Version 2.0

Issue and direction of Energy Network Optimization

in Petrochemical Industry

Infotrol Technology, Co., Ltd. since 2004

Revision History

Date Version Author Comment

2015. 10. 15 1.0 KTW Presentation Content Scheme

2015. 10. 16 1.7 KTW Presentation Content Scheme update

2015. 10. 19 2.0 WHK Review and update

Energy Network in Process Industry

3

q  Definition: Network of energy production, distribution and consumption

q  Network composition: Furnace, Boiler, gas turbine, HRSG, turbine, heat exchanger, electrical/steam

motor, let down equipment, heat pump, header line and users, etc.

q  Application area: Process industry such as petrochemicals, refinery and chemical companies etc

Energy Network Management Issues & Solutions

4

Issues Solutions Estimated Effect

Steam production and consumption is not matched (energy imbalance)

Data reconciliation based steam balance Increased steam data accuracy

Not concern on measurement error Data reconciliation based steam balance Erroneous measurement detection and management

Unknown energy loss Systematic unknown loss identification through energy balance

Unknown loss identification and reduce energy loss

Building steam balance for an event takes a long time

Real time on-line steam balance system Reduced engineer work load and improve energy system analysis

Energy intensity increase from the operational mistake

On-line operational surveillance and measure system

Improve energy intensity by reducing the operational mistake

Difficulty in setting new steam balance for operational and/or process changes

Build what-if utility simulator Complex-wide economic analysis for process and /or operational changes

Do not know whether the current steam operation is optimal

Need to build the optimal steam system Reduce energy intensity while supplying the required energy

Do not fully utilize the steam potential energy (exergy)

Build the steam utilizing maximization system

Maximizing the steam energy utilization

Lack of efficient response for the electric price change

Build the optimal system considering the electric price

Economic benefit from optimal operation of electric production and import

Typical energy management issues and solutions with economic effect in process industries such as petrochemical, refinery, etc.

Required energy management system to minimize the energy intensity

5

Area Required Function Estimated Effect

Plant-wide energy network steam/energy balance and Energy management system

•  Provide plant-wide energy network overview •  Data Reconciliation based energy mass balance •  Real time on-line management of energy

production and consumption •  Energy loss identification •  Easily maintenance and update of the system

•  Capturing plant-wide energy flow •  Enhanced accuracy of energy balance •  Real time on-line energy management •  Reduce energy loss •  Fast respond for process and/or

operational change

Energy system what-if simulation

•  Simulate for the process and/or operational change •  Evaluate complex-wide benefit from the sub

process energy reduction •  Define new energy projects

•  Establish new steam balance for changed process and/or operation

•  Economic analysis of each sub process energy reduction

•  Prioritize energy projects with estimated economic benefit

Optimization •  Real time on-line optimal operational guide while keeping the energy requirement

•  Provide breakdown effect of optimal operation •  Closed-loop optimization if necessary

•  Keeping real time optimal operation •  Identify the operational change resulting in

optimization •  Automatic optimal operation

Abnormal detection and root cause analysis of energy intensity

•  Abnormal detection and root cause analysis of Energy intensity by providing logical detection of abnormality

•  Fast detection and measure for increasing energy intensity

Support ISO50001 and greenhouse gas emission trading scheme

•  Support ISO50001 •  Support emission trading scheme •  Support energy accounting system

•  Support standardized energy management procedure

•  Provide energy accounting data, more accurate and credible

Project Objective

•  Complex-wide Energy Balance

•  Complex-wide Energy Network Optimization

•  Main Energy Equipment Efficiency Management

•  What-if simulation of energy network

•  Energy intensity management by plant or process

•  Energy Network optimization and management system

•  Energy balance and optimization report

•  Energy Usage Management by quantity and price base Note : Induce energy innovation by sharing company-wide information sharing using Web technology

Construct Energy Management system to optimize complex-wide energy network and minimize plant energy intensity

▣ Energy Network Optimization System

▣ Complex-wide Energy Management System

q  EMS q  ENetOPT Proposed Solution

7

q  Energy balance l  Steam production and consumption

balance l  Analyze erroneous measurement l  Analyze the energy & mass loss

identification (steam, trap, tracing) q  Simulation

l  Simulate Effect of New energy equipment installation

ü  Boiler, HSRG, Turbine investment effect

l  Simulate Effect of Plant Operation Condition

ü  MP, LP usage change (change due to product output or process revamp)

q  Energy equipment efficiency l  Boiler, Turbine, Pump, Heat exchanger

efficiency calculation and analysis q  Optimization

l  Load balance considering boiler efficiency l  Optimize Turbine exhaust, condensing and

electricity

q  Energy Network Monitoring l  Complex wide summary and detailed plant energy

network l  Steam/Condensate measured, balance and

optimization q  Inter-company utility trading history

l  Histories utility trading and reports via various diagram

l  Calculates optimum trade amount q  Greenhouse emission management

l  Histories and report green house gas emission q  Energy Intensity

l  Analyze the cause of plant energy intensity increase

q  Optimization l  Display and Report energy optimization condition

and result q  Equipment Efficiency

l  Equipment Efficiency calculation and monitoring l  Analyze abnormal operation cause

ENetOPT: Functional Configuration

8

Visual Modeling l Drag & Drop based visual

modeling of energy network l Equation-based system

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Monitoring Balance Optimization

Reporting Simulation

DB

ENetOpt System

Field data Interface l  OPC (DA3.0, UA) l  RTDB (PHD, CIM I/O, INSQL, PI) l  RDB (Oracle, SQL) l  XML

Optimization l Minimize energy cost l Maximize the utilization of high

value energy l Mixed Integer Linear

Programming

Simulation l Energy Production and

distribution simulation for the changed operational change

l Simulation for the new or changed facilities

l  Extend to operator training

Report l Steam /condensate balance l Energy Network optimization l Database of the all the input and

result l  Connect to the database for the

customized report

DCS SCADA

On-line Energy Balance l Energy balance for each

equipment, unit, plant and complex-wide

l  Data reconciliation with standard deviation of each measurement

Efficiency

Efficiency and Energy Intensity

l Equipment efficiency calculation l Unit and plant energy intensity

definition and calculation l Abnormal and inefficiency

operation detection

ENetOPT Applied Technology

9

ENetOPT: Visual Modeling

10

"   Mathematical modeled energy equipment stencil "   Multi-layer configuration "   Steam and Coolant equipment modeled template "   Can provide the custom specific energy equipment "   Can fully utilize MS VISIO functions such as hyperlink to user documents

q  Easily build the Energy Network by drag & drop energy equipment stencil l  Easily build and modify the energy network without any hard coding program l  ENetOPT creates automatically equation based code

Drag & Drop

ENetOPT: Plant-wide Energy Balance

"   Data Reconciled material balance and energy calculation based on the status of the flow "   Balance report created "   Automatic periodic running at the frequency given by user "   Use to analyze the energy loss identification, erroneous measurement, etc.

ENetOPT: What-if Simulation

12 12

"   Simulation for the change of operational conditions and/or energy equipment arrangement "   Analyze the effect of load change, new energy consumption and production facility, etc. "   Analysis report created

13

ENetOPT: Equipment Efficiency Management

13

"   Calculation and management of each equipment and unit section’s performance efficiency "   Early detection of inefficient equipment or unit section "   Analyze the performance trend of each equipment daily, monthly and yearly "   With logical flow chart program such as Infotrol’s IPOES to detect the source of efficiency deterioration

and to suggest the improvement

ENetOPT: Optimization

14

"   Maximization of high value energy utilization "   MILP engine "   Drag-and-drop modeling build internally cost function and all necessary constraints "   Optimal steam/ electric motor selection

Additional Constraints provided by User

EMS : Web-based EMS (Energy Management System) q  HTML5 based Energy Management System configuration

15

Energy  Production  and  Consumption  Monitor

Plant  Energy  Usage  and  Energy  Intensity

Complex-­‐wide  and  detailed  plant  energy  network

Utility    Unit  Price

Energy  Intensity  Monitor  and  AnalysisEnergy  Utility  (Steam,  Fuel,  Electricity)  Usage  Analysis

Real  Time  Abnormal  Operation  Detection  and  Alarm

Equipment  Efficiency  Monitor  and  AnalysisTurbine,  Heat  Exchanger,  Boiler  Efficiency

Analysis  of  Equipment  Efficiency  Degradation

Steam  Production  Price  Calculation

Green  house  gas  emission  management

Energy  Network  OptimizationOptimal  Operating  Condition

Current  Energy  Intensity  and  Energy  Equipment  Optimization  Effect

Inter-­‐Company  Energy  Utility  Trade  Management

EMS : Energy Produce and Consumption Monitoring q  Plant Energy Usage and Energy Intensity q  Complex-wide and detailed plant energy network q  Utility Cost Calculation q  Energy information including inter-company utility trading and green house gas management

16

EMS : Plant Energy Network Monitoring q  Report current fuel, steam, electricity usage, and trend q  Monitors the cost of energy utility and Greenhouse gas emission q  Induce energy usage reduction

17

EMS : Energy Network Monitoring

18

q  Complex wide overview energy network summary q  Detailed plant energy network q  Steam/condensate measured, balance and optimization result

EMS : Steam Cost Calculation and Management q  Real time and Monthly utility price calculation q  Water, Steam, Electricity, and Steam price calculation and management q  Systemize the utility product price calculation

19

W a te r P ro ce ss C h a r t

# Raw Water (Ton/Day) : 해당월

Won/Ton

0

##

##

##

##

FW3159

11130

42.9

0

1484

283

2663

#####

831

940

29,837

312

29.3

5

1829

1233

6396

809

783

8320

18776500144

#####

309

0

28150

00 0

0

1278211

116 983

-1220

1484824

1648

2709

1011

85

0

50

0134

550114840

757

1829 9000

30633,667

131

1011328611631280

26,031

757 1490

2247

141128792838

907

10

131

2575

907 1544

2838

2451

2683

-831

474

357

0.0

203

0

47

3,639 4125

5006

0

94756

10

0

3124

2815

0237

#####

0

3178 0

101000

0

2926

0

36.4

10

17334,648

2926 0

4,751

0

64284,572

120

358

25.6900

1,657

3,696

0

5045

47526.0820

6542

0

50

1829

2578

5000

1829

96

1139

7.3

114

50004900

5006

0

856

8091422

-2467

3201829

2792

392252

18222107

1573

58

144 0

3700

88

1086

1086

UW POT

POT

BFW

MWH

HPSLPC

#1CW

HPC

H/C

RW

RW

HPC LPC

H/C

BFW

MWH

HPS

#2CW

BTXCW

Co-genCW

UW

TW

TW

RW from R/O

C/F R/O Demi Pol.

Dea

Dea BLR

FBC

T/G

C/F R/O Demi Pol. Dea BLR T/G

Dea

#2 BFW (Boiler) 4,572 \₩/ton #1 HPS 760.00 kcal/kg

E le ct r ic i t y a n d S te am P ro ce ss C h a rt Fuel 단가 BC 131,853 \₩/FOEB #2 HPS 751.50 kcal/kg 7 5 5 .7 5

192.29 PFO - \₩/FOEB HPC 192.00 kcal/kg

BC - FOEB/hr PN 155,395 \₩/FOEB MPS 704.50 kcal/kg

PFO - FOEB/hr 179 COKE 116,658 \₩/ton MPC 153.60 kcal/kg

PN - FOEB/hr SPS - Ton/h - ℃ 30,819.25 28,094.10 KEPCO 109,492 VMW LPS 676.20 kcal/kg

- \₩/ton - Kg/cm2 HPS 755.75 kcal/kg LPC 100.00 kcal/kg

826 Kcal/kg 120 1,816,926 MPS 704.50 kcal/kg BFW 35 kcal/kg

BFW - Ton/h 127.67 LPS 676.20 kcal/kg 0.48- ℃ 효율 #DIV/0! % BD PFO - \₩/FOEB

- Kg/cm2 - Ton/h 58.8 Ton/h From #2 Cogen 3,838,312 139.0 Kcal/Kg 36,380 \₩/ton SPS 3935622.958

BC - FOEB/hr Electricity 23.70 MW 23.55 MW E le c t r ic it y 23.70 MWPFO - FOEB/hr 85,302 \₩/MW 85,842.0 \₩/MWPN - FOEB/hr SPS - Ton/h - ℃ SPS 128 Ton/h 2021312

- \₩/ton - Kg/cm2 30,826 \₩/ton #1 발전 사용

826 Kcal/kg 494 ℃ Condensate 5.34 MWBFW - Ton/h 51.1 Ton/h 103 Kg/cm2 66 Ton/h 0.15 MW 1,584,330,094 6,352,909,298.73

- ℃ 효율 #DIV/0! % BD 799 Kcal/kg 1,484 \₩/ton 5.19 MW- Kg/cm2 - Ton/h 효율 538 Kcal Loss 560

138.0 Kcal/Kg BFW 100 % 회수율 0.51 MW3.1 Ton/h 0.486422388 HPS tag MW/Ton 2.77

11.7 3,667 \₩/ton 62 Ton/hCoke 11.7 TON/hr SPS 120 Ton/h 499 ℃ 150 ℃ 29,256.42 \₩/tonB-C 0.2 FOEB/hr 28,094 \₩/ton 108 Kg/cm2 110 Kg/cm2 370 ℃

797 Kcal/kg HPS 124 Kcal/kg 43 Kg/cm2 69.1 19254.2 Ton/h 752 Kcal/kg #1 발전 HPS 사용 #REF!

BFW 122 Ton/h 효율 90 % BD 57.407 29,256 \₩/ton 0.061320755 23 Ton/h141 ℃ 2 Ton/h #DIV/0! #DIV/0!119 Kg/cm2 29,256.42 Loss #1 발전 (MP, LP 사용)

139.0 Kcal/Kg - Ton/h - Ton/h

BFO - FOEB/hr HPS HPSBFW - Ton/h SPS - Ton/h - HPS 54.2 Ton/h 378 ℃ 116.30 Ton/h 93.71 Ton/h 93.71 Ton/h

22 ℃ - \₩/ton - 29,256 \₩/ton 42 Kg/cm2 29,256 \₩/ton 29,256 \₩/ton 29,256.4 \₩/ton41 Kg/cm2 760 Kcal/kg 23 378 ℃

150 Kcal/Kg BD 31.3 42 Kg/cm2 1,842,304,572.58 225.03 효율 - % Ton/h 760 Kcal/kg 2,926,274,632.09

8,686,684 538.35 215.1256,462,892,770 4066368.432 36,312 4,768,579,204.68

11,925,972,330 336071.2753 JVC Elec #NAME? 29,256 3,428,140.15 JVC R-cogen #NAME?3,764,211.42 JVC Mu #NAME?

SPS - Ton/h 91 ℃ 144.4 Ton/h Electricity 4.17 MW 4.11 MW E le c t r ic it y 4.17 MWBFO - FOEB/hr - \₩/ton - Kg/cm2 36,380 \/ton 80,618 \₩/MW 81,856.0 \₩/MW 336322.5PFO - FOEB/hr 825 Kcal/kg 111.8 Ton/hPN - FOEB/hr 500.0 ℃ #2 발전 사용

BFW - Ton/h 효율 #DIV/0! % BD 94.0 Kg/cm2 Condensate 7.71 MW22 ℃ - Ton/h SPS 822 Kcal/kg 4 Ton/h 0.06 MW

- Kg/cm2 32.7 Ton/h 1829 \₩/ton 7.65 MW139 Kcal/Kg 효율 545 Loss

BFW 90.3 % 회수율 0.03 MWSPS - Ton/h 99 ℃ 1.65 MW/Ton 0.84

BFO - FOEB/hr - \₩/ton - Kg/cm2 4,572 HHPS tagPFO - FOEB/hr 825 Kcal/kg 150 ℃ 98 Ton/hPN - FOEB/hr HHPS 110 Kg/cm2 34,852 \₩/ton #2 HHPS 발전 4321014.2

BFW - Ton/h 효율 #DIV/0! % BD 1188627.554 34.3 Ton/h 135 Kcal/kg 420 ℃ 9 Ton/h24 ℃ - Ton/h 7537.723753 34,852 \₩/ton 44 Kg/cm2

0 Kg/cm2 72 1196165.278 420 ℃ LPS tag 788 Kcal/kg Loss140 Kcal/Kg 1196165.278 44 Kg/cm2 9.9 Ton/h - Ton/h

789 Kcal/kg 29,837 \₩/Ton HHPS tag HPSSPS 72 Ton/h 529 ℃ 132.7 Ton/h 124 Ton/h 131 Ton/h

BFO 35.5 FOEB/hr 73,501 \₩/ton 105 Kg/cm2 34,852 \₩/ton 34,852 \₩/ton 33,160 \₩/TonPFO - FOEB/hr 822 Kcal/kg 420 ℃ 370 ℃

PN 0 FOEB/hr 4624305.427 44 Kg/cm2 43 Kg/cm2

BFW 74 Ton/h 효율 91.1 % BD 123.4 3,428,140.15 788 Kcal/kg 751.5 Kcal/kg

128 ℃ 1.4 Ton/h 1196165.278107 Kg 4,624,305.43 36,732

134 Kcal/Kg BFW 7.3 Ton/h 33,159.90 4,572 \₩/Ton 47,763

36379.728 150 ℃ 34,934 137.6666667 64.6 110 Kg/cm2 256 6551 135 Kcal/kg

SPS 195 Ton/hCoke 18.44189007 Ton/h 22,644 \₩/tonB-C 0 FOEB/hr

BFW 199 Ton/h BD3 Ton/h

A s s u m p t io n s

2,021,386

#1 B o i le r

#2 B o i le r

#3 B o i le r

EB o i le r

#4 B o i le r

#5 B o i le r

#6 B o i le r

D e s u p e rh e a te r

#1/2/3T u rb in e

G e n e ra to r

#4/5T u rb in e

G e n e ra to r

D e s u p e rh e a te r

D e s u p e rh e a te r

T oP ro c e s s

T oP ro c e s s

To #1 Header +HOU

T oP ro c e s s

T oP ro c e s s

#8 B o i le r

HOU

Other  Cost Electricity  Cost

Electricity  Cost

Other  Price

Steam  CostWater  Cost

Raw  Water  Price

Raw  Water  Cost

Cost  :  Price  *  Quantity

Summary  of  Price  Determination

Steam  PriceWater  Price

Other  Cost Other  Cost

Determination  of  Price  by  LS  (Linear  least  squares)

Water  Processing  Steam  Proscessing  Electricity  Produce

EMS : Inter-company energy utility history

20

q  Reports inter-company energy utility history categorized by product and company q  Calculates Optimum Amount of Trade

Item Remark

Company & Product

Histories inter-company energy utility categorized by company and product

Trade Scheme

Report Trade quantity using various diagram

Report Generate Trade quantity report in monthly or in user defined interval

EMS : Green house gas emission management

21

q  Histories basic green house gas emission data q  Report Greenhouse gas emission

항목 내용

Summary

Emission Manage allowable emission quantity, accumulation in month term

Emission Report by Sector Manage greenhouse gas emission categorized by plant (Monthly Trend)

Emission Report by Team Manage team emission categorized by team, and comparison to previous month data (Monthly Report)

Company wise emission report Report fuel usage and emission categorized by plant and equipment

EMS : Energy Network Optimization q  Displays the result of energy network operating cost optimization q  Report Optimum Operating Cost q  Optimization can be interfaced to DCS

22

Typical System Configuration

23

Web based Energy Monitoring & Management: - Field Data, Balance and Optimization

Optional: Energy Intensity Analysis

ENetOPT server o ENetOPT o Web - based energy map

IPOES Server o IPOES 3 . 0 o Executable SOP

DCS

Infotrol DA ( OPC , PHD Interface ) Infotrol DA

( OPC , PHD Interface ) 서버 WorkStation

IPOES Design PC

Energy monitoring station

•  One license for server -  Used to plant-wide on-line

energy optimization system •  Two license for PC

-  Used normally for design, simulation and off-line optimization

Issues and direction

q  Steam mass balance l  For mass (steam/condensate) imbalance, it is not so sure whether it is caused by measurement

error, or any loss, or tracing and/or tracking, etc. l  Unmeasured value is estimated, but the balanced value for the estimated value is changed

significantly according to the operational condition. l  Gross error detection is very difficult since in most cases, measurement redundancy is not so

sufficient à Input data analysis for erroneous measurement à Gross error detection with logical analysis, statistical approach, and any neural and artificial

approach

q  Optimization l  It is necessary to include the planning functionality for On/Off and swing operation and minimum

operating and standby times of the equipment l  It is frequently asked to show the bottleneck constraint à Integrate utility planning and optimization à Search for active constraints

24

q  ENetOPT

Issues for the site application

25

q  Energy Intensity l  Root cause for energy intensity change of the plant is asked from clients l  It is necessary to compare the utility diagram and Process diagram à Statistical approach

q  Equipment performance l  User asked what is the main reason for the performance depreciation à Logical analysis for possible reason

q  Steam price l  It is necessary to calculate the steam price for each unit in real time à Real time estimation of steam value

q  EMS

EMS : Energy Intensity Analysis

26

q  Analyze the cause of plant energy intensity increase q  Reduced dimensional analysis by statistics

Real Time Reduced Dimensional Analysis

Hotelling T2 95% confidence limit

EMS : Energy Equipment Efficiency Monitoring and Analysis q  Main Energy Equipment Efficiency Calculation q  Main Energy Equipment Efficiency Monitoring q  Analyze Abnormal Operation Cause

27

Abnormal Operation Monitoring

Conclusion q  Typical approach of Energy Network optimization and management is well

established l  Data reconciliation based energy balance l  Energy Network optimization covering heat, electricity, fuel gas and hydrogen l  Energy management of monitoring energy production and consumption

q  Further enhancement of energy network optimization l  Gross error detection for the balance l  Energy Network optimization with planning functions

q  Further enhancement of energy management system l  Targeting on energy intensity reduction l  Energy intensity analysis to figure out the root cause of inferior energy performance

q  Eventually extend to energy network of other industries and covering city

28

ENetOPT, ENetPlan, ENetDisplay, IPOES & HIECON-I

Complex-wide Energy Balance

Equipment Efficiency

On-line Energy Intensity

Energy network optimal operation

Optimal production plan

What-if Simulation

Infotrol Technology Automation and Op

timization

8th Floor KT Mokdong Information Center 924 Mokdong Yangchun-Gu, Seoul, Korea

TEL: (02) 2061-7291 FAX: (02) 2061-7290 C.P.: 010-2320-4031 E-mail: infotrol@infotrol.co.kr Web site: www.infotrol.co.kr