From Steady-State to Dynamic Simulation: Benefits and Use … AWC NA Presentations Day... · 2019....

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From Steady-State to Dynamic Simulation: Benefits and Use Cases of Modern Process Simulation Tools

Aveva World Conference North America 2019, Andrea Milioni (BASF SE), Chloe Smith (AVEVA)

Internal

14.11.20192

• Introduction of the APC Team and challenges of the digital transformation

Advanced Process Control at BASF SE

• Use of Steady-State/Dynamic Models in different phases

Process Simulation During the Plant Lifecycle

• Use Cases of Dynamic Simulation by APC

Dynamic Simulation Using SimCentral

• Benefits from the use of a modern Process Simulator

Summary

Structure of the presentation

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Summary


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APC for continuous processes

• Multivariable Predictive Control (MPC)

• Real-time Optimization (RTO)

• Operator Training Simulators (OTS)

• Scenario Simulation

Advanced Data Analytics

• Online-monitoring and optimization

with empirical and grey-box models

• Offline Data-Analysis

APC for batch processes

• Multivariable monitoring and control

• Recipe Optimization

• Sequence optimization

Base Layer Control

• Controller Performance Management

• Advanced Regulatory Control

• Sequence/Procedure Automation

• Softsensors / Inferentials

• Process Analytical Technology

Innovation and Strategic Activities

Advanced Process Control (APC) at BASF SE

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Plant

Automation

actuatorssensors

Engineering Documentation and Modelling

RTO

Manual interface, characteristic for “Industry 3.0”

Research

Development

Engineering

ConstructionProcess Simulation

Construction

Design

Real World

Propan

Benzol

K200W205

W210

P205

B215

B100

W100

C100

K300

W310

V300

P315

B315

W305

P305P010

AbgasAbgas

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Diisopropyl- benzol

Cumol

P215

Engineering doc.

Dynamic Model

Challenges of the Digital Transformation

Status Quo:

often modelling activities from

“scratch”

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Plant

Automation

actuatorssensors

Digital Twin

RTO

Research

Development

Engineering


Construction

Design

Real World

Propan

Benzol

K200W205

W210

P205

B215

B100

W100

C100

K300

W310

V300

P315

B315

W305

P305P010

AbgasAbgas

Abgas

Diisopropyl- benzol

Cumol

P215

Engineering doc.

Dynamic Model

Digital Twin of Process BehaviorIntegrated Digital Technology for Engineering, Operation and Maintenance

Vision: Manual interfaces are eliminated

→ All islands are connected (seamless & bidirectional)

Modelling integration in lifecycle

(“Digital Twin”)

RTO

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Plant

Automation

actuatorssensors

Digital Twin

Research

Development

Engineering


Construction

Design

Real World

Propan

Benzol

K200W205

W210

P205

B215

B100

W100

C100

K300

W310

V300

P315

B315

W305

P305P010

AbgasAbgas

Abgas

Diisopropyl- benzol

Cumol

P215

Dynamic Model

Digital Twin of Process BehaviorIntegrated Digital Technology for Engineering, Operation and Maintenance

Vision: Manual interfaces are eliminated

→ All islands are connected (seamless & bidirectional)

Modelling integration in lifecycle

(“Digital Twin”)

Process Simulation

plays a crucial role to enable the use of an integrated Digital

Technology

RTO

Engineering doc.

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Summary


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ProcessSimulation

Initial Design

Initial Design – Process Engineering

(Steady-State Model)

• Conceptual Design

• Steady-State Simulation (H&M

Balance)

• Equipment Design

• Steady-State Detailed Simulation

Process Simulation during the plant Lifecycle

Initial DesignControl Concept

SelectionOperabilityAnalysis Operators Training Simulator (OTS)

Engineering & Construction Phase Operations Phase

Operations Support

Real Time Optimization (RTO)

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Operations Support


ProcessSimulation

Initial Design

Control Concept Selection

Control Concept Selection – Control

Engineering

• Overall Control Scheme

Development

• Evaluation of the Optimal Set-point

• Open Loop Step-test

• Closed Loop Step-test and

Controllers Tuning

Steady-State

Simulation

Dynamic

Simulation

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Operations Support


ProcessSimulation

Initial Design


OperabilityAnalysis

Operability Analysis

• Scenario Simulation: Changes in

Process Operating Conditions

• Disturbance rejection

• Start-up and Shutdown

• Early Detection of Operational

Challenges and Bottlenecks

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ProcessSimulation

Initial Design


OperabilityAnalysis

OperationsSupport

Operations Support

• Control Concept

Evaluation/Improvement

• What if? Analysis

• Troubleshooting

• Incident Scenario Reproduction

Operations Support

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Operations Support


ProcessSimulation

Initial Design


OperabilityAnalysis

OperationsSupport

OTS

Operators Training Simulator

• Control Room Operator Training

• Simulation/Validation of the main

operating procedures

• Validating DCS Control and Logic

Checkout

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Operations Support


ProcessSimulation

Initial Design

Control Concept

Evaluation

OperabilityAnalysis

OperationsSupport

OTS

RTO

Real Time Optimization (Online)

• Frequent changes to the plant (e.g.

feed composition)

• Steady-State Set-point Optimization

in presence of unconstraint non-linear optimum

• Data reconciliation to estimate

unmeasured process parameters

• Model can still be used for offline

analyses/studies

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Operations Support


ProcessSimulation

Initial Design

ControlConcept

Evaluation

OperabilityAnalysis

OperationsSupport

OTS

RTO

Main challenges:

• From Steady-State to Dynamic models

• Reuse of Models

Status Quo:

• Process Simulation is„standard“ only for Initial Design (Steady State)

• Dynamic Simulation limited to specific cases due to high

engineering effort (non-optimal tools)

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Operations Support


ProcessSimulation

Initial Design

ControlConcept

Evaluation

OperabilityAnalysis

OperationsSupport

OTS

RTO

Simulation Tool Requirements

• Easy to use (even for non expert

users)

• Fluid transition between Steady-State

and Dynamics in one Simulation tool

• Open Model Equations (easy to

identify the important parameters)

• Support of the complete lifecycle

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Summary


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Project 1: green field project, steady state simulation already present with “in -house” process simulation tool

◼ Main goal: evaluation of different control schemes with different dynamic scenarios (e.g. compositional change, flowrate change, disturbances etc.)

Dynamic Simulation using SimCentralUse Cases of Dynamic Simulation by APC

Feed

Distillate

Bottom product

Steam

Condensate

Of f gas

Cooling Water

Reboiler

Condenser

LIC

-

FIC

-

LIC

-

K1

FIC

-

PIC

-

TIC

-

Off gas

Condenser

Feed from Hydrogenation

Bottom

FIC

-

TIC

-

Nitrogen

Distillate

Condensate

Steam

Reboiler

Steady State model

(in-house tool)

Steady State model

(SimCentral)

Dynamic model

(SimCentral)

Control Concept Evaluation

Flowsheet Model in SimCentralControl concept scheme

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LIC

-

FIC

-

LIC

-

K1

FIC

-

PIC

-

TIC

-

Off gas

Condenser


Bottom

FIC

-

TIC

-

Nitrogen

Distillate

Condensate

Steam

Reboiler

Feed composition change: open loop response



Steady State model

(in-house tool)

Steady State model

(SimCentral)

Dynamic model

(SimCentral)


Control concept scheme

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LIC

-

FIC

-

LIC

-

K1

FIC

-

PIC

-

TIC

-

Off gas

Condenser


Bottom

FIC

-

TIC

-

Nitrogen

Distillate

Condensate

Steam

Reboiler

AC

Feed composition change: distillate online analyzer controller response



Steady State model

(in-house tool)

Steady State model

(SimCentral)

Dynamic model

(SimCentral)



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LIC

-

FIC

-

LIC

-

K1

FIC

-

PIC

-

TIC

-

Off gas

Condenser


Bottom

FIC

-

TIC

-

Nitrogen

Distillate

Condensate

Steam

Reboiler

AC

AC

Feed composition change: inlet feed online analyzer controller response



Steady State model

(in-house tool)

Steady State model

(SimCentral)

Dynamic model

(SimCentral)



Internal

Steady State model

(SimCentral)

Dynamic model

(SimCentral)

Model Validation

(PIMS)

Scenario Reproduction

Control Loop Evaluation

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Project 2: dynamic simulation of an existing Plant

▪ Main goal: to reproduce a Plant upset scenario in order to better identify the root causes / control loops evaluation


Flowsheet Model in SimCentralControl concept scheme

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Plant upset scenario reproduction

Steady State model

(SimCentral)

Dynamic model

(SimCentral)

Model Validation

(PIMS)





Real Data from PIMS

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Subsequent start-up reproduction

Steady State model

(SimCentral)

Dynamic model

(SimCentral)

Model Validation

(PIMS)






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Operations Support


ProcessSimulation

Initial Design

Control Concept

Evaluation

OperabilityAnalysis

OperationsSupport

OTS

RTO

Positive elements from the use of

SimCentral

✓ Easy to use (even for non expert users)

✓ Fluid transition between Steady-State and Dynamics

✓ Open Model Equations (easy to identify the important parameters)

✓ Robust and efficient Equation Oriented solver

✓ “Library” approach

✓ Interactive simulation with visualization of the results as “real time” data

SimCentral is an enabler to

address use cases for dynamic simulation

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Summary


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◼ Digital transformation: demand for models will increase

◼ Integrated Steady-State and Dynamic Simulation can enable the use of models during the whole plant Lifecycle

◼ Main benefits from a modern Process Simulation tool:

➢ Cross-functionality use of models: integrate competencies and enhance collaboration

➢ Model-based methods accessible for other domain experts (e.g. APC)

➢ Improvement of communication between technical departments and production management → generate trust into simulation models

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Summary

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From Steady-State to Dynamic Simulation: Benefits and Use … AWC NA Presentations Day... · 2019....

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