Author: N.Bonavita, G.Ciarlo Date: February 25 , 2014 MENA … · 2018-05-09 · §PEMS, Predictive...

© ABB GroupNovember 18, 2014 | Slide 1

MENA Offshore Platforms 2014Combining analytics and process automationfor enhanced emission control strategies:PEMS at work

Author: N.Bonavita, G.Ciarlo Date: February 25th, 2014

Emission Monitoring Systems

§ EMS encompasses the followingfunctions:§ Sampling

§ Analysis

§ Data Acquisition

§ Data Validation

§ Data Processing and Archiving

The Traditional Approach

© ABB Inc.November 18, 2014 | Slide 2

COCO

SO2SO2

NOxNOxHClHCl

HFHF O2O2

NH3NH3HgHg

TOCTOC

H2OH2O

DustsDusts

DioxinsDioxins

MetalsMetals§ The core of traditional Emission

Monitoring System are HardwareAnalyzer, integrated with IT andsoftware infrastructure for emissionstorage and reporting

IntroductionZooming on CEMS


Source: “EPA Handbook – Continuous Emission Monitoring Systems for Non-criteria Pollutants”, 1997

§ PEMS, Predictive Emission Monitoring Systems, represent analternative technology for emission monitoring based on software

§ PEMS provide emission estimation by means of sophisticatedModels based on mathematical and/or statistical techniques.

§ Models are able to exploit the inherent correlation existingbetween process variables (flow, temperature and pressure) andemission properties (NOx, SO2, CO, CO2).

§ Correlation are assessed and evaluated through fieldmeasurement campaigns:

§ Emission Data collected from existing HW analyzers orwhen not available temporarily installed at plant stack

§ Process Data from plant Control System (DCS, PLC) orProcess Historians

IntroductionWhat are PEMS?


§ A SYSTEM is defined as a collection of objects among which itexists a set of cause-effect relationships

§ A MODEL is defined as a set of rules by which, knowing theinputs, it is possible to derive the outputs behaviors

It is possible to quantitatively represent a system by a model:

Yi = Li [x1, x2, …, xs] i=1, …, r

Model-based Emission MonitoringWhere does it come from?

Let’s move from Definitions …

§ It is possible to classify modeling technique in two main groups:

§ Fundamental (or First-Principle) Models, where the descriptiveequations are derived from the basic physical and chemical laws

§ Empirical (or Data-driven) Models, where the models are built througha fitting-like procedure over the plant live data

Momentum Balance: gvvvd

vd rtrr-

¶¶

+¶¶

-¶¶

-= 2

2

xxxP

t

UA

UB

YA

YB

U Y++ +Y = a1UA+ a2UB+…

+UA UB YA

15.23 1.37 6.5416.02 1.39 6.5814.89 1.43 6.4115.75 1.47 6.38


Wide Spread of Process Computers, Distributed ControlSystems (DCS) and SCADA

Historical data are a valuable asset for bettercontrol, management and optimization

Data Collection and Storage is easy, cheap andstraightforward


§ Process Automation Trends in the last 25 years:

DRAFTStrictly Confidential


§ Leveraging and exploiting Process Automation, Analytics andInformation Technology to improve environmental monitoring andperformances

§ Exploiting the wealth of meaningful data available in modernindustrial plants to accurately estimate emission levels and deeplyunderstand how they develop and can be reduced

Model-based Emission MonitoringRationale for PEMS

PEMSMain Criticalities

§ PEMS successful implementation requires three mainingredients:§ Technology: i.e. SW environment able to handle

data from different sources, build and validateefficient models and endowed with proper facilitiesfor on-line deployment and monitoring

§ Know-how: i.e. highly skilled engineering resourcesable to blend instrumentation and analyticscompetences with process automation capabilitiesand modelling building expertize

§ Local Presence: in order to provide competitivesolutions (and efficient maintenance) serviceengineers should be next-door


§ A unique software platform, ABB proprietary, fordevelopment and deployment of empirical processmodels, featuring different technologies:§ Neural Networks

§ Statistical Regressions

§ Multivariate Statistical Analysis§ Equation-based models

§ Custom-based models (DLLs)§ It is composed by two different environments:

§ The Model Builder for data analysis, model buildingand validation

§ The On-line environment for effective and quickmodel deployment, execution and monitoring

PEMS: TechnologyABB Inferential Modeling Platform - IMP


PEMS: TechnologyIMP Model Builder – Features


§ Data Import from common sources like .xls,.csv, .txt etc.

§ Data pre-processing: Automatic OutlierRemoval to clean dataset for modelling fromanomalous process data

§ Correlation and PCA: specific advancedstatistical techniques to identify best processvariables influencing emissions or qualityvariables

§ Modeling functions are provided by proven,field-tested, latest generation routines

§ Model development executed throughWizards, to optimize manpower allocation

§ Model Explorer extends use of modelsbeyond on-line utilization (“What-if” analysis)


§ Quick and effective real-time implementationon different DCS through OPC

§ Supports multi OPC connection to gatherdata from different sources

§ Configurable filtering of inputs and outlierremoval strategies to verify and evidenceabnormal process condition and bad qualitydata

§ Emission estimation visualization, trendingand storing capabilities

§ Direct connection to Laboratory InformationManagement Systems

§ Direct connection with Data AcquisitionSystem.

§ Built-in functions for periodic recalibration(Bias calculation)

PEMS: TechnologyIMP On-line: – Features

Inferential Modeling PlatformInstallations

Hawaii

IMP© ABB GroupNovember 18, 2014 | Slide 13

PEMSApplication Fields

Two Main Possible Uses


Primary Source ofEmission Monitoring

Back-up/Validation ofExisting HW Analyzers

§ Coupled withtraditional CEMS toincrease theavailability of theEmissionMonitoring Systemup to 99,5%

§ Where CEMS arenot feasible or cost-effective

§ PEMS typical general requirements are:§ Plant has to be instrumented (T,F,P sensors) and

automated (PLC or DCS presence)§ Quality of combustion fuel has not to vary too much

or has to be monitored§ PEMS can be ideally applied to every combustion

process across the industry sectors from O&G, Chemical& Petrochemical to P&P, Cement, Metal, Power Utilities.

§ PEMS perfectly fit in Gas Turbine applications (Power,Compressor Drivers), Large Industrial CombustionEngines, Boilers and Furnaces.

PEMSApplication Fields


IMP

PTTTFT

NOxSO2CO


PEMS ApplicationIntegrated Architecture (Example)

HMI

EmissionManagementSystem

OPCServers

Controllers

Field

Ethernet TCP/IP

Ethernet TCP/IP

CEMS

PEMS ApplicationTypical SW Architecture (Back-up to HW CEMS)


TC FCFTTTFT PC

FIELD

+ -

IMP

ProcessVariables

AnalyzerValues

PredictedValues

S

“maintenancetrigger”

discrepancybetweenmeasured andpredictedvalues

Indication of maintenance need§ Physical sensor drift from model: by detecting the drift, maintenance needs

can be anticipated; maintenance activity can be validated by using the model


Physical Sensor

SW Sensor

40

45

50

55

60

65

70

75

80

85

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

AnalyzerModel

Alarm sent tomaintenance station

Maintenancesignal

Post maintenancevalidation

PEMS ApplicationExample: Maintenance trigger

PEMS ApplicationProject Execution

OfficeActivities

ImplementationSteps

DataCollection

Final Assessment &Commissioning

Model Validation

Inferential Model Buildingand Testing

Data Processing

On SiteActivities


PEMS Success Story #1Gas injection compressor units


§ Twin trains of gas compression§ Compressors gas turbine driven, each GT emission to a

dedicated chimney§ Two stage for each train (high and low pressure)§ PEMS installed at each stack (4 system)

PEMS Success Story #1Plant EMS: Hardware/Software architecture


Plant LAN

ABBIMP OnlineABB PGP

DCS Ring- Infi 90 Bailey

EMS Server-DuragNew Cabinet-

Control room

EMS Server: Third partyEMS Client: ABB PGP

EMS Client:§ Collects data from DCS and

make those available to IMP On-Line trough OPC Protocol.

§ Collects Prediction from IMP On-Line trough OPC and troughModbus send to EMS Server

EMS Server:§ Collects data from EMS client

and CEMS analyzer at stack§ Send data to Company HQDCS System

Connection to DCSConnection to EMS

Bailey Infi90ICI03Modbus

PEMS Success Story #1Conclusions

§ Commissioning successful completedby May 2008

§ It has been achieved the internationalcertificate EPA (US EnvironmentalProtection Agency)

§ First ABB commercial solution for anemission monitoring system based onSoftware Sensors, EPA Certified, inO&G field in Middle East Region.

§ Fully Integrated in the plant baseautomation system

§ A paper published on ABB review

§ 2013: major maintenance andrecalibration completed


§ Project includes the supply of PEMS for three stacks in a refineryin Mediterranean and inclusion in the existing EMS

§ Customer wanted to§ Increase CEMS service time to meet tighter regulation§ Prove the viability of PEMS technology to local environmental

legislator, pioneering the first application in the country

§ Site Selection§ Refinery is one of the biggest in Europe and has a production capacity

of 180000 bbl/day.§ PEMS are integrated in the existing EMS and act as back-up to

increase traditional CEMS availability for the three below plant units§ Sulfur Recovery Units (SRU)§ Fluid Catalytic Cracking Unit (FCCU)§ Belco Plant

§ Emissions and properties estimated:§ Flue Gas flow, CO, O2 ,SO2, NO, Particulate


PEMS Success Story #2Mediterranean Region Major Refinery

PEMS Success Story #2Sulfur recovery Units (SRU)


Characteristics :§ 3 parallel trains with different layout§ 3 feed gas with variable composition, coming from several

different plant units:§ SO2 rich gas (SRG)§ Sour water gas (SWS)§ Amine acid gas (AAG)

Plant configuration of the three sulfur recovery units

System includes:

§ 3 EMS client collecting emission datafrom stack analyzers

§ 1 EMS server for emission datareporting and storage for the wholerefinery

§ 1 PEMS server

§ 1 PIMS server collecting data fromdifferent DCS

PEMS Success Story #2EMS Hardware Architecture


PEMS Success Story #2EMS Human Machine Interface


PEMS Success Story #2PEMS Results: FCC


PEMSCEMS

PEMS Success Story #2PEMS Results: FCC


PEMSCEMS

NO Predictions and measured values in a 1-day span for the FCC unit

PEMSConclusions

§ PEMS are a cost effective solution to complete andenhance emission monitoring strategies.

§ PEMS features distinct advantages in a number ofapplications with or without HW analysers

§ ABB has the experience, the technology and the qualifiedlocal presence to provide the best solution no matter it is aHW-based CEMS, a PEMS or a smart and flexiblecombination

§ ABB owns IMP, a software tool recognized for PEMSdevelopment and deployment which has already a fewapproved (and certified!) installations.

Source: WW Emission Monitoring report- ARC 08/12

Author: N.Bonavita, G.Ciarlo Date: February 25 , 2014 MENA … · 2018-05-09 · §PEMS, Predictive...

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Transcript of Author: N.Bonavita, G.Ciarlo Date: February 25 , 2014 MENA … · 2018-05-09 · §PEMS, Predictive...