Power Plants and Boilers Models for Operator Training ... · Power Plant and Boiler Models for...

Power Plant and Boiler Models for Operator Training Simulators

P. Neuman

NEUREG, Plc., 193 00 Prague, Czech Republic

(Tel: +420-777-648-906; e-mail: [email protected]).

Abstract: A specific Operator Training Simulator for Power Plant’s Operational Staff (Boilermen,

Turbine Drivers, Engineers) is described in detail. The objective Power Plants Dynamic Models for

operator´s training in Czech Republic are used also in the first standard utilized Operator Training

Simulator (OTS) of coal-fired Czech Power Plants Opatovice. The Power Plants consist of six boilers

with steam capacity 250 t/h of each, common steam collector and of six turbogenerators with power 60

MWe each. Total heat capacity is 800 MWh. The process model is developed on the basis of

mathematical-physical analysis (”first principles” method) of the individual technological subsystems.

Dynamic model of the OTS consists of complex thermal power unit, i.e. of two steam boilers working

into one section of the common steam collector and of two steam turbines-generators. The process model

describes the standard and abnormal operation regimes in the range of 0 % - 100 % of Maximum

Continuous Rate, with implementation of individual disturbances by the instructor. The own-built library

called “EnergySIM” was developed. on the basis of MATLAB-SIMULINK packages.

Keywords: Power Plants, Steam Boilers, Pulverized Boiler, Fluidized Bed Boiler, Dynamic models,

Engineering and Operator Training Simulators

1. INTRODUCTION

The Technology Object Oriented Modeling describes each

part of the model as an object with certain behaviour

(Maffezzoni, 1992). To comply with this concept, an own-

built library, called “EnergySIM”, has been partially

developed (based on MATLAB - SIMULINK). The main

assets of „EnergySIM“ are the following ones:

- It is a modular system where the final model is obtained by

assembling instances of general-purpose models taken from

the library.

- The system is open in the sense, a user is free to expand the

default libraries with her own models.

- The library “EnergySIM” includes the models and modules

of many typical components that can be found in

thermoelectric power plants.

2. SIMULATOR CONFIGURATION

The OTS is of “partially stimulated type” and it is created

from modules of own NEUREG library called “EnergySIM”.

This library could be used for modelling all types of power

plants (Conventional Power Plants, Combined Cycle Power

Plants, etc.) based on the following modules: Drum Boilers,

Steam Turbines, Superheaters, Reheaters, Once-Through

Boilers, Fluidized Bed Boilers and Gas Turbines. The

“distributed control system” is emulated in MATLAB-

SIMULINK (Neuman, et al., 2003), too.

The basic information for creating structure of an OTS is

represented in a process diagram. It is demonstrated on an

example of a feeding water subsystem. This part is depicted

in Fig.1, that represents the Process Instrumentation Diagram

(P&ID). Other subsystems modelled in the same way are the

following ones: Feeding Water, Air Supply Loop, Coal

Feeders & Mills, Flue Gas Loop, Super Heaters, Common

Steam Collector, Steam Turbines & Generators (Neuman, et

al., 2002). In the P&ID, all the objects are depicted that are

either manipulated by control or where some measurement is

performed. It is typical for an OTS that all the information,

available in monitoring and control system, must be present

also in the models used in OTS. It is in this case only, that the

operator can manipulate all the valves, fans, switches etc. as

if he would do it in a real plant. This specific requirement

brings a need to have technology object-oriented models of

all such elements, that can be seen in the process diagram

(Neuman, et al., 2004).

3. MODELING OF SUBSYSTEMS

The principles for modelling are described in reference

(Ordys, et al.,1994). According to these principles, the library

“EnergySIM” includes the following modules: Gas and

Steam Turbine Units, Two Phase Units (HRSG, boiler-

evaporator, condenser, deaerator tank), Single Phase Units

(economiser, superheater), special Drum and Once-through

Evaporator Units, Water Storage, Media Flow Resistance

Unit, Heat Flow Resistance Unit, Burner Units, Combustion

Chamber Units, etc. Each module is derived from the three

conservation physical laws (“first principles”) and it needs a

few parameters. As the description of all modules would be

out of scope of this paper, only some basic modules are

shortly described.

3.1 Feeding Water Model

Preprints of the 18th IFAC World CongressMilano (Italy) August 28 - September 2, 2011

Copyright by theInternational Federation of Automatic Control (IFAC)

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The feeding water scheme, depicted in Fig.1, correspons to

P&ID diagram in Fig.2. and models the following processes:

Water is supplied through a feeding pump, which has been

modelled by its flow/pressure characteristics. The water is

pre-heated in two high pressure heaters (VTO) in series

using steam as heating medium. Cold water can also be

mixed in parallel with hot water from VTO. Then, the water

is passed through series of two primary (EKO I) and four

secondary economizers (EKO II). As the secondary

economizers are of special construction, they must be

modelled in two parts. Heated water after primary

economizer is also supplied as spray to the super heaters to

control the steam temperature. The pressurized water is

nearly at the saturation point and then, it is supplied to a

drum boiler where it is evaporated to steam. The evaporating

processes in the drum are difficult to describe and therefore,

three alternative models are offered for Engineering

Simulators (Neuman, 1997) or Operator Training

Simulators:1 - a simple second order model (without “swell

and shrink” phenomenon), 2 - a modified fourth order

“Aström” model (Astrom and Bell 2000), keeping the

dynamic behaviour of the drum boiler sufficiently simple for

modelling, but with reasonable precision, or 3 - a higher

order model necessary for realistic modeling of particular

operating conditions, like low-loads, fast start-up, or

abnormal shutdown (Neuman, et al., 2002).

The feeding water flow rate to the drum is controlled by the

feeding valve (NV) according to the water level in the drum

boiler, feeding water flow and steam flow from the boiler,

and pressure difference across is the feeding valve is

maintained by a differential valve (DV) – In Fig.1, it is

situated in the blocks V3_DV_NV1, V3_DV_NV2”,

whereas in Fig.2, these valves V01A / AG61,AG60 are

behind VTO II in series with NV. All the other valves realise

the switching functionality necessary during the swaping

between hot and cold-water branches. They are modelled but

not mentioned in this description. The P&ID diagram of this

feeding water subsystem is depicted in Fig.2, where each type

of described elements has its own object oriented block

realization.

Fig.1 SIMULINK scheme of the feeding water subsystem

(Drum Boiler)

Fig.2. The original P&ID Diagram Feeding Water


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3.2 Steam Turbine Model

3.2.1 Simple IEEE Steam Turbine Model

The simple IEEE dynamic model of steam turbine, presented

in Fig.3, is derived from the fact (see Eq. (1) that power of

turbine NT depends generally on product of three variables:

steam flow rate MT , (enthalpy) isentropic heat gradient H0

and internal thermodynamic efficiency ηTD . Those models

are used in Power Systems Model, e.g., in so called Network

Simulators (Neuman, et al., 1999).

NT = MT . H0 . ηTD (1)

Variable H0 depends on steam parameters (temperature,

pressure). In IEEE model, steam is supposed with constant

parameters (i.e. constant enthalpy). This approach

corresponds to standard operation of the block at nominal

parameters. However, for OTS purposes , this assumption is

completely unrealistic for modelling the power turbine due to

large changes in power during the start up and shutdown.

Variable ηTD depends on turbine speed in two ways: a) partly

through the friction and ventilation losses, b) partly through

the differences in speed triangle which describes steam inlet

into the blades of turbine. The effect caused by suggested

small changes of turbine speed in the range of +10 %

(enough for IEEE engineers) is also neglected, because

successive changes in efficiency are very small, practically

in unit percentage.

Dynamics of steam during flow through the individual parts

of turbine is described on the basis of steam expansion in

closed volumes. This dynamics is modelled as 1-st order

transfer functions. Time constants depend on volume of

relevant part of turbine, initial value of steam pressure ,

steam flow rate and also there exists a dependence of

specific steam volume on steam pressure. It means that time

constants are not constants any longer but that they depend

on the “working point” and its changing with the load.

However, these time constants are constant in the IEEE

models. The coefficients kLP and kHP respect the ratio of

energy production in the Lowpressure Part (LP) and

Highpressure Part (HP) of turbine.

Governor Output

Turbine Output

Mid and Lowpressure Part

Highpressure Part

R T

+ V T

1

v min

v max

-

p

1

G min

G max

Control Valves

Intercept Valves

+ T p 1

1

HP

k HP

+ T p 1 LP

k LP

P T M T

IV k

0

1

IV T

1

v Imin

v Imax

+ -

Fast Valving

p

1

0

1

v CStop

v IStop

T

1

R

+

+

+

N T

Reheater

BOILER

Fig.3. Block scheme of the simple IEEE steam turbine

model

The IEEE steam turbine model shows the turbine with steam

reheater, which is usually used for turbines in Czech

Republic. These turbines have more parts and the steam flow

rate is coming back into boiler reheater after expansion in HP

parts. For calculation of IEEE turbine dynamics, the above

mentioned simplifications are used, which are suitable only

for RT model of interconnected power systems, but not

acceptable for power unit training simulator. Therefore, the

specific realistic model of condensing steam turbines without

reheaters was developed.

3.2.2 The realistic Steam Turbine Model

Generally, in the case of the steam turbine, the mechanical

power is obtained by removing energy from the superheated

steam stream by expanding it to a lower pressure. In our case

steam enters the Highpressure Part HP Lowpressure Part LP

chest via the main admission control valves. After passing

through the HP stage the steam passes through the Low

Pressure (LP) stage before returning to the condenser.The

main modelling assumptions are as follows:

- Superheated steam is treated as an ideal gas.

- HP, LP, turbine stages are converted to equivalent nozzles

through which one-dimensional uniform polytropic steam

expansion takes place. - Energy storage volumes are lumped

- Inlet kinetic energy of steam to each stage can be neglected.

- Mass flow dynamics between input and output is modelled

as a 1st order lag.

The steam turbine model is sub-divided into two sections. A

section is defined here as consisting of a lumped steam

storage volume carrying dynamics, followed by a complete

turbine stage that is modelled by steady-state relationships.

Note that a complete turbine stage (HP, LP) comprises of a

number of impulse and/or reaction stages in series. High

pressure section, as an example, is described by following

equations:

- three differential equations of steam mass balance – eq. (2),

section mass flow dynamics, and heat balance – eq. (3),

- twelve algebraic equations, e.g. nozzle equation solved for

rate of nozzle pressure drop rhp. – eq. (5). There are five

inputs, seven parameters, one constant, and five outputs.

The following equations (2), (3), (4), (5), are selected as an

example from the whole complex set of equations. These

equations are implemented in SIMULINK (Neuman, et al.,

2003).

Mass balance equation has form:

ohpi wwdt

dV 0 (2)

Equation of conservation of energy (heat balance) has form:

000 hwhwhdt

dV ohpii (3)

Equation of perfect gas has form:

000

00

TRp

Tc

hhT in

p

in

(4)

Nozzle equation has form:


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m

m

pA

wrr

hphp

ohpm

m

hpm

hp 2

1

00

212

(5)

where:

V - chest storage volume, 0T - outlet steam temperature,

pc .- specific heat in constant pressure, 0 - outlet steam

density from the chest, 0h - outlet steam specific enthalpy

(from the steam chest), ih - inlet steam specific enthalpy,

iw - inlet steam flow, ohpw - outlet steam flow, hpr - ratio

of nozzle pressure drop, m - exponent of polytropic curve

for superheated steam, n - polytrope exponent for wet steam

3.3 Heat Exchanger Models

It is documented on principle scheme of general heat

exchanger– see Fig.4. The more detailed description of I/O

specification and parametrization is available in commercial

documents and customer manuals (Neuman, et al., 2004).

Chamber 1 RMF

RMF

RHF

in

in out

out

Chamber 2

Fig.4. Principle scheme of Heat Exchanger layout (where:

HF stands for heat flow, MF is mass flow)

The principles and parameters of economiser modules ECO

are following ones: V is volume, m is mass, Ai is cross

sectional area, Cp is specific heat, “alpha_i” and “alpha_o”,

are coefficients and variables of heat transfer calculation - see

Economizer menu, in Fig.5. There can be also seen the

following parameters: ho is enthalpy, Tm is mean

temperature of wall, T is temperature of wall surface.

The final goal is to develop reasonably complex non-linear

models that capture the key dynamical properties over a wide

operation range. Building a model from this library is very

easy and during modelling one can feel that he is constructing

an AutoCAD drawing of the model. In this way, every one is

able to build a model of his own choice very easily and

without deep knowledge of modelling. The modelling of all

the modules is based on the three-conservation laws, Mass,

Energy and Momentum balances (Dolezal and Varcop 1970).

To make the modelling a user-friendly process, a dialogue

box, as shown in Fig.5, will appear when user clicks the

mouse over the model (object). Initial conditions and

parameters of the block can be entered through this display

window. The chambers are divided mainly in two groups.

The first one in which the “water and steam flows”, and the

second one in which “air and flue gases flow”. Data in form

of a vector of ten variables are obtained from each unit; in

which first six (flow, enthalpy, pressure, temperature, quality,

total head) are common to all chambers and other four

depend on chamber (e.g. in boiler they are level, volume of

water, volume of steam and steam quality at the riser exit). In

case of flue gases, data in form of a vector of five variables

(flow, enthalpy, pressure, temperature, heat) are obtained.

Fig.5. Economizer menu for parameter setting

The primary unit of the library is given by the name unit

specified by the name which is used for its invocation and

has its corresponding menu e.g. Economiser in Fig.5

For example, boiler chamber, valve, pump etc. are units.

Units are combined in a sub-model. E.g. feeding water,

where there is a heat exchanger as shown in Fig.4, is a sub-

model. In chamber 1, water enters and leaves as steam

passing through a flow resistance, while in chamber 2, hot

flow gases enter and leave with heat loss through a flow

resistance. These two chambers are connected through a heat

resistance. Similarly, ECO is a “user application” of the

submodel “heat exchanger”.

4. EMULATION OF CONVENTIONAL BASIC LEVEL

CONTROL

The Distributed Control System (DCS) consists of manual

control from operator control panel (MOSAIC), control from

SCADA/HMI mimics and control from standard industrial

PID controllers. An example of the fully emulation scheme of

real DCS can be seen in Fig.6, where two cascade PID

controllers (blocks REG.1, REG.2) and logic control modules

(eg. Blocks 1.2, 1.3, 5.3) for level control in the drum have

been modelled (emulated) in MATLAB-SIMULINK.

Switching between manual control and PID control is given

either by operator (from SCADA/HMI or from MOSAIC) or

by a protection logic, where e.g. Feeding Water Valve (NV)

can be in PID control mode only when Difference Pressure

Valve (DV) is also in PID control mode – see Fig.2, Fig.1.

This switching is shown on bottom half of the Fig.6.


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Fig.6. Control system for water level control in drum boiler

All the PID controllers (blocks REG.1, REG.2 – in Fig.6) are

realized by Z-tranformation of the continuous PID controller.

Equation for the continuous PID is following one:

ddeT

r

dt

tdeTrtertu

I

D0

00 (6)

It is tranformed by trapezoidal method into discrete version

of controller (Balate, 2004):

0

1

1

2

2 qzqzqu (7)

where T is the sampling period

I

D

I

D

D

T

TrTTrrq

T

TrTTrrq

TTrq

0

000

0

001

02

5.0/

5.0/2

/

(8)

Dynamic simulation model can also be utilized in designing

the control system for operated processes. However the

control scheme and control algorithm have to be the same as

in real operation distributed control system, because OTS

must be fully realistic.

The development and verification of some advanced control

algorithms for the engineering dynamic model is also

possible but only in the frame of Engineering Simulators.

E.g., the extended Luenberger’s state controller-observer of

superheated steam temperature was developed for coal

pulverized steam boiler of Power Plant Shen Tou 500 MW,

in District Shan Si, China (Neuman, et al., 1988).

5. SIMULATION AND OPERATIONAL RESULTS

The OTS simulation transients displayed in SIMULINK and

SCADA/HMI are in following figures 7, 8, 9, 10.

Fig.7. Drum boiler water level transient in SIMULINK (time

scaling: 1 unit = 0,1 sec)

Fig.8. Drum water level transient in SCADA/HMI - OTS

The operational transients from real time process control is

very similar to the above mentioned simulation transients

(see Fig. 11), only a little slower. It is in convenience with

declared accuracy of a dynamic model of power unit.

E.g. , when controlling the level in the drum, the change of

steady state value dHdes = 2 cm has the simulated transition

time Tpr = 120 s, with change trend dH = 1 cm/13 s. The

values from the real process are Tprp = 160 s, and change

trend dHp = 1 cm/18 s.


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The similar simulation accuracy is achieved for controlling

the temperature of overheated steam (the simulated change

trend is dT = 1 °C/10 s), for the change of steady state value

dTdes = 5 °C. The same variable measured on the real process

is dTp = 1 °C/16 s.

Fig.9. Steam temperature transient in SIMULINK

Fig.10. Steam temperature transient in SCADA/HMI - OTS

Fig.11. Drum water level transient in real process

6. CONCLUSIONS

Operator Training Simulators require the high realism of the

models. Therefore the parametrization and verification of

model´s features were performed only with participation of

the very experienced operators of Czech Power Plants

Opatovice.

In the contemporary performed work, the circulating

fluidized bed (CFB) boiler model is developed (Majanne and

Köykkä, 2009). The simulator is also built with MATLAB

SIMULINK software. The model is also based on the mass,

energy, and momentum balances together with physical

behaviour of heat transfer, reaction kinetics etc. Dynamic

modelling and simulations have been used to examine the

operation of power plant with circulating fluidized bed boiler.

Hitherto simulations give a clear representation of CFB.

One of the future research subjects in this field is the

advanced intelligent control system design (Vasek, et al.,

2010) for a pilot operator training simulator OTS with

circulating FBB, which is in preparation process.

REFERENCES

Astrom, K. J. and Bell, R. D. (2000). Drum-boiler dynamics.

Automatica, Vol. 36, pp. 363 – 378.

Balate, J. (2004 ). Automatic Control (in Czech). 2nd

edition

BEN, Praha.

Dolezal, R. and Varcop, L. (1970). Process Dynamics –

Automatic Control of Steam Generation Plant.

Elsevier, London.

Maffezzoni, C. (1992). Issues in modeling and simulation of

power plants. In Proceedings of IFAC symposium

oncontrol of power plants and power systems, Vol. 1.,

pp 19-27, Munchen, Germany.

Majanne, Y. and Köykkä, P. (2009). Dynamic Model of a

Circulating Fluidized Bed Boiler. In Proceedings of

IFAC Symposium on Power Plants and Power

Systems Control, Tampere, Finland.

Neuman, P., Stecha, J. and Havlena, V. (1988), State

controller with observer design for superheater

temperature control. Preprints of 4th

IFAC Symposium

on Computer Aided Design in Control Systems

CADCS´88, Beijing, China.

Neuman, P. (1997), Engineering Simulator for Fossil Power

Plant. Preprint IFAC/CIGRE Symp. on Control of

Power Systems and Power Plants, Beijing, China.

Neuman, P., Máslo, K., Šulc, B. and Jarolímek, A. (1999).

Power System and Power Plant Dynamic Simulation.

In: Preprints of 14 th

IFAC World Congress, Volume

O, paper O-7c-04-02, pp. 179-184, Beijing.

Neuman, P., Pokorny, M., Varcop, L., Weiglhofer, W. and

Javed A.J. (2002). Engineering and Operator Training

Simulator of Coal-fired Steam Boiler. Proc. 10th Int.

Conference MATLAB´02, Prague, Czech Republic.

Neuman, P., Pokorny, M., Varcop, L. and Weiglhofer, W.

(2003). Operator Training Simulator of Coal-fired

Power and Heating Plants. Proc. 11th Int. Conference

MATLAB´03, Prague, Czech Republic.

Neuman, P., Pokorny, M., Varcop, L. and Weiglhofer, W.

(2004). Operator Training and Engineering Simulator

of Fossil-fired Power and Heating Plants. Proc. 6th

Int. Conference CONTROL OF POWER

SYSTEMS´04, Strbske Pleso, Slovak Republic.

Vasek, V., Neuman, P., Balate, J. and Vargovcik, L. (2010).

Intelligent Control System for Municipal District

Heating Networks. Annual Reports for Ministry of

Education Czech Republic, Nr. 2C06007, Prague,

Czech Republic.

Ordys, A.W., Pike, A.W., Johnson, M.A., Katebi, R.M. and

Grimble, M. J. (1994). Modelling and Simulation of

Power Generation Plants. London 1994, Springer-

Verlag.


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