Blendingwith DeltaV

Digital Inline Digital Inline Blending with DeltaVBlending with DeltaVby

Emerson Process Management @Copyrights

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AgendaAgendaAgendaAgenda What is Blending?

How do we do it?

Blend Ratio Control

Blend Quality Control & Optimization

Conclusions


What is BlendingWhat is BlendingWhat is BlendingWhat is Blending Definition – Uniform mixing of 3 or more different streams to produce a

product with specific properties

Problems:

Flow Constraints

Inventory Constraints

Accuracy & Precision

Poor Mixing (Tank stratification)

Approaches

Sequential Blending

Continuous Inline Blending


History of BlendingHistory of BlendingHistory of BlendingHistory of Blending Prior to 1990

Most blending is sequential

1990 – 2000

Most refinery (gasoline & diesel) blenders upgraded to inline blending

Some chemical blending converted to inline

2000+

Gasoline blenders forced to consider optimization

Most remaining sequential blenders upgrade to inline


Who Uses BlendersWho Uses BlendersWho Uses BlendersWho Uses Blenders Refineries

Gasoline

Diesel

Distillates, Solvents, Fuel Oils

Lube Oils

Asphalt

Chemical Plants

Other

Baby Formula

The blender is the cash register of the refinery


Blender’s Operating ProblemsBlender’s Operating ProblemsBlender’s Operating ProblemsBlender’s Operating Problems Make more grades with more specifications

using many more components

Make the grade on-spec with minimum giveaway, but don’t use too much of any one component

Don’t contaminate any finished product tanks because of bad line-ups, line fill, leaks, etc.

This is a manually intensive operation but doing it right is key to the refinery’s profitability

Increase capacity

Blend Operator


Improved Blending BenefitsImproved Blending BenefitsImproved Blending BenefitsImproved Blending Benefits Reduced “Giveaway” - Produce closer to specification, reduced cost of

producing average blend

Reduced Off-spec and co-mingled material

Reduced Reblending - increased capacity on blenders

Reduced Component and Product Inventory - reduced working capital

Reduced Blend period – Blend is on-spec from start to finish

Estimated benefits $0.05 to $0.10 per barrel of gasoline blended


Sequential Vs. Ratio BlendingSequential Vs. Ratio Blending One Component at a time

Economical Method (Lower Installation Cost)

Line Flush required for proper product quality

Blend Accuracy assured only for completed batches

Large volume blends will require long periods of mixing

In-line or all at same time

Requires meter and valve for each stream

Precise control of blending

Instantaneous alarms on blend available

Blend quality assured on aborted blends


An Integrated Application SolutionAn Integrated Application SolutionAn Integrated Application SolutionAn Integrated Application Solution Consulting

High Performance Field Instrumentation

Control Valves

Flowmeters

On-Line Analyzers

Conventional Analyzers (GC’s, NIR, etc)

Neural Network based inferential sensors

DeltaV Controller w/ Proven Configuration & Algorithms

Blend Quality Control, Optimization & Scheduling

Turnkey Skid

Installation, Start-up & Training

Financing


FC

Component Ratio Control

FI AI

Blend Quality Controller

On-Line Blend Optimization

Ratio Targets

Component Ratio & Quality Targets

Component Qualities & Limits

Desired Rundown Rate & Flow Limits

Blend Planning LP

PricesBatchesTarget RecipesTarget Inventories

Heel InformationComponent Quality & Availability

Blend Start/Stop

FC

FC

FC

DeltaV Blend

DeltaV Blend Control StrategyDeltaV Blend Control StrategyDeltaV Blend Control StrategyDeltaV Blend Control Strategy


Modular DesignModular DesignModular DesignModular Design Continuous or Batch (Tank) In-Line Digital Blending

Recipe Control 30 recipes with 80 configurable parameters each

Start/Hold/Resume/Complete logic

Blend Reports

Component & Additive Ratio Control Pacing (Instantaneous ratio control)

Memory (Total ratio control)

Ramp up/down

Dual Analyzer Trim Control Decoupling


OptionsOptionsOptionsOptions Basic Customization

Add/Delete streams

Custom graphics

Customer Tags

Define I/O

Add/Delete recipes/parameters

Optimization

Low level optimization in Analyzer control strategies

High level optimization integration (OPC)

Master Blend Control

Coordination of multiple blend headers

Integration of header and pipeline control (OM&S)


OptionsOptionsOptionsOptions Simulation

Training

Testing

Custom Interfaces (analyzers, optimizers, etc)

Special Calculations & Functions

Special equipment scheduling and blend line-ups based on production rates, equipment availability, etc

Derived Quality Calculations

Blend grade transition and Tank heel accounting

Tank Farm Management

Component, additive & product compatibility checking

Scheduling and Time-to-completion calculations


Standard DeltaV Blender AlgorithmsStandard DeltaV Blender AlgorithmsStandard DeltaV Blender AlgorithmsStandard DeltaV Blender Algorithms Blend Ratio Control

Streams

12 main component flows

4 additive flows

2 Analyzer trim controllers with decoupling (Optional)

Start/Stop Control

Sequential blender pump and valve line-ups

1 pump, 1 control valve, 1 flow transmitter per stream

Delay Sequences, ramping up/down

Analog & Discrete controls and monitoring of auxiliary equipment

Feed and Product tank level Monitoring

Header pressure & temperature control


Blend Start/Stop ControlBlend Start/Stop ControlBlend Start/Stop ControlBlend Start/Stop Control Startup Sequencing

Load Blend Order to on-line system

Log starting conditions to Blend Order DB

Flush lines

Zero totalizers

Select, Line-up, & Start pumps

Ramp valves open and put FC’s into control

Start ratio control, ramp to target rate

Shutdown Sequencing

Ramp down blend rate to minimum

Place FC’s in manual and close valves

Shutdown pumps

Log final blend results to Blend Order DB


Operator InterfaceOperator InterfaceOperator InterfaceOperator Interface Primary Operating Displays

Blend Setup

Blend Overview Graphic

Component & Additive loops

Analyzer Trim Control

Interlock/Permissive Status Displays

Active/Bypassed

Recipe management Displays

–Load recipes

–Modify recipes

–Save recipes

Support Displays

–Trends

–Alarm management

–Reports


Primary User ViewsPrimary User ViewsPrimary User ViewsPrimary User Views

Blend Control

Recipe Management Blend Setup

Blend Components


FC


FI AI


On-Line Blend Optimization

Ratio Targets

Component Ratio & Quality Targets


Desired Rundown Rate & Flow Limits

Blend Planning LP

PricesBatchesTarget RecipesTarget Inventories

Heel InformationComponent Quality & Availability

Blend Start/Stop

FC

FC

FC

DeltaV Blend

Blend Quality Control & OptimizationBlend Quality Control & OptimizationBlend Quality Control & OptimizationBlend Quality Control & Optimization


US Gasoline Regulatory Time LineUS Gasoline Regulatory Time LineUS Gasoline Regulatory Time LineUS Gasoline Regulatory Time Line

20052004200320022001200019991998199719961995

CARB CBG

EPA RFGPhase ll

EPA LowSulfur Gasoline

EPA RFG Complex Model

CARB MTBE Phase Out

EPA RFG Simple Model

Each New Regulation Means More Complicated Blending

199419931992

Mandated Oxygenates


Complicated Gasoline SpecificationsComplicated Gasoline SpecificationsComplicated Gasoline SpecificationsComplicated Gasoline SpecificationsParameter Current California

SpecificationOctane Per Grade

RVP 7.0 psi max

Sulfur 80 ppm max30 ppm av

T50 220 F max170 F min200 F av

T90 330 F max290 F av

Olefins 10 vol % max4 vol % av

Aromatics 30 vol % max22 vol % av

Oxygen 2.7 wt % max1.8 wt % min

To meet these specifications is a

complicated multivariable control

problem


Longer term coordination

Production Planning

Medium term definition of activities

Production Scheduling

Blend Control

Real-time regulatory control & optimization

Initial ConditionsPlanned production and/or material and resource constraints

Current Status and Performance Targets and recipes

Interactions between Planning, Interactions between Planning, Scheduling, and ControlScheduling, and ControlInteractions between Planning, Interactions between Planning, Scheduling, and ControlScheduling, and Control


So why isn’t recipe control enough for blending?

Production PlanningProduction PlanningProduction PlanningProduction Planning Linear Program (LP)

Run monthly (weekly?) with average product demand

Selects crudes, intermediates, and product purchases for future period (one to three months) to meet demand at maximum profit

Sets average blend recipes for period (assumed component quantities and qualities)


ProblemsProblemsProblemsProblems Simplified LP models

Crude assay database

Component properties are different than that assumed by Planning LP

Crudes are run individually or in blends different from average resulting from the Planning LP

Specific batches of gasoline have to be produced to a specific grade with the stocks on hand

How can we help solve these problems?


Multi-Period Blend Planning LPMulti-Period Blend Planning LPMulti-Period Blend Planning LPMulti-Period Blend Planning LP Multi-period, multi-blend, executed daily or weekly

Linearized blend models (recursive LP)

Determines optimum blends required to meet specific batches of product demands

Integrated with refinery planning LP

Inputs:

Product shipments, prices

Starting inventories

Projected component rates & qualities

Target ending inventories

Outputs:

Finished product batches

Target recipes for each batch

Target ending inventories for each period (products and components)


Traditional Blend Control ArchitectureTraditional Blend Control ArchitectureTraditional Blend Control ArchitectureTraditional Blend Control Architecture

Blend Models

AI

FC FC FC FC FC

AI

MPC Dynamic Models

Ratio Controls(Ramping & Pacing)

Flow Targets

Blend Property Control

Ratio Targets

Blend SchedulingTarget Recipe & Availability

Blend Models

Blend Optimization

Product Quality Targets

Component Flows


Blend Order Management System

Blend Order ManagementBlend Order ManagementBlend Order ManagementBlend Order Management

Blend Order Database

Blend Start/Stop Blend Order Execution

MMI

Blend Reports

Blend Reporting

Blend Optimizer


Blend Order ManagementBlend Order ManagementBlend Order ManagementBlend Order Management User Interface to Blend Order Database

Security functions

User authority changes with order status

Order Entry

Load from past orders

Order Management

Tracks orders through phases

Confirms required data input before changing phases

Approvals

Data validation

Blend Reporting


Blend Order Data ObjectBlend Order Data ObjectBlend Order Data ObjectBlend Order Data Object

Blend Order

• Blend Order ID• Blended Product Name• Blender ID• Order Status• Planned start/end time• Target Quantity• Product Quality Targets & Limits (up to 25 qualities)• Components and target quantities (up to 15 components)• Additives and target quantities (up to 10 additives)• Special instructions• Actual time for each status change• Final blend results• Operator comments


Blend Order PhasesBlend Order PhasesBlend Order PhasesBlend Order Phases

Planned

Approved

Selected

Starting

Active

Stopping

Complete

Hold

Blend Planner in Control

Operator in Control


Offline Blend OptimizationOffline Blend OptimizationOffline Blend OptimizationOffline Blend Optimization File based

Load inputs from stored blend orders

Alternative objective functions

Correct for heel

User can modify all inputs

Inputs:

Target recipe

Desired finished batch size

Finished product quality specs

Component qualities and availability

Heel quantity and qualities

Outputs:

Optimal blend qualities

Optimal recipe

Final batch size


Blend OptimizationBlend OptimizationBlend OptimizationBlend Optimization

• Optimum recipe

• Component usage

• Predicted qualities

Results

RTO+Real-Time

Optimization Engine

Inputs

• Prices

• Target Recipe

• Product Specs

• Component Availability

• Current Heel Quantity & Quality

Objective Function

• Maximize Profit

• Minimize Deviation from Target Recipe

• Min/Max use of Specific Component

Blend Models


• Total Blended Amount

• Predicted Density

• Predicted Qualities

Outputs

Blend ModelsBlend ModelsBlend ModelsBlend Models

• Component Name

• Amount to be blended

• Density

• Qualities

• Component Name


• Density

• Qualities

Components

• Component Name


• Density

• Qualities

Heel

• Product Name

• Amount

• Density

• Qualities

Blend Models

Blend Quality Library

• Density

• Sulfur

• Octane

• ASTM Distillation

• Aromatics

• Olefins

• Benzene

• RVP...


Inputs

• Prices

• Target Recipe

• Product Specs



RTO+Real-Time Optimization Engine

Objective Function

• Maximize Profit



Blend Models

• Optimum recipe

• Component usage


Results

Off-Line Optimizer

Multiple Optimizer ApplicationsMultiple Optimizer ApplicationsMultiple Optimizer ApplicationsMultiple Optimizer Applications

Real-Time Database

Inputs

• Prices

• Target Recipe

• Product Specs




Objective Function

• Maximize Profit



Blend Models

• Optimum recipe

• Component usage


Results

On-Line Optimizer

Blend Order Database

Inputs

• Prices

• Target Recipe

• Product Specs




Objective Function

• Maximize Profit



Blend Models

• Optimum recipe

• Component usage


Results

Blend Quality Control


Online Blend OptimizationOnline Blend OptimizationOnline Blend OptimizationOnline Blend Optimization Executes every 5-15 minutes

Runs for blend orders that are “Active”

Operator selects objective function

Outputs recommended results even in open-loop

Handles reduced degrees of freedom (e.g. 1 or more controllers in Auto)

Accommodates actual component qualities and blend model update from analyzers or lab

Inputs: Automatically loaded from RT database and blend order system

Outputs: Optimal instantaneous quality targets

Optimal recipe

Target batch size


ComponentsProduct

Tankage

TotalBlend

On-Spec

Heel

ComponentsProduct

In-Line

EachPart of Blend

On-Spec

Online AnalyzersBlend Property ControlOnline Blend OptimizationProduct Certification

Two Basic Types of BlendingTwo Basic Types of BlendingTwo Basic Types of BlendingTwo Basic Types of Blending


Accelerated Heel CorrectionAccelerated Heel CorrectionAccelerated Heel CorrectionAccelerated Heel Correction

FinalTarget

Percent of Blend

Octane

0% 100%

Heel

CurrentTank Quality

Blend headertarget adjusted

to meet final target

Current Blend Header Target


Blend ExecutionBlend ExecutionBlend ExecutionBlend Execution

FC


FI AI


Ratio Targets


Desired Rundown Rate, Header Pressure, Flow and

Valve Limits

FC

FC

FC

PI

Product Quality Targets


Blend Quality ControlBlend Quality ControlBlend Quality ControlBlend Quality Control

RTO+Real-Time Optimization

Engine

Blend Models

• Executes 1-2 minutes• Specifications can be:

- Target- Range- Max or min

Real-TimeDatabase

• Current Blend Quality Targets & Specs

• Current Component Ratios

• Blend Quality Analyzers

• Component Limits & Qualities

• Component ratio targets


Objective Function

• Primary: Meet Quality Specs

• Secondary: Minimize Deviation from Current Recipe


SummarySummarySummarySummary Pre-engineered proven application

Reduced risk

Leading Technology hardware platform

Non-proprietary

Longest Life Expectancy

Easily customized and extended

Integrate virtually any feature or function as required

Complete Engineering support from start to finish

Consultation

Main Automation Contractor

The Global Industry Leader


Technical AdvantagesTechnical AdvantagesTechnical AdvantagesTechnical Advantages Integrated suite of applications on DeltaV

Scaleable, Modular

Automated Startup/Shutdown

No need for multivariable control layer

Dynamics are trivial

No step tests required

Incorporates non-linearity

Simplifies architecture

Integrated set of blend models used by all applications

Non-linear

Biased by lab or analyzer data

Incorporate RFG simple and complex models

Integrated blend order management & reports


Moving Forward Moving Forward Moving Forward Moving Forward Complete Blend Optimization Modules

Parallel Effort to Develop Movements & Inventory Solution

Leverage Terminal Automation Solution

Blendingwith DeltaV

Technology

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