the weidt group - mn ashrae€¦ · modeling knowledge ]models allow us to imitate something we may...

2009 ASHRAE MN © 2008

THE WEIDT GROUP

DAVID A. EIJADI, FAIA

the weidt group®

collaborationanalysisresearch

HIGH PERFORMANCE BUILDINGS

WWW.TWGI.COM

+

2009 ASHRAE MN © 2008

THE WEIDT GROUP Building Performance ExpectationsHow and When to Set Them and Reset Them

The watchwords of our times for existing buildings include energy, measurement and accountability. Existing buildings are range in age from zero to forever. With all this attention on all these buildings, the challenges of setting realistic expectations of performance can be enormous.

We’ll look at which benchmarks and baselines you may need to use to set correct expectations.

We Believe as much as we can. We would believe everything if we could.- William James

What if we were rocket scientists

2009 ASHRAE MN © 2008

THE WEIDT GROUP Building Performance ExpectationsHow and When to Set Them and Reset Them

The secret to being seen as successful at prediction is to give and event or a time…but never both

USGBC and ASHRAE want their EUI

The Obama administration is looking for accountability

EEPS and REEPS

Ed Mazria is still looking for the big red button

2009 ASHRAE MN © 2008

THE WEIDT GROUP We are the Cause of our Own ConfusionPlease Define

Standard

Code

Benchmark

Baseline

Modeling

2009 ASHRAE MN © 2008

THE WEIDT GROUP We are the Cause of our Own Confusion

Energy modeling software tools are simply calculation tools — they are programmable calculators. Each has strengths and weakness and take time to learn to use well. We’ll assume that everyone in this discussion knows their tools and uses them well.

Energy tools are designed to model a single solution by integrating and aggregating many calculations in iterative time steps.

They do an enormous number of calculations in a short time and produce massive amounts of data.

There is no new math … no new physics.

2009 ASHRAE MN © 2008

THE WEIDT GROUP We are the Cause of our Own ConfusionPlease Define

There is however a vast number of variables to be input or accepted as default.

Setting up all the model variables can be very time consuming.

Accepting too many defaults can be risky and some modelers produce fewer models (less data) with more uninvestigated defaults

2009 ASHRAE MN © 2008

THE WEIDT GROUP We are the Cause of our Own Confusion

The charge to the design team — regardless of what else is said — is ultimately to design a solution through design services.

It is their core expertise and energy modeling software tools tend to be used as programmable calculators from one of two points of view

To test the hypothesis of a solution in service to the design and selection of equipment and

To prove attainment of a threshold like LEED points.

2009 ASHRAE MN © 2008

THE WEIDT GROUP We Can’t Know Everything all at OnceOn Thought and Decision Making

One Study at LBL suggests that at best every other decision we make is rational. The alternate is intuitive.

2009 ASHRAE MN © 2008

THE WEIDT GROUP We Can’t Know Everything all at OnceOn Thought and Decision Making

Our best decisions are a finely tuned blend of both feeling and reason

The mix depends on the situation

More than 4 Variable and the evidence says we are easily lead astray

When buying a house or a car it's best to let our unconscious mull over the many variables.

The human brain to register bad news more strongly than good. “Negativity bias” explains why in the average marriage it takes five compliments to make up for a single cutting remark

From the perspective of the brain, new ideas are merely several old thoughts that occur at the exact same time

2009 ASHRAE MN © 2008

THE WEIDT GROUP Human Beings

Left BrainLogical

Sequential

Rational

Analytical

Objective

Looks at parts

verbal

Black & White

Numbers

Sequence

Analysis

Lists

Critical Thinking

Right BrainIntuitive

Random

Holistic

Synthesizing

Subjective

Looks at wholes

Imagery

Color

Rhythm

Imagination

Daydreaming

Dimension

Creative Thinking

What if we were rocket scientists

2009 ASHRAE MN © 2008

THE WEIDT GROUP Rocket Science

Science is a body of empirical, theoretical, and practical knowledge about the natural world, produced by researchers making use of the scientific methods emphasize the observation, quantification, and prediction of real world phenomena by experiment.

There is the dual status of science as objective knowledge and as a human construct.

2009 ASHRAE MN © 2008

THE WEIDT GROUP Decision Making

Three basic kinds of information are needed

Information regarding policies and objectives

Information regarding possible alternatives and consequences

Information regarding the current state of the system From the Human

Factors Design Handbook

2009 ASHRAE MN © 2008

THE WEIDT GROUP Types of InformationProcessing Errors

Failure to detect the information due to overload or interference

Misidentification due to insufficient or inadequate clues

Improper weighting of the informational factors due to insufficient conceptualization of the action choices

From the Human Factors Design

Handbook

2009 ASHRAE MN © 2008

THE WEIDT GROUP What is to be Known

Total expected annual energy consumption

Relative energy consumption compared to Individual component alternatives

Integrated system alternatives

Code / baseline alternatives

Credits / points /awards

Incentives / rebates / tax deductions

It is the mark of an instructed mind to rest satisfied with the degree of precision which the nature of the subject permits and not to seek an exactness where only an approximation of the truth is possible.

- Aristotle

2009 ASHRAE MN © 2008

THE WEIDT GROUP The Code

Are based on Standards

Require interpretations and protocols

Establishes a minimum baseline

Raises minimum design standards

Code enforcement is less available than commonly assumed

Insufficient budgets for training and inspection

Codes do not address value

2009 ASHRAE MN © 2008

THE WEIDT GROUP Standards Vs. Analysis

Baseline Design

Design Assistance

Rating SystemDoes not helpmaking decisions

Analysis

2009 ASHRAE MN © 2008

THE WEIDT GROUP Common Pitfalls

The greatest obstacle to discovery is not ignorance— it is the illusion of knowledge

Daniel J Boorstin, Librarian of Congress

Model Expectation

Reality

SOURCE: THE WEIDT GROUP

Overcome

2009 ASHRAE MN © 2008

THE WEIDT GROUP Modeling Knowledge

Models allow us to imitate something we may someday have in the real world. Energy modeling—is about predicting the flow of energy demands and supplies throughout a building over relatively small increments of time so that we can use that information to inform the design and operation of what we build.

Over the past twenty-five years, computerized energy simulation models of buildings have moved from the realm of experimentation and design innovation into more general acceptance in design practice. However, these models are often not well understood.

2009 ASHRAE MN © 2008


Any sampling will produce a range of sentiments from appreciation to mistrust depending on individual expectations and success with energy models. But, opinions can easily be off the mark and without an understanding the design intent of the specific energy model.

There are those who point out that there are still differences between energy models and actual building energy usage.

All models are intentional abstractions and are not created equal. This presentation is intended to help you develop your own view point.

2009 ASHRAE MN © 2008

THE WEIDT GROUP Uncertainty Architects and Engineers

Degrees of uncertainty Master Planning

Plans +/- 10 to 1000 Feet

Pre-designPlans +/- 10 to 50 Feet

Conceptual DesignPlans +/- 5 to 20 Feet

Schematic DesignPlans +/- 1 Foot

Design Development Plans +/- 0.083 Foot

Contract Documents Plans +/- 0.021 Foot

Degrees of uncertainty* Master Planning

Energy +/- 25%

Pre-designEnergy +/- 20%

Conceptual DesignEnergy +/- 15 to 20%

Schematic DesignEnergy +/- 15%

Design Development Energy +/- 15%

Contract Documents Energy +/- 5%

* Depends on skill of the modeler

2009 ASHRAE MN © 2008


Energy modeling is not concerned with appearances. It is about behaviors we can not see but that impact us and our environment.

To model energy behaviors we need data on staticassemblies like the walls, windows, roof, structure, floors and insulation.

These assemblies, though predominantly static, are subject to energy flows – transmitting or resisting energy according to their mass, size, location and other properties. Collectively, these assemblies define the speed and effectiveness with which the architecture responds to or mitigates the natural environment.

Others will decide what is best for you according to their own interests.

What you do not assume – others will assume for you

2009 ASHRAE MN © 2008


A weather file called a Typical Meteorological Year, containing actual data from a real year, is used to model the architectural interaction with the environment.

Much depends on what the operators of the building will do in spite of what was set as design/modeling parameters. The uncertainty introduced by human behavior is sometimes cited as a reason not to do hourly energy simulation modeling and to use older, coarser methods for the design of architecture and mechanical systems.

2009 ASHRAE MN © 2008

THE WEIDT GROUP The LeverUncontrolled Properties

To model correctly, data on other dynamic energy sources and loads in the building such as

Hours of occupancy

Numbers of people

Process loads

Computers in use

Lighting design and control

Intended control of temperature / humidity ranges and outside air

All of these are dynamic sources of useful energy or a dynamic load to be mitigated.

Mathematical models exist for all these sources but this last set contains the greatest number of uncertainties.

2009 ASHRAE MN © 2008

THE WEIDT GROUP

Who Walls Roof Structures Floors Insulation HVAC Eq. Weather Hours Numbers Processes Plug Loads Design Control Design Control

Developer 1 1 1 1 1 1 1 1Owner 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Tennant 1 2 2 1 1 2 2Architect 2 2 1 1 2 1 1 1 1 1 1 1 1 1 1Engineer 1 1 2 1 1 2 1 1 1 1 1 2 2 1 2

Lighting Designer 1 1 1 2 2Occupant 2 2 2 2

Assumes 1Decides 2

Occupancy Non‐Regulated Energy Lighting Temp and Humidity Dynamic Conditions Static Assemblies

What remains a variable? Who controls them What becomes verifiable?

Who Walls Roof Structures Floors Insulation HVAC Eq.

Developer 1 1 1 1 1 1Owner 1 1 1 1 1 1

TennantArchitect 2 2 1 1 2 1Engineer 1 1 2 1 1 2

Lighting Designer Occupant

t plain knows better

Assumes 1Decides 2

Static Assemblies

Who Weather Hours Numbers Processes Plug Loads Design Control Design Control

Developer 1 1Owner 1 1 1 1 1 1 1 1

Tennant 1 2 2 1 1 2 2Architect 1 1 1 1 1 1 1 1 1Engineer 1 1 1 1 1 2 2 1 2

Lighting Designer 1 1 1 2 2Occupant 2 2 2 2

t plain knows better

Assumes Decides

Occupancy Non‐Regulated Energy Lighting Temp and Humidity Dynamic Conditions

2009 ASHRAE MN © 2008

THE WEIDT GROUP

SchDes DesDev ConDoc ConStr ComOcuConDes

Modeling CertaintyThe Model is Perfect

Well—not exactly perfect but, the model assumes a perfectly built facility with perfectly installed and commissioned equipment occupied by perfectly trained and well behaved people.

Is this really too much to ask?

Actual Energy Use

0%

25%

50%

75%

100%

Kno

wle

dge

2009 ASHRAE MN © 2008

THE WEIDT GROUP

SchDes DesDev ConDoc ConStr ComOcuConDes

Modeling CertaintyDesign Uncertainty

What is in fluxMaster planning / site selection

Total program area

What is in fluxInterior program arrangement

Façade development

What is in fluxMechanical system design

Lighting system design

What is in fluxEquipment selection

Controls specifications

What is in fluxCO’s/Substitutions

Shop Drawings and Installation

What is in fluxIntensity of use

Mechanical system controls

Model Uncertainty

Design Uncertainty

0%

25%

50%

75%

100%

Kno

wle

dge

2009 ASHRAE MN © 2008

THE WEIDT GROUP A Selected 88The Set

2009 ASHRAE MN © 2008

THE WEIDT GROUP

Variable Air Volume System / Water Cooled Centrifugal Chiller / All Electric

A Selected 88The Set

Common Strategies for all 6 Buildings Efficient glazing system

Daylight harvesting- dimming daylighting controls

Efficient envelope

Lighting controllers- occupancy sensors, central EMS

Efficient lighting design

Efficient mechanical system- chillers, fans and pumps

CO2 control of ventilation air

Efficient equipment

2009 ASHRAE MN © 2008


Home Mortgage Bldg D264,758 sf

Based upon field-review of the conservation measures, the project has the potential to save:

30% kWh per year

491 peak kilowatt electrical demand

2,955 MWh of electrical consumption annually

4,712,502 pounds of reduced carbon dioxide emissions

14,743 pounds of reduced sulfur dioxide emissions

8,952 pounds of reduced nitrous oxide emissions

2009 ASHRAE MN © 2008


Home Mortgage Bldg A-K-L124,749 sf

Based upon field-review of the conservation measures, the project has the potential to save:

27% kWh per year

165 annual peak kilowatts in electrical demand

Over 884,739 kWh of electrical consumption annually

Over 1,411,159 pounds of reduced carbon dioxide emissions

Over 4,415 pounds of reduced sulfur dioxide emissions

Over 2,681 pounds of reduced nitrous oxide emissions

2009 ASHRAE MN © 2008


Home Mortgage Bldg J 278,496 sf

Based upon field-review of the conservation measures, the project has the potential to save

25% kWh per year


2,444,264 kWh of electrical consumption annually




2009 ASHRAE MN © 2008


Home Mortgage Bldg C262,180 sf

Based upon field-review of the conservation measures, the project has the potential to save

28% kWh per year


2,662,129 kWh of electrical consumption annually




2009 ASHRAE MN © 2008

THE WEIDT GROUP

Sq.Ft.

264,758278,496262,180124,749

930,183

Code Base -Electric (kWh)

9,747,2749,943,1679,376,6173,336,822

32,403,880

Selected Bundle Savings -

Electric (kWh)

3,131,9943,146,7642,959,5861,148,505

10,386,849

Verified Savings -

Electric (kWh)

2,954,5472,444,2642,662,129884,739

8,945,679

Percent kWh

30%25%28%27%

28%

Percent Verified

93%79%90%76%

86%

Project Name

WDM Home Mortgage Bldg DWDM Home Mortgage Bldg JWDM Home Mortgage Bldg CWDM Home Mortgage Bldg A-K-L

WDM Well Fargo Totals

2009 ASHRAE MN © 2008

THE WEIDT GROUP ResultsEnergy Cost Savings – Presented ACEEE Fall 2006

Average – 38% Average – 30%

Ener

gy C

ost S

avin

gs (%

)

Highest Savings BundleSelected BundleLowest Savings Bundle

Credit - LEED Projects Cash - Utility Projects

-10%

10%

30%

50%

70%

Range of New Codes

2009 ASHRAE MN © 2008

THE WEIDT GROUP The LeverVerification

Source: HVAC Training and Quality Assurance, Tom Downey, Proctor Engineering Group, Ltd.

Measured Savings as a Percent of Achievable Savings (running average)

Program Startup, Learning Curve with Technician FeedbackProduction with Feedback Maintained

0%

20%

40%

60%

80%

100%

Disaster when Feedback was Removed

2009 ASHRAE MN © 2008

THE WEIDT GROUP Benchmarking MethodsComparisons

Compare a building to itself over time. i.e. utility bills

Compare a buildings rank within a population of similar building type and location.i.e, Energy Star

A Relative comparison typically expressed as a percentile ranking

Compare a building to an absolute Energy Use Intensity benchmark of a informed model.i.e. B3 Tool – Buildings, Benchmarking and Baselining

Use of a building model set to current practice or base energy code parameters

2009 ASHRAE MN © 2008

THE WEIDT GROUP The Data*

102 Projects started with KJWW (and 40 architects)

58 Projects with analyzable data 35% better than Code in the Selected Bundle kWh Savings

31% better than Code in the Selected Bundle Dollar Savings 88% dollars/kWh savings

36 Projects with analyzable field data30 % better than Code in the Field-Verified Dollar Savings

97% implementation rate

19 Projects with detailed strategy selections30 % better than Code in the Field-Verified Dollar Savings

15 Million Square Feet $0.41 to $0.46 dollar savings per square foot

* The data covers a 10 year span and “holes” in the data reflect projects that proceeded complete data collection practices or are still in process.

2009 ASHRAE MN © 2008

THE WEIDT GROUP

204%

117%108%

92%79%

67% 67% 63%

38%

0%

50%

100%

150%

200%

250%

Lighting Controls

Envelope Load Responsive

Outside Air Conditioning

Lighting Design Windows Cooling System

Efficiencies

Pump Motor Efficiencies

Heating System

Efficiencies

% Occurrence of Strategy Type Per Project

2009 ASHRAE MN © 2008

THE WEIDT GROUP

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Strategy Count/10

Number of Projects from High to Low Number of Strategies

Compare Strategy Count to % kWh Savings

Strat. Count %kWh Saved % $ SavedLinear (Strat. Count ) Linear (%kWh Saved) Linear (% $ Saved)

2009 ASHRAE MN © 2008

THE WEIDT GROUP

21

18

16

15

14

14

13

13

13

12

12

10

0 5 10 15 20 25

Occupancy‐sensing lighting controls

Dual‐level lighting controls

High‐performance glazing

Premium motor efficiency

Increased roof insulation levels

Variable frequency drives on fan motors

Increased wall insulation levels

Efficient direct system lighting design

CO2 Control of outside air

Variable frequency drives on pump motors

Total energy recovery of outside air

High‐efficiency gas boiler

Strategies in Order of Frequency with 10 or More Occurrences

2009 ASHRAE MN © 2008

THE WEIDT GROUP

50%

42%

8% 8%

0%0%

10%

20%

30%

40%

50%

60%

Increased roof insulation levels

Increased wall insulation levels

High‐performance roof insulation

High‐performance wall insulation

Green roof

Envelope Improvement Occurrence

2009 ASHRAE MN © 2008

THE WEIDT GROUP

50%

8%

0%

10%

20%

30%

40%

50%

60%

High‐performance glazing Exterior sun control

Window Strategies

2009 ASHRAE MN © 2008

THE WEIDT GROUP

71%

67%

25%

13% 13%

4%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Occupancy‐sensing lighting

controls

Dual‐level lighting controls

Stepped daylighting controls

Daylight dimming controls

Time sweep system lighting

controls

Strategic switching lighting

controls

Lighting Controls Occurrence

2009 ASHRAE MN © 2008

THE WEIDT GROUP

29%

21%

8%

4% 4%

0%

5%

10%

15%

20%

25%

30%

35%

High‐efficiency DX cooling system

High‐efficiency air‐cooled chiller

High‐efficiency water‐cooled chiller

Ground source heat pump

High‐efficiency heat pump

Cooling System Efficiency Occurrence

2009 ASHRAE MN © 2008

THE WEIDT GROUP

46%

38%

4%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

CO2 Control of outside air Total energy recovery of outside air Sensible heat recovery of outside air

Outside Air Strategies Occurrence in 24 Projects

2009 ASHRAE MN © 2008

THE WEIDT GROUP Energy Design Assistancewith Measurement and Verification

Performance Based Leading Edge Innovation

DomesticatedCodified

Daylighting / New Technologies

LEED / Green Globes

Code / ABG

CNC / EDA

ResearchComparative Analysis integrates the best of all approaches to market transformation

2009 ASHRAE MN © 2008

THE WEIDT GROUP

DAVID A. EIJADI, FAIA

JIM DOUGLAS, PE

BRIAN WASS, AIA

the weidt group®

collaborationanalysisresearch

HIGH PERFORMANCE BUILDINGS

WWW.TWGI.COM

+

Thank you