dr eduardo gallestey effective energy abb switzerland ... will try to give a very brief introduction...

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Effective Energy Management in the Cement Industry

Dr Eduardo GallesteyABB Switzerland

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CPM Overview

Process Optimization SolutionsPID Loop Performance Monitor

Expert Optimizer for Advanced Process ControlProcess Optimization

Economic Process Optimization

Typical applications in other industries

Knowledge Manager for KPI surveillance

Conclusions

Presenter

Presentation Notes

I will try to give a very brief introduction to cement production in general and then describe the process in Lägerdorf. I will cover the control objectives and the model, some implementation issues and I will elaborate on the results we were able to achieve during commissioning.

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Knowledge Based Solutions for Cement

Process Control, Laboratory, Manual Data

Raw Data

Information

Dispatch Automation Solutions

ERP

MM/SD PP-PI PM

Lab Solutions

Quality

Robotics

Knowledge Manager

Production Information Management

Production Accounting

SAP Integration

Laboratory Information Management


Thermal Energy Electrical Energy

Expert Optimizer

Kiln Optimization

Raw Mix Proportioning

Calciner Optimization

Grinding Optimization

Raw DataSetpoints

Plant Schedule

QM

Information

KBS Knowledge Based Solutions

Presenter

Presentation Notes

Portfolio Overview with the different Product groups Process Control System (not all have an ABB) Expert Optimizer born and based upon the LINKman optimization system, Advant Control System RMP raw mix proportioning Knowledge Manager = Information Management System Real-Time integration of automation, information, and collaborative business systems across the enterprise. Dispatch Automation System The System administers order handling, tracks deliveries, identifies vehicles, instructs and automates loading, controls traffic flow inside the plant, tracks quality data and reports dispatching AutoLab Automated Lab, Robot Economic Process Optimization thanks enterprise systems integration Closing the gap between financial goals and the process. In real time!

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Process Optimization Scope

Process Control and Sensors

MeasurementsActuator Setpoints

Advanced Process Control

Online Multivariable Control

Soft or Virtual Sensors

Plant StatusPlant Schedule



Short Term Production Scheduling

Actuators, Measurements

Loop Parameters

Loop Performance Management

Loop Tuning and Diagnostic

Plant Wide Disturbance Analysis

Presenter

Presentation Notes

Autopilot Analogy: Process Optimization: autopilot for the operator Economic Process Optimization: autopilot for the production manager

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Plant Surveys Prove the Need

Presenter

Presentation Notes

The slide present the results of a study performed by independent research centers on the number of loops with problems Many loops have problems, but only 4.4% of the total (on average) are retuned during one year.

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Loop Performance Manager Benefits

TuningWith LPM Process Engineers (also non expert in control theory) can optimize Loop behaviorBenefits: increase process profit, more stable working condition, more safety operations

AuditingControl Performance Monitoring is non-invasive, simple to perform and very efficientLPM detects automaticallyproblem at the beginning of their occurrencePerformance monitoring nowadays answers the most important questions to help the plant personnel to pinpoint and remove problemsThe right information to the right people

LPM is ABB’s solution for loop analysis and tuning

Presenter

Presentation Notes

Generally process automation is made of by I/O, DCS (hardware+software), measurement devices, actuators. LPM is a new product in automation scenario, having the task to optimize the behavior of the base components of process automation. Tuning With LPM it is easy to reach the optimal Loop behavior. LPM is based on the best tuning procedure as explained at University, but it is designed to be used also by not expert engineers. Tuning is very important and it results in increase profit, in stable working condition, in a more safety operations Auditing LPM auditing is a non-invasive techniques. Process engineers do not have to waste time in looking for problems, but LPM look automatically for them. LPM assist plant personnel to pinpoint problems LPM auditing reports are configurable in order to give scalable information form the not expert user to the best theoretical engineer.

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Expert Optimizer Scope

Process Control and Sensors

Measurements



Actuators Setpoints

Plant StatusPlant Schedule

Process Optimization

Kilns, Calciners

Blending

Flotation

Grinding

Presenter

Presentation Notes


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Estimation of process state variables

(MHE, Fuzzy Logic, Neural Networks)

Pro

cess

Sen

sors

Act

uato

rs

Computation of optimal set-points

(MPC, Fuzzy Logic)

Preprocessing of measurements

Post-processing of set-points

State estimates

Measurements

Set-points

(800

xA) C

ontro

l Pla

tform

Expert Optimizer – APC Strategy

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Graphical Model Development

drag & drop

HMI

Real-timeCalculation

Engine

Plant model

Libraries/Palette

State update

Control action

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Expert OptimizerThin client based graphical engineering and

programming environment Controls and optimizes your process by using

advanced control techniques and deep process knowledge

TechnologyModel Predictive ControlFuzzy Logic, Neural Networks

Typical BenefitsProcess variability reduced: 20%-50%Energy efficiency increased: 3%-5%Environmental compliance securedQuality requirements fulfilledManage operational complexity!

Installed BaseMore than 150 systems worldwideMore than 300 applications since mid 1990s More than 190 kilns, 90 mills, 40 ore blending

Expert Optimizer Solutions

Presenter

Presentation Notes


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How is it done? – “Adaptive” Heat and Mass Balance

Counter CurrentHeat/Mass Exchanger

Energy/Mass Source

Energy/Mass In

Energy/Mass OutEnergy/Mass In

Energy/Mass Out

Energy/MassSink

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Expert Optimizer for Calciners and Kilns

Presenter

Presentation Notes

Raw materials are preheated and then fed into a large rotating pipe of about 50mts length and 3-5 mts diameter. The pipe (called kiln) has a slope that makes the material to flow downhill. At the kiln lowest point there is a burner, which ensures acts as energy source. The material goes through a number of endothermic and exothermic chemical reactions as it flows through the kiln temperature profile. One controls kiln rotational speed, fresh feed, fuel and air supply in order to reach good product (clinker) quality at the highest production rate. Occasionally there are calcination stages before the kiln, which have their own burners and that thus must be controlled by their own. Intensive usage of alternative fuels (uncertainty in heating value and chemical composition) makes controlling these systems a very hard task.

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Kiln Model: Actuators and Compartments

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Cost Functions

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Results

-60 -40 -20 0 20 40 60 80 1000

2

4

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Temperature deviation from setpoint [°C]

Frac

tion

of to

tal m

easu

rem

ents

[%]

EO activeEO inactive

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Expert Optimizer Solutions in Cement

Raw Mix PreparationAdjusting additives for raw mix quality

Precalciner ControlFuel and Fan are controller toKeep temperature and O2 levels

Kiln ControlControlling fan, fuel and feed for stable kiln conditions

Mill ControlControlling fresh feed and separator speed to stabilize the mill

Mix Bed BlendingMixing the quarry zones for lower variability

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Expert Optimizer for Ore Concentrators

SAG and Ball Mill ControlControlling speed, feed, water and feed

Goal: stable mill conditions, lower energy consumption, more production

Flotation Circuit ControlControlling levels, air, and chemicals addition

Goal: better recovery at given grade

Presenter

Presentation Notes

Raw materials comes from different sources (quarries, power generation fly ash, etc, steel scrap) and is not homogeneous. In the cement process (but also in other industries like Alumina where different bauxites are mixed) the plant feed must be a mix of oxides in very precise proportions. The control problem is to adjust the feeder settings as to minimize feed chemistry deviations from targets set at the homogenizing silo, at the lowest possible raw materials cost. The problem is complex due to the large mass flow disturbances, long time delays, different grindabilities, etc.

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Flotation - Results

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Economic Process Optimization Real-Time integration of automation, information, and collaborative business systems across the enterprise.

Closing the gapbetween financial goals and the

process. In real time!

Economic Process Optimization thanks enterprise systems integration

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Electrical Energy Management

GoalsHigh production at lowest possible energy bill Contractual and equipment constraints Scheduling of big consumers

Problem CharacteristicsHigh power consumptionReaction to deviations from original plan Variable/complex electricity contractsDifferent consumers, different characteristicsNumerous productsSilos and conveyor belt system

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Presenter

Presentation Notes

Mills have to be scheduled regarding product type and production time in order to satisfy the product demands at the lowest electricity cost. Additional contractual constraints must be considered like maximum amount of available power at a given time, mill availability, etc. Planning horizon a few days ahead in an hour resolution.

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Electrical Energy Management ModulePower cost down by 2-3%Automatic rescheduling in case of unexpected eventsStrict contractual and equipment constraint satisfaction

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Applications done by ABB: Water SupplyWater Supply

Generation of schedules High pressure pumpsDelivery of ground water Purchase of ground water

DataWater demandReservoir levelsTransport timesEnergy prices

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Applications done by ABB: Steam SupplyIndustrial Steam Supply

ApplicationsAlumina plantsPulp and Paper PlantSteel

Control of boiler pressure SP Valves SPBuy and sell decisions

DataSteam demand (variable!)Node pressuresBoiler efficienciesEnergy prices

APC OFF APC ON

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Applications done by ABB: Pulp and PaperCustomer - Tiger Mill Fiber Line

Maximizing throughput at the right quality with the lowest cost

Result: on-line production planningManipulated variable optimization

Production prediction for 3 days

Problem sizeNumber of process units: 7

Number of buffers: 8

Fiberline model: 422 Variables

Number of EO manipulated variable: 16

Number of EO controlled variables: 8

TechnologyNonlinear Model Predictive Control

Modelica Models

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Knowledge Manager: Tracks Energy Consumption

Thermal Energy KPIsSpecific energy consumption per productThe rate of substitution of traditional fuels with alternative fuelsUnderstanding the economic impact of different fuel mixes

Electrical Energy KPIsSpecific energy consumption, material preparation, productsThe specific energy consumption per equipment and productUnderstand the impact of plant scheduling

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Effective Energy Management

Electrical Energy Savings by variable speed drive solutions Thermal Energy Savings by blending and kiln control systemsElectrical Energy Savings by grinding control systems

Thermal Energy Cost Savings by fuel mix optimizationElectrical Energy Cost Savings by mill schedule optimizationEnergy KPI Supervision with Knowledge Manager

Reduce your energy consumptionReduce your production costs

Gain environmental sustainability

Presenter

Presentation Notes

I summerize my presentation as followings: You can improve your energy management as follows Electrical Energy savings by using variable speed drive solutions Thermal Energy savings by using EO as Kiln Control system Thermal Energy and AF cost savings by using EO for fuel mix optimization Electrical Energy cost savings by using the mill schedule optimization I hope you come to the same conclusion that there is a set of tools and solutions available to Reduce your energy consumption Reduce your production costs Gain environmental sustainability

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OutlookAPC portfolio selected Winner of the Global Fuels Conference Award for “most innovative technology for electrical energy savings”

Selected by conference participants

Proof of customer value

Check for new solutions in conjunction with SOLBAS technology

dr eduardo gallestey effective energy abb switzerland ... will try to give a very brief introduction...

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