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第三版目录。
& d8 ~9 [3 ?* ^/ k8 P5 `1 Introduction 1
5 v. }! Y3 H( J- J6 G) [1.1 Purpose of the Course / 1
0 T& h7 |2 t( ^2 Q6 f# \1.2 Course Scope / 2
1 d7 ^% G/ b/ e+ |* l. N; G1.3 Economic Importance / 2
8 K W1 G l) T# p$ Y1.4 Deregulation: Vertical to Horizontal / 3& k) L+ M: e; w6 E1 a/ X z, f
1.5 Problems: New and Old / 37 r$ C8 `1 O/ i
1.6 Characteristics of Steam Units / 6
% ?4 e3 ~3 _4 C1.6.1 Variations in Steam Unit Characteristics / 10% Q V' Z e; {: ], s# C% t
1.6.2 Combined Cycle Units / 13) |2 N" K; c; `" l6 ]9 ^
1.6.3 Cogeneration Plants / 149 x- Q3 }9 W+ s. H; F
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
: `$ N- Q2 b) |1.6.5 Hydroelectric Units / 18
. i# x" R8 S" K t1.6.6 Energy Storage / 21
/ [9 y5 l9 R+ @& D. L1.7 Renewable Energy / 227 w& T% k3 ~9 c$ C6 C" ^2 k% ^& X
1.7.1 Wind Power / 23; d: ^$ H( I/ `- `9 I5 ^
1.7.2 Cut-In Speed / 236 M, n6 S N/ l" l
1.7.3 Rated Output Power and Rated Output Wind Speed / 24
4 B( D& |0 o* E* k0 t8 _( h1.7.4 Cut-Out Speed / 24
2 c& E' a! Z l4 q- Z- v) k1.7.5 Wind Turbine Efficiency or Power Coefficient / 24) {8 N1 P8 ^( o4 J' f% B
1.7.6 Solar Power / 25! N% l8 R& E" @
APPENDIX 1A Typical Generation Data / 267 ]! V' {8 B$ \4 |4 s9 t" Y
APPENDIX 1B Fossil Fuel Prices / 28
; u+ U) i4 g4 q! X4 x) |1 E7 CAPPENDIX 1C Unit Statistics / 29
& T8 {; H* B- V: |CONTENTS
5 t: Q2 [( J! _# q2 Tviii contents2 U0 ?, A9 x- ^$ I# z1 O
References for Generation Systems / 31
; ]5 F7 b6 \# H6 N5 o8 D' D. LFurther Reading / 31
% j8 Y6 P0 u( {' k$ c+ F. K2 Industrial Organization, Managerial Economics, and Finance 352 j# T; w3 [& r0 n! w
2.1 Introduction / 35& }2 _' B' l4 D
2.2 Business Environments / 36) h% {. v1 F0 o& Y. x1 H
2.2.1 Regulated Environment / 378 h7 }( n1 n* j/ E
2.2.2 Competitive Market Environment / 38
7 s+ M( I$ R; W' C2.3 Theory of the Firm / 407 w0 E& V! i& S; W
2.4 Competitive Market Solutions / 42$ U. m- t. }2 a! H' E
2.5 Supplier Solutions / 45* O5 G1 h0 E4 r/ C
2.5.1 Supplier Costs / 46
- x9 h9 F+ O/ ^ a( U" A* q2.5.2 Individual Supplier Curves / 46! y+ r6 J; Z3 ^9 V# Q/ P
2.5.3 Competitive Environments / 47
/ J- v& \' U3 P* A* O- ~; i2.5.4 Imperfect Competition / 51
6 V# F# G$ S( |$ J' B7 P# ?* {2.5.5 Other Factors / 52
5 r" P+ ^) N/ }$ O8 T& ?2.6 Cost of Electric Energy Production / 53' ~; R0 A% x, h0 n: p
2.7 Evolving Markets / 543 `$ ]4 E" |2 a
2.7.1 Energy Flow Diagram / 57
. D' z$ M+ [7 z& }2.8 Multiple Company Environments / 58. k& }: }1 H% i8 b
2.8.1 Leontief Model: Input–Output Economics / 58
9 {. t$ ^0 {& x2.8.2 Scarce Fuel Resources / 60* r* F, w' o9 _+ A, U @6 }2 m
2.9 Uncertainty and Reliability / 612 ?4 v) K4 t0 y' k2 {) W
PROBLEMS / 61% B! p4 D8 i; M( ?0 |
Reference / 623 _8 {+ X5 ?" [
3 Economic Dispatch of Thermal Units and Methods of Solution 630 `* j1 J- |; F6 s) U
3.1 The Economic Dispatch Problem / 636 t/ y/ j& J" j9 {- |! Y
3.2 Economic Dispatch with Piecewise Linear Cost Functions / 688 I8 ^9 y; z8 s$ [* S9 W, W: _
3.3 LP Method / 69- L( Z8 M% l9 l/ r1 A
3.3.1 Piecewise Linear Cost Functions / 699 t, i& T) |. f' ^" a( W% I
3.3.2 Economic Dispatch with LP / 71
) m7 O" A3 U: D/ f+ c7 m3.4 The Lambda Iteration Method / 73
& E/ c( J# |6 B6 M7 y# ]4 a3.5 Economic Dispatch Via Binary Search / 76* f+ P* A) i+ o( n4 s( j
3.6 Economic Dispatch Using Dynamic Programming / 78
3 Y# d% v- g, A; Y# U. I; _: I3.7 Composite Generation Production Cost Function / 81" M7 b% H, }) Z3 f! y/ {
3.8 Base Point and Participation Factors / 85' J8 ?' W+ O- q
3.9 Thermal System Dispatching with Network Losses& r5 n/ r, ?# C
Considered / 88
4 W, \3 ~& G" G* e5 bcontents ix
5 C3 c, V: ]2 h% u& R' H, h3.10 The Concept of Locational Marginal Price (LMP) / 92
- _; }3 X! c% D; ?* J' e0 h3.11 Auction Mechanisms / 952 Q* y, _# M2 A* z
3.11.1 PJM Incremental Price Auction as a
9 X* f4 B, R. U! ^, `$ V/ d$ @- uGraphical Solution / 95
+ x) A9 U: a) H$ w3 o W! M4 C! b7 g3.11.2 Auction Theory Introduction / 98) l6 x% f2 ~" I I; i
3.11.3 Auction Mechanisms / 1001 ^% t7 f0 j1 ^$ G6 T4 b6 ?
3.11.4 English (First-Price Open-Cry = Ascending) / 101
+ P" Q, P+ ?8 n! W$ g F3.11.5 Dutch (Descending) / 1037 d% U- d0 U# L5 n/ w
3.11.6 First-Price Sealed Bid / 104
' r* v4 D; K% u3.11.7 Vickrey (Second-Price Sealed Bid) / 105
6 p4 M7 t6 Q7 V/ X7 ]8 j+ a5 v3.11.8 All Pay (e.g., Lobbying Activity) / 105& z" ]* e8 L7 ]' Q
APPENDIX 3A Optimization Within Constraints / 106
: k3 A; @3 D& g( J' m/ pAPPENDIX 3B Linear Programming (LP) / 117
/ v2 r; v1 z* V8 }APPENDIX 3C Non-Linear Programming / 128
; F) I- {' }, t0 |0 JAPPENDIX 3D Dynamic Programming (DP) / 128$ E' U2 `( R1 c5 g$ _4 g2 f1 A
APPENDIX 3E Convex Optimization / 135. h& x2 ^. Z$ n0 H5 A6 s
PROBLEMS / 138
; z, ~* B/ g3 K8 J7 c4 wReferences / 146! s. v$ I0 F* @
4 Unit Commitment 147
0 S" K* {2 b3 f$ [, A" S$ W2 u! C4.1 Introduction / 1474 L" {6 j% j4 r# a+ P, o
4.1.1 Economic Dispatch versus Unit Commitment / 147
! k6 g6 m# k6 H1 m0 q4 N" y4.1.2 Constraints in Unit Commitment / 1523 c: y! P$ n) x6 t: f3 J
4.1.3 Spinning Reserve / 152$ b; b" M9 s$ ], ]% D
4.1.4 Thermal Unit Constraints / 1530 V& `5 W2 t% O8 ^% i+ n% s! ^
4.1.5 Other Constraints / 1556 Z2 P; J/ A; t: A0 `" c
4.2 Unit Commitment Solution Methods / 155' j K& P+ t5 ^% l) u$ f
4.2.1 Priority-List Methods / 156! P7 Y2 u/ \# R$ T
4.2.2 Lagrange Relaxation Solution / 157
0 [5 y/ N; P4 X$ U4.2.3 Mixed Integer Linear Programming / 166 n% P0 a Z3 k; T# r# g
4.3 Security-Constrained Unit Commitment (SCUC) / 1678 o* K" w! f6 `
4.4 Daily Auctions Using a Unit Commitment / 167& M$ H: n" w8 f' x0 w4 } c9 _1 G8 y
APPENDIX 4A Dual Optimization on a Nonconvex
7 a8 p" x- f1 i' @( ZProblem / 167
& c% J; C3 B, w2 U7 x; lAPPENDIX 4B Dynamic-Programming Solution to, a/ K/ C( @3 Z9 W* Q9 t, O
Unit Commitment / 1737 ^' y7 f- Y6 ^7 R' G1 t4 |
4B.1 Introduction / 173: l% l" x; y- ~8 W7 }% v
4B.2 Forward DP Approach / 1746 U+ {' G1 N, G3 G9 W( Y% |
PROBLEMS / 182/ }1 \, a+ a1 J" H
x contents) O0 n+ {) w2 i- G0 N8 _
5 Generation with Limited Energy Supply 187
/ Q% y9 Q+ S) e, B5 x& S( g4 N- x W$ [5.1 Introduction / 187
5 Q0 J) E8 P+ W$ F5.2 Fuel Scheduling / 188
1 \! q6 N5 W" J; |5.3 Take-or-Pay Fuel Supply Contract / 188" R5 P- d) s- J7 d( f
5.4 Complex Take-or-Pay Fuel Supply Models / 194
( O4 Z. P' Z: |$ h7 M+ Z1 U7 p5.4.1 Hard Limits and Slack Variables / 194
J- Z9 @) Z( u7 u K& a5 {5.5 Fuel Scheduling by Linear Programming / 195
/ v' Z5 N, P/ T* ~' V* ?5.6 Introduction to Hydrothermal Coordination / 202
) H" c; x. z' [& C& a5.6.1 Long-Range Hydro-Scheduling / 203
/ O, F; r. L) c z) J& I5 i5.6.2 Short-Range Hydro-Scheduling / 204
' B1 j+ _: r/ A0 x" y( |5.7 Hydroelectric Plant Models / 204" t5 M! f: ]. A, Z3 g0 u
5.8 Scheduling Problems / 207
& g/ k; c$ z" u; a5.8.1 Types of Scheduling Problems / 207" z! C6 I; T& ?! [9 Y
5.8.2 Scheduling Energy / 207- Z5 H' L5 f) Z& Y3 x% Y3 o
5.9 The Hydrothermal Scheduling Problem / 211* F2 @7 v' K. ?
5.9.1 Hydro-Scheduling with Storage Limitations / 2110 o/ H: `9 e# U! B5 `
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
- X2 C3 `+ {% d! ~, s5.9.3 Pumped-Storage Hydroplants / 218
* `4 U$ i T% b* {" D6 r* D k5.10 Hydro-Scheduling using Linear Programming / 222
. r h4 p L9 t. H2 _7 u) hAPPENDIX 5A Dynamic-Programming Solution to hydrothermal$ d8 A' Z6 c8 C2 i% x) |% f! Q0 ?
Scheduling / 2251 p P7 {# H7 ?8 `7 d: ]' T8 N3 K- j& G
5.A.1 Dynamic Programming Example / 227
3 o: \1 V0 Y$ _5.A.1.1 Procedure / 228, j. E* T7 K4 Z. p) a9 ]5 E
5.A.1.2 Extension to Other Cases / 231
( q" h' l$ ]4 s5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant2 i) Q; C" f3 |. m
Problem / 232
+ B- s8 K" H g7 A9 j2 J& KPROBLEMS / 2342 c0 H* i/ i4 t& p; z, w& S! Y! S
6 Transmission System Effects 243
9 X& o0 X' c* K z/ I9 J! l8 q0 X6.1 Introduction / 2437 Y& T3 _7 M& ]3 E, i
6.2 Conversion of Equipment Data to Bus and Branch Data / 2473 S- K6 B; K+ L" Z# {
6.3 Substation Bus Processing / 248
, T, @" h+ f6 I8 U8 ~6.4 Equipment Modeling / 248
7 k* L% `2 I6 O6.5 Dispatcher Power Flow for Operational Planning / 251
' m8 q+ h+ A2 v6.6 Conservation of Energy (Tellegen’s Theorem) / 252 M7 ~7 S/ [, u/ r
6.7 Existing Power Flow Techniques / 253: i$ R; }; K" ~8 N# ^
6.8 The Newton–Raphson Method Using the Augmented
- v+ ~- w6 i& V/ jJacobian Matrix / 254( K8 |- L2 v0 k" \% o8 F
6.8.1 Power Flow Statement / 254
! C* N# e. b6 `& D( S, @6.9 Mathematical Overview / 257
) x6 t& f# R) u/ r% l. b% K0 [contents xi
5 v' M& m* F* ?( P/ d# Z7 i6.10 AC System Control Modeling / 259
' |# m! j6 b* T" Q2 ~6.11 Local Voltage Control / 259
: x! a7 \* d0 D" Z5 q$ Z6.12 Modeling of Transmission Lines and Transformers / 259# |: V6 B6 b3 J' [" i( T6 E
6.12.1 Transmission Line Flow Equations / 259
6 c; k5 _7 c5 N' s) O4 J) [( {9 P6.12.2 Transformer Flow Equations / 260! s8 P2 o# Q7 U! `2 q& Y
6.13 HVDC links / 261
. Y1 e5 r1 Q# }' ?. W0 e6.13.1 Modeling of HVDC Converters/ o1 N F, D4 r( o
and FACT Devices / 264' j3 P$ B2 H' R# `( w& y
6.13.2 Definition of Angular Relationships in1 Z; A% ?5 n3 \' T, y" X; g* k
HVDC Converters / 264
4 d& J9 s5 Z% \6 [! G2 w0 x6.13.3 Power Equations for a Six-Pole HVDC) E) N. C5 N( u# C9 X) g \
Converter / 264
! c3 W3 Y' N0 A* k4 p# v" R2 j1 ?6.14 Brief Review of Jacobian Matrix Processing / 267
( }# l1 M6 O8 |' c/ m) X6.15 Example 6A: AC Power Flow Case / 269( H4 b/ o6 Y# y
6.16 The Decoupled Power Flow / 271
# O' m5 w/ I2 b' q/ a- Y6.17 The Gauss–Seidel Method / 275
5 @- g+ `: Q/ s0 p7 ~6.18 The “DC” or Linear Power Flow / 2772 Z' l% Z v6 W: u; b
6.18.1 DC Power Flow Calculation / 277* }' H, \ |, s9 @
6.18.2 Example 6B: DC Power Flow Example on the
% u7 ?" Y% @) QSix-Bus Sample System / 278
+ Y2 A) o$ m6 D, S6.19 Unified Eliminated Variable Hvdc Method / 278
! j" k- S/ d& X& Q w1 v3 n6.19.1 Changes to Jacobian Matrix Reduced / 279
& i# |5 ~! u9 f% j( M* }6.19.2 Control Modes / 280
" N9 R w7 P9 ?" c$ }6.19.3 Analytical Elimination / 280
3 ^! k, O+ ]8 L7 ` J6.19.4 Control Mode Switching / 283! x" o- h. ~2 t/ A7 u0 O
6.19.5 Bipolar and 12-Pulse Converters / 283
0 r/ @& Y) x6 H' d6.20 Transmission Losses / 284) |- B8 d$ f9 ` s$ a* k
6.20.1 A Two-Generator System Example / 284
) C1 }+ X) v7 v1 K4 r w; f6.20.2 Coordination Equations, Incremental Losses,
% U, J4 a, h* k0 `3 A' C5 f' p, tand Penalty Factors / 286
7 @& }3 V1 _) u4 m' K6.21 Discussion of Reference Bus Penalty Factors / 288: Q' k5 A1 G4 z: X0 \
6.22 Bus Penalty Factors Direct from the AC Power Flow / 289. N* E" X2 w! R# k3 ~
PROBLEMS / 291
) w8 D# Y6 t( Y- ]" R7 Power System Security 296
3 p3 r- F) u6 o l$ }( R' Y4 B P7.1 Introduction / 296
7 _* U A2 X9 U t+ [9 T7.2 Factors Affecting Power System Security / 3015 q9 v% E9 b2 u4 n0 z7 p
7.3 Contingency Analysis: Detection of Network Problems / 301
* s. U' r1 O/ O; l w$ v; F. g2 A7.3.1 Generation Outages / 301
4 s( ^ Q3 i+ N, Z8 O, a. B0 p7.3.2 Transmission Outages / 302
6 q! ^( B& Z- \7 K7 }xii contents
0 F w, d5 ^( Q7.4 An Overview of Security Analysis / 306
7 `* J' @* r: C$ I" R9 d7.4.1 Linear Sensitivity Factors / 307
& f0 e4 o I: A7 Z' c2 d+ F7.5 Monitoring Power Transactions Using “Flowgates” / 313
6 `2 y' T, k7 D9 y4 m0 k8 G7.6 Voltage Collapse / 315& v3 [* R- z9 o( D5 S# l
7.6.1 AC Power Flow Methods / 317
6 A H, x% K! ?& l) i! t/ H2 F7.6.2 Contingency Selection / 320
" y4 x8 D- J2 B e' g- E1 I7.6.3 Concentric Relaxation / 323
' a+ ?+ x! \, I7.6.4 Bounding / 325" H+ a; S$ x% |% ?, i N
7.6.5 Adaptive Localization / 3255 s5 c: l3 y9 }; C$ L; I
APPENDIX 7A AC Power Flow Sample Cases / 327- Y* E- \5 D; g9 r5 d$ c4 E
APPENDIX 7B Calculation of Network Sensitivity Factors / 336
+ {/ l; l! P& b7B.1 Calculation of PTDF Factors / 3366 X3 Y& U& s- _6 P, Q' L j! u
7B.2 Calculation of LODF Factors / 339* k" Y9 {! R8 p/ U- K
7B.2.1 Special Cases / 341, O9 X& A* u! _, v2 _; d$ R
7B.3 Compensated PTDF Factors / 343
* b, k+ `, Z$ u$ V: MProblems / 343: V: \! g* P, a$ _& m
References / 349, f r% v7 |& w9 K5 K$ n; `8 }
8 Optimal Power Flow 3503 a# o0 S; G& |4 y: m$ G
8.1 Introduction / 350
! C, n" O% F; O6 o. Z' r8 _* z8.2 The Economic Dispatch Formulation / 351, u2 J: h1 e O# E
8.3 The Optimal Power Flow Calculation Combining) p3 B7 E0 x. o& S: Q- n
Economic Dispatch and the Power Flow / 352
. F. i" s \7 r8.4 Optimal Power Flow Using the DC Power Flow / 3542 e1 I t2 O6 h7 M7 e
8.5 Example 8A: Solution of the DC Power Flow OPF / 356
5 i. |& p5 u/ e; K3 O* k3 Y8.6 Example 8B: DCOPF with Transmission Line: C! a! w2 G2 V6 E V
Limit Imposed / 361
: Y* E& K4 e3 Z8 k. S8.7 Formal Solution of the DCOPF / 3654 C& l, A7 |0 J' F) O3 v7 u7 h8 m
8.8 Adding Line Flow Constraints to the Linear Z+ a) O# t8 s7 e/ p2 c% z
Programming Solution / 365
9 Y/ c" w3 ]+ Z3 h* k- J8.8.1 Solving the DCOPF Using Quadratic Programming / 367' Z) O, n2 p; I( Y% _
8.9 Solution of the ACOPF / 368
) p# I3 y. J) c3 X# S0 b) X$ v" _8.10 Algorithms for Solution of the ACOPF / 369
8 V5 `7 E$ w; ?2 W) @8.11 Relationship Between LMP, Incremental Losses,9 ?8 c1 E1 I8 K" P5 T
and Line Flow Constraints / 3763 H! _% j& V4 v
8.11.1 Locational Marginal Price at a Bus with No Lines+ Q# X$ r |8 v7 l4 B! f2 V0 M
Being Held at Limit / 377
/ f5 r" q; c" x0 B5 s2 ^" w! z8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
3 X' w( ?# ^% D* c( a2 Lcontents xiii8 |/ Q! l- V3 e% L$ S
8.12 Security-Constrained OPF / 382- t5 i, D( |: x7 ^/ N+ S3 A0 E
8.12.1 Security Constrained OPF Using the DC Power Flow* F# ^9 p2 Z9 C4 s3 Z
and Quadratic Programming / 384
+ s: U) ~) E3 v* p8.12.2 DC Power Flow / 3851 U* P2 L9 K( r0 `
8.12.3 Line Flow Limits / 385
, V1 c& H) H3 W" i4 w! ]8.12.4 Contingency Limits / 3865 E& G( |3 C% p! R9 L) ?. e
APPENDIX 8A Interior Point Method / 3910 n: q. x1 p/ F" w9 ]
APPENDIX 8B Data for the 12-Bus System / 393
1 I7 ]6 y0 J, g: ^3 r7 b& qAPPENDIX 8C Line Flow Sensitivity Factors / 395
# N' e; S2 ?" c* `4 WAPPENDIX 8D Linear Sensitivity Analysis of the2 B) t/ w: s6 r) n
AC Power Flow / 3976 ^: d# d& U$ \8 }5 d* B3 T
PROBLEMS / 399
, e; I$ T- U# A9 i/ g, ?9 Introduction to State Estimation in Power Systems 403! F' \9 [# L$ k; Q8 X3 E9 S) K$ R
9.1 Introduction / 4036 s0 e8 o8 d, J: B: z7 Y2 j. T
9.2 Power System State Estimation / 404
# S2 r6 i" Y. e- O3 I# ?- _7 q9.3 Maximum Likelihood Weighted Least-Squares
+ O1 ^6 r4 e& r- z1 QEstimation / 408
7 E/ K! B- J ^0 \9.3.1 Introduction / 408% q8 v" r& S3 e0 _( h) X& p
9.3.2 Maximum Likelihood Concepts / 410! _2 D2 z5 a8 \
9.3.3 Matrix Formulation / 414
+ V7 Y8 @$ H: Y+ {9.3.4 An Example of Weighted Least-Squares. l8 x) C2 w4 o0 z! I% F7 V* d
State Estimation / 417
/ f& H5 h% P9 u& K' _; U6 ]9.4 State Estimation of an Ac Network / 4212 x6 A/ ]' I% R' P8 x
9.4.1 Development of Method / 421
& E, l0 k' `$ H7 [4 x; ?& h4 S7 P& h9.4.2 Typical Results of State Estimation on an3 }4 n6 R7 V3 h3 x: h8 o; U
AC Network / 424
' c- H& N+ P( n+ r$ [) i( U9.5 State Estimation by Orthogonal Decomposition / 428
' Y h' `$ e0 u1 D9.5.1 The Orthogonal Decomposition Algorithm / 431
+ [! h1 o. z b0 }9.6 An Introduction to Advanced Topics in State Estimation / 435
4 s' G3 D2 B) E9.6.1 Sources of Error in State Estimation / 435
( ?# u# U' o0 w" K9.6.2 Detection and Identification of Bad Measurements / 436
/ D2 b1 ~3 e" b, i/ u9.6.3 Estimation of Quantities Not Being Measured / 4436 `' a) T" _: V* P5 f3 O4 O
9.6.4 Network Observability and Pseudo-measurements / 444
" E9 f' `) `; |9 I! h9.7 The Use of Phasor Measurement Units (PMUS) / 447
. [: n0 P( f- m3 t9.8 Application of Power Systems State Estimation / 451
# C; r3 V3 h. W0 k- R$ A9.9 Importance of Data Verification and Validation / 454
( |( n, w/ ^, z# Z9.10 Power System Control Centers / 454- s( x Q8 P4 w8 ~/ h5 ^$ j
xiv contents
0 k* Z9 _' k1 g) g" v* ~APPENDIX 9A Derivation of Least-Squares Equations / 456' z6 \; @+ p# N2 D/ ^
9A.1 The Overdetermined Case (Nm > Ns) / 457
# Z. Y/ `! ^% `6 S5 K9A.2 The Fully Determined Case (Nm = Ns) / 4625 u0 A! I) I# m" d
9A.3 The Underdetermined Case (Nm < Ns) / 462
% ^) ~% z" r2 t v: B' tPROBLEMS / 464
* Q& v* @- Y; F7 x2 H( R10 Control of Generation 468
* J! i3 x2 C5 O! V- C0 s10.1 Introduction / 4689 ^. \- t+ o3 T+ y. j4 L
10.2 Generator Model / 470
% c+ |8 |6 |" I1 P; x$ r3 {10.3 Load Model / 473
) h0 \3 ~" ]3 M10.4 Prime-Mover Model / 475
5 U4 } v {( q7 @5 ~- f2 m10.5 Governor Model / 476
$ G% I$ y+ y: ~10.6 Tie-Line Model / 481
3 a. u% s, @& x0 X! L10.7 Generation Control / 485
6 }) }8 Y: K# v# I- B/ ?! n10.7.1 Supplementary Control Action / 485
" R5 Y6 i, X8 I7 r+ ]10.7.2 Tie-Line Control / 486
% f/ S4 n8 v# V2 ?10.7.3 Generation Allocation / 489/ k$ ?1 B4 ^- C9 |& b' g. `, S6 d8 f
10.7.4 Automatic Generation Control (AGC). C8 q2 k( K, r- d
Implementation / 491
- _% S. H) M# I s10.7.5 AGC Features / 495- j5 p& r- |1 U8 H$ L
10.7.6 NERC Generation Control Criteria / 496( k3 I2 c9 J' I
PROBLEMS / 497
0 t" z/ H& f+ ]+ ]References / 500% n, \ k# l3 Y, k" F
11 Interchange, Pooling, Brokers, and Auctions 501$ H C7 D8 a/ S- |9 M
11.1 Introduction / 501
i' T5 w; k6 Q! V$ y$ P5 x11.2 Interchange Contracts / 504
0 E% S9 Z3 H8 K& N- n11.2.1 Energy / 504
& }8 e, M7 }2 i: r6 S% A9 ^2 H11.2.2 Dynamic Energy / 506
7 t) K& n1 R; D1 e/ v11.2.3 Contingent / 506
! @; ^) g: `* }11.2.4 Market Based / 5071 z- N5 ]5 ?3 U* N% I6 U
11.2.5 Transmission Use / 5081 X# S6 e/ w& t% g5 G! a
11.2.6 Reliability / 517
& e8 ~, P. k( q, w% g5 n) N11.3 Energy Interchange between Utilities / 517* M* b! U9 @$ N& Y" I5 u2 h
11.4 Interutility Economy Energy Evaluation / 521
8 j1 y J' w) y- |11.5 Interchange Evaluation with Unit Commitment / 522( b, e- |3 P# y6 }. a
11.6 Multiple Utility Interchange Transactions—Wheeling / 523) ], S" c8 s) i8 Y; h" c+ V
11.7 Power Pools / 526
/ S, D9 @% B! T, Mcontents xv
& `6 J. k0 G/ _0 \( E2 i11.8 The Energy-Broker System / 529' P. E: ]. {( l* C9 j9 D
11.9 Transmission Capability General Issues / 5333 \! w$ C8 J' a' G B' j
11.10 Available Transfer Capability and Flowgates / 535
+ {& ^5 ]# G4 H, v+ N3 q8 E11.10.1 Definitions / 536& |; z) F U, r/ B
11.10.2 Process / 539
, H5 j9 F+ N4 V6 j11.10.3 Calculation ATC Methodology / 540
! l/ n& y: A& h e0 i& F11.11 Security Constrained Unit Commitment (SCUC) / 550
3 {+ `( M3 k5 F0 `9 Y' ^4 r9 Y11.11.1 Loads and Generation in a Spot Market Auction / 550( |- Y2 o+ L l7 d0 B$ i
11.11.2 Shape of the Two Functions / 5520 Q9 l/ @8 H( H! }
11.11.3 Meaning of the Lagrange Multipliers / 553
$ d" B5 Q: N' G3 e4 E2 `( n11.11.4 The Day-Ahead Market Dispatch / 554
/ M% `5 Q6 | W# }+ C5 r11.12 Auction Emulation using Network LP / 555" B" z' v# z0 Z$ o
11.13 Sealed Bid Discrete Auctions / 555
- d( @4 G0 v' A H* y7 H6 cPROBLEMS / 560% \7 [6 F( o1 o" F1 E$ m$ A: ]
12 Short-Term Demand Forecasting 566
: Y/ x$ Q" }1 r) ~1 P5 e" c6 C12.1 Perspective / 5668 k' _, J$ }5 x
12.2 Analytic Methods / 569
0 t% m) U J g12.3 Demand Models / 571. N5 x5 x- H3 m8 m9 w1 r
12.4 Commodity Price Forecasting / 572
9 q: L2 c2 x9 n& ^ Z8 K6 Q12.5 Forecasting Errors / 573
; Z& }! h* K5 b" Z8 }3 G12.6 System Identification / 573
" H/ @3 R: |$ U; i0 u! I12.7 Econometric Models / 574
8 a6 f9 F! z3 N3 w- C12.7.1 Linear Environmental Model / 574, N* I( r+ }# ~. e7 Z) V A4 w
12.7.2 Weather-Sensitive Models / 576
; U( @- R, e+ @2 Y9 Q12.8 Time Series / 578
2 t. }1 U, }" }% |# ~0 m. S12.8.1 Time Series Models Seasonal Component / 578
. J; h ?' c9 n; y. W5 K12.8.2 Auto-Regressive (AR) / 580
: e# J5 h3 f: e- ^7 r/ A12.8.3 Moving Average (MA) / 5819 }( j1 f- U9 M+ M- }4 ~
12.8.4 Auto-Regressive Moving Average (ARMA):
& U+ ?) U8 G! p0 S" T2 ?Box-Jenkins / 582: g: f n; ]3 _+ q
12.8.5 Auto-Regressive Integrated Moving-Average
% S: r7 s3 q' H, O& s" z: {) I' g! i(ARIMA): Box-Jenkins / 584
. A/ A" F) b, u5 A8 v) A3 C; c12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585# V0 V& P8 Y& _/ ?) s$ B, B: S) j
12.9 Time Series Model Development / 585
* A3 u0 q6 T6 u J3 R4 m. m12.9.1 Base Demand Models / 5863 }2 P. u) O, F9 l% \9 a
12.9.2 Trend Models / 586
x+ A* }& Q9 m, C- h& w3 U12.9.3 Linear Regression Method / 586
- H. D" m# l1 v/ B: _/ u* Axvi contents
% j! |' j* ?5 h! g! J12.9.4 Seasonal Models / 588- f1 A. {3 |4 P: A3 O
12.9.5 Stationarity / 588
, ~2 j% l6 Z4 U12.9.6 WLS Estimation Process / 590
& L3 b$ k2 a+ A( N" }3 Q$ @12.9.7 Order and Variance Estimation / 591, f2 `5 N5 @: `6 W
12.9.8 Yule-Walker Equations / 592) `3 q3 i% u, B6 O
12.9.9 Durbin-Levinson Algorithm / 5957 Z% [- s3 B2 q4 ~/ ]$ ~
12.9.10 Innovations Estimation for MA and ARMA3 J6 X3 f0 x4 \& q6 _: B( F
Processes / 598
* d! r% y3 j! Q' {+ G" Y12.9.11 ARIMA Overall Process / 600
2 U: N$ C: s$ t$ n9 c12.10 Artificial Neural Networks / 603
) J& w% m; M& {7 C$ \, R12.10.1 Introduction to Artificial Neural Networks / 604' t: q7 V* `" z5 {
12.10.2 Artificial Neurons / 605. s/ |0 u7 S9 K1 f3 p, B6 d
12.10.3 Neural network applications / 606
& i: C& O. @3 G1 p' \; d" p' G12.10.4 Hopfield Neural Networks / 606
9 e1 R5 d& Y6 s4 ]1 `- _12.10.5 Feed-Forward Networks / 607. o2 `$ ]) H6 ?" {
12.10.6 Back-Propagation Algorithm / 610: W3 W: E0 S' L5 ~6 A- K: G
12.10.7 Interior Point Linear Programming Algorithms / 6134 ]# j- r% J ~# H) t
12.11 Model Integration / 614- D0 i: T2 t9 S# T) {9 ]
12.12 Demand Prediction / 614
3 y9 _6 Q5 |3 J% i12.12.1 Hourly System Demand Forecasts / 615
9 R [3 Z: ?$ P& ~6 w12.12.2 One-Step Ahead Forecasts / 6150 n9 h7 b) w; E) R
12.12.3 Hourly Bus Demand Forecasts / 616
8 Z# Q; J+ j& ~/ M12.13 Conclusion / 616$ N6 b3 x! Y) S$ O" I. z
PROBLEMS / 617 |
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