdotal feedback on the usefulness of this. 
Because it causes people to look further – and that’s often half the battle in implementing EE.

## Benchmarking Methods...2

- Regression analysis
- Equation relates normalizing parameters and metric
- Used in EnergyStar
- Works well if:
- There is an adequate representative dataset
- Dataset includes range of possible efficiencies.
- Lack of adequate dataset for laboratories
- CBECS data limited by lab area, normalizing parameters
- Labs21 database collects normalizing parameters, but has limited data

**Notes:**
If the entire population is inefficient, it will cause efficient buildings to be rated as inefficient – this would be the case even if we took an existing sample of lab buildings.

CBECS only counts as lab buildings those that are over 75%lab as principal building activity. 
CBECS does not have any lab-specific normalizing parameters

So regression really is not an option for labs at this point in time. 
This was also the finding by another research group at CBE in berkeley.

## Benchmarking Methods...3

- Simulation-model based benchmarking
- Model is used to calculate a benchmark (e.g. “ideal” case)
- Model accounts for normalizing parameters
- Benchmark is compared to actual energy use

- Lab Module

- Non-lab
- Module

- Central
- Plant

- e = (Al * eil) + (Anl * einl)
- Al: Actual laboratory area
- Anl: Actual non-laboratory area
- eil: benchmark energy use intensity for lab module
- einl: benchmark energy use intensity for non-lab module

- Simulation model

**Notes:**
DOE2 benchmark model
Put in normalizing parameters such as ventilation rates, plug loads
Run model with weather file – ideally for the actual year

Multiply the simulated values for lab, non-lab intensities with actual lab, non-lab areas, that gives you an ideal energy use.
Take the ratio

You can then compare the EER for different lab buildings.

## EUI vs. EER

- EER improves “apples to apples” comparison

*Facilities located in cool-humid climate zone; standard occupancy hours (<= 14 hrs/day)*

**Site energy use intensity**

**Notes:**
Accounted explicitly for lab area
Accounted for regional weather differences, but not year to year

This by the way clearly illustrates why just EUI without lab area ratio could be very misleading.

## Labs21 Tool

- National database of lab energy use data
- Web-based input and analysis
- About 50 facilities - Building  and system level data
- Data Input
- Users input data
- All data reviewed before being accepted
- Data remains anonymous to other users
- Analysis
- Benchmarking using metrics with data filtering
- Model-based normalization currently not integrated with tool

**Notes:**

Data review:
	Sanity check
	Data definition consistency

## Slide 13

**Notes:**
For each facility you can enter several buildings and several years of data for each 

## Slide 14

**Notes:**
Estimated e.g. measure peak plug load in one lab module and extrapolate it – 
Generally discourage pure simulation data. 

## Slide 15

## Slide 16

## System Efficiency Metrics

- System metrics especially useful in labs

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

**Ventilation System Efficiency (Total W/cfm)**

**Notes:**
One important feature of the database is system level metrics
Good example of a metric that doesn’t really require normalization. 

## Rating Sustainability

- Labs21 Environmental Performance Criteria
- Point-based rating system
- Leverages LEED 2.1
- Adds new credits and prerequisites
- Modifies existing credits and prerequisites
- Over 40 industry volunteers
- Version 2 released 2002

## EPC: Extending LEED

- Emphasis on lab energy use, health & safety

| Sustainable sites | CFD or wind tunnel modeling of air effluents
Containment controls for liquid effluents |
| --- | --- |
| Water efficiency | Eliminate “once-through” cooling 
Process water efficiency |
| Energy and atmosphere
 | Optimize ventilation requirements
Energy efficiency for lab systems
Co-generation  
Laboratory plug-in equipment
Right-sizing HVAC |
| Materials and resources | Tracking and managing hazardous materials |
| Indoor environmental quality | Meet ANSI-Z9.5 ventilation requirements
CFD modeling of indoor airflow
Fume hood commissioning per ASHRAE-110
Self-identifying and failsafe alarm systems |

**Notes:**
Sus sites
Eliminate once-through cooling of lab equipment.

## Energy Efficiency Credit

- “Points” for % reductions below ASHRAE 90.1 base
- Current Limitations (LEED/ASHRAE 90.1):
- Fumehoods excluded from % reduction
- Fan power limitations unrealistic for labs
- Strategies not rewarded
- High performance fumehoods
- Minimizing reheat
- Occupancy controls (?)
- Low pressure drop design (?)
- Cascading air supply (?)

**Notes:**
Focus on reheat – will illustrate that in a moment

## Energy Efficiency Credit

- Labs21 modeling guidelines
- “Supplement” to ASHRAE 90.1
- Properly account for lab energy efficiency strategies
- e.g. reheat due to plug load schedule diversity

**Notes:**
Reheat
This shows some data from lab modules in a university building.
Note the diverity. 
Designers assume 14-16 W/sf
One issue is oversizing
But even if you addressed oversizing, you’d still have the issue of diversity 
Supply temps/volumes set for the worst zone, causing reheat in others. 

So in our modeling guideines, we’re requiring schedule diversity, so that the effect is captured, and designs that address it will be rewarded e.g. localized cooling.

Guidelines also used beyond LEED
PG&E savings by design
Labs21 benchmarking
BP guides using  parametric simulation studies

## Toward LEED for Labs

- EPC and LEED
- Labs21 does not provide certification
- EPC used for self-certification in many projects
- Effective in lab design charrettes
- Many EPC credits used for LEED innovation points
- USGBC developing LEED Application Guide for Laboratories (LEED-AGL)
- Uses EPC as starting point
- Draft expected Nov 04; Final expected mid-2005

## Lessons Learned

- Significant efficiency opportunities in labs
- Need to adapt benchmarking and rating systems
- Allow for diversity of functional requirements
- Simulation-based benchmarking preferred
- Consider energy use of core systems
- System level metrics important
- Ensure that rating approach accounts for all major efficiency strategies
- Don’t ignore “niche” buildings – they can add up!

**Notes:**
Small part of the pie, but there’s a lot of cream on that part of the pie. 
Labs can benefit from benchmarking and rating just like other commercial sectors

But systems need to be adjusted.

We tend to focus on big wedges. But we take only little bites out of it. 
Programmatically, it makes sense to look at smaller wedges that we can take big bites out of. 

## www.labs21century.gov

- PAMathew@lbl.gov