37
IETC Energy Manager's Workshop 1 1 The Industrial Energy The Industrial Energy Manager Manager’ s Essential s Essential Tool Kit Tool Kit Energy Managers Energy Managers’ Workshop Workshop 39 th Industrial Energy Technology Conference New Orleans, LA, 19 June 2017 J D Kumana, MS ChE Kumana & Associates, Houston, Tx [email protected] (281) 437-5906 2 Kumana & Associates, Houston, Texas © 2017 Outline Background Technical Approach Portfolio of Tools and Techniques Case Study (Lagniappe)

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Page 1: The Industrial Energy Manager’s Essential Tool Kitietc.tamu.edu/wp-content/uploads/sites/2/2017/06/Energy-Mgrs-Toolkit-Kumana-IETC-New...The Industrial Energy Manager’s Essential

IETC Energy Manager's Workshop 1

1

The Industrial Energy The Industrial Energy

ManagerManager’’s Essential s Essential

Tool KitTool Kit

Energy ManagersEnergy Managers’’ WorkshopWorkshop39th Industrial Energy Technology Conference

New Orleans, LA, 19 June 2017

J D Kumana, MS ChE

Kumana & Associates, Houston, Tx

[email protected] (281) 437-5906

2Kumana & Associates, Houston, Texas © 2017

Outline

� Background

� Technical Approach

� Portfolio of Tools and Techniques

� Case Study (Lagniappe)

Page 2: The Industrial Energy Manager’s Essential Tool Kitietc.tamu.edu/wp-content/uploads/sites/2/2017/06/Energy-Mgrs-Toolkit-Kumana-IETC-New...The Industrial Energy Manager’s Essential

IETC Energy Manager's Workshop 2

3Kumana & Associates, Houston, Texas © 2017

Industrial Processes – Inputs and Outputs

UTILITYSYSTEM

MFGPROCESS

WASTETREATMENTELEC

FUEL

ELEC?

RAW MATGHG

PRODUCTS

EFFLUENTDISCHARGE

ENERGY

CONTROLLABLE PARAMETERS

• RAW MAT YIELDS• REACTION KINETICS• UNIT OPERATIONS

• RECYCLE POINTS & RATES

• ENERGY CONSUMPTION

PROCESS MODS

• Heat Recovery • Power reduction• Optimize CHP

4Kumana & Associates, Houston, Texas © 2017

Impact on Profits

GHG EMISSIONS

ENERGY COST

WASTE TREATMENT

THROUGHPUT OR CAPACITY

YIELD + KINETICS

ENERGY EFF (SUPPLY)

ENERGY EFF (USAGE)

OPTIMUM RECYCLE

UNIT OPERATIONS

Page 3: The Industrial Energy Manager’s Essential Tool Kitietc.tamu.edu/wp-content/uploads/sites/2/2017/06/Energy-Mgrs-Toolkit-Kumana-IETC-New...The Industrial Energy Manager’s Essential

IETC Energy Manager's Workshop 3

5Kumana & Associates, Houston, Texas © 2017

Ideally, we should consider both Process and Energy on Integrated Basis

� PROCESS MODIFICATIONS

� Potentially Huge Impact, but Higher Cap Cost + some Potential Risk

� ENERGY EFFICIENCY OPTIMIZATION

� Smaller Impact, but Lower Cap Costs & Almost Zero Risk

6Kumana & Associates, Houston, Texas © 2017

NOT

MY

JOB

STEAM

POWERELECUTILITY

PARADIGM: Utilities available instantaneously at ZERO costRESULT: Waste Energy in both Process & CHP System

R1

R2 SEP

F1

F2

P1

P2

Y

Process Engineer’s Viewpoint

Page 4: The Industrial Energy Manager’s Essential Tool Kitietc.tamu.edu/wp-content/uploads/sites/2/2017/06/Energy-Mgrs-Toolkit-Kumana-IETC-New...The Industrial Energy Manager’s Essential

IETC Energy Manager's Workshop 4

7Kumana & Associates, Houston, Texas © 2017

B1 B2

DA

HRSG

C

Y

GT

condensate

BD

NOTMY JOB

PARADIGM: Must supply demand at ANY CostRESULT: High Flexibility, Low Efficiency

Utility Engineer’s Viewpoint

8Kumana & Associates, Houston, Texas © 2017

Economics

EnergyUtilitiesProcess

• Energy• Emissions• Capacity

Integrated Optimization Viewpoint

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IETC Energy Manager's Workshop 5

9Kumana & Associates, Houston, Texas © 2017

Outline

� Background

� Technical Approach

� Portfolio of Tools and Techniques

� Case Study (bonus)

10Kumana & Associates, Houston, Texas © 2017

Process Energy Optimization (PEO)

Using Energy Analysis (fuel +

power) to identify and exploit

profitable opportunities for

process efficiency improvement

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IETC Energy Manager's Workshop 6

11Kumana & Associates, Houston, Texas © 2017

PEO Integrates Process and Utilities

Energy Supply,Conversion, &

Distribution Systems

Waste Collection,Reduction, Recovery,

& Discharge

Raw Mat’ls:Feed Stocks,

Coal, etc.

FinishedChemical Products

Chemical Plant“Processing”

Steps (see PFD)

A “high level” view of the Process and Utility Systems

PEO looks at the Process and Utility Systems as a single Unified System

“We had never suspected that using energy differently can improve the process”.

David Broad, Site Mgr. BASF

12Kumana & Associates, Houston, Texas © 2017

PEO uses Financial and Technical Modelsto directly link Engineering w/ Economics

An Engineering Model A Financial Model

THE SYSTEM(EQUIPMENT)

THE PROCESS

¨TEMPERATURES, ETC.¨PRACTICES of PEOPLE¨ TECHNOLOGY

THE BUSINESS UNIT

Power Plant Cost

Center

RAWMATERIALS

ENERGY

SCRAP

DEPRECIATION,TAXES, INSURANCE $

LABOR $

OTHER $

ENERGY $

SCRAP $

NETSALES $

RAW MAT’LEXPENSE $

REWORK

OTHER

LABOR

GROSSSALES $

PROFIT $

G&A andSELLINGEXP$

RETURNS &DISCOUNTS $

REWORK $

• WASTEWATER TREATMENT $,• AIR EMISSIONS $• SOLID WASTEDISPOSAL $

ENVIRONMENTALEMISSIONS

FINISHEDPRODUCT

Optimization Links-- “X% What ifs”: What is the annual K$/yr saving from a 1% or 10% annual improvement in product output, yields, quality, maintenance

effectiveness, operator productivity and energy performance?

Optimization links ?

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IETC Energy Manager's Workshop 7

13Kumana & Associates, Houston, Texas © 2017

PEO Methodology

� Documentation - process & econ. models

� Correct product/waste & utility pricing

� Identify major $ impacts on Bottom Line, using sensitivity analysis (What If?)

� Focus on Critical Cost Issues (CCIs)

� 3-phase approach

• Level 1 – rules of thumb, ball park economics

• Level 2 – prelim calculations, conceptual design

• Level 3 – detailed calcs, vendor quotes

14Kumana & Associates, Houston, Texas © 2017

PEO – Key Features

� Integrated holistic analysis

� 3-phase approach (increasing levels of effort and accuracy)

� Collaborative Effort � Consultant plays

“coach/facilitator” role at Level 1; Team member at Level 2

� Immediate Results

� Implementation Road Map

� Thorough documentation

� Plant Ownership and Accountability (KPIs)

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IETC Energy Manager's Workshop 8

15Kumana & Associates, Houston, Texas © 2017

Outline

� Background

� Technical Approach

� Portfolio of Tools and Techniques

� Case Study (bonus)

16Kumana & Associates, Houston, Texas © 2017

Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• PROCESS MODS – higher capacity & yields, less waste

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

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IETC Energy Manager's Workshop 9

17Kumana & Associates, Houston, Texas © 2017

Example of 1-line Cost Flow Diagram

Utilities: Major Chemical Plant site, Texas

#1 #2 #3 #4 #5 #6

#7

Steam ElectricityNatural

GasCoolingWater

WastewaterTreatment

Incineration

CompressedAir

TreatedWater

Utilities

$6,647 k/yr55.9%150k MWh$44.4/MWh

$3,487k/yr29.3%590k MBtu$5.91/MBtu

$420k/yr3.5%10,244k kgal$0.041/kgal

$1k/yr0.0%1k SPU$1.20/SPU

$74k/yr0.6%3k klb$23.06/klb

$42k/yr0.4%58k kgal$0.724/kgal

$37k/yr0.3%214k kcf$0.174/kcf

#8$60k/yr0.5%314k kcf$0.174/kcf

$11,900k/yearEC TEX PE-1 Utilities

#9

$1,131 k/yr9.5%205k KESV$5.51/KESV

Nitrogen

CRITICAL COST ISSUES

18Kumana & Associates, Houston, Texas © 2017

Structured Brainstorming w/ Stakeholders

Site Participants Include:

� Site & Mfg. Unit Mgmt.

� Raw Matls./Interm. Supplier

� Process Tech. Experts

� Plant Shift Operations Rep.

� Maintenance Specialist

� Finance/Business Rep.

Totals: 6-10 Plant, plus 5-7 Consultant team

Involves Key People on an

‘AS NEEDED’ basis: Only

One Week per Mfg. Dept.

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IETC Energy Manager's Workshop 10

19Kumana & Associates, Houston, Texas © 2017

Summary of Level 1 study

Quickly Present and Implement SolutionsUser Friendly Reports

Jump Starts Program, Instant CredibilityCreates Immediate $$ Results

Identifies Most Valuable SolutionsUses Financial & Technical Tools

Saves Time, Maximizes ResultsFocuses on Critical Cost Issues

Doable Solutions, Commit to ImplementInvolves Your Key People

Lowers Unit Cost of Finished ProductIntegrates Process and Energy

BenefitsFeatures

20Kumana & Associates, Houston, Texas © 2017

Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• PROCESS MODS – higher capacity & yields, less waste

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

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IETC Energy Manager's Workshop 11

21Kumana & Associates, Houston, Texas © 2017

Heat and Material Balance Simulation Models (Process + Utilities)

� Essential to get full understanding of how the Raw Materials and Energy are used

� Helps to pin-point areas of opportunity

� Suggests potential process improvements

� Essential design basis for Level 2 Energy Optimization study (process heat recovery as well as CHP system)

22Kumana & Associates, Houston, Texas © 2017

Example PFD: Bio-process plant

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IETC Energy Manager's Workshop 12

23Kumana & Associates, Houston, Texas © 2017

Example HMB model – biotech plant

24Kumana & Associates, Houston, Texas © 2017

CHP System Simulation Model

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IETC Energy Manager's Workshop 13

25Kumana & Associates, Houston, Texas © 2017

Marginal steam prices - discontinuous

1

1.5

2

2.5

3

3.5

4

4.5

0 25 50 75 100 125 150

Klb/h STEAM GENERATED

Incre

men

tal

Ste

am

Co

st,

$/K

lb

Target Steam savings

26Kumana & Associates, Houston, Texas © 2017

Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• PROCESS MODS – higher capacity & yields, less waste

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

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IETC Energy Manager's Workshop 14

27Kumana & Associates, Houston, Texas © 2017

Operational Improvements

� Following industry Best Practices

� Reducing Process variability

� Flowsheet Improvements via simple process piping/control modifications

� Optimum equipment load allocation policies

� Performance Monitoring & Targeting

� Process Controls (eg. CHP optimizer, MVC)

Energy Cost savings can be achieved at little or no capital costthrough:

28Kumana & Associates, Houston, Texas © 2017

� Minimize running spares

� Avoid keeping equipment on hot standby

� Maintain Steam traps, insulation

� Steam/Air leak detection & repair program

� Cooling water treatment

� Boiler & Furnace O2 controls

� Burner management

� Flue gas stack damper control

� Minimize CW and process fouling

� Optimize HX cleaning schedules/techniques

Low-cost Best Practices

Motherhood and Apple Pie

MoreAdvancedmethods

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IETC Energy Manager's Workshop 15

29Kumana & Associates, Houston, Texas © 2017

Benefits of Reducing Process Variability

� Energy savings

� Capacity debottlenecking (throughput)

� Improved product quality

� Improved yield

� Reduced wastes

� Increased profitability

REF. G. Buckbee, “Closing the Gap between Engineers and Management”, Chem Eng Prog, May 2010

PV = Process Variable (eg. prod. moisture %)SP = set pointMV = Manipulated Variable (eg. steam flow)

(Steam flow rate)

(Product moisture content)

30Kumana & Associates, Houston, Texas © 2017

Flowsheet Improvements

• Minimize non-isothermal mixing

• Minimize non-isoconcentration mixing

• Minimize range of recycle loops

• Avoid needless heating / cooling / pumping

• Add Degrees of Freedom via piping/control modifications (e.g. bypasses, manifolds)

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IETC Energy Manager's Workshop 16

31Kumana & Associates, Houston, Texas © 2017

Examples of Simple Piping mods

PROC 1 PROC 2STORAGE

CW

STM

32Kumana & Associates, Houston, Texas © 2017

Load Management Concepts

� Minimize number of machines being operated in parallel

� Reduce the rate at which individual machines are being run, through minimizing recycle flows

� Operate equipment at near its maximum efficiency point, to the extent possible

� Assign maximum duty to the most efficient equipment (in a parallel set), and use the least efficient equipment as the “swing” machine

� Optimize sparing philosophy (eg. N+1 vs N+2)

� Add Degrees of Freedom as necessary

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IETC Energy Manager's Workshop 17

33Kumana & Associates, Houston, Texas © 2017

Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• PROCESS MODS – higher capacity & yields, less waste

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

34Kumana & Associates, Houston, Texas © 2017

Equipment Efficiency Upgrades

� Pumps

� Compressors

� Motors

� Heat Exchangers

� Fired heaters (furnaces)

� Boilers (fired and unfired)

� Steam & Gas Turbines

� Refrigeration cycles

Electronic spreadsheet templates are most convenient

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IETC Energy Manager's Workshop 18

35Kumana & Associates, Houston, Texas © 2017

Retrofit selected motors with VSDs

903 MWH/yr

= $24.4 K/yr

ROI = 17.8 %

CONFIDENTIAL

Generally best when

• HP > 500• Load < 70%

36Kumana & Associates, Houston, Texas © 2017

Pump Networks with and without VFDs

Capacity that results in ENERGY LOSSES (CV + Recirc.)

Load Management (pumps

on or off as required)

+ One pump running on VSD

(always ON)

Parallel +

Single VSDTime

Pump (n-1)

startup

n pumps ON

Pump n startup*

Flow Rate(Single or Parallel)

Head(Series)

1

2

n

All pumps on-lineat all times

Flow Rate(Single or Parallel)

Head(Series)

Time

“On-line”Capacity

Process Requirement

Intermediate scenario of Load Mgmt, where un-needed pumps are turned off, is not shown

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IETC Energy Manager's Workshop 19

37Kumana & Associates, Houston, Texas © 2017

HX modification strategy

Goal = Move operating point towards Target Zone

Target operating zone

Fouling zone

Velocity (and ∆∆∆∆P) too high

REF. Screenshot, ExpressPlus® s/w from IHS-ESDU (2006)

38Kumana & Associates, Houston, Texas © 2017

Shell-side Helical Baffles

BETTER TEMPPROFILE AND

FLOW PATTERN

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IETC Energy Manager's Workshop 20

39Kumana & Associates, Houston, Texas © 2017

Furnace/Boiler Air Preheating

40Kumana & Associates, Houston, Texas © 2017

Arbitrage: shifting duty between Utilities

New steam heaters can provide an additional degree of freedom to shift duty from high-cost hot oil to LP stm.

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IETC Energy Manager's Workshop 21

41Kumana & Associates, Houston, Texas © 2017

Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

• PROCESS MODS – higher capacity & yields, less waste

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

42Kumana & Associates, Houston, Texas © 2017

How can we reduce Process Heat use?

� Avoid needless consumption (eg. more efficient equipment and operation)

� Recover higher-grade ‘waste heat’as much as possible (HEN)

MedLow Hi

Reusableheat

CWRfg

PROCESS

TEMPERATURE

Not Reusable

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IETC Energy Manager's Workshop 22

43Kumana & Associates, Houston, Texas © 2017

Pinch Analysis: Composite Curves

Qcold

QhotT

em

p

Heat Load

Qhot & Qcold are the

energy targets

PinchUsed for Energy

Targeting

Used for Energy

Targeting

• Composite Curves represent the process heating and cooling duty profiles• Energy Targets are an excellent Benchmarking tool

44Kumana & Associates, Houston, Texas © 2017

T

CoolingWater

Steam

Process HeatTransfer

DO NOT

• use Steam below Pinch

• use CW above Pinch

• transfer heat from process

streams above Pinch to

process streams below

Pinch

The Pinch Principle

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IETC Energy Manager's Workshop 23

45Kumana & Associates, Houston, Texas © 2017

Grand Composite Curve - GCC

T

H

REFRIGERATION

COOLING WATER

LP STEAM

HP STEAM

Used for utilities

selection

Used for utilities

selection

46Kumana & Associates, Houston, Texas © 2017

Finding the Global Optimum ∆∆∆∆Tmin

Goal is to identify Near-Optimum ∆Tm range

Near-Optimal range

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IETC Energy Manager's Workshop 24

47Kumana & Associates, Houston, Texas © 2017

Grid Diagram identifies Pinch + XP ht tr

H1

H2 C

Pinch

176°

158° 158°

C2140° 140°

C1H140°

∆Tmin = 18°

XP ht tr is in this HX

212°

248° 86°

104°

356°

266°

48Kumana & Associates, Houston, Texas © 2017

Driving Force Plot – HX placement in HEN

Bad Match

Good match

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IETC Energy Manager's Workshop 25

49Kumana & Associates, Houston, Texas © 2017

Heat Recovery in Contractor’s design

Styrene Plant – new design, Japan (1)

50Kumana & Associates, Houston, Texas © 2017

Heat Recovery in optimized Pinch design

Styrene Plant – new design, Japan (2)

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IETC Energy Manager's Workshop 26

51Kumana & Associates, Houston, Texas © 2017

Save both Capital Cost and Energy

Styrene Plant – new design, Japan (3)

52Kumana & Associates, Houston, Texas © 2017

100% conversion of Q ���� W

T

HeatEngine W

Q - W

QA - (Q - W)

A + W

HeatEngine W

Q

B - QQ - W

No improvement in system ηηηη

T

Heat

EngineW

Q - W

B + (Q - W)

QA

A + Q

Appropriate Placement - Cogeneration

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IETC Energy Manager's Workshop 27

53Kumana & Associates, Houston, Texas © 2017

Optimum Utilities: Total Site Analysis

Curves are composites of the RESIDUAL heating and cooling duty segments from the GCCs of individual process units

Net processcooling demand= available heat

Net processheatingdemand

T

wHP

Req. Q

Enthalpy, MMBtu/hCW

BFW

LP stm

54Kumana & Associates, Houston, Texas © 2017

Typical On-line CHP s/w Architecture

Hydrogen Fuel Steam Water ElectricityUtility Systems

External Utilities

Contracts

Emissions

Regulations

ProcessIndustrial

Site

Real-Time Optimizer finds the best way to operate all utilities subject to

contractual, environmental and operational constraints

Optimum

Utilities

Operations

Report

Measurements

Optimum

Set Points

Key

Performance

Indicators

Monitoring

and

Accounting

Reports

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IETC Energy Manager's Workshop 28

55Kumana & Associates, Houston, Texas © 2017

Typical Savings = 4-5% vs Std practice

5,30 %

1,19%

-

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00

19-1

2

26-1

2

2-1

9-1

16-1

23-1

30-1

6-2

13-2

20-2

27-2

6-3

Day

Savin

gs / T

ota

l E

nerg

y C

osts

(%

)

Ahorros Anuales

> 2 MM €/year

> 4%

Y axis = Deviation from Optimum = Remaining Savings Opportunity

56Kumana & Associates, Houston, Texas © 2017

Workflow integrating Pinch Design method

� First structural optimization, using Pinch Analysis

� Then parametric optimization, using simulation models

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IETC Energy Manager's Workshop 29

57Kumana & Associates, Houston, Texas © 2017

Magnitude of Savings = f (Payback)

Savings vs Payback

0

20

40

60

80

100

120

0 2 4 6 8 10 12

Simple Payback, yr

% o

f M

ax P

ote

nti

al

Low

High

If you set unrealistic ROI requirements, you will FAIL

Here

or Here?

NOT

possible

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Why use Pinch Analysis?

� Systematic procedure can find best flowsheet structure, even (in fact especially) for very complex plants

� Quicker + cheaper than traditional approach

� Rigorous energy targets; we know when to quit

� Saves energy and capital without sacrificing safety, operating flexibility, or reliability

� For new plant design, there is an optimum time to do it; but Mgmt needs to be made aware.

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Technical Tool Kit

� “COST FLOW” DIAGRAMS for CCIs

� STRUCTURED BRAIN-STORMING

� PFDs and HMB SIMULATION MODELS

� OPERATIONAL IMPROVEMENTS

� EQUIPMENT UPGRADES

� PROCESS INTEGRATION (Pinch Analysis)

• OPTIMIZED HEAT RECOVERY

• OPTIMIZED CHP STRUCTURE

• PROCESS MODS – higher capacity & yields, less waste

� PERFORMANCE MONITORING

Level 1

Levels 2 & 3

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Performance Metrics - KPIs and EPIs

INDEX TYPEINDEX TYPE

Corp KPICorp KPI

Plant EPIsPlant EPIs

� Product

� Process

� Equipment

APPLICATIONSAPPLICATIONS

� Org efficiency trend

� External Benchmarking

� Cost Accounting

� Economic dispatch

� Planning

� Performance trend monitoring

� Operations troubleshooting

� Design Improvement

� Process control

� Equipment troubleshooting

� Targeted maintenance

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Multi-tier structure – drilldown capability

Company

Bus Line 2

Sales & Mktg

Bus Line 3 Bus Line 4Bus Line 1

Corp SupportGen admin

Plant DPlant A Plant B Plant C

Process 2 Process 3 Process 4 Process 5Process 1 Utilities

Fractionator Compressor Fired HeatersReactors

Plant E

HX Pumps

KPI s

EPI s

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Necessary Features of Good KPIs

�� Directional ConsistencyDirectional Consistency: When we do something good (e.g. make more profit), the KPI should get better

�� Magnitude ConsistencyMagnitude Consistency: The magnitude of change in the Index should closely match the change in profit, or efficiency, or whatever it is we are measuring.

All KPIs must meet these 2 tests

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90 MBDoe saved in 6 yr; 50% target over 10 yr

0%

20%

40%

60%

80%

100%

120%

0 1 2 3 4 5 6 7 8 9 10

Program year

Corp

Ene

rgy E

ffic

iency I

ndex

Actual

Potential

Forecast

Projected

Energystudies

Operation

Implement-ation

REF. J D Kumana, “Corporate Energy Management Programs: A Case Study”, Chemical News (Nov 2010)

Major International O&G Co, 15 plants

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Benefits of Systematic PEO Approach

Time

Sa

vin

gs

($

)

With PEO

NPV = 2X W/O PEO

NPV = X

PEO Creates More and Better

Solutions.

>>> Twice as much

implemented in half the

time!

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The End

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Case Study – generic BioTech plant

� High-value biomass product

� Fermentation + evaporation + drying

� Design based on scale-up of lab process

� 8000 hours per yr operation

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Simplified PFD

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Base Case Utility Consumption & Costs

What would YOU do to improve process efficiency & economics ?

(includes Dryer steam duty)

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Level 1 PEO idea: Btm Cycle Cogen

• Operate Boiler at max design pr (600 psig)

• Add new superheating section (to 700 F)

• Add new Back Pressure Stm Turbexhausting at 175 psig

PRELIM RESULTGood economicsWarrants more study

STBOILER

KW

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Level 2 PEO study: Energy Targets

QH target = 15.2 MMBtu/h, vs 24 MMBtu/h actual use

EVAP OH VAPEVAP DUTY

DRYERVAC JET EXHAUST

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Grand Composite Curve ���� partial MVR

CW

175# steam

MVR Vac jet exhaust

Evap duty

Evap OH vapor

Dryer duty

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Revised CCs with right-sized MVR

Vac jet exh Dryer duty

Evaporation duty

MVR disch vapor

Residual EvapOH vapor

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PFD for Optimum Process Configuration

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Optimized Utility Costs & Savings

• Minor changes � Major opex savings (energy + CO2 + WWT)• New cream separator + recycle improves yield• New fermenter cooling design saved 50% of Rfg (not described)• 60% smaller cogeneration project � capital savings• Negligible technical risk; Zero commercial risk• Straight-forward methodology (minimal trial & error)