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第三版目录。1 \6 O# j. j+ b2 W5 N9 k0 U
1 Introduction 1/ l- e2 s# B2 R# c# M k
1.1 Purpose of the Course / 1
% E3 Z4 G6 q5 ^4 t B0 S2 L1.2 Course Scope / 2
" q' c. i6 ?' Y F% u( H1.3 Economic Importance / 2
& r( U. R: \4 p1 `' C- r2 U9 ^1.4 Deregulation: Vertical to Horizontal / 3
2 m; V: i% d- A' K: B% `1.5 Problems: New and Old / 3
$ W! h. r1 g: a6 @6 \6 y1 u' U' A1.6 Characteristics of Steam Units / 6) p2 ]7 z9 [5 \7 g1 c
1.6.1 Variations in Steam Unit Characteristics / 10
3 a; F( i r; f9 u) r/ j& B' x1.6.2 Combined Cycle Units / 13
$ P& n8 W+ V x+ d9 M1 q1.6.3 Cogeneration Plants / 14
, c% _- u6 K7 B P/ m7 S1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
' ]' B% i4 P' Y& n8 Q4 |1.6.5 Hydroelectric Units / 18/ y5 C# A* v" C
1.6.6 Energy Storage / 21
\, a/ z( ]! M, ?. K1.7 Renewable Energy / 22/ e0 ]8 B7 x7 }+ v
1.7.1 Wind Power / 23
) {9 j# L5 y3 |; i1.7.2 Cut-In Speed / 23
3 K5 a/ G( ~# h" D1.7.3 Rated Output Power and Rated Output Wind Speed / 24
& q& `9 j5 E7 c q F1.7.4 Cut-Out Speed / 24+ x- p" }; H. _8 v5 v
1.7.5 Wind Turbine Efficiency or Power Coefficient / 246 F- `. D7 K2 ?+ ?7 F: U3 \! _
1.7.6 Solar Power / 25# V4 y( u) d. z3 [
APPENDIX 1A Typical Generation Data / 264 q7 g v* x4 r) H2 ?4 |) f
APPENDIX 1B Fossil Fuel Prices / 28& j" G/ n8 z9 v' a
APPENDIX 1C Unit Statistics / 29
8 f) X+ t- k7 D; ~2 ~! R3 Y; ]: SCONTENTS* i1 \! c b4 h# V1 M
viii contents) W, }1 F# a9 O8 G2 G
References for Generation Systems / 31
6 ~' i* N4 H" u6 ^8 j( l) OFurther Reading / 31) `( l: j, i2 X9 h' x
2 Industrial Organization, Managerial Economics, and Finance 35+ L# j f0 \, ?% y: K. ?
2.1 Introduction / 35
1 U" B" L: S! F% T8 O* A0 J2.2 Business Environments / 362 `7 S* S& f2 J' o# d+ W$ I# l# q( e
2.2.1 Regulated Environment / 37 d+ B! w! f' f# E' ~% ?: }6 D6 W
2.2.2 Competitive Market Environment / 385 W' t; H0 B6 M, a% c }7 O, K
2.3 Theory of the Firm / 40: n' a; z2 `0 H; S
2.4 Competitive Market Solutions / 423 D4 i. C; i4 @1 f$ O- `
2.5 Supplier Solutions / 45
7 P" D5 z+ R+ c* k2 o2.5.1 Supplier Costs / 46
8 [, x! `" Q. Z4 H, I% P. P2.5.2 Individual Supplier Curves / 46* b( i' M2 G8 N
2.5.3 Competitive Environments / 47
4 i' A$ }, n1 O0 v2.5.4 Imperfect Competition / 51! f- F' N: G' A) m8 c( H' ^
2.5.5 Other Factors / 52* T9 j! \. z& `$ o) l
2.6 Cost of Electric Energy Production / 53
, m5 ?. q8 H; {% M; q, d2.7 Evolving Markets / 54
- J/ u$ q, t: C: G7 d$ I2.7.1 Energy Flow Diagram / 57
3 N% i$ R O# M7 l2.8 Multiple Company Environments / 58
. ]$ F1 n4 v6 B2 d6 `! w0 D" s; E2.8.1 Leontief Model: Input–Output Economics / 58
( ]* f3 l( I8 x, r$ ^2.8.2 Scarce Fuel Resources / 60- H" }1 p5 ~& { T; t: v3 l
2.9 Uncertainty and Reliability / 610 J/ c+ C' J2 b% z+ N* k
PROBLEMS / 619 P+ K+ t1 A' L# h. ~
Reference / 62
3 `4 {2 U, ]; J0 n) o1 c3 Economic Dispatch of Thermal Units and Methods of Solution 63; G: v5 D7 m4 t9 C, r
3.1 The Economic Dispatch Problem / 63
* U& P+ v1 {1 \4 \3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68
e8 S% d! D( c* N. ?3.3 LP Method / 69
' G f! `3 O' e: V+ |8 c6 k3.3.1 Piecewise Linear Cost Functions / 69/ F6 w% A+ ~8 W) L. f
3.3.2 Economic Dispatch with LP / 716 l# k/ G" I9 Z# j, G
3.4 The Lambda Iteration Method / 73
5 Q5 U0 j+ F0 ~. @& N% Y3.5 Economic Dispatch Via Binary Search / 76
# i- |1 V) ?4 _2 _3 @7 X3.6 Economic Dispatch Using Dynamic Programming / 78
/ S* |, y5 A" {8 _" Y3.7 Composite Generation Production Cost Function / 810 I7 e! ~/ }* Y, ^2 n7 S6 R
3.8 Base Point and Participation Factors / 85 q0 h( q3 w! Y
3.9 Thermal System Dispatching with Network Losses+ U; S( V8 {% Y e7 C* ?0 U: |- d
Considered / 88. K$ p$ |- n$ p
contents ix5 j e, F0 w' F7 T" Y" t8 w
3.10 The Concept of Locational Marginal Price (LMP) / 92
, H7 c% M1 d5 T1 ]. X' Z3.11 Auction Mechanisms / 95/ {3 [, o) i9 `1 L# X& |6 E- e; h
3.11.1 PJM Incremental Price Auction as a$ ~( H/ _* o, [& S- `! Y
Graphical Solution / 95
) r) z8 k" R) y7 O3.11.2 Auction Theory Introduction / 983 ~9 V+ ?7 M* B' W/ g3 W
3.11.3 Auction Mechanisms / 100
0 l4 b: w* K. p4 E+ i9 m3.11.4 English (First-Price Open-Cry = Ascending) / 101
! }9 }! s. F$ F; b! W/ I, _3.11.5 Dutch (Descending) / 1031 {( a1 Z0 x+ R; ~; j1 x
3.11.6 First-Price Sealed Bid / 104
7 E# O; s6 K z: O4 J, r4 N3.11.7 Vickrey (Second-Price Sealed Bid) / 105
& z8 I& {4 C: \, e* r3.11.8 All Pay (e.g., Lobbying Activity) / 105
) H. ]6 w3 X, A: F3 N4 p3 AAPPENDIX 3A Optimization Within Constraints / 106 ]) ?, V D8 \+ Z
APPENDIX 3B Linear Programming (LP) / 117
# [; w8 q2 @$ ]) bAPPENDIX 3C Non-Linear Programming / 128
$ `/ z5 u$ I5 X; x0 Q; kAPPENDIX 3D Dynamic Programming (DP) / 128
+ I, R6 `, T! r: U4 Y/ }APPENDIX 3E Convex Optimization / 135, e' W* B0 }% ^8 I
PROBLEMS / 138$ `( x0 m1 m1 e, V. N9 K6 T) _
References / 146
" s6 |. c: {( o Q! @ E0 g: C4 Unit Commitment 147
1 q- f S' Z2 X; `& Y4.1 Introduction / 147' i# j; h0 p! F) H# D
4.1.1 Economic Dispatch versus Unit Commitment / 1473 o" k I# X# K! w+ i% X4 j
4.1.2 Constraints in Unit Commitment / 152
+ m- D2 x$ w' ~8 S/ S" L) M5 u4.1.3 Spinning Reserve / 152
" N2 N$ N" I+ X8 V. h6 e. u- o# k4.1.4 Thermal Unit Constraints / 153( \9 Z0 r/ e# z' ~$ I7 J2 W
4.1.5 Other Constraints / 155
& Y1 J* `. B! ^: b; y% r: X4.2 Unit Commitment Solution Methods / 155 r0 l8 g( u) g1 H3 t
4.2.1 Priority-List Methods / 156
2 U. A2 L& t o3 W4.2.2 Lagrange Relaxation Solution / 157
- R- j% x% v, s& C4.2.3 Mixed Integer Linear Programming / 166. U8 I* R& w' L6 o; |) c
4.3 Security-Constrained Unit Commitment (SCUC) / 167% z8 N0 ]* _1 N3 }) ^& T- c
4.4 Daily Auctions Using a Unit Commitment / 167* i9 e8 N* A P/ v" X
APPENDIX 4A Dual Optimization on a Nonconvex# D! p& i% G1 T4 I+ B; Z. d
Problem / 167, d) X& c! n6 k, h
APPENDIX 4B Dynamic-Programming Solution to
& D v' p" X8 K/ DUnit Commitment / 173
- o S9 q; x Y7 ?4B.1 Introduction / 173
1 g/ ` h9 `$ V2 l0 U4B.2 Forward DP Approach / 1741 g. k/ r4 k! i9 V) q
PROBLEMS / 1827 A O& D; f+ N
x contents7 y& O& Y' K, e, x+ w
5 Generation with Limited Energy Supply 187
. h* X! P6 D e, j5.1 Introduction / 187
! w) H0 @( ^7 J: ^5.2 Fuel Scheduling / 188/ T" F6 a& B8 a( @& }0 X
5.3 Take-or-Pay Fuel Supply Contract / 188, \7 ^5 a, n( X
5.4 Complex Take-or-Pay Fuel Supply Models / 1942 c; @4 K# t+ x6 K l- U& ~
5.4.1 Hard Limits and Slack Variables / 194
0 V, A" V( F3 }0 H7 W+ `5.5 Fuel Scheduling by Linear Programming / 195
1 b4 Z& U7 Q. G1 H1 N6 h1 |5.6 Introduction to Hydrothermal Coordination / 202
: T4 V8 `! u% z2 m5.6.1 Long-Range Hydro-Scheduling / 203
9 W. E2 C5 r- z& _3 o- e5.6.2 Short-Range Hydro-Scheduling / 2045 H/ s9 E3 L' w' t6 \
5.7 Hydroelectric Plant Models / 2042 G# J/ Z+ q* r& O$ q5 {
5.8 Scheduling Problems / 207
$ A7 q# P& ]' {" B, P5.8.1 Types of Scheduling Problems / 207
- A+ ^1 q$ v+ L: A" R5.8.2 Scheduling Energy / 207% o9 ^+ B4 s+ F. @. c- G8 P/ W
5.9 The Hydrothermal Scheduling Problem / 211$ E2 u8 p$ l" D& u" N, x- @% D3 L
5.9.1 Hydro-Scheduling with Storage Limitations / 211( U- C. r* m) V9 s
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
( \2 @' X- P' s9 G5.9.3 Pumped-Storage Hydroplants / 218
" [9 d; ]% ^1 i, f5.10 Hydro-Scheduling using Linear Programming / 222; n+ W6 g" l7 u! G8 L' V/ h
APPENDIX 5A Dynamic-Programming Solution to hydrothermal& \9 }- D$ ^5 G" V, [
Scheduling / 225
; w0 {; i8 A/ M6 F5.A.1 Dynamic Programming Example / 227
7 c$ ]; Y/ n* _1 s0 X& k$ j5.A.1.1 Procedure / 228) [0 Q1 a% Q$ m y3 v
5.A.1.2 Extension to Other Cases / 231
4 b \% a% N, y" l! J5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant! U9 b+ k7 g/ Q, J2 H$ v/ R9 z
Problem / 232" h: D3 p) m! R
PROBLEMS / 234
! f# N) } } ^3 u6 Transmission System Effects 243% D. i3 [$ {; G. [
6.1 Introduction / 243
4 R" |0 w0 _) I7 s/ x, J, O: v3 k6.2 Conversion of Equipment Data to Bus and Branch Data / 247# d9 o5 H! @# x5 |% G3 G+ d
6.3 Substation Bus Processing / 248
8 I" M$ ~ Y% z" o+ P! b6.4 Equipment Modeling / 248
0 b6 O" J2 y* ^" Y* ]+ J3 q3 J) j6.5 Dispatcher Power Flow for Operational Planning / 251
+ x) h! l$ X3 I/ m8 f6.6 Conservation of Energy (Tellegen’s Theorem) / 2520 x6 O2 d# a* \, Z+ o# G
6.7 Existing Power Flow Techniques / 2532 H) X4 f2 ~5 |) @8 t8 ?5 Z8 h! ^+ q3 {
6.8 The Newton–Raphson Method Using the Augmented
& [& ?( M0 E) yJacobian Matrix / 254
+ U# ^, [' |+ u2 \9 `6.8.1 Power Flow Statement / 254: }: h2 I: {& V* \
6.9 Mathematical Overview / 257
4 U- [- o& T* f0 Q! Dcontents xi; v: Z+ l4 s9 D n' E+ I& v. ~
6.10 AC System Control Modeling / 259
. s4 F2 S) F7 v6.11 Local Voltage Control / 259
B+ n6 a' v4 ?- P3 p6.12 Modeling of Transmission Lines and Transformers / 259- w% I+ |- \+ H( d
6.12.1 Transmission Line Flow Equations / 259
3 p7 \0 K j6 y3 w( ?6.12.2 Transformer Flow Equations / 2606 D7 x/ q, r- A; |
6.13 HVDC links / 2617 R4 O) d! S" y; G" I
6.13.1 Modeling of HVDC Converters
/ F0 o/ Y" h* ]1 Z- h% V* s1 Iand FACT Devices / 264
6 a7 ^ g( b, B* O. M3 N( ^6.13.2 Definition of Angular Relationships in
0 f- t( R d" D% H; T% x! cHVDC Converters / 264
& K) Y4 c" v8 s- Y& @! j6.13.3 Power Equations for a Six-Pole HVDC
$ [& h3 X ~6 b& k1 A7 B. fConverter / 264; @( A6 Z0 ?3 F
6.14 Brief Review of Jacobian Matrix Processing / 2672 e: b6 R6 `2 F l5 E2 g
6.15 Example 6A: AC Power Flow Case / 269
( q; y- [( l0 Z& B8 M; g* m6 _. t6.16 The Decoupled Power Flow / 271
- V; N) H+ e4 F- T6.17 The Gauss–Seidel Method / 275/ v' E( I& J8 E( p
6.18 The “DC” or Linear Power Flow / 277
2 o- l. Z/ Q/ p: C3 G1 x7 @6.18.1 DC Power Flow Calculation / 277
1 a8 o7 x4 R! Y) n! H$ H, t6 @6.18.2 Example 6B: DC Power Flow Example on the& [3 }& f0 o; W9 _" q
Six-Bus Sample System / 278
1 `6 Y1 C/ e8 _$ O; F6.19 Unified Eliminated Variable Hvdc Method / 278/ l) |* W+ H' [; h/ K& k6 V8 t" ?
6.19.1 Changes to Jacobian Matrix Reduced / 279
4 _% M$ l3 |- N9 Q/ J1 K6.19.2 Control Modes / 280
4 |" R. D# o$ v+ _3 M/ ~9 R6.19.3 Analytical Elimination / 280
4 f! `. ]; p" {/ p9 ^- g- v6.19.4 Control Mode Switching / 283' C, P+ v! k" Q! r# \
6.19.5 Bipolar and 12-Pulse Converters / 283
2 x: Z. K1 ~! d' p0 {* ~; u( f, L6.20 Transmission Losses / 284
M; E7 x* S( _' {3 g$ K2 X6.20.1 A Two-Generator System Example / 284) c2 N" W; {3 t% {
6.20.2 Coordination Equations, Incremental Losses,4 M1 o6 m6 g0 `2 I+ C6 \+ c2 M
and Penalty Factors / 286
! z7 N5 w4 H* p8 g+ z. A! \6.21 Discussion of Reference Bus Penalty Factors / 288
! d1 L; W% B! A# l6.22 Bus Penalty Factors Direct from the AC Power Flow / 289# J6 I8 @' b! _8 I' D6 x+ O
PROBLEMS / 291
6 M. h5 `) v6 Z( V( x5 p- X7 Power System Security 2965 d5 D" M8 F: s1 N% D: s
7.1 Introduction / 296
0 d% `. Y4 }6 w5 g$ P; s# a4 Z4 I7.2 Factors Affecting Power System Security / 301! o5 e6 X7 ^( x5 q% |/ Q$ F
7.3 Contingency Analysis: Detection of Network Problems / 301; m% f, e# D X8 J6 {, H3 ~6 `
7.3.1 Generation Outages / 301
- V9 l- }9 D! F/ N- E k& c7.3.2 Transmission Outages / 302- `* d( A- i4 h* k
xii contents8 \# u4 X8 X' L5 Q2 m- Q
7.4 An Overview of Security Analysis / 3069 T) n: E6 T2 P1 V) ?* i9 P4 a
7.4.1 Linear Sensitivity Factors / 307
$ G" P& V7 l2 S8 Z/ n4 `7.5 Monitoring Power Transactions Using “Flowgates” / 3136 m' g- O0 q% L+ o, _
7.6 Voltage Collapse / 315
3 z4 B) T/ ~( k/ W7.6.1 AC Power Flow Methods / 3172 a ]2 Q" ^ N! E
7.6.2 Contingency Selection / 320
+ V, Q" I4 d! x; f8 J( ?7.6.3 Concentric Relaxation / 323+ X! I1 L0 |! g5 K2 K
7.6.4 Bounding / 325* G* z0 q7 j4 A
7.6.5 Adaptive Localization / 3255 Z8 w4 w8 u3 l1 H" T
APPENDIX 7A AC Power Flow Sample Cases / 327
7 `5 P' M0 x- bAPPENDIX 7B Calculation of Network Sensitivity Factors / 336
# C6 u$ D( x: C' r7B.1 Calculation of PTDF Factors / 336
/ Y& u, e; f7 C/ b U7B.2 Calculation of LODF Factors / 339
' R8 u4 Y/ p, T5 K7B.2.1 Special Cases / 3413 U6 T2 R ~+ q# G* I. [# I
7B.3 Compensated PTDF Factors / 3430 L8 D3 _: }' p" l8 p8 O
Problems / 343! z4 E4 ]. q/ k$ a
References / 349
a& j. ?, O C3 n8 Optimal Power Flow 350* ], g. w. @$ f+ X0 ^$ B3 m! T
8.1 Introduction / 350. n; B$ { l H! b; O
8.2 The Economic Dispatch Formulation / 3513 \1 J! D* B B+ B; Y5 q2 r
8.3 The Optimal Power Flow Calculation Combining
. k; O, X1 J5 X1 MEconomic Dispatch and the Power Flow / 352
* _0 b; U$ m+ `/ l6 K8.4 Optimal Power Flow Using the DC Power Flow / 354
" O, j& p7 o/ y5 h, O" a. {8.5 Example 8A: Solution of the DC Power Flow OPF / 356
4 q/ f2 d% s* c' Z8.6 Example 8B: DCOPF with Transmission Line
1 {9 j7 Z/ Z3 F q9 b% a( uLimit Imposed / 3611 J( s- _) @9 V) x; D
8.7 Formal Solution of the DCOPF / 3657 j3 O8 Z3 u* e
8.8 Adding Line Flow Constraints to the Linear
: D0 z' M- _/ B2 {+ jProgramming Solution / 3655 Z& Z! Y0 K4 u( ?" O
8.8.1 Solving the DCOPF Using Quadratic Programming / 367
- t. `+ g7 N1 Q4 S* h, w8.9 Solution of the ACOPF / 368
0 f# x) ? y4 ~) q5 X8.10 Algorithms for Solution of the ACOPF / 369 M6 d" s- I4 T. A3 p3 K0 S
8.11 Relationship Between LMP, Incremental Losses,9 ]8 P( ^9 `! y+ L( M5 X$ n
and Line Flow Constraints / 376- K7 l- a) g( K$ a; Z( F
8.11.1 Locational Marginal Price at a Bus with No Lines
- I6 b1 Y5 H& H& [& u0 N8 }$ GBeing Held at Limit / 377( I, V* w* z9 ~, L
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
5 G! ?0 }0 k! i+ }8 tcontents xiii( N6 r3 t* ], G8 `
8.12 Security-Constrained OPF / 382
9 U' M) Q$ X! ~7 l. q8.12.1 Security Constrained OPF Using the DC Power Flow
0 W) |& G; k7 oand Quadratic Programming / 384
. p# p, e+ S7 w; ?: k8.12.2 DC Power Flow / 385
& d4 J# r4 @: t1 M8.12.3 Line Flow Limits / 3858 s" ~) K: k1 b4 d% s( O5 D! `) q
8.12.4 Contingency Limits / 386
- c/ g* }0 e' d0 @: i* Z9 KAPPENDIX 8A Interior Point Method / 391: @( L& ]4 U; X( o( d6 `
APPENDIX 8B Data for the 12-Bus System / 3937 l% o9 N/ O3 K# R
APPENDIX 8C Line Flow Sensitivity Factors / 3950 ]6 j+ \& G1 B
APPENDIX 8D Linear Sensitivity Analysis of the# [6 n, u, G) \& {3 m, H; y
AC Power Flow / 397
0 ]! M2 N! d8 i' U# \5 O5 YPROBLEMS / 399. w @1 w3 ?7 J2 h& j; M0 D$ l8 N
9 Introduction to State Estimation in Power Systems 403% X8 {3 ]6 x( `$ h
9.1 Introduction / 403
. ]' n' J* f4 L- a! [1 Q3 p) b- X9.2 Power System State Estimation / 404# I# S/ l! I. ]$ p) h4 E" f( T9 k
9.3 Maximum Likelihood Weighted Least-Squares9 S, o3 X6 u L3 D/ N" E* `
Estimation / 408
4 _% S/ s* T/ A4 L$ u$ V: c) J9.3.1 Introduction / 4080 z( X( B7 M" T
9.3.2 Maximum Likelihood Concepts / 410
( V& i4 N8 i/ ?: t+ C9.3.3 Matrix Formulation / 414 {4 a/ X6 c; V, ]7 ?
9.3.4 An Example of Weighted Least-Squares
2 C& z& H$ }! w) w+ }! [9 Q8 PState Estimation / 417" j9 T2 a- d1 T! m
9.4 State Estimation of an Ac Network / 421% J0 R9 ^& r% z* |. O8 k, k0 R
9.4.1 Development of Method / 4212 v" u4 s" x; M+ }9 h
9.4.2 Typical Results of State Estimation on an4 a: I) K1 p! b4 L
AC Network / 424
. k4 r5 `8 r3 d9.5 State Estimation by Orthogonal Decomposition / 428
( u& p' ^- G7 _( w1 A1 L1 h9.5.1 The Orthogonal Decomposition Algorithm / 431# x5 Q/ _$ v3 W
9.6 An Introduction to Advanced Topics in State Estimation / 435* l8 [' h v0 G7 @' _: x
9.6.1 Sources of Error in State Estimation / 4352 x8 v/ p0 P: Z: ? b! {
9.6.2 Detection and Identification of Bad Measurements / 436
& f( J, i+ s9 g, h L9.6.3 Estimation of Quantities Not Being Measured / 443
$ }$ @7 n$ |& t$ ^) H3 j6 N9.6.4 Network Observability and Pseudo-measurements / 444
& C& I, @/ q6 E& \* V( m9.7 The Use of Phasor Measurement Units (PMUS) / 447
) n( [5 v: n7 L! e9.8 Application of Power Systems State Estimation / 451" E" W7 \' a: c: [& E
9.9 Importance of Data Verification and Validation / 454
: O" i, ]7 L6 h, l) I1 x2 D' k9.10 Power System Control Centers / 454
4 p! M; z" L$ s2 Xxiv contents
0 }9 v' f' c1 Q0 }2 v3 M) yAPPENDIX 9A Derivation of Least-Squares Equations / 4561 o% H% a( t/ o! @
9A.1 The Overdetermined Case (Nm > Ns) / 457
5 Q; m- f2 Q- o B2 @( Z0 J' }8 z9A.2 The Fully Determined Case (Nm = Ns) / 462
7 N& n1 `1 a; Y, u3 y: ~! R9A.3 The Underdetermined Case (Nm < Ns) / 462: R, u6 V a6 e: u" X Y, f
PROBLEMS / 464
( O0 L2 J6 t' X1 X# c8 ^, g, ^10 Control of Generation 468% L; J, U' K o" _
10.1 Introduction / 4680 A9 \1 y' ^$ R* s- y8 S/ W
10.2 Generator Model / 470/ u F9 n4 G# Q% p2 @$ b" j
10.3 Load Model / 473) R5 K1 t3 A, h) G9 C
10.4 Prime-Mover Model / 4750 [- J1 a+ i: j {4 v7 c
10.5 Governor Model / 4765 N8 S6 l3 \( }4 H% e' y6 i; F
10.6 Tie-Line Model / 481* J( A' T( p, J
10.7 Generation Control / 4852 J/ c. r2 v1 [
10.7.1 Supplementary Control Action / 485
% U% ?2 M# ]6 ~. R w10.7.2 Tie-Line Control / 486, O. E: n) W' a& c4 _& G; G0 k3 k
10.7.3 Generation Allocation / 489
/ k8 z. ^; [) C10.7.4 Automatic Generation Control (AGC)
+ V; Q1 t) U: }9 JImplementation / 491* q/ T- Z1 Q) ` G; C4 {
10.7.5 AGC Features / 495
' m3 z' d: L; S& D4 b7 c8 B! v10.7.6 NERC Generation Control Criteria / 4961 F+ M2 P7 i% g% z: c' Q3 {
PROBLEMS / 497
: c$ _2 @4 R6 c' z! AReferences / 500) h; O- Z; e. v4 B) Z
11 Interchange, Pooling, Brokers, and Auctions 5012 P* e$ M, q) p+ ^; G
11.1 Introduction / 501. E4 o2 p) E; G+ @. [
11.2 Interchange Contracts / 504
8 ?4 j! ~; L' Z5 E p11.2.1 Energy / 5040 G5 u, y; ]+ \/ `% h
11.2.2 Dynamic Energy / 506
9 g. ~0 w" k# A% y- _' \3 R11.2.3 Contingent / 506
. u( Z2 v7 S( N+ }11.2.4 Market Based / 507
4 L \' d( p. U5 Q0 j; D11.2.5 Transmission Use / 508
! b6 K) H3 m4 M: }11.2.6 Reliability / 517
2 {- z1 X- m! h" T$ `$ T; u11.3 Energy Interchange between Utilities / 517- r, D7 c- V+ W
11.4 Interutility Economy Energy Evaluation / 521% _, @% ^7 T) K- O* l
11.5 Interchange Evaluation with Unit Commitment / 522/ t6 v, A$ X1 p3 e4 b- j
11.6 Multiple Utility Interchange Transactions—Wheeling / 523/ E0 s) [! D1 c, s: r) ^7 t o- Z- w
11.7 Power Pools / 526
- a& O6 D, m5 P# e1 f1 Qcontents xv
3 y2 r8 I$ K" ?6 {$ ~11.8 The Energy-Broker System / 529
^7 E0 k+ K* r+ X11.9 Transmission Capability General Issues / 533
/ }8 V" \' h$ M8 ~" s' L& W% b11.10 Available Transfer Capability and Flowgates / 535
: a+ T$ _- U) H: _/ v7 k6 R! B11.10.1 Definitions / 5362 r1 J2 p9 X) L
11.10.2 Process / 539
/ j, P$ \( L4 j2 @- \11.10.3 Calculation ATC Methodology / 540
, w2 B! H5 k8 u( Q" A7 @, N11.11 Security Constrained Unit Commitment (SCUC) / 550, Q( V1 Z/ y' }6 z* t+ E0 s9 R
11.11.1 Loads and Generation in a Spot Market Auction / 5508 E w6 m0 `. [/ o* u- i
11.11.2 Shape of the Two Functions / 552! ~: O0 q% ]0 i' f% Z8 a! M
11.11.3 Meaning of the Lagrange Multipliers / 5536 K" H- T. b" m
11.11.4 The Day-Ahead Market Dispatch / 5542 I: w- S$ e$ o! o, \( S! e1 P
11.12 Auction Emulation using Network LP / 555( o0 |; m/ Y4 N1 f
11.13 Sealed Bid Discrete Auctions / 5553 Z- y3 q/ {( U; ?! X( x8 Q I
PROBLEMS / 560. M% g! r/ {& M" t1 T" K& K
12 Short-Term Demand Forecasting 566
1 f3 d7 a0 W3 O. G( I7 P12.1 Perspective / 566
1 {3 B& j, e1 K12.2 Analytic Methods / 569
. |4 k+ g+ ^2 Y, | k% F( O8 o12.3 Demand Models / 5712 G9 |! y' ^/ d7 \
12.4 Commodity Price Forecasting / 572- {0 J. V6 g3 L+ H8 i* ?
12.5 Forecasting Errors / 573
: l* }, O: H' L8 i/ b12.6 System Identification / 573
& t2 S1 u* M5 [12.7 Econometric Models / 574
) [3 t8 U8 ^+ w- i0 R# U12.7.1 Linear Environmental Model / 574
/ S/ @4 R7 x1 f# T4 o/ j( E12.7.2 Weather-Sensitive Models / 576
1 Y) Z; [3 W" G' V12.8 Time Series / 578* a4 C0 d, \# S7 B# P4 R9 ^
12.8.1 Time Series Models Seasonal Component / 578% r* q0 l/ P2 q/ O: \7 C
12.8.2 Auto-Regressive (AR) / 580
, H" U3 Y: i, K12.8.3 Moving Average (MA) / 581- i: V x0 W( F g7 M5 h
12.8.4 Auto-Regressive Moving Average (ARMA):' K; e% t1 h5 f* N l4 R
Box-Jenkins / 582: r9 ]1 r) `% n( T# \
12.8.5 Auto-Regressive Integrated Moving-Average
5 g" b9 t5 O# d, G# H8 K(ARIMA): Box-Jenkins / 584
; I3 e6 t6 _; A; X, Q' I1 K12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585, ~/ g! S9 ?! H' A4 v/ d- s! h
12.9 Time Series Model Development / 585
* T' X) n/ P9 x b4 B( c. |12.9.1 Base Demand Models / 586- i: ^0 a( n( u; N, D- `4 I7 l
12.9.2 Trend Models / 586
2 J/ ]" F c. C1 \' n$ M3 ^ e12.9.3 Linear Regression Method / 586: o% d9 ^6 _& _* j$ F1 s" m7 U9 K' Q
xvi contents
; ~4 }4 R) R- \$ v( e) c5 Q* s12.9.4 Seasonal Models / 588
4 V, I* J. v& ~% s1 v# [9 R# U; W8 ?% M12.9.5 Stationarity / 588$ p5 _" S1 b' \* |
12.9.6 WLS Estimation Process / 590$ S' E, z" {, S4 B
12.9.7 Order and Variance Estimation / 5915 k% `% `% u. d0 f' z t
12.9.8 Yule-Walker Equations / 5926 a9 `6 U( g7 d
12.9.9 Durbin-Levinson Algorithm / 595
1 V0 w5 a" {8 g2 {2 A" z12.9.10 Innovations Estimation for MA and ARMA
6 w9 h2 a4 \& B M+ c7 E! DProcesses / 598 O; z' T3 {" H2 A3 S
12.9.11 ARIMA Overall Process / 600$ R6 {' O! E9 g, ]
12.10 Artificial Neural Networks / 603
. g" I# Z! G/ ~12.10.1 Introduction to Artificial Neural Networks / 604
/ M8 r6 C/ X+ u12.10.2 Artificial Neurons / 605
8 @$ k; ]8 X, c* a12.10.3 Neural network applications / 606
( C" x R7 O! y, {' [4 x" D, z12.10.4 Hopfield Neural Networks / 606
2 u# B4 C2 K5 W12.10.5 Feed-Forward Networks / 607
, N0 k- \4 x- Q0 x0 _* i12.10.6 Back-Propagation Algorithm / 610
& t/ F- v3 g& c9 |12.10.7 Interior Point Linear Programming Algorithms / 613
$ a: ?1 ~2 R$ o" _12.11 Model Integration / 614
5 c; I: w5 ^6 p+ w6 j7 y12.12 Demand Prediction / 614
8 M$ C* r1 F! V/ [12.12.1 Hourly System Demand Forecasts / 615/ p$ O! B, X, Q5 e8 x/ F2 h
12.12.2 One-Step Ahead Forecasts / 615
' y5 c4 o- K& n. S8 Y12.12.3 Hourly Bus Demand Forecasts / 616! l0 h( f* o! }
12.13 Conclusion / 616
5 z5 }0 A& |* t% A3 VPROBLEMS / 617 |
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