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第三版目录。, B& N9 L! L' {$ D
1 Introduction 1
; ]4 {! q- h- G" X8 K# Z1.1 Purpose of the Course / 1
4 k7 w0 H2 u, `$ ? N3 D# m" n8 B1.2 Course Scope / 2
- Q. r, C; p& W+ m( F |. F1.3 Economic Importance / 2* a8 P0 W' H: g' Z& q
1.4 Deregulation: Vertical to Horizontal / 3
0 j! r; ?$ }8 r: z1.5 Problems: New and Old / 3* ~* ?, \' f$ g! W }* H
1.6 Characteristics of Steam Units / 6. g: b) i5 {; C7 Q# p9 N- Y
1.6.1 Variations in Steam Unit Characteristics / 10
$ j" ~5 M* g* J, g1.6.2 Combined Cycle Units / 13
, P6 f% D. z4 y0 } t) i1.6.3 Cogeneration Plants / 14
- Y+ Q2 \ L/ B* b# K1.6.4 Light-Water Moderated Nuclear Reactor Units / 17/ V6 j0 L) X4 i. M
1.6.5 Hydroelectric Units / 18
. x; h! d2 A+ _1 w: f1.6.6 Energy Storage / 21
) K: V- v1 E3 s( F/ @0 {3 L9 M1.7 Renewable Energy / 22
; A& i+ T/ H3 @! Y! H# f1.7.1 Wind Power / 23% G; B# f4 `5 |$ ` D$ {1 b+ v
1.7.2 Cut-In Speed / 230 H( d& R/ T9 m6 S+ m
1.7.3 Rated Output Power and Rated Output Wind Speed / 24
# I- \- t2 |) J" [/ o- X1 H1.7.4 Cut-Out Speed / 24
' y; S6 h' B s1.7.5 Wind Turbine Efficiency or Power Coefficient / 24
0 F3 L: c. ` |# Q* C1.7.6 Solar Power / 25
7 V l' @ E, HAPPENDIX 1A Typical Generation Data / 26: p8 J$ T9 q: [. o# k
APPENDIX 1B Fossil Fuel Prices / 286 g2 P! W) T4 @' M& ]% m; t. z& D
APPENDIX 1C Unit Statistics / 29# y, G# ^/ p8 R M* ~* h" `1 g
CONTENTS
* i; u8 y* ^/ n1 u1 m0 Jviii contents' l4 K! q9 _7 A! m7 L
References for Generation Systems / 31
! z* k. N2 E7 d8 U9 |/ y$ A! sFurther Reading / 31# e* b) y, M/ O- W2 z' J$ j: u
2 Industrial Organization, Managerial Economics, and Finance 35+ p5 \9 a( R. P5 {5 |8 j
2.1 Introduction / 35
; G& p. D( K& J- ^" N$ e2.2 Business Environments / 36 ? L/ \8 f) o# ]* f2 U6 i
2.2.1 Regulated Environment / 37
1 S/ f/ p+ ~- F* R R* L/ @; E) M2.2.2 Competitive Market Environment / 38+ y. Z3 { B2 m# T3 l3 i
2.3 Theory of the Firm / 40
# L/ K' X/ g3 z- T s& ]2.4 Competitive Market Solutions / 42
5 ~) }+ `* N& U, X8 j- E$ C$ k% O% C2.5 Supplier Solutions / 45
6 O. d! s5 m) ~1 X2.5.1 Supplier Costs / 46! k) ` y( p) ]1 g, c
2.5.2 Individual Supplier Curves / 465 l$ f1 B. r% ~3 ^' s
2.5.3 Competitive Environments / 47
/ T+ o% r* i$ A @1 \9 H% t$ L" }2.5.4 Imperfect Competition / 51
9 D9 i+ k9 O: q5 p2 c6 T; {! F$ @2.5.5 Other Factors / 52% P, _' b: y& Z0 j5 P% A
2.6 Cost of Electric Energy Production / 53# R: `0 |# x6 D( t) T" \" W
2.7 Evolving Markets / 54
7 ?' b7 o: B7 z# u5 ~: q8 N( r; e2.7.1 Energy Flow Diagram / 577 G3 a# K" M9 n V4 a
2.8 Multiple Company Environments / 58+ H+ _$ h6 T1 W P5 D+ h! \/ |
2.8.1 Leontief Model: Input–Output Economics / 58+ ^. t% X! j; }9 y7 K# p2 {
2.8.2 Scarce Fuel Resources / 60
2 W; {2 R* o- R* [7 v2.9 Uncertainty and Reliability / 61
3 V8 i! ~( o5 n+ j, h3 ?0 L LPROBLEMS / 61
! _' Q, ^( ?7 A6 F& S7 w, Y) ]$ sReference / 62$ s# `- w# u" A
3 Economic Dispatch of Thermal Units and Methods of Solution 63
, {( R. R% T: C9 a+ f3.1 The Economic Dispatch Problem / 63
! Z, M+ ~4 r+ C( T& K3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68
5 v# m" d7 E8 N. | i4 z" N. C3.3 LP Method / 69' W- L6 W3 S8 {
3.3.1 Piecewise Linear Cost Functions / 69
+ u, L( I2 D0 G/ E. [3.3.2 Economic Dispatch with LP / 71" M) t9 N( {* z4 V" L e1 B
3.4 The Lambda Iteration Method / 73" J. V! Q* R; ?" d* L% K. r, W
3.5 Economic Dispatch Via Binary Search / 76
- F: [$ Z# s; A" P3.6 Economic Dispatch Using Dynamic Programming / 78 D4 l6 i" B! [/ t4 ?; q' u
3.7 Composite Generation Production Cost Function / 81
7 l6 v* v* ]3 K5 O. {0 u% R. @% ?7 Z3.8 Base Point and Participation Factors / 85
# k: [5 R+ [# e% U) ]" A7 n! A3.9 Thermal System Dispatching with Network Losses* { a- R/ B4 p/ ?1 l) q3 f7 R
Considered / 88* O/ X. Z' o# w, \; H
contents ix
& I& |* O5 f( i9 j4 @ l1 q& ]& u3.10 The Concept of Locational Marginal Price (LMP) / 92) W& A; E6 G5 V4 s: X
3.11 Auction Mechanisms / 959 P; P m; a a& j9 M" r: c
3.11.1 PJM Incremental Price Auction as a3 d8 E% L# g x1 e
Graphical Solution / 95
) K0 _. F- B0 H3.11.2 Auction Theory Introduction / 98# [' E5 \; X- x" f/ j" B
3.11.3 Auction Mechanisms / 100) T7 D- h+ ]* Y+ \
3.11.4 English (First-Price Open-Cry = Ascending) / 101& d$ {! x! K/ I0 O5 {1 S! y/ g
3.11.5 Dutch (Descending) / 103' O; N7 b% u$ y- w5 i. e; J
3.11.6 First-Price Sealed Bid / 104
# j; ^- j( M: Z/ y3.11.7 Vickrey (Second-Price Sealed Bid) / 105
, T! W2 G* C5 I6 B$ G3.11.8 All Pay (e.g., Lobbying Activity) / 105
( s/ ?2 |5 n0 W0 L$ T' m- K4 d( W' s# PAPPENDIX 3A Optimization Within Constraints / 106
$ `- |) N' V5 B3 S" MAPPENDIX 3B Linear Programming (LP) / 117; ]* g. r6 P( \( r; a z
APPENDIX 3C Non-Linear Programming / 1283 J+ V1 Z9 K# Z. e5 n: O; `6 }- M
APPENDIX 3D Dynamic Programming (DP) / 128
/ ]& S" U* u# q' B8 @& s9 Q3 {APPENDIX 3E Convex Optimization / 135( P! E" y, O8 }
PROBLEMS / 1383 a+ _( y# [2 y: O! [& I A6 @
References / 146
! e! F% V' d' _- m/ G( b4 Unit Commitment 147. b$ U# }. T/ Z) o* O) n* X3 }6 c7 b
4.1 Introduction / 147
# H) ~ `7 S0 X5 y- m* j4.1.1 Economic Dispatch versus Unit Commitment / 147
y# x5 |% D4 X G% M# Q4.1.2 Constraints in Unit Commitment / 152
( ?( V2 k: E( c" u) [4.1.3 Spinning Reserve / 152* l3 R y- A6 ^: D+ C
4.1.4 Thermal Unit Constraints / 153* y* `0 H9 [; l- t, l0 [
4.1.5 Other Constraints / 155
; |, M0 N1 h$ `; `3 w2 }5 {% {4.2 Unit Commitment Solution Methods / 1555 e6 Y( U& i4 [( o% ]: R
4.2.1 Priority-List Methods / 156. v4 R9 U1 y3 f& A7 O) s, t
4.2.2 Lagrange Relaxation Solution / 157
) }2 L" v I9 x% x: h4.2.3 Mixed Integer Linear Programming / 1667 b) T0 A ?! J8 D! `, B3 P. a
4.3 Security-Constrained Unit Commitment (SCUC) / 167$ h! {# E0 f( x, ~
4.4 Daily Auctions Using a Unit Commitment / 167
) X" O7 \; {# iAPPENDIX 4A Dual Optimization on a Nonconvex
3 g, M. Y8 N) b, U! @Problem / 167
* X" L' J0 I; {4 q7 ?0 }4 E3 vAPPENDIX 4B Dynamic-Programming Solution to
* I6 n+ p3 W6 h* A+ VUnit Commitment / 173
. [& \/ v( m+ C; ?$ L4B.1 Introduction / 173
( E% m/ ?2 J8 K) j. C4B.2 Forward DP Approach / 1745 _! q& A! I: n. B7 N& | L/ o2 D
PROBLEMS / 1825 p E4 y* e9 l
x contents# I: ?" K; K3 f v# c
5 Generation with Limited Energy Supply 1876 y3 u- j( @, m4 ^1 K @
5.1 Introduction / 187
, n6 [/ M- f2 D" O5.2 Fuel Scheduling / 188% T: X% b& V! L4 Q
5.3 Take-or-Pay Fuel Supply Contract / 188
( }+ h1 R% v" ~7 r5.4 Complex Take-or-Pay Fuel Supply Models / 194
' ?: x( s5 H( t" W# P8 n# X5.4.1 Hard Limits and Slack Variables / 1943 o% S: F4 Q( i: g6 l, H# U: L
5.5 Fuel Scheduling by Linear Programming / 195
: j0 [6 {& Y6 w2 m0 {5.6 Introduction to Hydrothermal Coordination / 202
/ C" w2 j) Y! ^% R: ^" g5.6.1 Long-Range Hydro-Scheduling / 203- U9 w p, z3 z2 Z: O$ A- Y
5.6.2 Short-Range Hydro-Scheduling / 204
1 Q* m+ T" \2 W: K( B! g$ E5.7 Hydroelectric Plant Models / 204
2 I& {5 S) p3 R3 p% X! a& g+ ?8 ^5.8 Scheduling Problems / 207
- _1 M( Y3 M. P. A( }5.8.1 Types of Scheduling Problems / 207
2 |1 N! H% q, ?5 w5.8.2 Scheduling Energy / 207- u( ^- b1 _/ V
5.9 The Hydrothermal Scheduling Problem / 211# J; j0 p* j) W8 K' r4 h2 z# F `
5.9.1 Hydro-Scheduling with Storage Limitations / 211
. S) V4 u2 c( r i) F5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
2 U1 K' n: F$ d. O! H5.9.3 Pumped-Storage Hydroplants / 218
- O2 w5 u: d, ?) f4 T$ d m& R; I3 ^# J5.10 Hydro-Scheduling using Linear Programming / 222
- u! o' O% a; r0 u2 y; V- @APPENDIX 5A Dynamic-Programming Solution to hydrothermal8 Z* H& t' S2 d: A# O7 ]
Scheduling / 225, a3 J% t% k* v8 ?8 h& o& X" c7 o/ P2 R
5.A.1 Dynamic Programming Example / 227
* @. G( @3 o- @3 Z; [# e- J5.A.1.1 Procedure / 228
& \9 P$ k v% _5.A.1.2 Extension to Other Cases / 231
( \. G) Q6 M ]/ `) B) z3 v5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant; c9 a9 s- J2 n9 e* o
Problem / 232, \: Q( @- Z7 n' g, v" W
PROBLEMS / 234
9 x9 T' ~! I: M' N- w+ i6 O6 Transmission System Effects 243
% N5 r3 \% g- m) n4 i- y' [6.1 Introduction / 243
& [: B% V1 t$ d* Z5 u, c2 G4 c6.2 Conversion of Equipment Data to Bus and Branch Data / 247
& d9 a! c9 W& E9 { u6 i7 h6.3 Substation Bus Processing / 248
$ x" e# ^! H' [6.4 Equipment Modeling / 248
( i$ G. v4 _; y; A: C% R7 {" L3 ?5 V6.5 Dispatcher Power Flow for Operational Planning / 251& r, _6 |$ Q; F, ~
6.6 Conservation of Energy (Tellegen’s Theorem) / 252
8 H/ b; l: k8 j S4 h/ }1 v8 m6.7 Existing Power Flow Techniques / 2535 A0 |4 Q5 }1 k0 X
6.8 The Newton–Raphson Method Using the Augmented' }) ~, v3 M6 G, x
Jacobian Matrix / 254
& N, C S* S! P" r. j1 U r6.8.1 Power Flow Statement / 254, X5 H2 z4 B6 p( d3 @, k9 B2 ^4 y
6.9 Mathematical Overview / 257% n1 X) G! F' g% l
contents xi0 z) [; A5 P; N) P' ^; c
6.10 AC System Control Modeling / 2596 F9 Z0 V2 X* F$ `' h" {
6.11 Local Voltage Control / 259
( v1 v8 f+ P! E1 Y, c( k1 I' ]1 u# R6.12 Modeling of Transmission Lines and Transformers / 259
; \0 E, D; F( s; j8 j/ D9 h: O6.12.1 Transmission Line Flow Equations / 259! m! `# a) ~( T. }' p
6.12.2 Transformer Flow Equations / 260
: s) A1 |# k! ~- T7 w" {: A6.13 HVDC links / 261) `! P# n6 O0 Z. e! f
6.13.1 Modeling of HVDC Converters
, v; K6 V, ~& ?2 M* vand FACT Devices / 264/ h9 ^) a7 B8 c' c6 l6 r" s2 R& t0 A
6.13.2 Definition of Angular Relationships in
. x# X+ T3 M+ u& t# D7 X( vHVDC Converters / 264
" l+ g& g( p, d7 W" `+ L6.13.3 Power Equations for a Six-Pole HVDC
; D1 Q: j5 R, T! {% YConverter / 2646 x/ G& _4 `' @2 Y" J0 }/ i* Z
6.14 Brief Review of Jacobian Matrix Processing / 2676 _% E# f- X& X. R
6.15 Example 6A: AC Power Flow Case / 269
7 _* P0 ?9 C: A0 F" p6.16 The Decoupled Power Flow / 271/ p: k, a) {" J5 N
6.17 The Gauss–Seidel Method / 2755 o. \: P# v2 Q: x, u% A7 i9 y
6.18 The “DC” or Linear Power Flow / 277
, b4 N1 S, \# P) |6.18.1 DC Power Flow Calculation / 277, M( U: k/ p, x
6.18.2 Example 6B: DC Power Flow Example on the' b$ b1 b5 W: }& K3 E( w. M8 L
Six-Bus Sample System / 278
* j) @1 E' m" N9 i6.19 Unified Eliminated Variable Hvdc Method / 278, q" A2 Z# ~6 d6 Y8 y. `$ I
6.19.1 Changes to Jacobian Matrix Reduced / 279
! D! F+ s1 K4 x- t3 A6.19.2 Control Modes / 280+ ~' |/ ]1 s) i- Q
6.19.3 Analytical Elimination / 280
; T3 L$ |$ H# J' D9 `6.19.4 Control Mode Switching / 283* `; y$ J* Y. W+ W
6.19.5 Bipolar and 12-Pulse Converters / 283+ P! @7 S4 q P8 d
6.20 Transmission Losses / 284/ U1 m0 E7 \2 r' Y4 w" S3 f! L
6.20.1 A Two-Generator System Example / 284! d; B4 j& u$ \! E
6.20.2 Coordination Equations, Incremental Losses,( o6 ?( c; x% |. i* F
and Penalty Factors / 2866 Z- i' I z1 j% B- d8 K; X
6.21 Discussion of Reference Bus Penalty Factors / 2889 o) @# T: @3 ]8 e0 _& `4 Y
6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
; `9 m* |. a" J Q# |: gPROBLEMS / 291. w6 q8 z4 X" V3 |: W% }* \
7 Power System Security 296
$ U0 ~. v7 e2 g7.1 Introduction / 296- P& Q: \% l) _4 R# F3 X( m
7.2 Factors Affecting Power System Security / 3019 ? ?- {1 Z" |9 c, k, o
7.3 Contingency Analysis: Detection of Network Problems / 301$ g; D2 U- y: W, C4 s: F
7.3.1 Generation Outages / 3019 a% D* Q3 a' O) f
7.3.2 Transmission Outages / 3028 r, `0 F1 F5 m. T- _5 Y/ p
xii contents
1 k# W( s t# }2 [9 |8 F7.4 An Overview of Security Analysis / 306
$ L8 S9 d; @2 Y* _! D6 d7.4.1 Linear Sensitivity Factors / 3073 E: F' \. R, Y+ I; r1 K
7.5 Monitoring Power Transactions Using “Flowgates” / 313# |2 U2 A' m3 ]
7.6 Voltage Collapse / 315# }+ K& D, p, r$ W
7.6.1 AC Power Flow Methods / 317
! E* j6 M0 p7 g. C2 ]: V7.6.2 Contingency Selection / 320
5 E5 p0 I( d2 k& c6 N4 I: s' [" F& @7 l( @7.6.3 Concentric Relaxation / 3235 D6 Q* u8 W6 n0 z: _. Q5 q$ k& n
7.6.4 Bounding / 3250 B7 v1 b: O/ }8 J
7.6.5 Adaptive Localization / 3259 d0 p1 {4 J- Z c) B
APPENDIX 7A AC Power Flow Sample Cases / 327
5 B9 _3 {) s. M9 ?; B. bAPPENDIX 7B Calculation of Network Sensitivity Factors / 336
7 \7 v% S9 s1 x: Y& F7B.1 Calculation of PTDF Factors / 3367 ~+ T7 z& e7 r0 l6 W( E
7B.2 Calculation of LODF Factors / 339+ j& w. c* t6 t& E" {) P" H
7B.2.1 Special Cases / 341
9 s6 d0 P% z( [2 ~& H- z- w7B.3 Compensated PTDF Factors / 343
( d0 \( ?" S, X. y& DProblems / 3436 a0 |: a# R- [) E+ ^8 l2 ]9 Q( v
References / 3497 G1 f. N3 V! Z0 l B" y
8 Optimal Power Flow 350
8 ]& m9 c0 _$ D/ S/ z( I! C8.1 Introduction / 350 V" v4 v3 k0 a6 a. G2 {* ~3 x4 N
8.2 The Economic Dispatch Formulation / 351
- z2 j8 s' _: Z, S3 s8.3 The Optimal Power Flow Calculation Combining; u k8 p7 `! {7 \* M
Economic Dispatch and the Power Flow / 352- C" v* i, I! x1 l- j3 v
8.4 Optimal Power Flow Using the DC Power Flow / 354' W0 z" \4 N# D. W$ x5 y; V% a
8.5 Example 8A: Solution of the DC Power Flow OPF / 356
4 T; o+ `1 ?+ L" ?0 l8 h" V8.6 Example 8B: DCOPF with Transmission Line
& x, H/ A" `5 Y& I$ w% w7 @+ ?; iLimit Imposed / 3619 w9 D- G/ O! U9 |
8.7 Formal Solution of the DCOPF / 365/ {* {% N8 |2 w6 y# v) A, A1 A
8.8 Adding Line Flow Constraints to the Linear
5 `7 ^/ w8 k! r! F G+ WProgramming Solution / 365
! m$ U1 {6 b0 u0 \$ k0 e( m8.8.1 Solving the DCOPF Using Quadratic Programming / 367
) G+ ^0 M3 n: s8.9 Solution of the ACOPF / 368; ]9 Q* p& R, g7 s/ v
8.10 Algorithms for Solution of the ACOPF / 369
! u, D* g& J7 v) J$ D1 q" o+ q/ [; E8.11 Relationship Between LMP, Incremental Losses,5 c3 ^0 o" Z, h- O( A& v) D
and Line Flow Constraints / 376
5 z! y$ b! m3 v8.11.1 Locational Marginal Price at a Bus with No Lines
: E0 Y0 {( F3 oBeing Held at Limit / 377
( [4 m5 D! a; Y: p+ I9 j4 r) I5 {8.11.2 Locational Marginal Price with a Line Held at its Limit / 378+ g, O' m6 v4 T8 c1 n5 {
contents xiii# K# r% X6 P0 y1 G6 o. U% ~
8.12 Security-Constrained OPF / 3823 ~8 s3 w" o$ ^: r$ V
8.12.1 Security Constrained OPF Using the DC Power Flow
& b" V) K6 S) z" ]9 L: Oand Quadratic Programming / 384
F6 f7 U# G4 m; e, J, A8.12.2 DC Power Flow / 3858 H+ I& _* J* ?" D
8.12.3 Line Flow Limits / 385! q; c, w, Q; C+ V$ ~6 N' R
8.12.4 Contingency Limits / 3861 `3 H' M, \0 L- K
APPENDIX 8A Interior Point Method / 391
, h% }& _+ f* P/ z. \APPENDIX 8B Data for the 12-Bus System / 3938 u/ q7 A2 o& x
APPENDIX 8C Line Flow Sensitivity Factors / 395
' r5 ?" c! J& s+ c- C+ _APPENDIX 8D Linear Sensitivity Analysis of the% M' n- A" W+ ~. {# c& Y
AC Power Flow / 397% P& p$ s& g. ~. U
PROBLEMS / 399
/ L8 V' J; D7 O9 Introduction to State Estimation in Power Systems 403
0 e O; ^+ s }4 `- q2 K. [9.1 Introduction / 403
7 O! G8 ~; H8 W6 L5 u% l9.2 Power System State Estimation / 404
9 p7 W$ y4 T$ {6 Y1 x$ ~9.3 Maximum Likelihood Weighted Least-Squares w$ ?! b, V% E6 D( {6 B
Estimation / 4087 |, p# p2 W/ M9 ~- w. B: y
9.3.1 Introduction / 408
3 J$ P G5 b. t" k9.3.2 Maximum Likelihood Concepts / 410, Z# d& d( q" [) p. k/ L, g
9.3.3 Matrix Formulation / 414, P( Z: _9 I! U
9.3.4 An Example of Weighted Least-Squares# V% b, q3 q! _
State Estimation / 417% R4 h7 V: h5 X
9.4 State Estimation of an Ac Network / 421" c7 Q2 J# ` p, Q" L" P) s
9.4.1 Development of Method / 421
, J) o$ j* l) B- h" M# F9.4.2 Typical Results of State Estimation on an
2 {/ H# s2 J9 {7 O3 _/ LAC Network / 4247 X0 h/ |$ o* d& V
9.5 State Estimation by Orthogonal Decomposition / 428: _) g8 _# P& \9 \
9.5.1 The Orthogonal Decomposition Algorithm / 431
+ p1 X9 t' a1 k7 J9.6 An Introduction to Advanced Topics in State Estimation / 435+ c" H: c" U" i8 r( @- o
9.6.1 Sources of Error in State Estimation / 4358 K# R3 d m: f* J, @& }5 d a
9.6.2 Detection and Identification of Bad Measurements / 436
f% C9 j9 n% ^& X% V( ~9.6.3 Estimation of Quantities Not Being Measured / 443
) J1 u9 _6 K- `, e; C: c9.6.4 Network Observability and Pseudo-measurements / 444: d' P z6 K+ a4 e
9.7 The Use of Phasor Measurement Units (PMUS) / 447
+ O3 M: P# g) b6 m1 r9.8 Application of Power Systems State Estimation / 451
4 K5 t! L/ N1 g0 ]5 }3 Y9 j9.9 Importance of Data Verification and Validation / 454
1 k$ F5 R& I+ p( L* P/ p5 v9.10 Power System Control Centers / 4543 z8 z% l& S$ `+ |5 n' W
xiv contents
X9 A9 s' a) j. v0 CAPPENDIX 9A Derivation of Least-Squares Equations / 456) O. |8 t" E/ y" n
9A.1 The Overdetermined Case (Nm > Ns) / 457
# H7 k; h9 ]( I' D: }9A.2 The Fully Determined Case (Nm = Ns) / 462
$ d1 {+ j+ ]5 z1 m( r( ~9A.3 The Underdetermined Case (Nm < Ns) / 462, f6 t, Y5 ~; y" ], Z
PROBLEMS / 464
8 C% s; {+ s: G10 Control of Generation 468& {% e' \, x% \" S. J
10.1 Introduction / 468+ P1 G7 Q `, @
10.2 Generator Model / 470. Z/ a. E, B+ O
10.3 Load Model / 4732 m$ f- D+ P; ]
10.4 Prime-Mover Model / 475. H& T% E7 B: `# x3 s' h
10.5 Governor Model / 476
* H/ X' d* }3 w! P9 g+ q10.6 Tie-Line Model / 481
8 K( A i& v2 C$ R# D10.7 Generation Control / 485: `5 n+ v' g3 z0 I
10.7.1 Supplementary Control Action / 485# E4 h: o! ?5 V5 ]) R
10.7.2 Tie-Line Control / 486
" Q9 G5 P E6 V& u7 W10.7.3 Generation Allocation / 489
+ M! s* N+ m* z; P: ]10.7.4 Automatic Generation Control (AGC)
) ~5 V$ `- G$ BImplementation / 491; B3 `' K- y% E& T- N& m
10.7.5 AGC Features / 4951 O6 }: p1 A$ i- u' N v
10.7.6 NERC Generation Control Criteria / 496$ c% P2 i( i* X- ]$ M) g1 _9 h' X# k
PROBLEMS / 497
: i: L3 w: C/ g' u. [1 mReferences / 500. v6 b8 G* J* }. u$ T' O
11 Interchange, Pooling, Brokers, and Auctions 5016 |. f- `% A2 Z5 t$ z) O
11.1 Introduction / 501: ~( d0 [8 d9 d- W: n, ^ A
11.2 Interchange Contracts / 504% u. u, U* m5 v0 S. D5 {; b' v7 U
11.2.1 Energy / 504
' X6 p) \: [9 U8 M. U11.2.2 Dynamic Energy / 506( D# F! b' k* I5 d( r0 Q5 n; w' o
11.2.3 Contingent / 5066 N, h8 \9 r" J, Z. |( F
11.2.4 Market Based / 507; V0 E; i' K% u( l3 t- Y
11.2.5 Transmission Use / 5089 q/ ]2 F4 ]3 }. U
11.2.6 Reliability / 517
. i: }& ^8 i3 i6 L11.3 Energy Interchange between Utilities / 5177 k) i7 k$ a3 T8 F4 l7 y
11.4 Interutility Economy Energy Evaluation / 521, R4 u1 c N8 N9 p- k: R8 a: r7 y
11.5 Interchange Evaluation with Unit Commitment / 5223 S+ W6 O& F1 O/ J* \
11.6 Multiple Utility Interchange Transactions—Wheeling / 523
0 G0 I0 w7 w/ D( b8 X6 c6 I* P11.7 Power Pools / 526* F) ^- _& { ]5 j0 |
contents xv
6 R3 V; b$ V9 N5 A# Z6 g11.8 The Energy-Broker System / 529
! o; n/ y! @9 t l4 \- B) P2 B11.9 Transmission Capability General Issues / 533
, x% E$ X, a2 @$ U5 q11.10 Available Transfer Capability and Flowgates / 535
6 j+ p$ M' j) C- a# H9 M, _11.10.1 Definitions / 536
8 h) E) y2 T, a$ A. }11.10.2 Process / 539; n+ Q5 [0 f% N1 f) M
11.10.3 Calculation ATC Methodology / 5400 O3 N% d& L& a8 z! m
11.11 Security Constrained Unit Commitment (SCUC) / 550
a6 d+ X6 P2 A. F9 Q/ Z11.11.1 Loads and Generation in a Spot Market Auction / 550
2 {$ H S4 \) B& G11.11.2 Shape of the Two Functions / 5525 W# n% t+ p9 u, T# s# P" |' p
11.11.3 Meaning of the Lagrange Multipliers / 553 s' Q% S" t- ^1 z) @, b
11.11.4 The Day-Ahead Market Dispatch / 554
: W0 t! A6 Z# m7 w0 g9 r11.12 Auction Emulation using Network LP / 555
' D& n% [8 ~# ]! c0 @$ I0 `11.13 Sealed Bid Discrete Auctions / 5555 q* L3 R# f3 z3 i
PROBLEMS / 560
/ r, _$ d$ t/ M% f12 Short-Term Demand Forecasting 566
: c9 i8 A6 q7 F' l12.1 Perspective / 566
# c$ A0 V9 B. Q0 R; p/ l12.2 Analytic Methods / 569
+ ^- O+ G2 G o0 G# j9 [12.3 Demand Models / 571
5 D7 E+ w5 x" G) ]* }12.4 Commodity Price Forecasting / 5720 l) G7 q, y- S, i/ S4 {
12.5 Forecasting Errors / 573
" U3 Z n3 h# t$ o- v$ n12.6 System Identification / 573
8 j$ \( e/ ^1 c* Z/ o/ n5 q12.7 Econometric Models / 574
+ _, b: r' P6 I; m" i# y12.7.1 Linear Environmental Model / 574) I5 E+ |% O/ A6 f
12.7.2 Weather-Sensitive Models / 576
& Z+ c% K! Q# c2 E; u12.8 Time Series / 578) e2 ]! h# l- e8 ^5 F6 A4 h, [
12.8.1 Time Series Models Seasonal Component / 578
9 |6 T: x. \& ]; M7 ^$ F12.8.2 Auto-Regressive (AR) / 580
; i; [2 K. c, l; @' Z$ H12.8.3 Moving Average (MA) / 581. }( l/ ~3 P3 T% n9 m+ o
12.8.4 Auto-Regressive Moving Average (ARMA):1 P7 f% p2 P G/ e6 j; J9 }" y
Box-Jenkins / 582: Y1 _' v9 D l/ d: J
12.8.5 Auto-Regressive Integrated Moving-Average
2 L6 B7 q7 B/ Q2 Z5 y(ARIMA): Box-Jenkins / 5846 {6 e/ i5 h/ c" X2 W0 D
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585& F" e7 ?* H$ ~
12.9 Time Series Model Development / 585* x9 Y" L7 Q6 E2 \
12.9.1 Base Demand Models / 586
8 \) f" x+ d0 ^* J' |8 N12.9.2 Trend Models / 586, F! N; A' k) `- q2 m( @
12.9.3 Linear Regression Method / 586
. k* n- Z4 g- P$ P) w9 l, Wxvi contents% G) v' a3 {5 ~8 ]5 o1 N0 p. Q
12.9.4 Seasonal Models / 588
) y- p9 `/ f. Q: V) M- f0 n/ F- G12.9.5 Stationarity / 588
! U) f. U5 Z& S& x F( y12.9.6 WLS Estimation Process / 590
* A Y3 Y, m' g0 X! ?8 Z( q, S$ a12.9.7 Order and Variance Estimation / 591) r3 @; o6 l6 M
12.9.8 Yule-Walker Equations / 5923 T* X5 s( {5 U6 N" J
12.9.9 Durbin-Levinson Algorithm / 595
4 t! ?& {4 S% t8 Q12.9.10 Innovations Estimation for MA and ARMA
/ k1 s$ Y5 T$ h" y7 mProcesses / 598$ b7 {2 m! ]; ~
12.9.11 ARIMA Overall Process / 600, a) B8 Q1 h9 [5 [
12.10 Artificial Neural Networks / 603" D# m( Y6 u) }$ `
12.10.1 Introduction to Artificial Neural Networks / 604- M$ _# A8 ?; [- H6 N$ q. u
12.10.2 Artificial Neurons / 6051 x4 x0 d" u' i+ f6 l- I( g
12.10.3 Neural network applications / 606% L% `5 \+ t( c
12.10.4 Hopfield Neural Networks / 606" v5 R }, b! @! k0 b/ Z1 B
12.10.5 Feed-Forward Networks / 607% U0 F! b6 y5 p; j0 p' w
12.10.6 Back-Propagation Algorithm / 610
. z7 Z+ \, H' U12.10.7 Interior Point Linear Programming Algorithms / 613( _6 K- j9 c& W- P# n
12.11 Model Integration / 614
1 E6 d9 i/ u* n: j12.12 Demand Prediction / 614
0 B; \; y) h# X& F12.12.1 Hourly System Demand Forecasts / 6156 U8 V! ], R& O) c3 B% O1 ?% {* e
12.12.2 One-Step Ahead Forecasts / 615
2 H2 @7 c+ N1 ~1 Q12.12.3 Hourly Bus Demand Forecasts / 616- ~. B5 o: z- f2 N* J5 O
12.13 Conclusion / 616
0 x& E+ ^- J3 U7 Z" [1 UPROBLEMS / 617 |
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