Inter-area Oscillations in Power Systems 5 j- N$ M2 b* g$ { o" { $ _* G" C3 J' m8 h" y- t A.R.Messina (Editor) 0 V5 ]- H. B* N' u Centro de Investigacion c4 c" o8 `8 _) k I de Estudios Avanzados1 f6 c% E5 c0 P) ^/ y8 l( i
del IPN - O3 Y+ D# s2 E+ V Guadalajara, Mexico 2 x2 M+ A; }) f" ]- S" t$ h4 p 6 M: M6 P+ {$ Y; c" V/ gInter-area Oscillations in Power Systems: A Nonlinear and Nonstationary # `( [8 M0 B" U; \
Perspective deals with the development and application of advanced $ T$ P6 d# }$ A
measurement-based signal processing techniques to the study, % B5 X. R; i T% l* Z
characterization, and control of inter-area oscillations in power systems. , ^( J6 b* D) c( E/ t* \2 i3 x
The material reviews recent advances in understanding, modeling and 8 j8 y9 b- p; T0 w
controlling system oscillations with special emphasis on the analysis and 6 ]# u7 n) w5 \! ~+ Wcontrol of complex time-varying (and possibly nonlinear) power system M. W. b: Z; X1 O( K. y
transient processes. % ]& I9 c) d! J0 P; D8 z3 S+ q( ZThe book is organized into eight chapters written by leading researchers 3 h2 ~0 \6 [! r! U! e
who are major contributors in this field. The authors provide techniques , W& k, h4 d& t U ~1 T1 `; ^' x9 vthat explicitly address the nonlinear and nonstationary aspects of the # B, S( h- U; F* Gproblem. Efficient methods to generate time-varying system approximations ( w: a# q' D$ m4 z- x$ Gfrom both measured and simulated data are proposed. Attention is also given 7 f5 @ }1 t' g; y9 Z' R$ U- F2 q# ?to the vital new ideas of dynamic security assessment in real-time 1 _* Y$ Y7 {/ c( }1 u7 K8 c3 z! h3 C+ g
implementations and the development of smart, wide-area measurement and " R8 R2 ~. X; c( \% g, ^4 G& }6 scontrol systems incorporating FACTS technologies. Application examples : V2 Q# u; H+ ?1 i8 [& Z
include the analysis of real data collected on grids in western North ( l& r" x- r# L
America, Australia, Italy and Mexico.3 M/ z6 ^7 [# T
Inter-area Oscillations in Power Systems: A Nonlinear and Nonstationary 9 Z0 m" z! ~2 M1 _
Perspective is a comprehensive, systematic account of current analysis $ Q3 Z- r) o' ~: D! M2 n3 nmethods in power system oscillatory dynamics in both time and frequency * ^6 E9 v4 N, G' @domains ranging from parametric and non-parametric signal processing ! J) M' |. z I/ B; g
methods, to data-driven time-series models and statistical approaches./ M9 k2 e$ x1 S# R/ S4 C! V
Table of Contents # x3 U, ]% t( f! R* PContents( q: X( S6 C3 p& d1 y
6 l& J _5 ^9 \9 k8 ^% K( E1 Signal Processing Methods for Estimating Small-Signal Dynamic8 y4 v& |3 r; _) x5 k, r
Properties from Measured Responses. . . . . . . . . . . . . . . . . . . . . . y4 d/ Q6 ~' R" ?! ~; S. . . . 14 l8 h9 H+ t* r2 S; C8 Y3 c6 ^# G
Daniel Trudnowski and John Pierre ) H$ Z% ]1 z( v4 R, W& S6 x' h1 M3 w; l+ v
- D- X# T$ A! w# D; x! W" j7 P2 [7 k& ] \
+ G2 e. E2 x0 j' a" T7 f/ n
2 Enhancements to the Hilbert朒uang Transform for Application to# ^) e; S1 c. J! {7 e
Power System Oscillations . . . . . . . . . . . . . . . . . . . . . . . . . 1 C5 [3 y v- {" f8 X
. . . . . . . . 37 - w2 L5 @' G( z+ M* m: jNilanjan Senroy4 s2 ?6 P! h6 E4 t8 S' ]
, l6 X. a' Z- G% ~) u
3 Variants of Hilbert朒uang Transform with Applications to Power 7 B& r! I. q7 d. R3 H8 gSystems?Oscillatory Dynamics . . . . . . . . . . . . . . . . . . . . . . . % U8 G4 l) W$ I* B. . . . . . 63) {& ~7 N, {1 g0 N
Dina Shona Laila, Arturo Roman Messina, and Bikash Pal & D7 z) R7 P2 Y8 F, @& e2 B; Q8 b3 u " ]( c( i5 N9 t# G4 Practical Application of Hilbert Transform Techniques in Identifying 3 G1 M0 B( G5 ]' ^& ~Inter-area Oscillations . . . . . . . . . . . . . . . . . . . . . . . . . . . q6 K/ \0 q5 k# W0 x
. . . . . . . . . . 101+ `, ?) N7 w6 H/ _
T. J. Browne, V. Vittal, G.T. Heydt, and Arturo Roman Messina8 X0 E3 I, X% e+ F8 @: w) h
# `! o: H. Y) ?* j
5 A Real-Time Wide-Area Controller for Mitigating Small-Signal 2 c' m( E8 x0 G* g$ _5 V4 k6 BInstability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . * _/ q8 a4 N7 m5 N; ]1 C" X
. . . . . . . . . . . . . . 127 ! n0 h( e# S" q# sJaime Quintero and Vaithianathan (Mani) Venkatasubramanian A% R4 \# h/ |" h9 a* P* o 1 N7 }- O! H& }, {3 m6 Complex Empirical Orthogonal Function Analysis of Power System8 s+ v' s$ @ {) S2 t
Oscillatory Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 h$ H5 l, B# E) q1 @2 M. . . . . . . . . . 159. y9 V' E( d) R L5 k6 O0 Y! O1 ]
P. Esquivel, E. Barocio, M.A. Andrade, and F. Lezama8 ^1 A8 Q$ @# U- f2 L" A( o
]8 g$ u! Z( @! U5 p; W
7 Detection and Estimation of Nonstationary Power Transients . . . . . . 189! a' a: V+ s5 E5 Z) f
Gerard Ledwich, Ed Palmer, and Arindam Ghosh6 t9 v" a' ^7 l1 {0 q