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第三版目录。
) F2 h' a# v6 }2 [. M1 Introduction 12 d; S! @7 C, C4 i
1.1 Purpose of the Course / 1 X/ S% f9 K4 Y+ p+ [4 m
1.2 Course Scope / 2- T4 x: e, D) A4 r e, A
1.3 Economic Importance / 2
# Q% B6 }3 b' K( _: q1.4 Deregulation: Vertical to Horizontal / 35 g" g4 Z. Q' |
1.5 Problems: New and Old / 3
) [' I; t: j0 u r! w: b! }+ H1.6 Characteristics of Steam Units / 6# b8 e6 E; d5 L# M- b9 q
1.6.1 Variations in Steam Unit Characteristics / 10
) R7 _. v! r1 F0 f, o) F1.6.2 Combined Cycle Units / 13
5 d1 l# I( u0 y$ c c; C$ x4 x1.6.3 Cogeneration Plants / 14 x; l% y7 Z5 l" P" h3 N* ? p
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
, f- \0 d3 `2 z0 z+ u& x# c6 L7 j1.6.5 Hydroelectric Units / 18
5 ?9 E% K/ F# a, k6 f1.6.6 Energy Storage / 21
% N9 |$ s1 {* l4 I# i+ N, A4 c; _2 z1.7 Renewable Energy / 227 ], M+ I- p5 d
1.7.1 Wind Power / 23 ?: P6 h" ?; |3 [2 D
1.7.2 Cut-In Speed / 23
6 a: B6 i0 L7 g9 c% }! t1.7.3 Rated Output Power and Rated Output Wind Speed / 24% x5 `2 ~# _! i7 H$ K: X* {" B3 U
1.7.4 Cut-Out Speed / 24
+ t% ?! u9 O5 Y8 O% s1.7.5 Wind Turbine Efficiency or Power Coefficient / 24/ e2 y8 g% L9 ^, w+ U" E( F8 l
1.7.6 Solar Power / 254 U- d) p* R6 e$ Q5 x" w
APPENDIX 1A Typical Generation Data / 260 d( B" \7 n+ W* r! ]$ H
APPENDIX 1B Fossil Fuel Prices / 28% Z: g0 k" c# W, D
APPENDIX 1C Unit Statistics / 29! ~* Z6 z+ m6 V$ R6 a7 c% ?
CONTENTS
8 |$ w8 |( k- S4 Q& G! kviii contents4 m A2 ]/ `5 U! C
References for Generation Systems / 31
/ E" Z' f& T0 s3 L2 x* Y: TFurther Reading / 31
, v+ c' O# Y9 l2 Industrial Organization, Managerial Economics, and Finance 35
# A, n% \3 u* ^ S+ N" [2.1 Introduction / 35$ Q/ T4 N! g' i/ S. A* J+ P
2.2 Business Environments / 36
* J2 W3 o# p- Y1 k2.2.1 Regulated Environment / 37; F$ T5 h6 K5 _( }' `6 o
2.2.2 Competitive Market Environment / 38
/ Q2 x2 C+ m9 {8 R, F) s |2.3 Theory of the Firm / 40
0 Y3 c' W& l+ M& I8 W5 d2.4 Competitive Market Solutions / 42
! ]& J2 I2 F7 n8 B9 n+ Q1 K2.5 Supplier Solutions / 45% A* f6 ]" n0 {, P. C$ O
2.5.1 Supplier Costs / 46
/ w1 p5 `1 P; ?8 e; B3 U% K2.5.2 Individual Supplier Curves / 46! F- d( h3 `; I# r: J
2.5.3 Competitive Environments / 47
1 G8 X, X" f y# \% O2.5.4 Imperfect Competition / 513 T$ ^/ A2 W* \+ N5 U3 T( n, W
2.5.5 Other Factors / 52
+ H. J( Z% y5 s2.6 Cost of Electric Energy Production / 53
& `. J, ], R9 Y. e9 @* H, P2.7 Evolving Markets / 541 m" ]. Q4 J: m. m
2.7.1 Energy Flow Diagram / 575 m' A0 |& i9 _: c
2.8 Multiple Company Environments / 58
8 F, ?: I9 B `2.8.1 Leontief Model: Input–Output Economics / 58
" ]/ a- G6 T8 j0 ^5 L" j! k2.8.2 Scarce Fuel Resources / 608 {4 v3 b9 W! h9 T- o
2.9 Uncertainty and Reliability / 61
/ A1 d! l9 I% R& \' y0 |3 CPROBLEMS / 61
/ X4 y+ G0 l1 @9 P; a) `) v; @. xReference / 62
2 j' B8 Z9 I5 `/ n! Y3 Economic Dispatch of Thermal Units and Methods of Solution 63( `- \3 x$ D1 B. Y, _6 m
3.1 The Economic Dispatch Problem / 630 W% X, @8 {" a% q! b& r& Z. O
3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68
; K% P* t9 ~5 m7 F3.3 LP Method / 69
: n: U t1 ?7 [3.3.1 Piecewise Linear Cost Functions / 691 ~9 M! u# B4 |4 U/ s3 {
3.3.2 Economic Dispatch with LP / 717 R! |! ^8 Q0 N0 o
3.4 The Lambda Iteration Method / 73+ _( v3 X, g0 C) l
3.5 Economic Dispatch Via Binary Search / 76" W8 i/ P* H3 l, ^! W
3.6 Economic Dispatch Using Dynamic Programming / 78
! y' W: t: ^; ^, A# x7 i3.7 Composite Generation Production Cost Function / 81* @' J9 Z& N% g, q! `
3.8 Base Point and Participation Factors / 85& {8 W" q( Q* q6 i
3.9 Thermal System Dispatching with Network Losses
7 a. }; j3 z8 Q- LConsidered / 88. |2 Q6 ]# V3 O( g! D) F. V' L
contents ix8 I" R9 w& d$ f
3.10 The Concept of Locational Marginal Price (LMP) / 92! a8 `: Y( T" q: W- g% h
3.11 Auction Mechanisms / 954 R0 ?3 l& u0 M7 n6 n! W+ I
3.11.1 PJM Incremental Price Auction as a
5 [; P/ g; [6 ?1 C/ uGraphical Solution / 95
% Z3 w: s* e5 S. q; l" o7 w) S1 [3.11.2 Auction Theory Introduction / 98
7 [( ]$ W0 [/ d( I3 p3.11.3 Auction Mechanisms / 100+ A0 E! |% { a" M* D
3.11.4 English (First-Price Open-Cry = Ascending) / 101
0 l% v. _) s0 [1 y3 }) S4 p3.11.5 Dutch (Descending) / 103
, T" F# p$ V3 T2 G9 D# ~6 \: }3.11.6 First-Price Sealed Bid / 104
$ r( x. o6 X/ e4 ^$ W, @3 O3.11.7 Vickrey (Second-Price Sealed Bid) / 105( D" k: ~2 s- ?! ~+ F( x
3.11.8 All Pay (e.g., Lobbying Activity) / 105" F5 x6 Y6 F( k6 |
APPENDIX 3A Optimization Within Constraints / 106
; r+ v7 T/ O. u2 ]APPENDIX 3B Linear Programming (LP) / 117
) U9 l8 [6 Z' K6 sAPPENDIX 3C Non-Linear Programming / 128
7 T/ l9 {6 N0 l9 S. AAPPENDIX 3D Dynamic Programming (DP) / 128
5 o# J, E+ f3 O0 s/ p1 {& K+ N9 eAPPENDIX 3E Convex Optimization / 1359 |/ |- h& |5 X7 ]* d0 j; [
PROBLEMS / 1385 O% D- r+ }6 q5 y; Z
References / 146
" K( ~$ B& v q. D6 j& r) O4 Unit Commitment 147
5 l* c9 @& C' o( B4.1 Introduction / 147) f- F# W- {7 {3 ?3 P
4.1.1 Economic Dispatch versus Unit Commitment / 147' P' J, W% I5 ?5 ?$ y; L/ O
4.1.2 Constraints in Unit Commitment / 152
! c; S$ q/ _2 t' p* `4.1.3 Spinning Reserve / 152+ c) A- L/ H; f, Q, D& Z' G5 t
4.1.4 Thermal Unit Constraints / 153 t1 f i" o# t9 W
4.1.5 Other Constraints / 1558 r5 D5 @4 X+ n5 R
4.2 Unit Commitment Solution Methods / 155! x% v# K' J R9 z( W2 y. x
4.2.1 Priority-List Methods / 156
. a8 F) e0 z" p" P2 r4.2.2 Lagrange Relaxation Solution / 1574 A% j+ J* X- ]. W
4.2.3 Mixed Integer Linear Programming / 166
, |$ \8 n2 N: L; E6 D4.3 Security-Constrained Unit Commitment (SCUC) / 167
/ i; }7 \% J, e( P& }2 t- y4.4 Daily Auctions Using a Unit Commitment / 1676 }6 M, l. P$ S0 Y# |6 Z
APPENDIX 4A Dual Optimization on a Nonconvex% r- X+ R. ]- W
Problem / 1673 O. d( B* t9 D
APPENDIX 4B Dynamic-Programming Solution to7 p( @2 P2 l8 r2 n' v( G
Unit Commitment / 1739 o! g2 C& ?9 y! X. D* h( |
4B.1 Introduction / 173
G/ G: s0 F5 d1 ~' A/ x4B.2 Forward DP Approach / 174
% w" |) T2 i# O: aPROBLEMS / 182
' Z9 N7 o9 h' |3 F6 E8 jx contents3 Z' Y2 o* [! o s! ^' I2 M) r# E
5 Generation with Limited Energy Supply 187+ O7 S' r( X: B6 Q7 ~
5.1 Introduction / 187) m8 I v1 @9 e
5.2 Fuel Scheduling / 188& x/ o4 o1 Q/ l2 W/ n9 N# v0 j
5.3 Take-or-Pay Fuel Supply Contract / 188( v* n$ N( Z1 {6 W
5.4 Complex Take-or-Pay Fuel Supply Models / 194
6 p7 A% A5 C( {: `, m3 I% }5.4.1 Hard Limits and Slack Variables / 194
) C' I8 f5 X6 {8 I" t! G z1 q5.5 Fuel Scheduling by Linear Programming / 195
1 \- v* D7 f: l- [5.6 Introduction to Hydrothermal Coordination / 202, B u5 K7 d4 B4 B1 S) [8 H" d
5.6.1 Long-Range Hydro-Scheduling / 203
0 m; M& [) h4 h* J% v5.6.2 Short-Range Hydro-Scheduling / 204
! V& U, r; E( H# ?, A5.7 Hydroelectric Plant Models / 2040 [$ V/ G. u+ n3 W$ g+ l
5.8 Scheduling Problems / 207
! R& G b, B, E5.8.1 Types of Scheduling Problems / 207
! k" m5 g5 N6 o5 c3 f$ @9 _ r5.8.2 Scheduling Energy / 207
. Y' b6 o* C" a* l" p5 ]/ G5 n- P M5.9 The Hydrothermal Scheduling Problem / 211
& C& o" C- D1 H( Q6 t: I: u5.9.1 Hydro-Scheduling with Storage Limitations / 2116 o R/ w- ~" s1 B
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216; U7 \7 i0 G& J* t3 l& m
5.9.3 Pumped-Storage Hydroplants / 218! e a$ W7 e2 e; B. t; Z# d+ C
5.10 Hydro-Scheduling using Linear Programming / 222
: g+ ^3 { h9 O8 M+ \1 i# h( PAPPENDIX 5A Dynamic-Programming Solution to hydrothermal
: m% ?+ ]5 M& CScheduling / 2258 x% e1 ~2 R1 j2 Q: u9 B
5.A.1 Dynamic Programming Example / 227
+ H, F4 r. p: S4 @" C( [: x5.A.1.1 Procedure / 228( B$ P9 i$ s/ n: ?) H
5.A.1.2 Extension to Other Cases / 231( [7 |" [, T& ^' N" j- T
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
$ T# e- u4 E4 M; cProblem / 232
: f2 ?+ I5 `0 N, ~! X7 o/ Y8 hPROBLEMS / 234* A- |% q1 C7 X1 ]
6 Transmission System Effects 243
f2 J4 b, u% p0 \- \0 @: D6.1 Introduction / 243
; `" @) K6 W" r" _, k2 }) |6.2 Conversion of Equipment Data to Bus and Branch Data / 247
( D1 s+ _& N u# ^3 [4 _6.3 Substation Bus Processing / 248
: w$ z9 Y0 ~! O2 B6.4 Equipment Modeling / 248
# D. q4 m) l/ I2 V4 ^: N, s6.5 Dispatcher Power Flow for Operational Planning / 251
9 ^" M6 s& R; s" f! j/ M6.6 Conservation of Energy (Tellegen’s Theorem) / 2523 P- G8 R* D; B9 q; v J
6.7 Existing Power Flow Techniques / 2537 ~1 O/ W4 l- Q" `3 D, o
6.8 The Newton–Raphson Method Using the Augmented6 z* z3 ?4 `1 c8 q! T- l4 y- g2 p
Jacobian Matrix / 2541 f+ `; l4 s" h, [8 U2 w
6.8.1 Power Flow Statement / 254+ h& |5 Q4 @6 U' V
6.9 Mathematical Overview / 257
2 s, ~( P8 x2 M* v/ ccontents xi8 I$ v1 N3 f4 @" S/ }- W( n7 Q/ N2 j
6.10 AC System Control Modeling / 259
( M8 J4 w# P# U0 e6.11 Local Voltage Control / 259
' b6 Z0 \2 b+ k, @8 d6 t/ o6.12 Modeling of Transmission Lines and Transformers / 259$ ~( t5 f! e: k0 ?5 U& W
6.12.1 Transmission Line Flow Equations / 259' I& P2 U" C0 [: Z& K5 [# d
6.12.2 Transformer Flow Equations / 260
^" w2 _ g7 t) [- P; ^6.13 HVDC links / 261) |" a' d9 e8 w
6.13.1 Modeling of HVDC Converters! @2 \1 z4 Z. S. ?
and FACT Devices / 2643 u# ~% f& u- a1 p, D- _' {: D0 ?$ z
6.13.2 Definition of Angular Relationships in
1 m4 s; X) t8 H$ kHVDC Converters / 264! g- J7 L! \# A& K7 [8 I9 z6 |
6.13.3 Power Equations for a Six-Pole HVDC" N, u; B2 x5 y8 z1 D; r3 c, n! \
Converter / 264% L: s& U7 s8 F, H
6.14 Brief Review of Jacobian Matrix Processing / 2672 e- j! q2 h; E- g& U+ O
6.15 Example 6A: AC Power Flow Case / 269
+ X. p3 i5 G. j- [6 D/ D' r6.16 The Decoupled Power Flow / 271
5 @& u7 @* I1 t: u' W. N8 R5 a6.17 The Gauss–Seidel Method / 275
# P. L. q! Y3 X& G& l9 |1 J6.18 The “DC” or Linear Power Flow / 277) \, l6 [8 ~2 ~# w4 R6 B7 i% h
6.18.1 DC Power Flow Calculation / 277
, N. U' k$ t& b4 Y" a6.18.2 Example 6B: DC Power Flow Example on the& p' z6 ~2 G3 g, O. S
Six-Bus Sample System / 278
6 r8 x! f2 [& |9 f6.19 Unified Eliminated Variable Hvdc Method / 278' u, Q' `9 B1 M8 F, Z% C
6.19.1 Changes to Jacobian Matrix Reduced / 279 Z0 \: X" [5 g( B; A3 K0 F+ z
6.19.2 Control Modes / 280
( f- {& Q6 K: Y# X6.19.3 Analytical Elimination / 280* ^2 J$ [0 P# Q) I
6.19.4 Control Mode Switching / 283
# X" o# o$ _) U4 r" L6.19.5 Bipolar and 12-Pulse Converters / 283
8 B- r1 s) Z3 Y4 w3 U1 n; p6.20 Transmission Losses / 284
. s* [1 _, |1 a! w8 y6.20.1 A Two-Generator System Example / 284" G2 N+ h! t5 c1 i: w6 U$ Q2 ]5 d
6.20.2 Coordination Equations, Incremental Losses,; O1 g; k4 @5 d$ m. S6 N: d
and Penalty Factors / 286
* r1 t6 c* C6 v% j* \; R( R6.21 Discussion of Reference Bus Penalty Factors / 288
5 Q) T6 M8 m. K; c2 o3 R6.22 Bus Penalty Factors Direct from the AC Power Flow / 2893 C/ o* Z ~2 G) N8 j' {7 A
PROBLEMS / 291
" l% {. S. ]: \2 U. a8 T7 Power System Security 2963 j( C* I% c8 a. @! ^8 Y
7.1 Introduction / 296
% v0 V, v4 m' E# r7.2 Factors Affecting Power System Security / 301$ s) _1 M9 G" h
7.3 Contingency Analysis: Detection of Network Problems / 301
7 q+ @3 g) R6 I" a' F; O+ r) T' O7.3.1 Generation Outages / 301
6 \- N0 d+ O- k, a, d7.3.2 Transmission Outages / 302. f! F: a9 w4 J
xii contents; _4 H: f# ^& N
7.4 An Overview of Security Analysis / 306
" ?, D1 v# E! o# o. T1 u- I) _7.4.1 Linear Sensitivity Factors / 307
2 N. C! g! H3 }% ]- A( |7.5 Monitoring Power Transactions Using “Flowgates” / 3132 q/ ^" J; R. c+ X
7.6 Voltage Collapse / 3153 V0 [, r: w. n/ _2 r+ d D
7.6.1 AC Power Flow Methods / 317 _+ b0 q! [* h& }$ v
7.6.2 Contingency Selection / 320- N6 y$ D/ z+ T: G9 q3 o- C9 z
7.6.3 Concentric Relaxation / 323/ A5 v& n; G) m8 v7 ?
7.6.4 Bounding / 325
9 P5 _1 t1 y6 D' |( J3 l7.6.5 Adaptive Localization / 325/ h0 l$ V7 ?9 v- \5 R- L* ^
APPENDIX 7A AC Power Flow Sample Cases / 327
7 o6 {1 g1 v, t; f# PAPPENDIX 7B Calculation of Network Sensitivity Factors / 336
# u5 y+ q2 T9 A' @9 g7B.1 Calculation of PTDF Factors / 336
+ i* o9 L6 \1 s2 e8 k+ V7B.2 Calculation of LODF Factors / 339 T) O/ A: l: D. c8 K, r$ Q
7B.2.1 Special Cases / 341
( i9 k# K$ l8 i( a' @3 V" S7B.3 Compensated PTDF Factors / 343
4 N" ?& P! g, P9 {; O- D* RProblems / 343
" \* x- n8 I7 z, G. k" EReferences / 349
: U' Y# a. C9 V! R8 J, W# t- G. Y8 Optimal Power Flow 350
8 a5 X; P5 F& [# @8.1 Introduction / 350
0 `# R) a7 b- d( H# y+ n$ y8.2 The Economic Dispatch Formulation / 351
4 j$ U/ L# Q+ [8 A8.3 The Optimal Power Flow Calculation Combining# e. {; o, k! Q6 @9 o8 S. {
Economic Dispatch and the Power Flow / 352
9 \6 a6 ^" ?) {8.4 Optimal Power Flow Using the DC Power Flow / 354
6 Z* p1 y G; ~! R1 q" Z- Z: G; c8.5 Example 8A: Solution of the DC Power Flow OPF / 356! a9 f2 O! R% `2 s( C' _
8.6 Example 8B: DCOPF with Transmission Line
1 o% D5 T2 O w/ L; ]) m$ D8 RLimit Imposed / 361
, @: C. s- O& S: G8.7 Formal Solution of the DCOPF / 365
& c; i+ t' J$ d7 ?- c! ]0 A: |* T8.8 Adding Line Flow Constraints to the Linear6 F# Y4 }: V6 Q' q Q1 p. }8 d
Programming Solution / 365 e* t& r" N/ Y4 ~# U
8.8.1 Solving the DCOPF Using Quadratic Programming / 367
) G% ?$ K% l* y& _' H( Q8 w4 q8.9 Solution of the ACOPF / 368% n |) Y, U5 \! f& S
8.10 Algorithms for Solution of the ACOPF / 369
* d+ C) P- @7 ^" f# w4 s) ^) `( C8.11 Relationship Between LMP, Incremental Losses,
8 H H: T9 }% e( o/ Iand Line Flow Constraints / 376
5 U4 f+ x y" I; V4 G7 S8.11.1 Locational Marginal Price at a Bus with No Lines6 y/ x' k+ @7 j) f# R3 H% Z
Being Held at Limit / 3771 M( G+ |$ D% t* M3 f- [) n
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
- A( N' ?8 b( ]; l8 D- Kcontents xiii
9 D9 s1 I+ ^: f/ A, c0 m/ h8.12 Security-Constrained OPF / 382+ _0 b2 p* I1 ^
8.12.1 Security Constrained OPF Using the DC Power Flow
/ a: M# z Y; D% Yand Quadratic Programming / 3849 d% S2 W: n7 A/ X+ V5 Q
8.12.2 DC Power Flow / 385 b0 ^1 k6 g j' D. E" l
8.12.3 Line Flow Limits / 385
2 k" [2 t1 f1 V+ W# |+ |8.12.4 Contingency Limits / 386( {3 {2 Q* P) u: H! {/ W1 P
APPENDIX 8A Interior Point Method / 391" [$ r+ P0 z# D# b/ f5 F8 Z
APPENDIX 8B Data for the 12-Bus System / 393* l7 i' Y2 E$ q* U0 M1 Z
APPENDIX 8C Line Flow Sensitivity Factors / 395
3 @0 q' p9 j+ \: j- d2 h; m) GAPPENDIX 8D Linear Sensitivity Analysis of the
, A- H3 z3 ]# DAC Power Flow / 397' e' R; b4 W( D1 `- g0 y% s9 C
PROBLEMS / 399, z: Y/ G* j! Z* s
9 Introduction to State Estimation in Power Systems 4031 H+ L' l" z- x7 [3 ?& y
9.1 Introduction / 403" _" y3 F$ t4 `, ?3 D! o1 b8 t
9.2 Power System State Estimation / 404; U# m+ K( v0 X) a) u9 X
9.3 Maximum Likelihood Weighted Least-Squares
3 ?) B$ w1 E6 f: yEstimation / 408
- V5 o( O. ]+ Z1 Z! `) @+ v9.3.1 Introduction / 408# a# P% h. D8 m% w% @# k* Q, X. S! t
9.3.2 Maximum Likelihood Concepts / 410
1 x6 i% h- }1 l, v0 T" D9.3.3 Matrix Formulation / 4143 W+ z( e' \) {" H
9.3.4 An Example of Weighted Least-Squares
/ @+ l& y3 n' T! X" l& OState Estimation / 417
4 O! |2 U+ l/ S9.4 State Estimation of an Ac Network / 4216 R$ [# C+ r; l& T6 p
9.4.1 Development of Method / 421
0 p$ z' Q9 W O% j9.4.2 Typical Results of State Estimation on an, \8 i/ b1 L ?9 g5 j7 I
AC Network / 424, s9 [3 s5 ? ]7 B m0 _
9.5 State Estimation by Orthogonal Decomposition / 428' F1 _/ k0 `" k8 T
9.5.1 The Orthogonal Decomposition Algorithm / 431, h! x" W9 {) o4 J* \7 a
9.6 An Introduction to Advanced Topics in State Estimation / 435" O, w. O) g/ z+ v* N2 d
9.6.1 Sources of Error in State Estimation / 4350 b+ `/ T3 S: ~- u0 u, K6 m
9.6.2 Detection and Identification of Bad Measurements / 436
; X7 t6 n& Z/ Z) F/ I- A3 j9.6.3 Estimation of Quantities Not Being Measured / 443
$ s3 u( ^# T9 f7 n$ @9.6.4 Network Observability and Pseudo-measurements / 444. w4 {& E* _ V u3 s1 s2 _
9.7 The Use of Phasor Measurement Units (PMUS) / 447, j6 o+ n9 ?- h, P' S
9.8 Application of Power Systems State Estimation / 451+ k1 G3 \$ M: p% c/ ` v
9.9 Importance of Data Verification and Validation / 454
4 C) Y2 `, l) b; M* J9.10 Power System Control Centers / 4549 N" C$ i4 _4 S4 i ]% Q6 S
xiv contents! b# K8 @; z: V$ S* v W6 {
APPENDIX 9A Derivation of Least-Squares Equations / 456
1 d, m6 b$ s, @) k9A.1 The Overdetermined Case (Nm > Ns) / 4571 n$ X" t2 x( @0 O2 {! f
9A.2 The Fully Determined Case (Nm = Ns) / 462
* j* C; o, Y4 r) J9A.3 The Underdetermined Case (Nm < Ns) / 462
' i2 W& O) @/ j/ Z; M7 s$ g( ePROBLEMS / 464" ~ y c! x' A- z
10 Control of Generation 468. Y$ W u! E; D% w1 n5 S
10.1 Introduction / 468
" q m% g1 f6 ?10.2 Generator Model / 4704 }2 k: k5 l- c" P: S# @
10.3 Load Model / 473- C0 R% b% J% t, X
10.4 Prime-Mover Model / 475
3 s; V, X. l8 P3 H& ~4 j10.5 Governor Model / 476; ^5 ?3 T% d! v3 u
10.6 Tie-Line Model / 481
' H% Q& T" @" h0 e3 k" C10.7 Generation Control / 485. L8 p: T! C) `& a, V; X1 t
10.7.1 Supplementary Control Action / 4852 g8 n( ~# i. X. [# W
10.7.2 Tie-Line Control / 486
+ d: K' K8 ?! W2 J% D5 h- C$ ?10.7.3 Generation Allocation / 489* y6 l+ x" B5 A
10.7.4 Automatic Generation Control (AGC)3 j2 p: u# \2 w
Implementation / 4911 |, U- k. c' F1 }- L' c1 j
10.7.5 AGC Features / 4951 w- `4 t0 H9 J1 v/ {
10.7.6 NERC Generation Control Criteria / 496
1 D" A. B: {# d) e4 R+ s$ x( CPROBLEMS / 497
# n2 @6 d/ R+ Z0 Q cReferences / 500' Q8 ^8 _2 P: R `( f7 ]
11 Interchange, Pooling, Brokers, and Auctions 5012 k$ `/ C9 h* H, X4 X! A: }1 x
11.1 Introduction / 501
# l3 s& B& m5 W/ O; w, }9 A1 O# H$ c11.2 Interchange Contracts / 504/ I' G8 T9 U' K
11.2.1 Energy / 5040 i4 u) T. A/ C* G7 Y3 g
11.2.2 Dynamic Energy / 506
$ ]/ `, J1 L' a. X$ r5 t" |, h% [- |! J11.2.3 Contingent / 506# T1 d" a ]! m( j, E6 B3 \" A2 F: _
11.2.4 Market Based / 507
& p" [0 U5 \( m) b11.2.5 Transmission Use / 5081 y$ R' e# q" Z7 _, A: m2 K
11.2.6 Reliability / 517
6 A( F3 ?- C+ [/ k( b! j+ W1 L11.3 Energy Interchange between Utilities / 517& D3 R* U9 @/ c% |: v9 x: c
11.4 Interutility Economy Energy Evaluation / 521$ x+ u7 X' L6 R
11.5 Interchange Evaluation with Unit Commitment / 522
7 m, ~1 n7 L$ J& V11.6 Multiple Utility Interchange Transactions—Wheeling / 523. E( D1 F. S+ h1 o2 t, W5 p
11.7 Power Pools / 526) N/ o3 A2 k* w- h
contents xv
. M$ {# o% N. h( ?11.8 The Energy-Broker System / 529
5 ^) r) @! l4 q. }11.9 Transmission Capability General Issues / 533
/ G# T9 z9 h' I2 G11.10 Available Transfer Capability and Flowgates / 535
2 j& X% p) V6 X- \8 q; T11.10.1 Definitions / 536, V) P6 t. G7 n( s c
11.10.2 Process / 539# C% t) S# n/ U( l8 u5 H
11.10.3 Calculation ATC Methodology / 540
0 m+ {: H# E4 q* k, o* e11.11 Security Constrained Unit Commitment (SCUC) / 550
$ ]1 n' y3 M- c! I3 @+ E- V* n11.11.1 Loads and Generation in a Spot Market Auction / 550, S0 ~% r! D0 M9 @7 r
11.11.2 Shape of the Two Functions / 552& a# w6 s7 `" j k$ Q3 q O x4 ]
11.11.3 Meaning of the Lagrange Multipliers / 553+ r) D) W, B2 M4 W) o" B
11.11.4 The Day-Ahead Market Dispatch / 554
4 H1 M3 j% P5 v+ g/ `9 t11.12 Auction Emulation using Network LP / 555
1 B6 \ S8 i( D j, H4 s5 ?7 W- `11.13 Sealed Bid Discrete Auctions / 555
1 ]! G( W, S' f; IPROBLEMS / 560
" G7 @" `0 u( s/ s* m. O7 L* }! R12 Short-Term Demand Forecasting 566
7 { e/ y$ d! b6 L% N( e2 R12.1 Perspective / 566
+ x* o5 w0 d, v7 |" J q12.2 Analytic Methods / 569# [: j: r. ~) Q6 _% U, p
12.3 Demand Models / 571
9 ^- ^2 A6 I5 _7 \4 ?* {! z& Q12.4 Commodity Price Forecasting / 5721 t4 k0 j( L2 z, Y. Q \& R3 f
12.5 Forecasting Errors / 5739 {/ B# G( X# [/ [7 L) l
12.6 System Identification / 573
3 d6 x' S+ f. h2 ~* s7 K3 H12.7 Econometric Models / 5744 X6 B; ]6 v) h T# |2 x" `; t, o
12.7.1 Linear Environmental Model / 574
" d% G3 Z% u; g" m8 X( W12.7.2 Weather-Sensitive Models / 576- d7 b+ Y: \% D% p( Y' {/ Q1 r
12.8 Time Series / 5786 l* }' u+ G! S' E- o" \
12.8.1 Time Series Models Seasonal Component / 578" g# U6 X/ z" u7 w
12.8.2 Auto-Regressive (AR) / 580
4 I& k) Z7 u, o12.8.3 Moving Average (MA) / 5819 |/ w6 |1 U) [
12.8.4 Auto-Regressive Moving Average (ARMA):
' O, S. ~: q3 }0 o0 Y2 s, a, nBox-Jenkins / 582
3 w/ ^% U. P5 J0 h' {" N12.8.5 Auto-Regressive Integrated Moving-Average
6 t; q# U6 X/ U2 l! ], u }7 `(ARIMA): Box-Jenkins / 584
8 N! G6 P! j3 U. y% w- y6 H12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585& l* c2 z3 ?+ W* _3 N8 {
12.9 Time Series Model Development / 585 P) C F( z- N, I
12.9.1 Base Demand Models / 586 i9 `! }2 P7 R8 k6 n
12.9.2 Trend Models / 586
+ Q, O7 r2 K8 L12.9.3 Linear Regression Method / 586
! d: p5 J" U9 H" k- Sxvi contents
& u! z8 d' g+ {7 p* [0 J* L: u4 H3 l12.9.4 Seasonal Models / 588' d1 y' j$ T7 x" P5 r1 |' P; I* ~
12.9.5 Stationarity / 5888 R M3 O/ M9 c# P
12.9.6 WLS Estimation Process / 590
! g( p3 C1 O E- s. e$ ^! g+ j, Z12.9.7 Order and Variance Estimation / 591' @. x( }6 @4 |) E1 Z n
12.9.8 Yule-Walker Equations / 592& ~5 y2 `5 F: c( l$ }2 L- U/ O
12.9.9 Durbin-Levinson Algorithm / 595" G3 z. M# H f8 ? Z# P) K! F l
12.9.10 Innovations Estimation for MA and ARMA& O) [ t( `& ]$ m6 N+ o1 w9 [* U
Processes / 598
' s" g$ a: E4 `+ v8 F1 x" x. z12.9.11 ARIMA Overall Process / 600* A7 m( B+ ]% q* y
12.10 Artificial Neural Networks / 6034 U. S( h& Y# I* R7 t2 K& @
12.10.1 Introduction to Artificial Neural Networks / 604
' I1 |/ b3 y, p, P12.10.2 Artificial Neurons / 605
4 E) p; E5 e$ g7 O12.10.3 Neural network applications / 6061 @+ }' Q, |) y9 @6 j
12.10.4 Hopfield Neural Networks / 6060 ]3 T4 p" a. @: y9 e" m
12.10.5 Feed-Forward Networks / 607
0 R( U9 }2 B# d( y% f' s& C/ r12.10.6 Back-Propagation Algorithm / 610
, S8 o% ~1 b# g. H- `# e: [" {12.10.7 Interior Point Linear Programming Algorithms / 613
% `- u, T6 J0 T8 R- u# N8 M' ]12.11 Model Integration / 6148 @& r/ {/ \, b& h0 j+ T& e/ I2 z
12.12 Demand Prediction / 614
: `: N5 M3 d9 n; R12.12.1 Hourly System Demand Forecasts / 6154 H9 h$ B; o5 I I; D
12.12.2 One-Step Ahead Forecasts / 615' z, C s6 }: E! r
12.12.3 Hourly Bus Demand Forecasts / 616* h @9 R6 o. A9 i0 Z8 N& {4 L
12.13 Conclusion / 616( c8 |0 n4 p8 d' d
PROBLEMS / 617 |
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