Alison Williams and Kat

April 29‐30, 20

ASRAC Pumps Working Group

Life Cycle Cost Analysis
2

Market & Technology

ScreeningAnalysis

EngineeringAnalysis

Energy Use & End Use LoadCharacterization

ShipmentsAnalysis

NationalImpactAnalysis

Markups forEquipmentPriceDetermination

Life-CycleCost andPayback Period Analysis

Manufacturer Impact Analysis

NOPR Rulemaking Stage
3

Markups Analysis

Purpose

• Determine consumer pump prices based on man

costs prices, both for baseline and higher efficien

equipment

• Characterize pump distribution channels

Method

• Identify distribution channels• Estimate the consumer prices by applying marku

manufacturer selling price
4

Markups Analysis

• Four primary distribution channels:

Channel: From Manufacturer Share of S

Pump OEM to Distributor to End User 87

Pump OEM to OEM to End User 8%

Pump OEM to End User 2%

Pump OEM to Contractor to End User 1%

• Do any of these distribution channels have intermediate s

accounted for – i.e., to distributor to contractor to end use

• Are there any missing channels?

• Do the shares look reasonable?
5

Markups Analysis

• Sources:

– Original equipment manufacturer (OEM) mar

Census Bureau, Manufacturing Industry Serie

– Distributor markups: U.S. Census Bureau, Bu

Expenditure Survey 

– Contractor markups: RS Mean Electrical Cos– Sales tax rates: 2011 Sales Tax Clearinghous

• Outputs

– Baseline and incremental markups
6

Markups Analysis• Markups relate price to cost of goods sold (CGS).• Baseline markups relate price to cost for baseline products. 

‒ Baseline markups indicate a consumer price that covers 

retailer’s or distributor’s expenses plus profit. 

• Incremental markups relate the incremental change in consu

to the incremental change in CGS for higher-efficiency produ

‒ Some costs remain constant as CGS increases. 

‒ Incremental markups cover only expenses that vary with 

expenses that increase due to an increase in product eff

• Weighting the markup values for each actor by the respectiv

of each channel yields an average overall baseline markup o

and an overall incremental markup of 1.24.
7

NOPR Rulemaking Stage

Market & Technology

ScreeningAnalysis

EngineeringAnalysis

Energy Use & End Use LoadCharacterization

ShipmentsAnalysis

NationalImpactAnalysis

Markups forEquipmentPriceDetermination

Life-CycleCost andPayback Period Analysis

Manufacturer Impact Analysis
8

Energy Use Characterization

Purpose

• Develop annual energy use data for pumps based on field operati

conditions

Method

• Developed distributions of pump operating hours and duty points 

for variability in the field
9

Annual Energy Use Calculation• Pump shaft power is calculated at each load point ba

assumed load profiles and performance curves (from 

database)

• A motor is sized based on the power curve

– Motor losses are calculated at each load point (according t

method developed for the test procedure)

• Hours of use at each load point is calculated from an

operating hours and weights at each load point

• All pumps are assumed to be throttled in this analys

– We will do a subgroup analysis for variable speed pumps in 

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10

Energy Use Variability• Annual energy use depends on a number of factors t

depend on the user, rather than the pump

• Duty point

– Power P and flow Q

• Load profile

• Annual hours of operation

– Depends on application

• Pump sizing, here represented by a “BEP offset”

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– X is chosen from a uniform distribution between ‐0.25 to 0

– This reflects the generally accepted operating range of pum

75% to 110% of BEP

– Head and efficiency are calculated from pump data
11

Energy Use Data Sources• Information on duty points :

– Ag/Irrigation Farm and Ranch Irrigation Survey (FRIS)

• Estimate duty point from average flow and head

– WSU Motors database contains energy audit data for sever

motors, including HP, hours per year, primary application

• May be biased toward larger motors; mostly comm & ind

– PG&E pump test data contains duty points at a single point 

• May be biased to larger pumps or those operating more freq

– WSU and PG&E are not statistical samples

– Use Mfr shipments data to estimate distribution of pumps 

• No data on load profiles

– Commercial building simulation for space conditioning app

– Four simple load shape types assigned randomly to pump u
12

Example: Duty Points for Irrigation from FRIS

0

20406080

100120

0 500 1000 1500 2000 2500 3000 3500 

Power

Flow

Irrigation Pumps on Farms Other Than for Wells (FRIS 2008)
13

Energy Use Load Profiles• PER calculated based on 4 typical load profiles:

– Flat load (LP0): 100% load point only

– Flat/over‐sized (LP1): equally weighted at 75% and 100% lo

– Variable load/over‐sized (LP2): increasing load, peak at 100

– Variable load/under‐sized (LP3): increasing load, peak at 10

with overload at 110% load point

• Should load profiles be associated with applications rathe

randomly selected?
14

Annual Operating Hours (1)

• Distributions of annual operating hours by application ba

consultant estimate

• “Other” estimate based on average of data for other five app

• The range of operation accounts for lead/lag pump situa

Quintile 1 Quintile 2 Quintile 3 Quintile 4 

CoolingWater

2500 3500 5000 6000 

Boiler Feed 2000 3000 4000 5000 

Circulation 2000 3000 4000 5000 PressureBoost

300 600 1000 2500 

Irrigation 300 600 1000 1500 Other 600 940 1500 3300 
15

Annual Operating Hours (2)

• Only other data source is the WSU motors database

• Are there any other data sources that would help qua

the range of operating hours?

Application Average from WSU Data Consult

Estima

Boiler Feed 4800 4000Circulation 5800 4000Cooling Water 6600 5000

Other 6800 1500Pressure Boost 6400 1000
16

NOPR Rulemaking Stage

Market & Technology

ScreeningAnalysis

EngineeringAnalysis

Energy Use & End Use LoadCharacterization

ShipmentsAnalysis

NationalImpactAnalysis

Markups forEquipmentPriceDetermination

Life-CycleCost andPayback Period Analysis

Manufacturer Impact Analysis
17

Life Cycle Cost (LCC) Analysis

• Purpose

• Assess the LCC impacts for the consumers (users) of commerci

industrial pumps under the considered efficiency levels.

• Method

• LCC equals total installed costs plus the sum of annual operatin

discounted to a particular base year.

• Analysis models the uncertainty and variability of inputs using 

Carlo approach and probability distributions.

• This just means that many of the variables (discount rate, oper

hours per year, total lifetime operating hours, load profile type

chosen from distributions.

• The resulting LCC sample contains 10,000 unique rows
18

LCC: Overview

Total Installed Cost

Payback Period

Lifetime Ope

Cost

Energy Consumption

Electricity Prices

Annual Energy Cost

Repair Cost

Maintenance Cost

Electricity Price

Trend

Annual Operating

Cost

Lifetime

Discount Rates

Customer Price

Installation Cost

From EngineeringAnalysis

Distributor Markup

Contractor Markup

Sales Tax Markup

From Markups

Analysis

Baseline MSP

Std‐level MSP

From EngineeringAnalysisPrice is a functionof efficiency

From Energy Use

Analysis
19

• 10,000 pump installations for each LCC run

• Each installation is the combination of a pump user and a 

• User characteristics are the same for all efficiency levels

– This includes the pump lifetime and operating hours

• In the base case, pumps are distributed to users according 

efficiency distribution in the shipments

• Pump characteristics change with EL if and only if the user

case pump does not pass the efficiency criteria for that EL

• If a pump fails, a new pump is chosen based on least cost

– Choose randomly among all pumps within a 10% band

Mechanics of the LCC (1)
20

Mechanics of the LCC (2) Representative Units

• Key feature for the LCC is a distribution of equivalent 

that vary only by efficiency (PER, C‐value, etc.)

• The LCC uses a set of representative units constructed 

binning the manufacturer survey data

– 9 power bins x 9 flow bins, logarithmically spaced

– All efficiencies within a bin are assumed available for the rep 

– Pump curve, efficiency curve, base price and BEP efficiency a

normalized to the bin average specific speed and flow

– C‐values are not affected
21

LCC Representative Units (1)
22

LCC Representative Units (2)

C = constant

C= Flow

Eff

C= Flow Bin

• Pump da

binned

• This ensu

pump rem

available efficiency 

• Also prov

distributiefficienci

• Surfaces 

“C=constequivalenefficiencidifferent 
23

LCC Representative Units (3)

C = constant

C= Flow

Eff

C= Bin Avg Q

C= Flow Bin

• Within a b

shipment‐average pcharacteri

– Specific – BEP flo– Pump c– Efficien

• Normalize 

using the equation

• Pump pric

the base p

average pefficiency 
24

• BEP (flow, head) – Rep unit

• Pump curve (head as a function

of flow) – Rep unit

• Efficiency curve (as a function of

flow) – Rep unit

• BEP pump efficiency

• Equipment price

• Sector• Application• BEP offset (duty point

• Load profile

• Electricity price• Discount rate

• Lifetime• User weight

Installation = Pump + Pump User of the LCC (2

Pump Pump User
25

Pump User Weights (1) Flow Chart

W

Fr

tot

b

typ

po

se

ap

Distribution by

power, speed,

application

Consultant’s estimate

Distribution

by sector

Manufacturers

Shipments Data

Distribution of

pump type, speed,

power, flow

WSU Motor

Database:

Comm/Ind

PG&E Pump Test

Municipal

USDA Census

Ag/Irrigation
26

Sector

Application Commercial Industrial Agricultural MBoiler Feed X XCirculation X XCooling Water X X 

Irrigation XPressure Boost X X X Other X X 

Pump User Weights (2) Calculation Method

• Each product class (pump type and speed) has 10,00

samples in the LCC

• Distribute across power and flow bins based on ship

• For a given power and speed, distribute across appl

using the motors, pump test or agricultural data

• Limit some applications to some sectors
27

Pump User Weights (3) Sectors

• The available data allow estimation of weighting by • Sector weights also provided from a consultant repo• Difficult to isolate clean water pumps

• Do the estimates seem reasonable?

• Are there other sources of data /information to help inform 

Data Est Consultant Est

Agriculture 7% 5%Commercial 60% 49%Industrial 30% 40%Municipal 3% 6%
28

LCC Inputs: Installation and Repair Costs• Installation Costs:

– DOE assumed that installation costs will not change as a fu

efficiency

– These costs are not included in the model

• Annualized Repair and Maintenance:

– DOE assumed that repair and maintenance costs will not ch

function of efficiency

– These costs are not included in the model

– Repairs accounted for implicitly in lifetime estimates

• Will repair and maintenance costs change as a function of 

efficiency (when considering only hydraulic redesign)?

• Will installation costs change as a function of efficiency (whe

considering only hydraulic redesign)?
29

LCC Inputs: Lifetime• A distribution of pump mechanical lifetime (hours) by equipme

was provided by a consultant.

• Pump lifetime in years is estimated as the ratio of mechanical l

annual operating hours.

Equipment Class Average of Mechanical Life (Hours)ESCC 1800 22,200

ESCC 3600 22,100

ESFM 1800 15,100

ESFM 3600 14,600

IL 1800 25,000

IL 3600 24,600

• Are there cases where this assumption would not hold? For 

example, pumps with low hours of use?
30

LCC Inputs: Lifetimes in the LCC Sample of 10,0
31

LCC Inputs: Energy Prices

• Electricity prices are used to convert energy use to energy costs. • Use national average energy prices by sector, published in AEO2• Commercial and industrial sectors only; use industrial prices for m

agricultural users

• Price trend used to calculate energy costs over the pump lifetime

Sector 2014 Electricity

Price (2013$/kwh)

Commercial .10Industrial* .07

*Used for Agricultural and Municipal also
32

LCC Inputs: Discount Rates

• DOE uses the discount rate to determine the present value 

operating expenses.

• DOE derived a distribution of discount rates for the applicab

– These distributions were developed by estimating the weighte

cost of capital (WACC) for commercial, industrial, and municipof pumps.

– WACC includes:

 Financial cost of any debt incurred to purchase equipment Opportunity cost of any equity to purchase equipment.

Mean Std. Dev.

Commercial 5.1% 1.3%Industrial* 5.2% 1.2%Municipal 4.5% 0.5%

*Used for Agricultural as well
33

LCC Base‐Case Efficiency Distribution

• Base case efficiency assignment accounts for the market share of 

different efficiency levels.

– LCC analysis recognizes that consumers already purchasing pu

efficiencies greater than or equal to a prospective standard lev

impacted by the standard.

– Base case distribution based on shipment data provided by manuf

– All efficiency levels are represented to a fairly significant exten

case

PER 0 PER 10 PER 25 PER 40 PER 55 PER 70 PE

ESCC 1800 12% 15% 13% 12% 14% 19% 

ESCC 3600 2% 6% 7% 10% 4% 8% 

ESFM 1800 2% 19% 12% 25% 13% 24% 

ESFM 3600 4% 18% 12% 13% 8% 15% 

IL 1800 12% 18% 6% 10% 13% 18% 

IL 3600 26% 16% 5% 6% 9% 8% 
34

LCC Example Results: Average life‐cycle cost

PER_0 PER_10 PER_25 PER_40 PER_55 

ESCC

1800 12,512 12,446 12,308 12,255 12,14

3600 9,112 9,086 8,988 8,917 8,84

ESFM

1800 14,749 14,721 14,557 14,494 14,2

3600 15,692 15,598 15,393 15,230 15,0

IL

1800 13,171 13,137 12,966 12,913 12,8

3600 11,633 11,168 11,069 11,028 10,9
35

LCC Example Results: Average life‐cycle cost sa

PER_10 PER_25 PER_40 PER_55 PER_70

ESCC

1800 66 205 257 368 478

3600 26 124 195 266 355

ESFM

1800 28 193 255 464 599

3600 94 300 462 601 798

IL

1800 34 205 257 343 441

3600 465 563 605 680 828
36

LCC Example Results: Distribution

• Plot shows all product classes combined• At PER 40 about 60% of market is unaffected etc.
37

LCC Example Results: Interpretation (1)• The LCC is the sum of a cost and a benefit which are

calculated independently (example below ESCC 1800

• The LCC benefit provides an upper bound on the cos

efficiency that the user can pay without economic lo
38

LCC Example Results: Interpretation (2)

• The cost of improving efficiency is summarized in the 

curve” presented below as product cost vs. C‐value forepresentative unit (ESCC 1800)
39

Extras
40

Pump User Weights Results (1800 speed)

1800 RPM Motor ‐ Di Values

HP Bins

Buildings ‐ Boiler Feed

Buildings ‐ Circulation

Buildings ‐ Cooling Water

Buildings ‐ Other

Buildings ‐ Pressure Boost

Industrial ‐ Boiler Feed

Industrial ‐ Circulation

Industrial ‐ Cooling Water

Industrial ‐ Other

1.00 24% 17% 2% 11% 25% 6% 8% 0% 3% 41.80 22% 28% 7% 13% 16% 44% 11% 11% 12% 123.25 22% 13% 19% 16% 11% 11% 6% 4% 14% 125.85 10% 23% 28% 26% 11% 11% 8% 14% 20% 24

10.54 2% 6% 13% 8% 9% 0% 10% 11% 8% 1718.98 10% 7% 19% 16% 5% 0% 16% 21% 14% 1334.20 12% 4% 6% 7% 18% 6% 30% 0% 14% 561.62 0% 0% 4% 1% 5% 11% 3% 11% 8% 8

111.01 0% 1% 1% 2% 2% 11% 5% 11% 6% 6200.00 0% 0% 0% 0% 0% 0% 3% 18% 1% 0

TOTAL 100% 100% 100% 100% 100% 100% 100% 100% 100% 100
41

Pump User Weights Results (3600 speed)

3600 RPM Motor ‐ Di Values

HP Bins

Buildings ‐ Boiler Feed

Buildings ‐ Circulation

Buildings ‐ Cooling Water

Buildings ‐ Other

Buildings ‐ Pressure Boost

Industrial ‐ Boiler Feed

Industrial ‐ Circulation

Industrial ‐ Cooling Water

Industrial ‐ Other

1.00 36% 0% 4% 2% 28% 29% 11% 0% 1% 1.80 16% 26% 21% 20% 32% 8% 37% 9% 6% 3.25 28% 23% 23% 12% 2% 13% 21% 9% 14% 5.85 4% 14% 17% 24% 26% 16% 16% 64% 30% 

10.54 6% 11% 13% 10% 0% 0% 3% 9% 15% 18.98 0% 26% 23% 19% 13% 13% 0% 9% 15% 34.20 4% 0% 0% 12% 0% 8% 13% 0% 15% 61.62 0% 0% 0% 0% 0% 8% 0% 0% 2% 

111.01 6% 0% 0% 0% 0% 5% 0% 0% 0% 200.00 0% 0% 0% 1% 0% 0% 0% 0% 1% 

TOTAL 100% 100% 100% 100% 100% 100% 100% 100% 100% 
42

Commercial Building Simulation• 8760s data from Energy+

• Pumps included in the system:

– SWHSYS1 PUMP– COOLSYS1 PUMP

– HEATSYS1 PUMP– TOWERWATERSYS PUMP

• Analysis Approach:

– 5 bins between min(flow>0) and max(flow)

• Example:

– Building Type = Hospital
43

0%

10%20%30%40%50%60%

0% 20% 40% 60% 80% 100%

Percentage of 8760s

Percentage of Max(Flow)

SWHSYS1 PUMP

bin1bin2bin3bin4bin5

0%

10%20%30%40%50%60%

0% 20% 40% 60% 

Percentage of 8760s

Percentage of Max(F

COOLSYS1 PUM

0%

10%20%30%40%50%60%70%80%90%

0% 20% 40% 60% 80%

Percentage of 8760s

Percentage of Max(Flow)

HEATSYS1 PUMP

bin1bin2bin3bin4bin5

0%

10%20%30%40%50%60%70%80%90%

100%

0% 20% 40% 60% 

Percentage of 8760s

Percentage of Max(F

TOWERWATERSYS