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第三版目录。
+ U# \# C% A, U1 ?1 Introduction 1
9 a+ _3 w3 z S7 e, X9 s) f+ s1.1 Purpose of the Course / 1
' N" d; E: L" f+ m1.2 Course Scope / 2 d! i$ N1 M; ?0 U! @) x3 w
1.3 Economic Importance / 2" r) }# O/ @" \8 P, y$ |
1.4 Deregulation: Vertical to Horizontal / 3
6 n* H! B- }7 b+ ?. C# A/ A' ^1.5 Problems: New and Old / 3- K$ `. e4 K7 T: _
1.6 Characteristics of Steam Units / 6
' w$ r7 m! K" ?" c& ]1.6.1 Variations in Steam Unit Characteristics / 10
' B5 \6 F, U1 ^$ E1.6.2 Combined Cycle Units / 13. R9 T- [8 [/ X1 `/ b4 V/ c3 w) ? o
1.6.3 Cogeneration Plants / 14
5 S- s. I& j( f8 [1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
8 a# e) D& r8 u# P# g2 l# w1.6.5 Hydroelectric Units / 18& S8 }8 w1 q3 i5 \3 V9 [
1.6.6 Energy Storage / 21. ^4 C& F* v: T: E6 L* ^0 ^
1.7 Renewable Energy / 22
! A% L/ ]3 p4 j' }8 N# d% x! O8 n1.7.1 Wind Power / 23/ U+ m3 o, R, @- e$ h) F! Z) o" `) U
1.7.2 Cut-In Speed / 23+ c$ c4 e( k* A/ a7 G- z$ u$ s
1.7.3 Rated Output Power and Rated Output Wind Speed / 24
# Z P# N4 G: d% G/ E1.7.4 Cut-Out Speed / 24
4 w4 N! E" i" L. O3 Z5 e- S; I1.7.5 Wind Turbine Efficiency or Power Coefficient / 248 [8 a5 c4 A; }# f
1.7.6 Solar Power / 25% j8 o. s6 M* W) b& X' f
APPENDIX 1A Typical Generation Data / 26
( o& n1 l. X- u% q8 @) @4 R; nAPPENDIX 1B Fossil Fuel Prices / 281 F! A6 v- v3 q) P% x h
APPENDIX 1C Unit Statistics / 29
! X# v4 j9 d) J/ z( A) RCONTENTS
/ d" R( H1 I9 Iviii contents
3 o. @$ I& r$ L; o- ^/ zReferences for Generation Systems / 319 B- O2 P) `! H4 B3 c) S, z* o
Further Reading / 31
3 `, ^- F* v7 u' M, k2 Industrial Organization, Managerial Economics, and Finance 35
. I0 E% p) w/ a* G$ V5 K* g/ h2.1 Introduction / 35. l. F u- p r s; Q- d7 i
2.2 Business Environments / 363 W7 [. T6 h% F- k8 G. U
2.2.1 Regulated Environment / 37
# v" L) _2 b6 A. {4 _! ~2.2.2 Competitive Market Environment / 38
- V3 `* ?' M" Q. j# T; _2.3 Theory of the Firm / 40
+ J* m* C2 P6 ^: u% ?3 y' _2.4 Competitive Market Solutions / 42
* D' a1 Y! k. G2.5 Supplier Solutions / 45
, q8 v/ R! L3 A( o* w2.5.1 Supplier Costs / 461 c0 ~" q3 |: I7 b a" Z& ^- X
2.5.2 Individual Supplier Curves / 46
+ t- x# h6 c; M6 _- d2.5.3 Competitive Environments / 47% e5 k4 U9 I7 A* S' O/ y1 b
2.5.4 Imperfect Competition / 51. ~" g! L: l! g
2.5.5 Other Factors / 520 x5 O) w( K4 z3 Y6 w- ?, W
2.6 Cost of Electric Energy Production / 53/ _. c; v+ S9 f, J% l' d& H
2.7 Evolving Markets / 54
8 P& p( K) H9 P" E& }: Y8 h2.7.1 Energy Flow Diagram / 57$ n! R, G5 p+ a( E! Q
2.8 Multiple Company Environments / 585 h5 M; M6 D5 H: z" H
2.8.1 Leontief Model: Input–Output Economics / 581 z+ T% q# g. r( v k. M
2.8.2 Scarce Fuel Resources / 604 [4 [3 f$ p# a' `3 }, k9 W% n
2.9 Uncertainty and Reliability / 61
- [8 y5 z; p _! v F" q5 UPROBLEMS / 612 \2 x) g- U2 w7 O- _
Reference / 62
& L9 w$ g" l/ Z$ g7 L) w( @/ F5 X3 Economic Dispatch of Thermal Units and Methods of Solution 63+ z0 X6 x1 m: ]; V
3.1 The Economic Dispatch Problem / 63
% z7 z0 U1 t! w4 @3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68, |: a' P9 y/ `. I2 v
3.3 LP Method / 69
0 ^& V( V: b, i: j3.3.1 Piecewise Linear Cost Functions / 69
" w c% i8 r- \) Z) H3.3.2 Economic Dispatch with LP / 719 q0 ^! k) J& n4 z6 c1 d: [
3.4 The Lambda Iteration Method / 73" C: s8 T1 j. q) K: u. [1 S" f
3.5 Economic Dispatch Via Binary Search / 76 a& y6 H% a& x; C
3.6 Economic Dispatch Using Dynamic Programming / 785 j% f3 Q4 T. G$ n. u) o6 G# E
3.7 Composite Generation Production Cost Function / 81, M' h& {- i$ c
3.8 Base Point and Participation Factors / 85
9 ~, O P5 O- b6 F- ^6 e3.9 Thermal System Dispatching with Network Losses
3 e6 M( R6 V6 k7 a7 xConsidered / 88
2 R# P; l# B2 kcontents ix
) `1 X7 g% A2 B6 @, Y3.10 The Concept of Locational Marginal Price (LMP) / 92
# o" O N! n! y" o0 P3 A! O1 T3.11 Auction Mechanisms / 95
" n) n @9 R# T2 u3.11.1 PJM Incremental Price Auction as a0 b& j; t' n& J t+ l
Graphical Solution / 95- e# D# r5 k% j$ g0 }5 I
3.11.2 Auction Theory Introduction / 98/ U. F& m9 d, N
3.11.3 Auction Mechanisms / 100. y9 f! @0 Z3 i7 D K0 u- R
3.11.4 English (First-Price Open-Cry = Ascending) / 101# R" d! U% x5 o6 M) O) A6 c
3.11.5 Dutch (Descending) / 103; A7 L+ g: A5 f
3.11.6 First-Price Sealed Bid / 104. y' q3 _/ R _- `& n5 R
3.11.7 Vickrey (Second-Price Sealed Bid) / 105
/ n( y& I& v9 K, T& a7 t. `3.11.8 All Pay (e.g., Lobbying Activity) / 105
+ [8 M, g' p# b( D" Z, ZAPPENDIX 3A Optimization Within Constraints / 1069 n4 o4 P' Q% |* c. \% l! z
APPENDIX 3B Linear Programming (LP) / 117
0 w1 R/ I, D- K" }( G$ V( \% Q2 IAPPENDIX 3C Non-Linear Programming / 1281 }1 m0 R! M: ]$ T" _9 {
APPENDIX 3D Dynamic Programming (DP) / 1285 b0 \4 Y( f7 m9 P `# f; M
APPENDIX 3E Convex Optimization / 135
' F! D z1 p+ nPROBLEMS / 138
2 U6 ?+ e5 j1 ~' nReferences / 146! B7 w8 ~$ B0 {& E" Z, L) R" \
4 Unit Commitment 147
8 N2 N0 m8 S7 V8 Q) X& B/ K1 M& E6 S4.1 Introduction / 147
' ~# K& F" W" s8 u t; \ b$ ^4.1.1 Economic Dispatch versus Unit Commitment / 147' {' G- e0 m& C' ]) ~& a' \' A: B
4.1.2 Constraints in Unit Commitment / 152! k, Z6 i& ~+ [. G
4.1.3 Spinning Reserve / 152
4 f" E, j' E! A, v' J1 a4.1.4 Thermal Unit Constraints / 153/ K9 y0 g0 s2 o( G2 d
4.1.5 Other Constraints / 1555 Y/ P: Z$ Z/ t K
4.2 Unit Commitment Solution Methods / 155
7 u$ m( n! V) \9 B3 A4.2.1 Priority-List Methods / 156: S( I# f9 W& a- Q
4.2.2 Lagrange Relaxation Solution / 157; j6 |, j6 M! l1 _1 I
4.2.3 Mixed Integer Linear Programming / 166' w+ f6 e. r+ t8 F. g! g
4.3 Security-Constrained Unit Commitment (SCUC) / 167
. ~1 c1 O% u7 r# e$ l. o4.4 Daily Auctions Using a Unit Commitment / 167
+ p* v+ P r: }1 o* I3 u5 \0 qAPPENDIX 4A Dual Optimization on a Nonconvex
8 F/ i E' ?/ l8 I( |* |3 bProblem / 167: }2 w/ c/ E6 K+ N0 X2 _ Q- ~
APPENDIX 4B Dynamic-Programming Solution to
7 s5 l& X! z- u" ~Unit Commitment / 173' t( [7 @ n& P. a
4B.1 Introduction / 173
) ~1 e5 t8 x! E4 H2 J/ X4B.2 Forward DP Approach / 174
( [) ]# d- G% Y- D2 ?9 ZPROBLEMS / 182
% d+ n% H: M/ ?- J- f+ Mx contents
# ~) V+ n% _, _0 w" a o5 Generation with Limited Energy Supply 187( ? A. S k6 Y; w
5.1 Introduction / 187
% W2 P' d3 n8 o* g1 ?) i5.2 Fuel Scheduling / 1886 |: {% G! _ U& r& R. Y3 k
5.3 Take-or-Pay Fuel Supply Contract / 188
" C% C5 R" n1 u! I: @1 A' G0 e8 `3 @5.4 Complex Take-or-Pay Fuel Supply Models / 194
- U1 J9 d8 g$ [5.4.1 Hard Limits and Slack Variables / 1949 @7 c$ n1 M! `- j/ z. J
5.5 Fuel Scheduling by Linear Programming / 195
! t/ i* j6 @# a5.6 Introduction to Hydrothermal Coordination / 202
' F" A# J, T# `' C# Q# B5.6.1 Long-Range Hydro-Scheduling / 2039 h. }6 k4 g& D: P
5.6.2 Short-Range Hydro-Scheduling / 204
: J. X- t) m9 A1 s; n5.7 Hydroelectric Plant Models / 204
5 d. {: X0 Z/ V7 X5.8 Scheduling Problems / 2072 a6 ]' O9 k5 T7 Q) s& w
5.8.1 Types of Scheduling Problems / 207
! U6 j2 m( J w! n2 A, G: D1 }9 j; G5.8.2 Scheduling Energy / 207
" M9 j7 j$ q% i% k0 ?' `: L5.9 The Hydrothermal Scheduling Problem / 211
V& o( W h3 s3 K. _# Y5.9.1 Hydro-Scheduling with Storage Limitations / 211
! g" E+ M& |! C. p. y5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216: w6 p" } ^1 {4 k
5.9.3 Pumped-Storage Hydroplants / 2188 o- p1 ~; w+ R4 i+ u, X
5.10 Hydro-Scheduling using Linear Programming / 222
7 u1 l) z9 T2 q# O2 uAPPENDIX 5A Dynamic-Programming Solution to hydrothermal" I1 r2 |0 o% h' a7 }+ t, Z
Scheduling / 225
: ^* w4 R* k( L5 a5.A.1 Dynamic Programming Example / 227
& `$ R+ m) U* ~& `1 V5.A.1.1 Procedure / 228- o- t/ i0 r& B1 A! t
5.A.1.2 Extension to Other Cases / 231
7 _" I; G$ ^' u* V8 R0 ~5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
0 a s0 c' k8 A/ \% j2 HProblem / 232
. w. Q5 J1 h2 t5 O! D- KPROBLEMS / 234
4 m: a0 ]3 I( j9 l. C6 Transmission System Effects 243
9 n0 |1 y* Z% M0 l' [ M o6.1 Introduction / 243
% j, I' Q# l8 Q3 k5 d6.2 Conversion of Equipment Data to Bus and Branch Data / 2477 n; m$ d9 s, N7 H9 Y; R7 D
6.3 Substation Bus Processing / 248
8 k- S$ Y3 b2 i6 f! F# n% ^6.4 Equipment Modeling / 248( i: B* D) T' n6 y6 Y
6.5 Dispatcher Power Flow for Operational Planning / 251
^+ x* s t2 {: s7 E/ [/ A6.6 Conservation of Energy (Tellegen’s Theorem) / 252
2 m. j; N! \. C7 A) E6.7 Existing Power Flow Techniques / 253. Q. ~3 t0 l$ @7 e3 i
6.8 The Newton–Raphson Method Using the Augmented
7 f% q9 m+ u- S' D7 SJacobian Matrix / 254
% X/ G# m, A5 u6.8.1 Power Flow Statement / 2544 h1 L; w* s. h- o
6.9 Mathematical Overview / 2575 F* \, t' i! x9 D6 A: h+ z! A
contents xi. a0 H. W- I9 G9 \& E, e) H9 k
6.10 AC System Control Modeling / 259$ O7 W, `$ J+ o5 S
6.11 Local Voltage Control / 259
* B9 y h7 t% J. N! v' Y( v* r6.12 Modeling of Transmission Lines and Transformers / 2595 k: j6 T ^0 {: y% h" M$ J1 n+ y* S
6.12.1 Transmission Line Flow Equations / 259( A% }3 j& K4 @3 y
6.12.2 Transformer Flow Equations / 260
: g6 ^) D6 E, H6.13 HVDC links / 261
( @& e+ K5 E3 |* ]& q. Y6.13.1 Modeling of HVDC Converters$ |* h' |% v: F: | K. O; V
and FACT Devices / 264
3 G/ s( C* g, O4 t9 }6.13.2 Definition of Angular Relationships in7 L9 z1 k4 y c Y& k' x' p
HVDC Converters / 264' M3 |4 k2 C! p, J' H
6.13.3 Power Equations for a Six-Pole HVDC; _, m! k! M; |. m
Converter / 264* ~6 N2 L# w! A0 J
6.14 Brief Review of Jacobian Matrix Processing / 267- S5 g/ c8 R: l5 `/ E* G* G
6.15 Example 6A: AC Power Flow Case / 2691 [) y$ E/ k* t7 P% _
6.16 The Decoupled Power Flow / 271
, v8 B8 R* I" T X" f2 P+ V6 c6.17 The Gauss–Seidel Method / 275
' R0 ^" p- x& \3 j1 X6.18 The “DC” or Linear Power Flow / 277
' s$ j5 m# J D/ Z. l5 p6.18.1 DC Power Flow Calculation / 277" N7 S0 ?: P6 [8 n% \; J; a
6.18.2 Example 6B: DC Power Flow Example on the
6 }0 h S, @+ {" ?- _: L: C! \1 dSix-Bus Sample System / 2787 ^$ K& K" k* e) A' t# a: T8 q
6.19 Unified Eliminated Variable Hvdc Method / 278
( g" G( L X: A6.19.1 Changes to Jacobian Matrix Reduced / 279
! x1 P: d$ \7 S4 I& h6 F, I6.19.2 Control Modes / 280: E) x# T m# I
6.19.3 Analytical Elimination / 280
5 p' Q W( @* B+ E! L( h6.19.4 Control Mode Switching / 283
* l. r# w0 D: ~" q9 S1 M3 L4 N6.19.5 Bipolar and 12-Pulse Converters / 283
, C/ h: k& r( R8 Q* v& z$ f6.20 Transmission Losses / 2848 {; Z& J, K' I2 v( H, E& a) c
6.20.1 A Two-Generator System Example / 284& g' ?' v, M. A4 I7 o
6.20.2 Coordination Equations, Incremental Losses,0 K1 y$ k# a/ t m2 L. ~ ?" f
and Penalty Factors / 286+ {4 |& R1 J% ~9 w5 B
6.21 Discussion of Reference Bus Penalty Factors / 288
: s. g; \3 w2 ` U6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
0 d( [9 ]$ ~" r( J. f3 e, X }' f: ]0 TPROBLEMS / 291
V V/ r& n! V b# }3 `1 s8 G7 Power System Security 296. X5 p& h5 N0 o9 x, Z) H& N: [
7.1 Introduction / 296
* w0 S" e2 t, a) D M0 V7.2 Factors Affecting Power System Security / 3013 W% B* c; a# [6 a( Q5 @* w7 N6 k
7.3 Contingency Analysis: Detection of Network Problems / 301
* ~' p! i% A. v y1 T _7.3.1 Generation Outages / 3013 B- K) L# `! V- Z. a3 U' e ]4 H
7.3.2 Transmission Outages / 302
7 D9 q& A9 f3 M6 yxii contents: |# \6 b( P9 n, @2 a" @+ t
7.4 An Overview of Security Analysis / 3068 ` m6 x. n6 Q; H$ n' W
7.4.1 Linear Sensitivity Factors / 307
8 H/ M' H6 e' ?7.5 Monitoring Power Transactions Using “Flowgates” / 3134 C8 U2 @; K& d
7.6 Voltage Collapse / 315
: r) z l$ ]9 a1 ^0 G7.6.1 AC Power Flow Methods / 3170 v2 t+ _3 u3 [. g3 [
7.6.2 Contingency Selection / 320
' k5 N- ~) e8 ]/ A7 c& ] z+ F7.6.3 Concentric Relaxation / 323& p5 v% r8 V: q
7.6.4 Bounding / 325
! B" @ x' f2 ~1 x7.6.5 Adaptive Localization / 3251 T7 ~8 L8 H" `
APPENDIX 7A AC Power Flow Sample Cases / 327
- G! a7 d/ g6 H4 g0 DAPPENDIX 7B Calculation of Network Sensitivity Factors / 336, \$ v" n! b5 G1 ^7 s3 j
7B.1 Calculation of PTDF Factors / 336
/ s3 U( h9 C9 }7B.2 Calculation of LODF Factors / 339
" \1 Y% T! R5 }1 I# s/ |2 ~ _7B.2.1 Special Cases / 341: v# P% f0 A+ Z5 c7 e3 m
7B.3 Compensated PTDF Factors / 343- e" D" \. R& d4 `8 `7 d5 X- Z3 T
Problems / 343
; W6 ]. n+ L p, |8 Z* |References / 349' u0 }! k4 { H
8 Optimal Power Flow 350
, K7 B9 z% A/ T% \# C8.1 Introduction / 3509 ^ w4 [! p8 D t' |% J" Y7 G
8.2 The Economic Dispatch Formulation / 351& j) }/ t" c, N
8.3 The Optimal Power Flow Calculation Combining
) o( c, S, w$ T+ L2 n# gEconomic Dispatch and the Power Flow / 352& P" I: l$ w1 I$ b/ ^. [: H
8.4 Optimal Power Flow Using the DC Power Flow / 354( s9 `% G( W0 W* \) C
8.5 Example 8A: Solution of the DC Power Flow OPF / 356
9 |/ s* f: d, s1 e8 Q: B Y8.6 Example 8B: DCOPF with Transmission Line
5 Q, R; [" _2 L SLimit Imposed / 361
$ h& W" z- N) p/ }( R, m8 r% D: o5 S8.7 Formal Solution of the DCOPF / 365
6 ?+ ]) S* L) ?. r2 v+ o8.8 Adding Line Flow Constraints to the Linear
( E! V$ N, @! TProgramming Solution / 365
$ ?: V H% _6 K$ h8.8.1 Solving the DCOPF Using Quadratic Programming / 367
- v1 h) [4 L- H& |3 Y7 @) @; }+ q8.9 Solution of the ACOPF / 368) z! {+ m3 w, h4 w0 u
8.10 Algorithms for Solution of the ACOPF / 3691 V: P6 d' b: g7 N! m. D# F
8.11 Relationship Between LMP, Incremental Losses,+ u9 ?! \, k# h' C# u' I
and Line Flow Constraints / 376
; G" I y: U t. [, V k& K8.11.1 Locational Marginal Price at a Bus with No Lines
8 i# p$ r1 f# @0 i' NBeing Held at Limit / 3770 Z/ p, j; X ^: x, \
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
7 \ T3 o7 Q5 X. M' ycontents xiii
) x( b& \ `* p5 H8.12 Security-Constrained OPF / 382$ {- V' l" I7 V0 }/ a
8.12.1 Security Constrained OPF Using the DC Power Flow
6 M' ]7 f2 L2 n# gand Quadratic Programming / 384
0 W9 b7 H0 L K8.12.2 DC Power Flow / 385
* N) d# z0 k. Q* l! R8.12.3 Line Flow Limits / 385
7 p6 |4 }" F4 {2 h p9 q f8.12.4 Contingency Limits / 386
* Z! j6 P: B( x2 G, QAPPENDIX 8A Interior Point Method / 391, B- O( X7 [* d6 Z+ G
APPENDIX 8B Data for the 12-Bus System / 393
9 |1 n. y$ s( b% R: m. tAPPENDIX 8C Line Flow Sensitivity Factors / 3951 ^7 R1 Z4 H$ A
APPENDIX 8D Linear Sensitivity Analysis of the7 S4 M: L- d/ Z* N
AC Power Flow / 397- {- n0 q2 Y( I) ?
PROBLEMS / 399! {1 r# K6 f T) M
9 Introduction to State Estimation in Power Systems 403
; z( c7 O- P8 V2 Q- i9.1 Introduction / 403
6 ~# B4 Y1 G* N9.2 Power System State Estimation / 404* U5 |) W0 u1 n$ O
9.3 Maximum Likelihood Weighted Least-Squares
: S' s7 b9 `( l& y' b( U2 AEstimation / 408
9 v3 I2 Y. |4 A& c& O9.3.1 Introduction / 408
, ]0 O0 b/ W& P+ A9.3.2 Maximum Likelihood Concepts / 4105 R+ y, o; @# ?4 q i
9.3.3 Matrix Formulation / 4141 \- L* e4 N3 [/ w
9.3.4 An Example of Weighted Least-Squares2 B. }6 Q' G# @. {
State Estimation / 417: E& @. `3 N {6 Y8 ^9 s+ v9 {
9.4 State Estimation of an Ac Network / 421
- [4 X+ {9 I3 y6 ]2 `9.4.1 Development of Method / 421. r* ^1 ^: r6 b2 z& P; v" c
9.4.2 Typical Results of State Estimation on an
. z+ R; F3 E( O; S$ a& KAC Network / 424: x0 n: {' R0 _ g. f& d
9.5 State Estimation by Orthogonal Decomposition / 428
2 M. ~( H: m7 C) @5 T' v$ L9.5.1 The Orthogonal Decomposition Algorithm / 431
% \$ S. H8 P0 b: ]8 ^& ~/ N! t9.6 An Introduction to Advanced Topics in State Estimation / 435
( N3 l0 } \5 L, b: r9.6.1 Sources of Error in State Estimation / 435
) t( Z* F0 ]% L3 t+ }+ W9.6.2 Detection and Identification of Bad Measurements / 436
A" f k1 ?& n+ F) R9.6.3 Estimation of Quantities Not Being Measured / 4434 a) R5 f8 n1 z( p8 H% ]
9.6.4 Network Observability and Pseudo-measurements / 444
" p+ F: R" d& q7 ~9 ?6 x9.7 The Use of Phasor Measurement Units (PMUS) / 447
- C4 o3 Y' f' p: }1 ]" G9.8 Application of Power Systems State Estimation / 451
4 f# V3 _4 w) q* p9.9 Importance of Data Verification and Validation / 4542 V1 S' c5 m( [" u
9.10 Power System Control Centers / 454
4 G$ H2 R# ~2 U8 q, N% c% bxiv contents$ w! K; k: }2 t# Y
APPENDIX 9A Derivation of Least-Squares Equations / 456
6 J3 V8 ?5 F- q7 R; \' b9A.1 The Overdetermined Case (Nm > Ns) / 457
5 _9 l- d/ Q+ |9A.2 The Fully Determined Case (Nm = Ns) / 462; W, R# \# e7 J K& X+ Q+ g. `
9A.3 The Underdetermined Case (Nm < Ns) / 462
. } R l' i- z" S1 _. q2 UPROBLEMS / 4642 |9 \* ~. o, g3 C& C9 y2 |+ K& Z
10 Control of Generation 468/ s" ? J& h: T' @( x
10.1 Introduction / 468" d5 Q; Z* g' i/ S( b3 ]2 B) w4 d
10.2 Generator Model / 4709 p+ J/ W3 |/ ~5 |5 G8 ]( |% }
10.3 Load Model / 473+ Q5 m/ b" q6 g3 B' h5 M
10.4 Prime-Mover Model / 475
; _6 E: ?( N9 ^ q( p) q10.5 Governor Model / 476" C" _9 Y8 ?: K8 V. k( Q& _4 k
10.6 Tie-Line Model / 481
: d! q" |! i. d7 D r% _1 x* z. v2 Z( A10.7 Generation Control / 485
5 }8 W" W2 ]6 p( J10.7.1 Supplementary Control Action / 485
4 a! V8 D t" {! X10.7.2 Tie-Line Control / 486
) C. I/ m2 Z; G10.7.3 Generation Allocation / 489: p5 o* D5 _3 c! _/ i
10.7.4 Automatic Generation Control (AGC): [2 `6 O( }. ~2 Y; s# j# v
Implementation / 491, q9 f6 f, z/ c$ Z1 d2 D
10.7.5 AGC Features / 4959 q+ h( R, _ ^: ^
10.7.6 NERC Generation Control Criteria / 496! X; ?9 h' p/ r% n& V
PROBLEMS / 497; P2 ^& N8 W) a; u$ o# G$ \
References / 500$ G" U6 u6 ~2 P+ Z- y- j
11 Interchange, Pooling, Brokers, and Auctions 501$ f v( O) E) z* W: g) m
11.1 Introduction / 501 g: S& U x7 B7 Y
11.2 Interchange Contracts / 504
% @% H @- H4 {3 B11.2.1 Energy / 5047 ^% F# q: _! z2 Z" a! @
11.2.2 Dynamic Energy / 506
% ?8 |& q4 o; g11.2.3 Contingent / 5062 `, O' M$ v2 {1 N- u
11.2.4 Market Based / 507) C8 n9 |- r6 r* D
11.2.5 Transmission Use / 5085 N) _- y# S4 _1 i
11.2.6 Reliability / 517$ M0 |! p" J/ ~# }7 w3 s% b
11.3 Energy Interchange between Utilities / 517' S4 Y$ _- o% E. d e8 k! P/ }
11.4 Interutility Economy Energy Evaluation / 521( g5 l8 t9 o1 @2 H
11.5 Interchange Evaluation with Unit Commitment / 522& O4 x" |* U8 ]0 g9 o0 J0 r+ C* ^
11.6 Multiple Utility Interchange Transactions—Wheeling / 523
$ |6 f* ^4 }: a8 v4 T11.7 Power Pools / 526
- ~: n8 E" o) J7 t% Pcontents xv
`, |+ R1 U) Q- {! e11.8 The Energy-Broker System / 529
+ w* i8 c! Q* a) U11.9 Transmission Capability General Issues / 533
0 y& r; i4 F( H# n11.10 Available Transfer Capability and Flowgates / 535* Q3 H; ^4 r1 F. v* p) a5 H) _3 ?
11.10.1 Definitions / 536
8 E4 Q6 }3 G, K" o2 g% b; F11.10.2 Process / 539
, N# a% I: ?& p. ]11.10.3 Calculation ATC Methodology / 540
' c! P% p1 m0 X6 U+ \/ v6 L4 f9 K11.11 Security Constrained Unit Commitment (SCUC) / 5502 V& a7 ?) X5 A; N8 L% O, E
11.11.1 Loads and Generation in a Spot Market Auction / 550
% P9 e8 E0 F3 x: K+ G# `! O% Z; F11.11.2 Shape of the Two Functions / 552
1 V' e3 }9 [# ?( F% o1 t T11.11.3 Meaning of the Lagrange Multipliers / 553+ L R. g* {' L5 x
11.11.4 The Day-Ahead Market Dispatch / 554( Z7 ]% z) B9 K$ y7 k: Z
11.12 Auction Emulation using Network LP / 555; p6 l; ^. ~* L
11.13 Sealed Bid Discrete Auctions / 555" e$ ^- x- H, _* X4 Q2 c/ F
PROBLEMS / 560: z. n9 Y8 F! O
12 Short-Term Demand Forecasting 5664 ^- V. d3 b6 u, e% h- c: G/ B" p2 }
12.1 Perspective / 566% R1 ^6 l/ r, J3 W
12.2 Analytic Methods / 569
- u G1 i- Q# g K H12.3 Demand Models / 571
, F1 ?' v% z' o8 d12.4 Commodity Price Forecasting / 572+ d* \# r3 V5 s; ]
12.5 Forecasting Errors / 573+ O9 A/ V5 d j6 r
12.6 System Identification / 573
' o+ v* _, c) Z$ S5 [8 y12.7 Econometric Models / 574& Z! T& s( ^/ z$ w) ]
12.7.1 Linear Environmental Model / 5740 a/ H, k# T2 a* B
12.7.2 Weather-Sensitive Models / 576
3 z2 ]6 _8 E3 v5 q& G12.8 Time Series / 578
! O$ @" m- R0 B12.8.1 Time Series Models Seasonal Component / 578
- t9 V) [9 Z; B5 J% M# y12.8.2 Auto-Regressive (AR) / 580
3 p V2 g; Q* _- w( Y2 ~6 e a12.8.3 Moving Average (MA) / 581
2 t0 y" L+ V1 M. e% E12.8.4 Auto-Regressive Moving Average (ARMA):
# J8 ], K# B* r! S6 P. n4 Z( KBox-Jenkins / 582
( m& H$ K: @* G a' e |12.8.5 Auto-Regressive Integrated Moving-Average) D4 q# m5 Z% q% l! b! t: N
(ARIMA): Box-Jenkins / 584
! p, l' H' v6 a A% |12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585* j$ @0 ~# P: e7 o' w! q# Z5 X
12.9 Time Series Model Development / 585. k, K' \5 T* ?' ?+ g2 @# o4 d: R
12.9.1 Base Demand Models / 586& d, V X1 G" g2 {" d+ p
12.9.2 Trend Models / 586
/ ^5 S* b' k& M- p/ K# ?12.9.3 Linear Regression Method / 586
' u' |9 U0 S! [# }1 Y0 Z, Uxvi contents
, R3 h3 `; ~# P" }. M( } E12.9.4 Seasonal Models / 588
7 D+ ~$ K9 [. U1 G& S12.9.5 Stationarity / 588
' M; U$ C; ?$ {12.9.6 WLS Estimation Process / 590
& J- i" y* Y) Q% u7 a( z12.9.7 Order and Variance Estimation / 591$ s& f/ R4 ^1 A6 F
12.9.8 Yule-Walker Equations / 592
- j& o/ D3 y7 g1 G# S6 m4 X/ s4 Y12.9.9 Durbin-Levinson Algorithm / 595! k) l9 b0 n! u' t( |6 M2 c# ]
12.9.10 Innovations Estimation for MA and ARMA3 |3 H+ ~8 I" O, _1 K
Processes / 598
0 T8 A/ O( B) B& l: o12.9.11 ARIMA Overall Process / 600
0 t: t( @/ h/ @8 G, T12.10 Artificial Neural Networks / 603+ n) }( q8 O% j' A% L4 L# p) A, l
12.10.1 Introduction to Artificial Neural Networks / 604- `# r- n9 o4 L# ^1 U$ T; D; B( u
12.10.2 Artificial Neurons / 6051 R- ^/ L% N3 {! Z0 {
12.10.3 Neural network applications / 606
& K% D7 v/ |: s" c1 ~6 b12.10.4 Hopfield Neural Networks / 6060 S6 G; h% H& P: a2 c
12.10.5 Feed-Forward Networks / 607
2 @. ^4 _; N$ _2 r& E( Q12.10.6 Back-Propagation Algorithm / 6107 B! Z- y+ e: _5 Y0 Y" M( ` D
12.10.7 Interior Point Linear Programming Algorithms / 613
$ V# n& E( G% j( o12.11 Model Integration / 614$ H/ }# X0 V+ m1 v
12.12 Demand Prediction / 6149 Q3 T, Q; t: \3 G4 ^+ Q, e7 b
12.12.1 Hourly System Demand Forecasts / 615% z e3 Z! j/ ` }( F
12.12.2 One-Step Ahead Forecasts / 615 [( J1 Y* K8 K9 ~6 `
12.12.3 Hourly Bus Demand Forecasts / 616
! a5 o2 _7 ^- s) c5 j12.13 Conclusion / 6167 Y3 w7 |5 I: C6 B; f
PROBLEMS / 617 |
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