ECE 522 Power Systems Analysis II 3.2 Small Signal Stability

Similar documents
ECE 422 Power System Operations & Planning 6 Small Signal Stability. Spring 2015 Instructor: Kai Sun

ECE 422/522 Power System Operations & Planning/Power Systems Analysis II : 6 - Small Signal Stability

State space systems analysis

Brief Review of Linear System Theory

ELEC 372 LECTURE NOTES, WEEK 4 Dr. Amir G. Aghdam Concordia University

EECE 301 Signals & Systems Prof. Mark Fowler

Introduction to Control Systems

STUDY OF SUBSYNCHRONOUS RESONANCE AND ANALYSIS OF SSR

ECEN620: Network Theory Broadband Circuit Design Fall 2014

The Performance of Feedback Control Systems

Fig. 1: Streamline coordinates

CONTROL SYSTEMS. Chapter 7 : Bode Plot. 40dB/dec 1.0. db/dec so resultant slope will be 20 db/dec and this is due to the factor s

Time Response. First Order Systems. Time Constant, T c We call 1/a the time constant of the response. Chapter 4 Time Response

CONTROL ENGINEERING LABORATORY

Automatic Control Systems

x z Increasing the size of the sample increases the power (reduces the probability of a Type II error) when the significance level remains fixed.

State Space Representation

Lecture 30: Frequency Response of Second-Order Systems

STABILITY OF THE ACTIVE VIBRATION CONTROL OF CANTILEVER BEAMS

Problem 1. Problem Engineering Dynamics Problem Set 9--Solution. Find the equation of motion for the system shown with respect to:

Erick L. Oberstar Fall 2001 Project: Sidelobe Canceller & GSC 1. Advanced Digital Signal Processing Sidelobe Canceller (Beam Former)

1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations

System Control. Lesson #19a. BME 333 Biomedical Signals and Systems - J.Schesser

ECM Control Engineering Dr Mustafa M Aziz (2013) SYSTEM RESPONSE

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Isolated Word Recogniser

EE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations

u t u 0 ( 7) Intuitively, the maximum principles can be explained by the following observation. Recall

Signal Processing in Mechatronics

Last time: Ground rules for filtering and control system design

Power System Simple Model. Stabilizer. Hydro Turbines. Impoundment Hydropower. Basic Components of Power Plant. Penstock Governor. Dam.

MAHALAKSHMI ENGINEERING COLLEGE TIRUCHIRAPALLI

Professor: Mihnea UDREA DIGITAL SIGNAL PROCESSING. Grading: Web: MOODLE. 1. Introduction. General information

2C09 Design for seismic and climate changes

Lecture 25 (Dec. 6, 2017)

Chapter 7: The z-transform. Chih-Wei Liu

Performance-Based Plastic Design (PBPD) Procedure

EE 508 Lecture 6. Scaling, Normalization and Transformation

LECTURE 13 SIMULTANEOUS EQUATIONS

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Answer: 1(A); 2(C); 3(A); 4(D); 5(B); 6(A); 7(C); 8(C); 9(A); 10(A); 11(A); 12(C); 13(C)

High-Speed Serial Interface Circuits and Systems. Lect. 4 Phase-Locked Loop (PLL) Type 1 (Chap. 8 in Razavi)

Dynamic Response of Linear Systems

8.6 Order-Recursive LS s[n]

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION

10-716: Advanced Machine Learning Spring Lecture 13: March 5

Definitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients.

ECONOMIC OPERATION OF POWER SYSTEMS

THE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS

Queueing Theory (Part 3)

Chimica Inorganica 3

ELEC 372 LECTURE NOTES, WEEK 1 Dr. Amir G. Aghdam Concordia University

Dynamic Response of Second Order Mechanical Systems with Viscous Dissipation forces

Heat Equation: Maximum Principles

TESTS OF SIGNIFICANCE

Control of a Linear Permanent Magnet Synchronous Motor using Multiple Reference Frame Theory

FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING

} = 0 [ III-2b ] [ ] a exp [ i k r. [ ] a t. { } n, a r. ( ) = i ˆ. ( ) = i. ( ) exp i r. a exp i k r. a, etc...

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and

Explicit scheme. Fully implicit scheme Notes. Fully implicit scheme Notes. Fully implicit scheme Notes. Notes

For a 3 3 diagonal matrix we find. Thus e 1 is a eigenvector corresponding to eigenvalue λ = a 11. Thus matrix A has eigenvalues 2 and 3.

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course

Run-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE

Frequency Domain Filtering

6.003 Homework #3 Solutions

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

ECE 442. Spring, Lecture - 4

Capacitors and PN Junctions. Lecture 8: Prof. Niknejad. Department of EECS University of California, Berkeley. EECS 105 Fall 2003, Lecture 8

ELE B7 Power Systems Engineering. Symmetrical Components

ELEG3503 Introduction to Digital Signal Processing

Time-Domain Representations of LTI Systems

Nonlinear regression

Both Paths Satisfy the Dynamic Equations

Sinusoidal Steady-state Analysis

5.74 TIME-DEPENDENT QUANTUM MECHANICS

Applications in Linear Algebra and Uses of Technology

Assignment 2 Solutions SOLUTION. ϕ 1 Â = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ.

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

Statistics and Chemical Measurements: Quantifying Uncertainty. Normal or Gaussian Distribution The Bell Curve

Statistical Inference Procedures

Adaptive control design for a Mimo chemical reactor

3-PHASE INDUCTION MOTOR TESTS (SI 2)

The Pendulum. Purpose

Systems of Particles: Angular Momentum and Work Energy Principle

Load Dependent Ritz Vector Algorithm and Error Analysis

Introduction to Signals and Systems, Part V: Lecture Summary

ECE 308 Discrete-Time Signals and Systems

ADVANCED DIGITAL SIGNAL PROCESSING

SOLUTION: The 95% confidence interval for the population mean µ is x ± t 0.025; 49

Weak formulation and Lagrange equations of motion

Virtual Synchronous Motor Dynamic Power Decoupling Strategy

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y

Complex Analysis Spring 2001 Homework I Solution

mx bx kx F t. dt IR I LI V t, Q LQ RQ V t,

20. CONFIDENCE INTERVALS FOR THE MEAN, UNKNOWN VARIANCE

5.76 Lecture #33 5/08/91 Page 1 of 10 pages. Lecture #33: Vibronic Coupling

Dr. Seeler Department of Mechanical Engineering Fall 2009 Lafayette College ME 479: Control Systems and Mechatronics Design and Analysis

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.

Vibration Absorbers/Neutralisers. Professor Mike Brennan

Transcription:

ECE 5 Power Sytem Aalyi II 3. Small Sigal Stability Sprig 18 Itructor: Kai Su 1

Cotet 3..1 Small igal tability overview ad aalyi method 3.. Small igal tability ehacemet Referece: EPRI Dyamic Tutorial Chapter 1 ad 17 of Kudur Power Sytem Stability ad Cotrol Chapter 3 of Adero Power Sytem Cotrol ad Stability Joe H. Chow, Power Sytem Coherecy ad Model Reductio, Spriger, 13

3..1 Small Sigal Stability Overview ad Aalyi Method 3

Power Ocillatio The power ytem aturally eter period of ocillatio a it cotiually adjut to ew operatig coditio or experiece other diturbace. Typically, ocillatio have a mall amplitude ad do ot lat log. Whe the ocillatio amplitude become large or the ocillatio are utaied, a repoe i required: A ytem operator may have the opportuity to repod ad elimiate harmful ocillatio or, le deirably, protective relay may activate to trip ytem elemet. 4

Small Sigal Stability Small igal tability (alo referred to a mall diturbace tability) i the ability of a power ytem to maitai ychroim whe ubjected to mall diturbace I thi cotext, a diturbace i coidered to be mall if the equatio that decribe the reultig repoe of the ytem may be liearized for the purpoe of aalyi. k +P P() It i coveiet to aume that the diturbace cauig the chage already diappear ad detail o the diturbace are uimportat P The ytem i table oly if it retur to it origial tate, i.e. a table equilibrium poit (SEP). Thu, oly the behavior i a mall eighborhood of the SEP are cocered ad ca be aalyzed uig the liear cotrol theory. 5

Claic Model SMIB Sytem With all reitace eglected: T = P = P = P = P P e e t B max (T e ) = EE X T B max i d K S P e +jq e P t +jq t P B +jq B (P e =T e ) (T m ) dd d = w D wr dt dd wr H = Tm - Te - KD D wr dt =DT -DT -K Dw m e D r»dt -K Dd-K Dw m S D r Note: H i r i p.u. i rad. K D K S i p.u i p.u/rad Liearize wig equatio at = : T d e D Te» D d= KSD Sychroizig torque coefficiet: K S = P cod = EE B max XT d cod 6

State pace repreetatio d dt é w ù é Dd ù édd ù éù DT = K S K + ê D w ú ê r w ú ê r 1 ú ëd û - - D H ê ë û H H ú ë û ë û m K D Kw wdt D d+ D d+ D d= H H H Apply Laplace Traform: 1 wdt D d = KD Kw + + H H H m m Characteritic equatio: K K w + D + = H H 7

A harmoic ocillator F = M x=-k x-d x + D K M + M = H w K D d =-K D d- Dd (if DT = ) D w K K w + D + = H H m + zw + w = Dampig ratio Natural frequecy It ha two cojugate complex root ad it zero-iput repoe i a damped iuoidal ocillatio:, = jw=-zw jw 1-z : 1 1 t xt () = Ae i( wt+ j) -zwt = Ae - + i( wt 1 z j) The time of decayig to 1/e=36.8%: 1 1/ 8

Ocillatio Frequecy ad Dampig of a SMIB Sytem + zw + w = K K w + D + = H H, = jw=-zw jw 1-z 1 EE B ( KS = cod = Pmax co d) X T Note the uit: r i i p.u. i i rad. K D i i p.u K S i i p.u/rad w w EE cod w = + w = K = H HX B S T w K w = w 1- z = KS - H 16 H D z - 1 K = = = K D T D w K 8 HE EB co S Hw w + d 4 X =- zw =- KD H How do ad chage with the followig? if H (lower iertia) if X T (troger tramiio) if (lower loadig) 9

Sytem Repoe after a Small Diturbace d dt x1 é w ù Dd Dd DT = K S K + ê D w ú ê r w ú ê r 1 ú ëd û - - D H ê ë û H H ú ë û ë û é ù é ù é ù =Dd D u = D H T m x =D w =Dd / w r éx ù é 1 w ù é x ù é 1 ù = + Du ê x ú ê -w w -zw ú ê x ú ê 1ú ë û ë û ë û ë û x () t Ax() t Bu() t é1 ù y() t = Cx() t =ê ê 1ú éx êx 1 ù ú ë û ë û (Aumig the agle ad peed to be directly meaured) m Apply Laplace traform: X() x() AX() BU() D U() = Du Y() X() ( IA) x() BU() é + zw ê ê w w ú ë- û + zw+ w [ + U ] X () = () () x B D é + zw w ù é ù é Dd() ù ê-w w ú é Dd() ù = ë û ( + ) u ê wr() ú zw w ê D wr() ú ëd û + + ëd û êë úû w ù ú 1 + Zero-iput Zero-tate Zero-iput Zero-tate 1

é + zw w ù é ù é Dd() ù ê-w / w ú é Dd() ù = ë û ( + ) u ê wr() ú zw w ê D wr() ú ëd û + + ëd û êë úû Zero iput repoe E.g. whe the rotor i uddely perturbed by a mall agle () ad aume r ()= D ( zw) d() d() = + D + zw + w w Dd() / w D wr () =- + + zw w Ivere Laplace traform D w =D d / w = ( w -w )/ w i pu r D u = D H T m Zero tate repoe E.g. whe there i a mall icreae i mechaical torque T m (= P m i pu) ( ) r pu ( ) r u ( ) u Dd() -zw Dd i rad = e t i( wt+ q) 1-z Dw r wdd() -zwt i rad/ =- e i wt 1 - z i r rad i rad T 1 1 e i 1 m t H T m / t H 1 e t i t Dampig agle: co 1 11

Example Exp. 11. & 11.3 i Saadat book H=9.94, K D =.138pu, T m =.6 pu with PF=.8. Fid the repoe of the rotor agle ad frequecy uder thee diturbace (1) ()=1 o =.1745 rad () P e =.pu Zero iput repoe: ()=1 o ()=16.79+1=6.79 o Zero tate repoe: P e =.pu ()=16.79+5.76=.55 o 1

Small Sigal Stability of a Multi machie Sytem Iter area or itra area mode (.1.7Hz): machie i oe part of the ytem wig agait machie i other part Local mode (.7 Hz): ocillatio ivolve a mall part of the ytem Cotrol or torioal mode (Hz ) Iter area model (.1.3Hz): ivolvig all the geerator i the ytem; the ytem i eetially plit ito two part, with geerator i oe part wigig agait machie i the other part. Itra area mode (.4.7Hz): ivolvig ubgroup of geerator wigig agait each other. Local plat mode: aociated with rotor agle ocillatio of a igle geerator or a igle plat agait the ret of the ytem; imilar to the igle machie ifiite bu ytem Iter machie or iterplat mode: aociated with ocillatio betwee the rotor of a few geerator cloe to each other Due to iadequate tuig of the cotrol ytem, e.g. geerator excitatio ytem, HVDC coverter ad SVC, or torioal iteractio (ub ychroou reoace) with power ytem cotrol 13

High & Low Frequecy Ocillatio Wheever power flow, I R loe occur. Thee eergy loe help to reduce the amplitude of the ocillatio. High frequecy (>1. HZ) ocillatio are damped more rapidly tha low frequecy (<1. HZ) ocillatio. The higher the frequecy of the ocillatio, the fater it i damped. Power ytem operator do ot wat ay ocillatio. However, whe ocillatio occur, it i better to have high frequecy ocillatio tha low frequecy ocillatio. The power ytem ca aturally dampe high frequecy ocillatio. Low frequecy ocillatio are more damagig to the power ytem, which may exit for a log time, become utaied (udamped) ocillatio, ad eve trigger protective relay to trip elemet 14

Blackout o Augut 1, 1996 1. Iitial evet (15:4:3): Short circuit due to tree cotact Outage of 6 traformer ad lie,1 MW lo 97 MW lo. Vulerable coditio (miute) Low damped iter area ocillatio Outage of geerator ad tie lie 11,6 MW lo 3. Blackout (ecod) Uitetioal eparatio Lo of 4% load 15,8MW lo 15 14 13 1 11.76 Hz ocillatio dampig ratio >7% Mali-Roud Moutai #1 MW 15:4:3.64 Hz ocillatio dampig ratio =3.46% 15:47:36.5 Hz ocillatio dampig ratio 1% 15:48:51 3 4 5 6 7 8 Time i Secod Traiet itability (blackout) 15

Ocillatio Mode of a Multi machie Sytem i the Claic Model Hi d i dt P P i 1,,, mi ei co i co P E G P E G EEY E G EE B G ei i ii ij i ii i j ij ij ij i ii i j ij ij ij ij j1 ji j1 ji j1 ji, B Y i, G Y co ij i j ij ij ij ij ij ij (Igorig dampig) Liearizatio at ij : ij ij ij i i co ij ij ij ij co co i ij ij ij ij H H i i d dt d dt i i K i 1,,, j 1 ji j 1 ji ij ij EE B co G i i j ij ij ij ij ij Sychroizig power coefficiet P K = E E B co G i ij ij ij i j ij ij ij ij ij compared to K S = EE X T B cod 16

Hi d dt i K i 1,,, j1 ji ij ij Note: There are oly ( 1) idepedet equatio becaue ij =, o we eed to formulate the ( 1) idepedet relative rotor agle equatio with oe referece machie, e.g., the -th machie. d i d K, 1,, 1 jj i dt dt H H 1 R K ijij i j1 j1 ji Coider each i = i - d K K K K, i 1,, 1 1 i ij i i j ij j dt Hi j 1 H j1h Hi ji ji d 1 i dt j1 i 1,,, 1 ij j ii Kij Ki ij Kj Kij Hi j1 H H Hi ji 17

State pace repreetatio Let x, x,, x,,, ad 1 1 1 1 x, x,, x,,, 1 1 1 x 1 1 x1 1 x x 1 x 1 x 1 x 11 1 1 1 x x 1 1 1 x 1 x x 11 1 11 X 1 I X A It characteritic equatio I-A = ha (-1) imagiary root, which occur i (-1) complex cojugate pair A -machie ytem ha (-1) mode Read Adero Example 3. ad 3.3 about the liearizatio ad eige-aalyi o the IEEE 9-bu ytem 18

Formulatio of Geeral Multi machie State Equatio The liearized model of each dyamic device: x i Aixi Biv i Cx Yv i i i i x i Perturbed value of tate variable i i Curret ijectio ito etwork from the device v Vector of etwork bu voltage B i ad Y i have o-zero elemet correpodig oly to the termial voltage of the device ad ay remote bu voltage ued to cotrol the device i i ad v both have real ad imagiary compoet Such tate equatio for all the dyamic device i the ytem may be combied ito the form: x ADxBDv i C xy v D x i the vector of tate variable of the complete ytem A D ad C D are block diagoal matrice compoed of A i ad C i aociated with the idividual device Node equatio of the tramiio etwork: i= Y N v The overall ytem tate equatio: x A xb ( Y Y ) C x = Ax Read Kudur ec. 1.7 for other related iformatio, e.g. load model liearizatio ad electio of a referece rotor agle D 1 D D N D D 1 D D( N D) D AA B Y Y C 19

Modal aalyi (eige aalyi) o a dimeioal oliear ytem Equilibrium x (with u ): Liearizatio at the equilibrium x : coider a perturbatio at x ad u

Eige vector For ay λi, the colum vector i atifyig Ai λii a right eigevector of A aociated with λ Modal 1 AΦ ΦΛ Λ diag( λ1, λ, λ 1 Φ AΦ Λ A Similarly the row vector matrix A Φ T T T 1 j Left eigevector aociated with j j j j Ψ,,,,,, T ψ, ) if ha ditict eigevalue i called (uually true for a real-world ytem) The left ad right eigevector correpodig to differet eigevalue are orthogoal (row vector of -1 are left eigevector of A, o we may let = C -1 where C i a diagoal matrix or imply equal to I if ormalized) ΨΦ I if i j, or 1 i j i i i λ 1

Free (zero iput) repoe ad tability x Ax Liearized ytem without exteral forcig To elimiate the cro-couplig betwee the tate variable, coider a ew tate vector z i t z z 1 i izi zi t zi e t z t 1 z Λz = Φ AΦz Φz AΦz x(t) Φz(t) 1 izie i1 1 z t Φ x t Ψx t z t z x c i i i it i t xe c e x (c i i the magitude of the excitatio of the i th mode) i i i i i1 i1 it 1t t k ki i k1 1 k i1 x (t) c e c e... c e t Free repoe i a liear combiatio of mode t Each eigevalue = j A real eigevalue (=) correpod to a o-ocillatory mode. a decayig mode ha <; a mode with > ha aperiodic itability. Complex eigevalue () occur i cojugate pair; each pair correpod to oe ocillatory mode Frequecy of ocillatio i Hz: f= / Dampig ratio (rate of decay) of the ocillatio amplitude i

Mode Shape ad Mode Compoitio t t z (t), z (t),..., z (t) T x Φz 1 1 T T T T t t,,, x (t), x (t),..., x (t) z Ψ x 1 1 The variable x 1, x,, x are origial tate variable choe to repreet the dyamic performace of the ytem. Variable z 1, z,, z are traformed tate variable; each i aociated with oly oe mode. I other word, they are directly related to the mode. The right eigevector i give the mode hape of the i th mode, i.e. the relative activity of the origial tate variable whe the i th mode i excited: The k th elemet of i, i.e. ki, meaure the activity of tate variable x k i the i th mode The left eigevector i give the mode compoitio of the i th mode, i.e. what weighted compoitio of origial tate variable i eeded to cotruct the mode: The k th elemet of i, i.e. ik, weight the cotributio of x k activity to the i th mode T k ki i i1 x (t) z t z (t) x (t) i ik k k 1 3

Participatio factor ΨΦ I ΨΦ p 1 ii ik ki ik k1 k1 ki meaure the activity of x k i the i th mode ik weight the cotributio of thi activity to the mode Participatio factor p ki = ik ki meaure the participatio of the k th tate variable x k i the i th mode. p ki i dimeiole ad hece ivariat uder chage of cale o the variable Quetio: coiderig = -1, why do we have to defie the mode hape, mode compoitio, ad participatio factor, eparately? Lear Kudur Example 1. o a SMIB ytem 4