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第三版目录。
3 r7 m. H* X1 r8 J: r1 Introduction 1
! b; V- K% ?8 ?3 c! ]1.1 Purpose of the Course / 1: u1 I: \; i$ @- R6 c
1.2 Course Scope / 28 g; h: h6 r( u/ q
1.3 Economic Importance / 2# m5 F9 x9 f7 p9 S8 N. i
1.4 Deregulation: Vertical to Horizontal / 3
) m3 a* x# k3 p; G" @* y1.5 Problems: New and Old / 3
$ _% a. B: B( l2 N6 ~7 r1.6 Characteristics of Steam Units / 63 y, ~ @4 J5 n: n
1.6.1 Variations in Steam Unit Characteristics / 10
; r8 {4 C6 _1 Y1 h4 ?1.6.2 Combined Cycle Units / 13
# y( d( W g( p4 s& l1.6.3 Cogeneration Plants / 14
0 w- r, q6 f% G, @1.6.4 Light-Water Moderated Nuclear Reactor Units / 17) N1 X) Z1 [% ^ S3 c- s7 X ?
1.6.5 Hydroelectric Units / 18
. W( `( U6 ?" y* c: d# r1.6.6 Energy Storage / 211 m0 n$ e5 E+ w# Z
1.7 Renewable Energy / 22
F( n& w/ D' l1.7.1 Wind Power / 23$ [9 B8 F# y+ \! j& t( o0 Z/ I. I
1.7.2 Cut-In Speed / 23
h4 g; Y8 @8 L' Y$ U0 W1.7.3 Rated Output Power and Rated Output Wind Speed / 24
* ]/ o% n5 F O8 H" p1.7.4 Cut-Out Speed / 24
. P j- W, g& F6 O5 l5 V! }1.7.5 Wind Turbine Efficiency or Power Coefficient / 242 [0 O, U4 C, S" m/ @7 f4 b: P' L" N
1.7.6 Solar Power / 25
, U& s0 O8 v' n: H8 T, z* ~3 l8 jAPPENDIX 1A Typical Generation Data / 26
0 Q# p# M5 E) f, [' jAPPENDIX 1B Fossil Fuel Prices / 28" k3 L/ c: ]/ \3 U* H
APPENDIX 1C Unit Statistics / 29
: q: f% X0 t. a: }0 S$ {: T/ L, fCONTENTS
4 o$ D. q) B/ U9 kviii contents
2 c: Y9 w$ e" F* P; ?2 B# jReferences for Generation Systems / 31* ^& w9 i' |; F/ p) P1 q* H R
Further Reading / 31
% e; C5 }, _5 X- l* V2 Industrial Organization, Managerial Economics, and Finance 35
( `9 z+ S! O K) o2.1 Introduction / 35- [6 r3 B3 Z) D
2.2 Business Environments / 36
& J0 @5 E7 \* i& R8 a. C8 W2.2.1 Regulated Environment / 37
; h$ t: q' v* b4 l& P2 |; L2.2.2 Competitive Market Environment / 38( A* f$ |# l ^- {! K: z
2.3 Theory of the Firm / 40* S# g4 ?/ @: V# _* ?
2.4 Competitive Market Solutions / 425 F% j/ f0 r7 ] s1 e; W; Q
2.5 Supplier Solutions / 45# @3 X! a" M2 L. s4 @
2.5.1 Supplier Costs / 46
9 H( e7 i& A. D1 c, `8 \& V7 K5 G" A2.5.2 Individual Supplier Curves / 46+ L2 N8 Y3 O7 n. b
2.5.3 Competitive Environments / 47
( \7 B. i0 n( D" X0 l+ r1 M1 Z5 e2.5.4 Imperfect Competition / 51
5 K+ J' f+ |7 r( `4 _% S \' W0 ?2.5.5 Other Factors / 52+ g- n+ R! r6 _6 l+ i" E
2.6 Cost of Electric Energy Production / 53
8 m. R6 }* T ?: B$ Y2.7 Evolving Markets / 547 v \4 r! k% A
2.7.1 Energy Flow Diagram / 57
+ g# ^; W+ G: @: _' ~2.8 Multiple Company Environments / 58* V; z4 e1 ?; y
2.8.1 Leontief Model: Input–Output Economics / 58
, y) U2 Y5 M: d7 b3 m& N( V2.8.2 Scarce Fuel Resources / 60
1 B, V( R. A$ v% p5 |+ ?; h2.9 Uncertainty and Reliability / 61; O) q1 M' v1 U: b) k8 k& Y: e- S5 H
PROBLEMS / 61: C2 s) _2 ^: P2 S. @; c! G
Reference / 62
- n- l n5 ?1 g* s3 Economic Dispatch of Thermal Units and Methods of Solution 63
9 T3 h% I6 c. A/ _" Y3.1 The Economic Dispatch Problem / 63
. X' ]5 Z0 {# D& a* _% R$ Z3.2 Economic Dispatch with Piecewise Linear Cost Functions / 680 I9 q+ h. n2 _' l" |: D! T5 H
3.3 LP Method / 697 S: v0 s {0 K; w% d2 Z: R% K
3.3.1 Piecewise Linear Cost Functions / 69, X; f+ ^0 M* S( H, e
3.3.2 Economic Dispatch with LP / 711 w8 ~, V, B2 s, `. M
3.4 The Lambda Iteration Method / 73
# M) ]' ~6 p8 g1 N$ M3.5 Economic Dispatch Via Binary Search / 76. h+ a* f: K" j% B; ]/ V
3.6 Economic Dispatch Using Dynamic Programming / 78( L( _' _9 f& {/ `2 n. w. N! ~
3.7 Composite Generation Production Cost Function / 81% R9 j1 C- M6 c& I
3.8 Base Point and Participation Factors / 85& ?# ^* d3 k( ]' l1 Q( s
3.9 Thermal System Dispatching with Network Losses
4 j, @+ P2 Y1 dConsidered / 88
3 G6 I3 q; R' ?7 Bcontents ix
' h; }* U# p& T1 e3.10 The Concept of Locational Marginal Price (LMP) / 92# k$ @" Y# D9 w
3.11 Auction Mechanisms / 95, {. k4 f/ M! J" R) M- e
3.11.1 PJM Incremental Price Auction as a+ k( W& i/ T, @$ f# N
Graphical Solution / 95
0 M1 L1 O y6 ~3.11.2 Auction Theory Introduction / 988 R) o. t: F. c: V7 h. r: p0 g7 t
3.11.3 Auction Mechanisms / 100
# a. h. h" P# q' k3.11.4 English (First-Price Open-Cry = Ascending) / 101. k2 a3 G) I3 b$ t
3.11.5 Dutch (Descending) / 103) i& H) ~, g% _! I& P
3.11.6 First-Price Sealed Bid / 104
' r( `! d! y2 y; U8 J7 ?3.11.7 Vickrey (Second-Price Sealed Bid) / 105
8 F, R* C0 g4 V! ]. C. k3.11.8 All Pay (e.g., Lobbying Activity) / 105
/ R9 N; e$ h+ N) pAPPENDIX 3A Optimization Within Constraints / 106
q4 F2 t& | A5 L4 D/ `APPENDIX 3B Linear Programming (LP) / 1173 }. A# {$ Z: b, O$ W- @- }
APPENDIX 3C Non-Linear Programming / 128
$ d9 r4 Z+ S' a2 E( q; F9 CAPPENDIX 3D Dynamic Programming (DP) / 128
% j/ e) H# \2 H+ S, P& V, sAPPENDIX 3E Convex Optimization / 135; b. u4 F6 C) O. b! h
PROBLEMS / 138# B1 B- L7 J9 g- k8 p7 f
References / 1465 G |2 u* G' ~+ g6 V
4 Unit Commitment 147
$ [7 Y/ v4 A3 i0 Q4.1 Introduction / 147% W8 {+ p. v7 o: `. {0 {. i
4.1.1 Economic Dispatch versus Unit Commitment / 1472 N. t! @* O# X( _' g' L# ~- ]
4.1.2 Constraints in Unit Commitment / 152
* M! Z& ]! d Y: g# l1 n0 e4.1.3 Spinning Reserve / 152
# p$ B, W, P. z7 j6 u! a4.1.4 Thermal Unit Constraints / 153
u# f1 L3 \/ l: W. B4.1.5 Other Constraints / 155
1 b0 [, V2 L4 m8 x- S2 z; R7 E$ p4.2 Unit Commitment Solution Methods / 1557 h- x, g* x2 z- u- ]5 n4 Y
4.2.1 Priority-List Methods / 156
! m# n) _8 Z+ C5 f4.2.2 Lagrange Relaxation Solution / 157
* \4 x' j* f7 r9 B' D& D' g4.2.3 Mixed Integer Linear Programming / 166! h3 G& @9 l1 ]4 L& W( U0 U
4.3 Security-Constrained Unit Commitment (SCUC) / 167 O* R- h7 q; s& n
4.4 Daily Auctions Using a Unit Commitment / 1673 ^ V" e% X6 M+ M8 [& n
APPENDIX 4A Dual Optimization on a Nonconvex1 ?7 e; J, U9 V( C) o- H% `* l8 s
Problem / 167) P$ ^' r0 h7 ?* U! J% y
APPENDIX 4B Dynamic-Programming Solution to7 O( v7 T% |* o& O1 m6 M9 d9 z4 h
Unit Commitment / 173
7 e! \1 E1 ^; g" j8 ?' m4B.1 Introduction / 1730 S7 M! ?" F, R. P# W" k1 h
4B.2 Forward DP Approach / 174
) |' s/ c* J# O: e O7 R: dPROBLEMS / 182+ J2 v9 n. h9 |( s
x contents
! D8 n# @5 o, [8 ~2 z5 Generation with Limited Energy Supply 187% K* t" ?0 x1 D3 i
5.1 Introduction / 187
& w0 t- L. [! v$ j. `) w( X# y5.2 Fuel Scheduling / 188
# L6 t2 K/ v( r* n$ q& D) C5 T2 Q3 J5.3 Take-or-Pay Fuel Supply Contract / 188+ ~" u3 |$ L! J
5.4 Complex Take-or-Pay Fuel Supply Models / 194
" B F3 ] `( s7 Y( |5.4.1 Hard Limits and Slack Variables / 194- u3 y: T# t6 L: ^+ H
5.5 Fuel Scheduling by Linear Programming / 195% U- j% U7 I- Y4 S5 H& J0 D- G
5.6 Introduction to Hydrothermal Coordination / 202! S5 {1 h7 A2 g9 j- S# K
5.6.1 Long-Range Hydro-Scheduling / 2036 A$ j& r9 V; l+ L- z/ n* t
5.6.2 Short-Range Hydro-Scheduling / 204/ m7 b7 Z+ k( d0 q h6 p
5.7 Hydroelectric Plant Models / 204& J2 L0 f0 W# N
5.8 Scheduling Problems / 207
) o p0 e5 r/ Q4 l! i+ T5.8.1 Types of Scheduling Problems / 207
8 ~5 m& \, W y5.8.2 Scheduling Energy / 2076 X' I' ]# k1 b- h7 k! O
5.9 The Hydrothermal Scheduling Problem / 211* c5 M5 b4 A7 h- Z. X
5.9.1 Hydro-Scheduling with Storage Limitations / 211
% O, d2 l1 O8 I2 _: {5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
9 y/ V% ]1 @- Y5.9.3 Pumped-Storage Hydroplants / 218: z9 l( u+ H# B% R! J- F
5.10 Hydro-Scheduling using Linear Programming / 222
, T+ U0 O2 V3 B# x2 WAPPENDIX 5A Dynamic-Programming Solution to hydrothermal
; R+ U; |& |; \% {+ ]Scheduling / 2255 r1 A% C c5 `( W
5.A.1 Dynamic Programming Example / 227
! p8 O1 w9 |3 P. W, |# h! ?8 r1 E5.A.1.1 Procedure / 228+ z% K& C* w4 g2 z" _& z0 \
5.A.1.2 Extension to Other Cases / 231 E2 G7 ~/ `! U
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
" ]( k2 [ `8 v lProblem / 2324 _! ?8 V" ~( U, d8 v$ i# n
PROBLEMS / 234/ T7 A" k3 ~4 R. ?
6 Transmission System Effects 243
. ^( _( O' r1 O1 n! s9 _/ o0 F6.1 Introduction / 2432 A) @4 h* ]7 J4 y
6.2 Conversion of Equipment Data to Bus and Branch Data / 247
* c( b" p* j% ?6.3 Substation Bus Processing / 248 q' s+ }6 A6 y8 F& c) w0 f
6.4 Equipment Modeling / 248+ f d) w+ }; s5 F& l
6.5 Dispatcher Power Flow for Operational Planning / 2517 C% h$ r" {/ t+ u. H, v7 }
6.6 Conservation of Energy (Tellegen’s Theorem) / 252
. E/ f6 C9 C# j5 [6 E7 m2 s' c6 c D' l6.7 Existing Power Flow Techniques / 253$ B: V/ n. ]/ ~' K. h5 g
6.8 The Newton–Raphson Method Using the Augmented3 W6 x3 R8 t" y1 s! |' @
Jacobian Matrix / 254$ m ~6 r5 c5 p' E
6.8.1 Power Flow Statement / 254, ~4 b/ |& ]5 n, u. @$ `
6.9 Mathematical Overview / 257
6 U) @7 q* g! ycontents xi( l: o* A3 m% `- g
6.10 AC System Control Modeling / 259
. G6 t* [& o! b: [9 d4 J- v. {6.11 Local Voltage Control / 2596 Q# B4 y5 s% |, N
6.12 Modeling of Transmission Lines and Transformers / 259) c4 s% R" n. d% v6 ?9 }& v
6.12.1 Transmission Line Flow Equations / 259
4 j7 G+ {0 P/ Z& h. d+ Y) |( ]/ h6.12.2 Transformer Flow Equations / 260
, y; N2 p/ O2 | R6.13 HVDC links / 261
8 d! R& t6 E/ R3 k! l6.13.1 Modeling of HVDC Converters6 y) T0 ?$ R) t. _9 Z
and FACT Devices / 264
8 W) T+ j3 c9 y6 A. _4 I6.13.2 Definition of Angular Relationships in5 |6 M5 O; w7 [' Z- e# J
HVDC Converters / 2642 ]' I* F3 O- K) V2 s- g! P
6.13.3 Power Equations for a Six-Pole HVDC
3 p, K4 @. w/ W) K n7 ?# WConverter / 264+ z2 f& `! F! H
6.14 Brief Review of Jacobian Matrix Processing / 267
/ \1 }) w2 ^' z3 \% @3 w4 z$ ^6.15 Example 6A: AC Power Flow Case / 269/ W/ f% J) |' U. A g
6.16 The Decoupled Power Flow / 271/ o: q9 i `0 A
6.17 The Gauss–Seidel Method / 275, n" k' R% [& h/ B! ?" T
6.18 The “DC” or Linear Power Flow / 277. ~9 F/ u5 k: \6 {6 v
6.18.1 DC Power Flow Calculation / 277
/ E0 A a, t) n1 x Z0 i# K6.18.2 Example 6B: DC Power Flow Example on the
& K+ u. `2 R: Z( ~* b% lSix-Bus Sample System / 278
+ Y; K$ ]) D8 c b+ T, X& f, K6.19 Unified Eliminated Variable Hvdc Method / 2787 }2 ~3 f: J4 Y5 h9 X
6.19.1 Changes to Jacobian Matrix Reduced / 279
8 m/ O3 G4 n+ ?2 F9 `4 k' I* r6.19.2 Control Modes / 280! x( w- ^4 M1 x$ j6 L
6.19.3 Analytical Elimination / 280
* _1 `2 X5 p2 ?! O; s& h6.19.4 Control Mode Switching / 283
( T+ C. W3 N, t( \2 ^6.19.5 Bipolar and 12-Pulse Converters / 283, |5 s# q" G7 C$ f3 ^) k" R; D
6.20 Transmission Losses / 284. g4 y$ ~. L4 g
6.20.1 A Two-Generator System Example / 284
3 H7 V3 I: A, f6 u6.20.2 Coordination Equations, Incremental Losses,$ @7 T7 O8 G+ P" ]8 ?, d6 c, n
and Penalty Factors / 2867 E* X/ A2 z( z$ Y
6.21 Discussion of Reference Bus Penalty Factors / 288
0 g# c' }: L7 u& @) }. R' R6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
) t& _7 m2 [+ i' H7 A( e0 V7 MPROBLEMS / 291
9 V0 B$ E/ R. O7 Power System Security 296$ b" ~3 X+ ]8 T1 u
7.1 Introduction / 296
/ R7 |, R* d% ]* ~/ t7.2 Factors Affecting Power System Security / 301
" u' Y3 g6 K# b* N7.3 Contingency Analysis: Detection of Network Problems / 301
* Q& q7 o7 E# F7.3.1 Generation Outages / 301; J0 Q# X8 D" ]$ D) M0 x+ i1 j# {
7.3.2 Transmission Outages / 3024 A0 e+ b8 X4 ?' K
xii contents$ ^% q; f" B1 t; N* U. r) X1 L" T
7.4 An Overview of Security Analysis / 3062 L% m7 s/ r% x3 ~
7.4.1 Linear Sensitivity Factors / 307; x0 h# @( @7 @9 @8 }2 T
7.5 Monitoring Power Transactions Using “Flowgates” / 313" x7 a7 J' O* a. j [1 |+ b
7.6 Voltage Collapse / 315, s6 q0 q3 V& U; m7 k. b/ ]- v
7.6.1 AC Power Flow Methods / 3170 K ^) a& O& |+ p. D9 {
7.6.2 Contingency Selection / 320
; k8 N& ~3 x! E7.6.3 Concentric Relaxation / 323% e+ W9 _* u$ h
7.6.4 Bounding / 325+ ]* u( A" P( O9 p7 {
7.6.5 Adaptive Localization / 325: Q- c( S7 @* U* T6 _2 b, }6 \
APPENDIX 7A AC Power Flow Sample Cases / 327; Q5 Y& L9 M; X
APPENDIX 7B Calculation of Network Sensitivity Factors / 336
" b8 a& |1 B' ~) Y6 O7B.1 Calculation of PTDF Factors / 336( E% U C/ i0 i% S( a3 J. s. {! h3 G
7B.2 Calculation of LODF Factors / 339, {6 d8 F/ k. a
7B.2.1 Special Cases / 341
9 `. _; ^$ D( o1 S* Y0 u$ b1 M7B.3 Compensated PTDF Factors / 343) S3 s: k% P% T7 h. a
Problems / 343
# S* W% k+ H0 M7 O* BReferences / 349
1 a r* o" h s+ d. [6 I8 Optimal Power Flow 350* ]3 W; y8 \/ l: @8 ^" y
8.1 Introduction / 350
3 M7 Q6 O# B- M7 M8.2 The Economic Dispatch Formulation / 3515 Y! ~* o9 I& O$ V$ w* q
8.3 The Optimal Power Flow Calculation Combining
! f- P# |; w4 Y7 }. M) V9 |4 S- sEconomic Dispatch and the Power Flow / 352# \( C7 K8 ^% Q, @( O( u6 T8 o
8.4 Optimal Power Flow Using the DC Power Flow / 354, A. |/ X) q8 s9 e. S( n! R
8.5 Example 8A: Solution of the DC Power Flow OPF / 356
& g3 Z+ @4 U# H& M8.6 Example 8B: DCOPF with Transmission Line7 E3 p4 l! l& S0 [ J
Limit Imposed / 3613 T( q6 i, v6 v y& e
8.7 Formal Solution of the DCOPF / 365
3 L/ s* K. U$ U5 W$ N+ H8.8 Adding Line Flow Constraints to the Linear
; Z. F+ ^% |+ @4 O. d; _! W6 _& n0 oProgramming Solution / 365
% h' O) s% U% _' l8.8.1 Solving the DCOPF Using Quadratic Programming / 3670 C8 c" G( A" C2 \7 g5 X/ t
8.9 Solution of the ACOPF / 368 t2 E0 j& Y" ?9 I; a
8.10 Algorithms for Solution of the ACOPF / 369
9 [9 o/ P+ K! r# \8 c- a+ ]8.11 Relationship Between LMP, Incremental Losses,! F$ h9 @, F6 \8 [5 L6 g' M
and Line Flow Constraints / 376
3 x- B) x! D. D. D3 ?9 r8.11.1 Locational Marginal Price at a Bus with No Lines
; t$ M, H x- B- sBeing Held at Limit / 377
3 Y" S7 ?: B& T1 L9 W! v8 o8.11.2 Locational Marginal Price with a Line Held at its Limit / 378( ~: K. U4 w1 x; C
contents xiii. _! D" s% z5 c7 J9 F
8.12 Security-Constrained OPF / 3823 _$ o1 x' I" j/ B
8.12.1 Security Constrained OPF Using the DC Power Flow$ l2 I/ Z) i! `! T, Z
and Quadratic Programming / 384 G# i3 \3 a0 n, ^/ l
8.12.2 DC Power Flow / 385
3 b8 ]( e0 b' n& k8.12.3 Line Flow Limits / 385
+ g) z$ ~1 o7 k; ~" q: T8.12.4 Contingency Limits / 386
4 [( O7 w6 @- t% x7 lAPPENDIX 8A Interior Point Method / 391% \% B- R7 ^& w
APPENDIX 8B Data for the 12-Bus System / 393
5 ~; d4 b+ u' RAPPENDIX 8C Line Flow Sensitivity Factors / 395
v, c' Y! b. {/ b; \( M# p4 qAPPENDIX 8D Linear Sensitivity Analysis of the# e. j9 F+ h5 m- l9 ~ |: D8 `
AC Power Flow / 397
7 Q5 J* `0 S9 Z& H& g- xPROBLEMS / 399. u# K: X* U, _
9 Introduction to State Estimation in Power Systems 4035 w; J0 |5 A( H( a) \ l
9.1 Introduction / 403
2 f% d6 g( h" u6 P3 i* Q2 _9.2 Power System State Estimation / 404
& f& e3 i! x: i+ _9.3 Maximum Likelihood Weighted Least-Squares
" }) F4 R% ~9 R* U( Y- G" ~5 ^; PEstimation / 4086 \% I) t: o6 o% e& h5 |
9.3.1 Introduction / 408
7 Z' G- ]: d; X9.3.2 Maximum Likelihood Concepts / 410
2 j5 l- s: E8 B5 U) ]9.3.3 Matrix Formulation / 414
0 z1 u# v. H3 H( L+ H9.3.4 An Example of Weighted Least-Squares |1 i/ x7 ]$ O" `0 S
State Estimation / 4179 F$ C7 |2 ~. @. `" |! D
9.4 State Estimation of an Ac Network / 421 w1 z- B, s$ q2 N
9.4.1 Development of Method / 421
q9 J, ?9 X/ m; _$ j9.4.2 Typical Results of State Estimation on an: H: D+ E1 Z! B
AC Network / 424* p+ x- k- r% m* W' J! ~; J
9.5 State Estimation by Orthogonal Decomposition / 428
# r+ Y" Z6 v# C9.5.1 The Orthogonal Decomposition Algorithm / 431
5 u* p* |; ~# C9.6 An Introduction to Advanced Topics in State Estimation / 4353 |4 r9 h, v: y: X
9.6.1 Sources of Error in State Estimation / 4352 y2 F; u" y+ s2 y( x/ y4 x3 t
9.6.2 Detection and Identification of Bad Measurements / 436
7 C9 u* C( G! g+ m W9.6.3 Estimation of Quantities Not Being Measured / 443- `" n$ _* \# v/ ^, ]
9.6.4 Network Observability and Pseudo-measurements / 444
6 o& ^) X5 Z4 Z( B# E4 T9.7 The Use of Phasor Measurement Units (PMUS) / 447
( ^% R$ J! w8 U" S9.8 Application of Power Systems State Estimation / 451
. ^- e- p/ |8 _9.9 Importance of Data Verification and Validation / 454
! C$ E3 r' R5 c3 }) r& E- i9.10 Power System Control Centers / 4544 ^) S) K' ?7 U: |
xiv contents
9 b6 p1 J- k! ^0 ^APPENDIX 9A Derivation of Least-Squares Equations / 456
L8 |, ~8 D4 r% z) L; X9A.1 The Overdetermined Case (Nm > Ns) / 4577 L; R2 U6 F' H% _" H- | M
9A.2 The Fully Determined Case (Nm = Ns) / 4621 C/ z. O; a3 m8 c! Y. g5 `
9A.3 The Underdetermined Case (Nm < Ns) / 462
3 ]# o# l3 C- L( xPROBLEMS / 464
- A+ w% Y4 ]5 @10 Control of Generation 468
" Y% c/ _! F; i' K& L10.1 Introduction / 468
; Q: `3 N( V* Q6 C7 H0 ]) g* N) ?10.2 Generator Model / 470
6 ~ w/ k. n' P u, @3 k" H10.3 Load Model / 473
3 r& Z3 E" C$ j _7 C10.4 Prime-Mover Model / 475- z& c! R4 B% p$ K8 |3 X1 A# s* O
10.5 Governor Model / 4768 r6 G) F% v* I2 ?7 X
10.6 Tie-Line Model / 481+ `4 }* x2 J! s# ^6 V' Z+ a+ Z
10.7 Generation Control / 485
! ]0 w- v3 b, K7 K* `10.7.1 Supplementary Control Action / 485
" ` q" ^* W) t# K: A10.7.2 Tie-Line Control / 486
5 T* ^" Q# r0 O" I% B* s9 j10.7.3 Generation Allocation / 489
$ q" v* A8 {" m! W: ]2 k10.7.4 Automatic Generation Control (AGC)
3 ^: |: w5 K1 VImplementation / 491, U Z. m: l! T0 u$ v- L
10.7.5 AGC Features / 495
5 l- r/ E( W! x/ _; P4 K0 i7 l) D# \10.7.6 NERC Generation Control Criteria / 496$ l3 U& s1 d/ i1 M
PROBLEMS / 497! L% Y( F& j2 B# [3 [
References / 500
9 I- w; {# Q! a( n! N11 Interchange, Pooling, Brokers, and Auctions 501* F8 i5 d9 F+ V7 _4 ^6 ^
11.1 Introduction / 501' @: f4 H' d: m" E4 m, q
11.2 Interchange Contracts / 504) L* y6 P$ B5 Y" N2 S% ^8 K$ Z
11.2.1 Energy / 504
! ?- R5 z' t' g0 R2 _4 X7 r' k6 N% H11.2.2 Dynamic Energy / 5062 S7 r1 R. N" U" L8 Z* ?( `
11.2.3 Contingent / 506$ s4 _5 a: a# O* N% P
11.2.4 Market Based / 507 c; ]1 w* f( _' c" Y
11.2.5 Transmission Use / 508
- ~& ?8 H8 R7 f# ~8 ~11.2.6 Reliability / 5177 h6 G4 I5 o8 I$ g2 c2 d% F. h
11.3 Energy Interchange between Utilities / 517 j# Z( O; |" b& Q
11.4 Interutility Economy Energy Evaluation / 521
% j3 o' F, C- i, E11.5 Interchange Evaluation with Unit Commitment / 522" P, ]8 Q! e& V( S# P! _
11.6 Multiple Utility Interchange Transactions—Wheeling / 523
/ S) L: o s, ?9 _! n" A% Q11.7 Power Pools / 526
& y! H7 }) O. [1 gcontents xv' S7 N: X% E: c9 X* c+ w
11.8 The Energy-Broker System / 529
1 P! `8 B3 a5 l9 Y# a11.9 Transmission Capability General Issues / 533
- X; i0 a. h* [2 f/ D1 M" A/ J11.10 Available Transfer Capability and Flowgates / 535
+ n3 p$ |, T8 s, j' D11.10.1 Definitions / 5367 h' Y2 C# B+ \. J
11.10.2 Process / 539- E, y8 D! {/ M( Y: N' ~- @# r
11.10.3 Calculation ATC Methodology / 540
; z2 Q& j9 `+ C0 L2 _) Z- ?11.11 Security Constrained Unit Commitment (SCUC) / 550
4 L% Y% A" d6 T0 ?3 Y; H3 W7 T11.11.1 Loads and Generation in a Spot Market Auction / 550
' W R/ e3 W, a N11.11.2 Shape of the Two Functions / 552! s* T4 D5 U$ K5 W* n# U8 ~, U- D
11.11.3 Meaning of the Lagrange Multipliers / 553- T. u% r- v" |) k- u
11.11.4 The Day-Ahead Market Dispatch / 554$ W; t( B+ h) S
11.12 Auction Emulation using Network LP / 555: r; @- |5 z- w8 {2 v
11.13 Sealed Bid Discrete Auctions / 5553 W* v8 x6 ?' G- d4 Z1 F
PROBLEMS / 560
$ M. E( X J2 _12 Short-Term Demand Forecasting 5667 N3 W7 `8 y* a" W& s7 O9 \" e
12.1 Perspective / 566
: h) D' R- I3 b3 i12.2 Analytic Methods / 5696 z* Z$ W; Y4 e( C
12.3 Demand Models / 5711 O$ z7 \9 \! Q/ i; Q
12.4 Commodity Price Forecasting / 572 I9 G4 n- R' L8 n* Z: l
12.5 Forecasting Errors / 5736 L7 @8 ~3 F( G7 I/ A( O [
12.6 System Identification / 573
' `3 d$ k. _1 d12.7 Econometric Models / 574
) d6 E t9 K! Z) N8 [! U" g; }12.7.1 Linear Environmental Model / 5745 _. r8 M4 a4 l& s! S
12.7.2 Weather-Sensitive Models / 576- J# _" B- P6 z
12.8 Time Series / 578! z/ ?) L* v) A- Z
12.8.1 Time Series Models Seasonal Component / 578
5 V/ m! Q% b3 L12.8.2 Auto-Regressive (AR) / 5802 X; x5 a" s# q3 ]- V& q3 q
12.8.3 Moving Average (MA) / 5810 ^& B0 P. r! Z) S- v
12.8.4 Auto-Regressive Moving Average (ARMA):1 w# {" Y$ ~( @$ |
Box-Jenkins / 582" D n; a2 _2 I2 M
12.8.5 Auto-Regressive Integrated Moving-Average) M o) P+ y) a; D' q/ K
(ARIMA): Box-Jenkins / 584; e+ u1 O3 e% }9 u5 F3 U6 d' N
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585" [- Y3 R+ e) S5 u; x) N. N2 k
12.9 Time Series Model Development / 585
G4 o M) |* o+ G- X/ |12.9.1 Base Demand Models / 586! H# e0 L$ F7 v$ k4 o0 f
12.9.2 Trend Models / 586
& K; [7 `* m1 M7 m0 ]12.9.3 Linear Regression Method / 586
6 V9 X3 `; A, Dxvi contents, _ R# x5 v" `, u
12.9.4 Seasonal Models / 588
8 M6 Q- ^' B+ E5 V$ o0 ^% r3 y+ R12.9.5 Stationarity / 588- ` x; n' b" Z6 E D! G+ [! j
12.9.6 WLS Estimation Process / 590: l" n7 ^9 z3 g9 ]2 Y
12.9.7 Order and Variance Estimation / 5914 q$ q4 b# }/ H2 c0 b5 n1 y0 q' P
12.9.8 Yule-Walker Equations / 592
6 P$ F, p7 x% Z3 D12.9.9 Durbin-Levinson Algorithm / 5959 V6 O" V/ C4 R4 Z5 y2 L
12.9.10 Innovations Estimation for MA and ARMA
" z0 w: ^$ d7 y: oProcesses / 598
; A7 _* ~0 ~* q( I5 F. M12.9.11 ARIMA Overall Process / 6005 T R6 ]/ z5 M6 N; k- |8 ?# ~
12.10 Artificial Neural Networks / 603
, J- Y# @. i% {! O12.10.1 Introduction to Artificial Neural Networks / 604
) J: O& O5 d; v( x0 S7 t1 ]: M1 G12.10.2 Artificial Neurons / 605
& ?9 x; O" O0 \4 w) k12.10.3 Neural network applications / 606
# w# {" z( d) E1 S4 ]* O& H' y12.10.4 Hopfield Neural Networks / 606! u% f3 p. u2 t+ h
12.10.5 Feed-Forward Networks / 607$ @/ z. _: ^& H/ I
12.10.6 Back-Propagation Algorithm / 610
; N& d/ m8 v9 L3 M R V) p12.10.7 Interior Point Linear Programming Algorithms / 6130 f: u2 b0 _$ L2 [6 _
12.11 Model Integration / 614- E8 T" F7 ^3 E2 H7 g0 N7 A
12.12 Demand Prediction / 614* D, J& g3 d: c1 h7 p' D, p' [- R( z
12.12.1 Hourly System Demand Forecasts / 615
* o6 S! [# h( m3 U: ~8 @6 w12.12.2 One-Step Ahead Forecasts / 615. g+ X7 t9 m* I" q9 ~' m% h ]& S
12.12.3 Hourly Bus Demand Forecasts / 616
5 `1 k4 F' F) \3 L/ K12.13 Conclusion / 616
, K ? w. S+ Z( \PROBLEMS / 617 |
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