Study of Supercritical Coal Fired

Power Plant Dynamic Responses and Control

for Grid Code Compliance

Prof Jihong Wang, Dr Jacek D Wojcik (University of Warwick)

Dr Yali Xue (Tsinghua University)

THE UNIVERSITY

of BIRMINGHAM

Mathematical Modelling and Simulation of Power Plants and CO2 Capture

WORKSHOP

University of Warwick, 20th-21st March 2012

Outline

• Overview of the EPSRC Project (J Wang)

• Power Plant Modelling (J Wojcik)

• Power Plant Simulation (Y L Xue)

• Summary (J Wang)

THE UNIVERSITY

of BIRMINGHAM

Outline

• Overview of the EPSRC Project

• Power Plant Simulator

• Power plant modelling

• Summary

THE UNIVERSITY

of BIRMINGHAM

Supercritical technology

Subcritical

(conventional)

Supercritical Ultra supercritical

Temperature

(°C)

500 – 550 500 – 600 550 – 600, (600 – 700)*

Pressure (MPa) 16 – 17 24 – 26 27 – 32, (40 – 42)*

Features Drum: single

reheat

Once through:

single reheat

Once through: double

reheat

Efficiency

cycle (%)

33 - 35 40-45 42 – 47, (50 –

55)*

THE UNIVERSITY

of BIRMINGHAM

Future new power plants in the UK - SUPERCRITICAL

THE UNIVERSITY

of BIRMINGHAM

Power generation responses

to the demand changes

Fast enough to satisfy the grid

specification

Subcritical water-steam cycle

Drum – energy storage

Supercritical water-steam cycle (no

phase change)

Once-through operation – no energy

storage

Challenges: Can supercritical power generation responses to the demand

changes fast enough to satisfy BG Grid Code requirement?

Subcritical Supercritical

THE UNIVERSITY

of BIRMINGHAM

Project Objectives

Through study supercritical coal fired power plant

mathematical modelling and simulation:

• to understand the dynamic responses of

supercritical power plants

• to investigate the possible strategies for

improvement

THE UNIVERSITY

of BIRMINGHAM

List of UK power stations

- All Subcritical (~33% efficiency)

THE UNIVERSITY

of BIRMINGHAM

Station Name Representation Company Address Capacity

in MW

Aberthaw B National Ash RWE Npower The Leys Aberthaw, Barry South

Glamorgan

CF62 42W 1,489

Cockenzie ScotAsh Scottish Power Prestopans East Lothian 1,152

Cottam EDF Energy EDF Energy Cottam Power

Company, PO Box 4, nr

Retford

Nottinghamshire DN22 0ET 1,970

Didcot A National Ash RWE Npower Didcot Nr Oxford OX11 7HA 2,020

Drax Hargreaves CCP Drax Power Limited Drax Selby North Yorks YO8 8PQ 3,870

Eggborough British Energy British Energy Eggborough Goole North

Humberside

DN14 0BS 1,960

Ferrybridge C Keadby generation

Ltd

Scottish & Southern

Energy plc

PO Box 39, Stranglands

Lane

Knottingley West

Yorkshire

WF11 8SQ 1,955

Fiddlers Ferry Keadby generation

Ltd

Scottish & Southern

Energy plc

Widnes Road Cuerdley Warrington WA5 2UT 1,961

Ironbridge EON UK PowerGen Buildwas Road Telford Shropshire TF8 7BL 970

Kingsnorth EON UK PowerGen Hoo Saint Werburgh Rochester Kent ME3 9NQ 1,974

Longannet ScotAsh Scottish Power ScotAsh Ltd, Kincardine-

on-Forth

Fife FK10 4AA 2,304

Lynemouth Alcan Alcan Primary Metal -

Europe

Ashington Northumberland NE63 9YH 420

Ratcliffe EON UK Powergen Ratcliife on Soar Nottingham NG11 0EE 2,000

Rugeley International Power International Power Rugeley Power Station Armitage Road Rugeley WS15 1PR 976

Tilbury B National Ash RWE Npower Fort Road Tilbury Essex RM18 8UJ 1,020

West Burton EDF Energy EDF Energy West Burton Power

Company, Retford

Nottinghamshire DN22 9BL 1,932

Wilton Hargreaves CCP ICI PO Box 1985, Wilton

International

Middlesborough TS90 8WS 100

Collaboration Mathematical

modelling, simulation study, dynamic

response analysis, optimal control,

Grid Code studies

Supercritical water, test rig evelopment, Experimental tudies, data collection and

analysis

Industrial scale power plant modelling and

simulation, software

development, verification

Power plant control, intelligent

algorithms,

Consortium interactions

Exchange of

materials, data, information

Integrated testing programme

Shared models, software and simulations

Team

University of Warwick:

Prof J Wang, Dr J Wojcik

Mr M Draganescu, Mr S Guo

University of Birmingham:

Dr B Al-Duri, Mr O Mohamed

Tsinghua University

Prof. J F Lv, Prof Q R Gao, Dr Y L Xue

North China Electric Power University

Prof X J Liu, Prof G L Hou

THE UNIVERSITY

of BIRMINGHAM

THE UNIVERSITY

of BIRMINGHAM

Frequency in the Power System - Mr M Draganescu

Definition:

Power System Frequency can be defined as a measure of the electrical

speed of the synchronous generators connected to the grid; this is a

common value at every point in the grid.

Frequency – constant value

Electricity

Generation

Electricity

Demand at all time.

Electricity

Generation Electricity

Demand Frequency

Deviations

Power System

Instability Total Outage

(Blackout)

PGen PDem

THE UNIVERSITY

of BIRMINGHAM

UK Power System

Transmission System Operators (TSOs):

• National Grid

• Scottish and Southern Energy

• Scottish Power

System Data:

TSO Circuit Voltage

[kV]

Circuit Length

[km]

National Grid 400, 275 ~14,000

Scottish and

Southern Energy 275, 132 ~5,000

Scottish Power 400, 275, 132 ~4,000

Electricity Supplied by Fuel Type in 2010:

THE UNIVERSITY

of BIRMINGHAM

UK Power System — The Grid Code —

Frequency Control Strategies

Type of Frequency Control

Strategy Response Time

Primary Frequency Response active power increase within 10 s and

maintained for another 30 s

Secondary Frequency Response active power increase within 30 s and

maintained for another 30 min

High Frequency Response active power decrease within 10 s and

maintained thereafter

Nominal Frequency: 50 Hz

Frequency Variation Interval [Hz]

Normal

Operation Critical Situations

49.5 – 50.5 47.0 – 52.0

THE UNIVERSITY

of BIRMINGHAM

Test:

A frequency ramp decrease/

increase of 0.5 Hz over a period of 10 s.

Frequency Response Capability of a Generating Unit

UK Power System — The Grid Code —

Outline

• Overview of the EPSRC Project (J Wang)

• Power Plant Modelling (J Wojcik)

• Power Plant Simulation (Y L Xue)

• Summary (J Wang)

THE UNIVERSITY

of BIRMINGHAM

Exact mathematical model of SCPP consists of: • Coal mill (Pulverised-Fuel)

• Supercritical Boiler

• Steam Turbine

• Synchronous Generator (SG) and Electric Power System (EPS)

• Excitation System – Auto Voltage Regulator (AVR) and Exciter

• Governor (GOV)

• Boiler Control System

Power Plant Modelling

WC

ΔPpa

Tin

SC BOILER

WFWF Steam Turbine

Synchronous

Generator COAL MILL

Electrical Power System WPF

PM

Excitation

System

EFD

PMSP

CVArea IVArea

Pe Pe Pg Qg

Ug

δ Eqb

Edb

Ig

Ig

Ug

Governor Δω

WSC

PRH

B+jG

Single-Machine Infinitive Bus

Control System

Mathematical model of Supercritical Power Plant - Block diagram.

Mathematical modelling of Supercritical Power Plant in Matlab®/Simulink® software environment

Two different types of pulverised coal mill in power plants

Power Plant Modelling Coal Mill Model Implementation in Matlab®/Simulink® software environment

Vertical Spindle

mill Tube-Ball mill

s

1cM

pfM

Kf Ap1 Ap2 Wc

K1,K2,

K3,K4,

K5,K6,

K7,K8,

K14,

K17 K16 ΔPout, Mpf_initial

Wpf

Mc_initial K15

Mc

Mpf

ΔPout , ΔPin , Tin , Tout

P

T

s

1

Model based on mass balance and heat balance:

Block diagram of coal mill model.

Graphical

Unit

Interface

‘On-line Condition and Safety Monitoring of Pulverised Coal Mills

Using a Model Based Pattern Recognition Technique’

Prof Jihong Wang, Dr Jianlin Wei, Mr Paschalis Zachariades, Mr. Shen Guo

Differential equations

Hi 1

Ts P

Q

wo Ho

Ki

wi

hi

V

p v h τ

wi ho wo

q

Model based on mass balance and energy balance

Steam pressure model

KECO

CVArea

1

TECOs

Ho1

Hi1

AECO√

1

TWWs

Ho2

Hi2

AWW√

1

TSHs

Ho3

Hi3

ASH√

1

TCVs

Ho4

Hi4

X

KWW

KSH

1

1+TFFs

1

TRHs

Ho5

Hi5

X

IVArea

KRH

Feedwater flow

Fuel flow

WCV

WRH

Block diagram of boiler model. Where: Hi, Ho – input/output gain of steam flow entering/leaving associated nodes, P – node pressure,

Q – heat transfer to node, Wi – flow rate of fluid entering node, Wo – flow rate of fluid leaving node

Differential equations

BECOECOoFWFiECOECO QKWHWHPT 11

BWWWWoECOiWWWW QKWHWHPT 22

BSHSHoWWiSHSH QKWHWHPT 33

CVoSHiCVCV WHWHPT 44

BRHRHoCViRHRH QKWHWHPT 55

BPFBFF QWQT

The steam patch is divided into following parts: • Economiser node

• Waterwall node

• Superheater node

• Main steam line node

• Reheater node

Power Plant Modelling SC Boiler Model Implementation in Matlab®/Simulink® software environment

Fuel Air Feedwater

HP IP+LP

to

con

den

ser

Water-Steam loop in basic once-through boiler design.

Econo- miser

Flue gases

F. de Mello: Dynamic Models for Fossil Fuelled Steam Units in Power System Studies. IEEE Transactions on Power

Systems, Vol.6, No.2, 1991.

HP Steam Chest

Tandem-Compound Single-Reheat

Steam Turbine

Generic Model of Steam Turbine/

Tandem-Compound Single-Reheat Steam Turbine

Pm1

1

1+sT4

1

1+sT5 1

1+sT6

1

1+sT7

K1

K2

K3

K4

K5

K6

K7

K8

GVArea

π PMS π

IVArea

Differential equations

SCAreaBSC WGVPWT )(4

RHSCRH PWPT 5

CRRHCR WWWT 6

Power Plant Modelling Steam Turbine and Governor Models Implementation in Matlab®/Simulink® software environment

DEH control system – block diagram, where: ∆f – frequency deviation; ∆n – speed deviation; K– speed drop ;

Pref – reference load signal; Pload – load signal;

Pms – main steam pressure.

∆f

Pref

V D

1

1+sT1 PID K

-

∆n

Pload

Pms

1

0 1

2

3

4

feed forward loop

DEH control system

feedback loop

Control mode Switch

S1 S2 S3 S4

SC on off off off

SCLF on off on off

SCPF on off off on

SCLFF off on on off

SCPFF off on off on

s

DPPT emm

)( ''''''''''

0 dddqqqd XXIEEET

)( ''''''''''

0 qqqdddq XXIEEET

)( ''''

0 dddqfdqd XXIEEET

)(0 ''''

0 qqqddq XXIEET

Differential equations

Power Plant Modelling

Synchronous generator connected to a large power system

(Single-Machine Infinite-Bus): a) diagram of connection, b) equivalent electrical circuit (π).

Synchronous Generator Model Implementation in Matlab®/Simulink® software environment

Electric Power System (EPS)

C

D

q

= t

A

B

d

Q

f

(Xd – X’d) (X’d – X"d) X”d

Efd

E’q E”q Uq

Id (Xq – X’q) (X’q – X”q) X”q

E’d E”d Ud

Iq

Rotor d-axis Rotor q- axis

Generator equivalent circuits

DRsT1

DRsK

s

IRK

EsT

1

fd

EE

S

PRK

EK

AsT1

AK

FsT1

FsK

Efd

VPF

VREF

─

─ VC

─

DC4B excitation system

hIR uKx 1

2h

DR

DR2DR xu

T

KxT

213 xxu

T

KKVKxT h

DR

DRPRTAA

434 xEKVxT

KxT fdEX

E

FF

fdEXfdE EKVxET 3

DC

4B

Differential equations

AC

8B

Differential equations

2h

DR

DR2DR xu

T

KxT

hIR uKx 1

3213 xxxuT

KKKxT h

DR

DRPRAA

FDDEXE IKxKVxxT 434

hIR uKx 1

ST

4B

Differential equations

212 xxuKxT hPRA

32311

xKK

KKx

KK

KKKKx

PMG

IMG

PMG

IMPMGIM

Power Plant Modelling

E

FDCN

V

IKI

NEX IfF

EE VS

EK

DK

A

A

sT

K

1

DRsT

DRsK

1

s

IRK

PRK

Efd

─

IFD

VPF VREF

─ VC

uh

EsT

1

AC8B excitation system

TV

TI

E

FDCN

V

IKI

TLPITPE IXKKjVKV )(

NEX IfF

GK

AsT1

1

s

KK IR

PR s

KK IM

PM Efd

VPF VREF

─ VC

IFD

─

ST4B excitation system

Evaluation of the exciter

saturation curve SE(Efd).

E

FDC

V

IK NEX IfF

Efd

IFD

VE

b.)

III

I

II

1

1 0

a.)

FEX

IN

Three-phase bridge rectifier: a.) voltage-

current characteristic, b.) block diagram.

Excitation System Model Implementation in Matlab®/Simulink® software environment

IEEE Standard 421.5-2005: IEEE Recommended Practice for Excitation System Models for Power Stability Studies

Integrating the intelligent optimisation algorithms with the power plant

model for parameters identification

Power Plant Modelling Model Parameters identification process in Matlab®/Simulink®

SIMULINK®

Simulation for new

parameters (+measurement

input DATA)

Parameters update

MATLAB®

Genetic

Algorithm

[Toolbox]

Plant measurement

DATA from

SC Power Plant

Data input to model

Simulated and measured

outputs YES

NO

Model

Parameters

Stopping

criterion

met

?

Model = structure + parameters

Power Plant Modelling

Steady-State Data Start-Up Data

Parameters identification process based on measurement data from SCPP

GA Fitness Function: Based on measured data form SCPP

1. Mechanical Power output Pm

2. Main steam pressure MSP

3. Reheater pressure RHP

Error calculation based on Integral of

Time Absolute Error (ITAE) criteria:

Input Data: Output Data:

FWF – feedwater flow

FF – fuel flow

Pm – mechanical power

MSP – main steam pressure

RHP – reheater pressure

MODEL

Power Plant Modelling Model Parameters Verification – Results for the best parameters set

data from industry

Simulink model

000 Pm – mechanical power

2000 4000 6000 8000 10000 12000 14000 0.3

0.4

0.5

0.6

0.7

0.8

0.9

t [s]

PM

[p

u]

00 MSP – main steam pressure

2000 4000 6000 8000 10000 12000 14000 0.4

0.5

0.6

0.7

0.8

0.9

1

t [s]

MS

P [p

u]

2000 4000 6000 8000 10000 12000 14000 0.3

0.4

0.5

0.6

0.7

0.8

t [s]

RH

P [p

u]

00 RHP – reheater pressure

Outline

• Overview of the EPSRC Project (J Wang)

• Power Plant Modelling (J Wojcik)

• Power Plant Simulation (Y L Xue)

• Summary (J Wang)

THE UNIVERSITY

of BIRMINGHAM

Content

Tsinghua University

Development of 600MW supercritical pulverized coal

power plant simulation software

Summary

Tsinghua University is ranked the top university in China Seasons in Tsinghua University, located in Beijing

Ther

mal

En

gin

eeri

ng

Dep

artm

ent

Institute of Thermal Engineering

Institute of Power Mechanics & Engineering

Institute of Fluid Mechanics & Engineering

Institute of Engineering Thermophysics

Institute of Simulation & Control of Power System

Division of Thermal Power System State Key Laboratory of Control & Simulation of Large Power System & Generation Equipment

Tsinghua University has 56 academic departments

Research and Teaching in Power Plant Modeling and Simulation at Tsinghua University

• The research in this area has over 30 years history

• Giving great contributions to China power industry development

• Playing a major role in training key skilled personnel required in China

• Leading in the research areas of power plant modeling and simulation, clean coal technology and CCS

• State-of-the-art research facilities

Operator skills contest 135MW CFB Power Plant Simulator State Key Task 10.5 National Development Plan in China

Energy and Power Engineering Simulation Practice Compulsory Subjects for 3rd year undergraduates

Teaching facilities

Development of large scale power plant simulation software

• Principle

• Theoretical basis – System Theory, Control Engineering, Computer Science

– Thermodynamics, Fluid dynamics, Combustion

– Mass/Energy/Momentum conservation equation, heat transfer equation, state equations

Example - comparison results of a CFB simulator - Bed temperature, coal and oil flow rate in startup process

Bed Temp.

Feed Coal

Feed Oil

Field data Simulation results

600MW SCPC Simulation Scope

Objective

– Understand the dynamic load response character of SCPC

– Improve its control quality

Simulation Scope The complete process of SCPC power plants from fuel preparation to electricity output

– Main devices • Boiler, Turbine, Generator,

• Auxiliary Power, and related auxiliary machine

– Control Systems • DAS/MCS/FSSS/BMS/SCS/ECS/DEH/ETS

– Malfunctions simulation

– Human Machine Interface

600MW SCPC Simulation – Hardware Configuration

仿真服务器

就地操作站1 就地操作站2 DCS操作站2

……

指导教师工作站

DCS操作站1

……

大屏幕投影

工程师工作站Instructor Station Simulator Server

Local Operator Station DCS Operator Station

Large Screen

Display

Engineer Station

600MW SCPC Simulation - Software Structure

Simulation

Support

System

Process models

Control system models

Database managem

ent

Network communic

ation

Real-time running

Model develop support

600MW SCPC Simulation - Key Challenges

(1) Dynamic model of water fall

• Subcritical boiler riser tube – one-section lumped parameter model

• Supcritical boiler water fall – multi-section lumped parameter model

– At subcritical pressure, the water is heated gradually into steam-water mixture (two phase flow)

– At supercritical pressure, the water is heated and evaporated into steam directly (one phase flow)

– Near the critical point, the specific heat capacity shows dramatic change

1 2 N

Heat

OutletInlet

Heat

Inlet Outlet

600MW SCPC Simulation - Key Challenges

(2) Dynamic model of build-in startup separator

(3) Build the steam/water thermodynamic property calculation method

Subcritical Supcritical

Steam Water Separator Steam Chamber

Wet State Dry State

Boundary Node

600MW SCPC Simulation - Key Challenges

(4) Control system model

• Automatically stabilize the process to improve the operator training quality

• Basis for advanced study on control system strategy and controller parameter optimization

Keep a proper coal water ratio - to track the unit load command quickly while minimize the main steam temperature

Feed forward signal from unit load command - to coordinate boiler/turbine response

Control intermediate point temperature or enthalpy - to keep stable heat distribution in water wall

Multivariable nonlinear control

600MW SCPC Simulation - Feedwater Control

Feed water flow control in once-through supercritical coal-fired boiler is different with that in drum-type boiler

– The fluctuation of feed water flow or combustion ratio all have great impact on the dynamic of unit load and main steam temperature due to lack of drum

– To regulate unit load with minimum main steam temperature variation, the combustion ratio (fuel and air flow) and feed water flow should keep a proper ratio—coal/water ratio

Control scheme: • Outer loop: feed water flow

command, consists of two parts: a basic command comes from coal-water ratio calculation, then plus a calibration signal from middle point temperature control.

• Inner loop: feed water pump speed control

600MW SCPC Simulation – Human Machine Interface

600MW SCPC Simulation – progress summary

• Completed

– Main devices modeling

– Substance property calculation

– Main Control system modeling

– Main steam-water system modeling

• To be developed

– HMI (DCS, DEH, MEH, etc) to facilitate the research on dynamic response for grid code compliance

– Joint debugging and integration of the whole simulator

– Dynamic characteristic analysis and coordination control strategy optimization

– Research on CCS+PC

Outline

• Overview of the EPSRC Project (J Wang)

• Power Plant Simulation (Y L Xue)

• Power Plant Modelling (J Wojcik)

• Summary (J Wang)

THE UNIVERSITY

of BIRMINGHAM

Summary

• The grid code study and comparison are carried out

• The first version of Mathematical modelling for the whole

plant process was derived

• Simulation programme at the industrial scale is to complete

soon.

• Post combustion CCS process dynamic simulation study

started a few months ago (Shen Guo)

• Computational intelligent algorithms are used for optimisation

THE UNIVERSITY

of BIRMINGHAM

Summary

Next stage work:

dynamic responses analysis and Grid Code compliance

control strategy for improvement of dynamic responses

in parallel with:

Post combustion CCS dynamic modelling

and simulation is on going

new/additional intelligent algorithms for power plant

optimisation

THE UNIVERSITY

of BIRMINGHAM

Summary

Collaboration:

We would like to work with other academic

institutes together in the research area of

mathematical modelling and simulation of

large scale power plant with CCS process.

THE UNIVERSITY

of BIRMINGHAM

Thank You!

THE UNIVERSITY

of BIRMINGHAM