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第三版目录。
7 V/ z5 V1 U3 j0 O, i6 \, |1 Introduction 1
3 B. \5 \' R) V! Q) f0 D1.1 Purpose of the Course / 19 P* b+ _: l4 I$ V
1.2 Course Scope / 2
( n! M; X5 J$ y( C2 D/ g1.3 Economic Importance / 2
( q# D9 m2 [$ k. P$ ^- ]% \1.4 Deregulation: Vertical to Horizontal / 3/ E( d7 E4 B" E
1.5 Problems: New and Old / 3
3 a! U1 h7 k1 T& ?0 Y8 ]" Z1.6 Characteristics of Steam Units / 6
2 u& V& H& X6 A3 B1.6.1 Variations in Steam Unit Characteristics / 10! e& w' `! p% K2 \6 I G. w7 [
1.6.2 Combined Cycle Units / 13
( X" Y: E% o% L/ B6 K1.6.3 Cogeneration Plants / 14
9 Y) p3 x% l# g& s5 l, v1 D1 B1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
1 D0 y1 g/ G0 }8 C8 S. z1.6.5 Hydroelectric Units / 18- z! V1 S. h/ {1 |1 w: c' v
1.6.6 Energy Storage / 21. h: B$ p# x5 r2 t0 P) P! l4 F) M) _
1.7 Renewable Energy / 22" T3 c+ ~$ n! E# D3 b) a
1.7.1 Wind Power / 232 d$ q& l/ D7 Q8 a3 }; h
1.7.2 Cut-In Speed / 23
0 { X/ h6 g5 h8 ^) X1.7.3 Rated Output Power and Rated Output Wind Speed / 24' {# V/ l9 j7 N0 `
1.7.4 Cut-Out Speed / 24; c" v3 U4 ]& b/ f7 g6 b
1.7.5 Wind Turbine Efficiency or Power Coefficient / 24
5 U, y, t) v6 `" A8 u' h1.7.6 Solar Power / 25 `! O1 h' o+ ]5 v* C7 Q8 e' u
APPENDIX 1A Typical Generation Data / 26 N/ G+ D! i7 F, w
APPENDIX 1B Fossil Fuel Prices / 28$ M6 D; h. _$ g/ X6 k7 b0 J4 e% Y
APPENDIX 1C Unit Statistics / 29
5 a7 K: B6 b1 ]4 E8 _3 v' W) |9 ~8 fCONTENTS
O. x0 ^ h6 E' X9 bviii contents! q' j3 J- F4 r8 X$ G
References for Generation Systems / 313 P* p2 Z. Z2 r. r/ z* ?7 N J2 _ k
Further Reading / 31; q9 K8 T' s; q8 H
2 Industrial Organization, Managerial Economics, and Finance 35
* L e7 w/ K7 I6 t4 o4 F7 P2.1 Introduction / 35
0 g3 [- B+ F9 g! A( C8 A1 K% Z2.2 Business Environments / 36+ w4 M; T' h$ V5 B
2.2.1 Regulated Environment / 378 l; W& Y! [9 N- h/ ]0 X" G
2.2.2 Competitive Market Environment / 380 m# U6 A* G7 W+ ^, I1 b& p
2.3 Theory of the Firm / 400 S: ?) V6 W3 F- \
2.4 Competitive Market Solutions / 42
" n* w: h6 T) k+ g. n2.5 Supplier Solutions / 45( \+ s' D, v! A) R) \6 k0 K* x
2.5.1 Supplier Costs / 460 s, x. W$ ^/ r$ }
2.5.2 Individual Supplier Curves / 46
3 B" ?* q V, ~3 L2.5.3 Competitive Environments / 47
7 _* ?0 ]$ M. s- W& u2.5.4 Imperfect Competition / 51: |* ^- q" B- K8 N$ `3 F3 v; }
2.5.5 Other Factors / 52
5 w+ p# M+ T0 u* y8 c: D$ k2.6 Cost of Electric Energy Production / 53+ h6 x3 b5 n4 n; Y6 d. }/ \
2.7 Evolving Markets / 54" F( W/ A' ?1 w
2.7.1 Energy Flow Diagram / 57; B: n: X1 h$ q( @& t/ z! t+ G, A- a
2.8 Multiple Company Environments / 58
; z. y6 a9 N: y6 |2.8.1 Leontief Model: Input–Output Economics / 58/ W2 c2 v8 w# P% @0 f, ]) o( H
2.8.2 Scarce Fuel Resources / 60& [7 p+ B& f; y
2.9 Uncertainty and Reliability / 619 ?2 ]3 U/ n/ |. h4 o: h- ?& M
PROBLEMS / 61 J% H& F% {6 \5 w
Reference / 62
! |" \* \1 U5 l/ q# t7 f5 A3 Economic Dispatch of Thermal Units and Methods of Solution 63
& | ~% ^$ ^* B1 M3.1 The Economic Dispatch Problem / 63
9 A0 g, c. f5 o, ~& H$ o3.2 Economic Dispatch with Piecewise Linear Cost Functions / 687 y; M; r ?% I7 C
3.3 LP Method / 69, p8 \' k" C. |2 H- ?, h
3.3.1 Piecewise Linear Cost Functions / 693 ~9 {% y% u* O ^% d5 w) P* D
3.3.2 Economic Dispatch with LP / 71+ g* V1 j1 a( `
3.4 The Lambda Iteration Method / 733 y8 e' C8 P. Y/ ~ _2 G2 s+ L
3.5 Economic Dispatch Via Binary Search / 76# |0 i8 j8 w- r2 y5 k1 q
3.6 Economic Dispatch Using Dynamic Programming / 78
# y3 p. N" V+ A+ _2 k* h3.7 Composite Generation Production Cost Function / 81
. L- U9 A, {9 N6 n6 T! s8 y, U3.8 Base Point and Participation Factors / 85
; R: H& n% q# b; v3.9 Thermal System Dispatching with Network Losses1 x5 q3 a& p3 C' H8 j* [( \- E
Considered / 88" k; D" ^& Y) q8 l7 J# t$ O
contents ix
, C; _$ s6 U' @, ^# f2 k7 f3.10 The Concept of Locational Marginal Price (LMP) / 92" _0 _) e+ H3 N$ c
3.11 Auction Mechanisms / 95
5 Q% w% I. M& e6 L5 Q+ g3.11.1 PJM Incremental Price Auction as a: T) w ^2 E5 ? y4 J: J; J
Graphical Solution / 95, ?1 ? M" J! F# U8 Z$ A
3.11.2 Auction Theory Introduction / 982 _4 f9 T5 X2 F- i& B/ |
3.11.3 Auction Mechanisms / 100# w) v9 I8 I- Y
3.11.4 English (First-Price Open-Cry = Ascending) / 101' Y; c& p6 F1 G7 o6 L" X
3.11.5 Dutch (Descending) / 103
8 r6 Y% s7 e& i, {) ~3.11.6 First-Price Sealed Bid / 104
2 w0 I9 y1 w! S5 O2 \7 w; F! I$ [1 C3.11.7 Vickrey (Second-Price Sealed Bid) / 105
. n5 _2 w9 r; g# ~) r. P1 T. L+ z3.11.8 All Pay (e.g., Lobbying Activity) / 105' l P( t0 C& a* E
APPENDIX 3A Optimization Within Constraints / 106
% v2 b& l* k3 P( _) e) vAPPENDIX 3B Linear Programming (LP) / 1172 K& I* l$ R, l- v0 `
APPENDIX 3C Non-Linear Programming / 128
' J Z" r s# O% a/ O7 m$ nAPPENDIX 3D Dynamic Programming (DP) / 128
8 A0 E8 Z" S* E7 M7 vAPPENDIX 3E Convex Optimization / 135
4 h- f" t) J$ m Q+ j4 pPROBLEMS / 138
& W! i% r+ ~6 t5 Y( U7 ?$ u g& jReferences / 146
1 s: O$ @% \5 m/ x2 I4 Unit Commitment 147
( K5 v, O" I' p6 R4 n4.1 Introduction / 1475 F+ m" s# e2 B5 s
4.1.1 Economic Dispatch versus Unit Commitment / 147( [! F2 W1 }5 ^& I5 W) U
4.1.2 Constraints in Unit Commitment / 152- |. G9 `8 p2 `% i* M8 H/ w7 W
4.1.3 Spinning Reserve / 152' O0 [% d0 [6 S
4.1.4 Thermal Unit Constraints / 1539 c t' P! I' `2 O" Q" h
4.1.5 Other Constraints / 155! }: ~7 ?2 R6 i3 {- V
4.2 Unit Commitment Solution Methods / 155
( M S9 Q( ]( e4.2.1 Priority-List Methods / 1566 r4 R0 A! T, V9 M3 F2 E s# G
4.2.2 Lagrange Relaxation Solution / 1577 Q' H6 A2 |& S, a8 ~6 O; R
4.2.3 Mixed Integer Linear Programming / 166
* d7 m, e8 U- z) J9 A& @9 b9 B) d* H4.3 Security-Constrained Unit Commitment (SCUC) / 167
~: l( p6 _5 m4.4 Daily Auctions Using a Unit Commitment / 1676 B* m& T- n# o: c
APPENDIX 4A Dual Optimization on a Nonconvex$ z6 g# Z& N" w, n8 |9 V/ }
Problem / 167
# i2 K8 M) _% f: xAPPENDIX 4B Dynamic-Programming Solution to' | Q4 m& E; y: B& f
Unit Commitment / 173: G- C: I. n2 N: _" e9 }
4B.1 Introduction / 1735 T [2 W2 p: H/ C7 C
4B.2 Forward DP Approach / 174* ~2 }3 T. a4 Z5 K; }* [! O( Z
PROBLEMS / 182; F/ S5 d8 E) p' u1 B$ M0 C3 N
x contents, P3 {9 Z# m3 C; y, d, f
5 Generation with Limited Energy Supply 187) k( I) ], g) G' O
5.1 Introduction / 187
5 y/ k4 q; }4 a* |% x- R1 i5.2 Fuel Scheduling / 188& i4 B4 f) w, X
5.3 Take-or-Pay Fuel Supply Contract / 188
2 h/ y, q3 ^2 G8 ~/ _1 w5.4 Complex Take-or-Pay Fuel Supply Models / 1942 x9 u, Q3 d. j3 k( F6 x8 G1 p
5.4.1 Hard Limits and Slack Variables / 194
( g2 l- \7 o: Z+ N! ~2 ]5.5 Fuel Scheduling by Linear Programming / 195
5 ?& m% h5 } U8 _) z- d' c# t% k: N5.6 Introduction to Hydrothermal Coordination / 202
: @$ C ]; q% W" T4 {6 G4 C5 l5.6.1 Long-Range Hydro-Scheduling / 203
. @ G) ?4 L) r/ e* ~ }5.6.2 Short-Range Hydro-Scheduling / 204# W0 {# Z1 t, e' @% Z: t/ v1 X6 H
5.7 Hydroelectric Plant Models / 2048 Q1 x6 {! M. h! R" N3 }$ |8 K
5.8 Scheduling Problems / 207
3 B5 b4 Z) s8 B0 V# i1 w0 G5.8.1 Types of Scheduling Problems / 207, P% i; i* F" Z
5.8.2 Scheduling Energy / 2072 _0 ~* k+ w( G1 y) @9 g
5.9 The Hydrothermal Scheduling Problem / 211
2 P2 z( \9 q6 X7 S: X5.9.1 Hydro-Scheduling with Storage Limitations / 2117 m6 I* j( v& I; d5 x
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
0 W- |% S( Y6 q P' A+ W/ z1 c5.9.3 Pumped-Storage Hydroplants / 218- l& |* w4 R; v1 R9 J; G( J
5.10 Hydro-Scheduling using Linear Programming / 222
0 r4 A; r2 w) G& S: s/ @ JAPPENDIX 5A Dynamic-Programming Solution to hydrothermal7 F' a5 n8 B! v
Scheduling / 225 y0 e/ o* ^& h! e2 e
5.A.1 Dynamic Programming Example / 227
4 z+ {7 z. i8 S7 {. l" }5.A.1.1 Procedure / 228
" ^' P7 b6 |1 B5.A.1.2 Extension to Other Cases / 231) Z- a, Y+ v0 D6 L1 A9 p
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant1 U+ R. Y" f) q' ]! W
Problem / 2323 L A& ~, n) f& c7 K
PROBLEMS / 234
/ u7 t* C" @( v# Q& e6 Transmission System Effects 243
8 F! f7 [8 ]& B& J' O$ G( q6.1 Introduction / 243
5 b( k+ Q% k1 e/ `0 O8 B% e6.2 Conversion of Equipment Data to Bus and Branch Data / 247! W; `* B' i6 v% j: z6 f3 m5 G
6.3 Substation Bus Processing / 2485 @- K5 _9 `3 D) l. e- k. {7 B
6.4 Equipment Modeling / 248
8 p2 h$ s& c# L& L0 {9 A1 \7 X6.5 Dispatcher Power Flow for Operational Planning / 251
3 Y& Y( ~. D! N# p' H2 P6.6 Conservation of Energy (Tellegen’s Theorem) / 252
* E- v0 E$ i; {9 J6.7 Existing Power Flow Techniques / 253( {4 i4 C1 p7 C0 R& O) h5 ?4 j
6.8 The Newton–Raphson Method Using the Augmented
1 F% c! R% C" ]1 A/ |) MJacobian Matrix / 254
# `: ?- O( @# s7 J7 l6.8.1 Power Flow Statement / 254
: i& y0 J" ~, A; q8 A+ ^2 F% Y' H6.9 Mathematical Overview / 257
; W6 G2 {1 B- _# v5 s- j9 T2 e6 pcontents xi
k3 S7 n! F# M' ?6.10 AC System Control Modeling / 259
' H) H9 |; J' L% k1 Z/ [6.11 Local Voltage Control / 259
1 K7 S) u$ E& y9 F8 z5 N6.12 Modeling of Transmission Lines and Transformers / 259
; N6 l* a1 L! G! ]0 Z+ K6 K6.12.1 Transmission Line Flow Equations / 259
9 P' [' f" _6 ^ [7 t6.12.2 Transformer Flow Equations / 260
* A% q8 A) p# m1 p# t/ S6.13 HVDC links / 261
- C8 L+ B, u, \. Z. |2 y6.13.1 Modeling of HVDC Converters w9 E/ B. ~1 z
and FACT Devices / 264% y. z3 n7 e) H. J- d y
6.13.2 Definition of Angular Relationships in: Z4 e( p. L) y- s* u
HVDC Converters / 2647 H% _2 T6 ]7 ~% W4 f7 ]/ M
6.13.3 Power Equations for a Six-Pole HVDC/ p: o# `8 _+ h/ f
Converter / 2643 j3 ]6 [% P! o/ c7 i# |2 \0 x
6.14 Brief Review of Jacobian Matrix Processing / 267
- C! j. o# W" s! E6.15 Example 6A: AC Power Flow Case / 269
% {- H. |; K! N& ^# w. v2 A6.16 The Decoupled Power Flow / 271
! ~2 Z/ c9 ^* K3 t0 y6.17 The Gauss–Seidel Method / 275
- M0 }4 Y* f7 f7 q% b0 z8 _) n6.18 The “DC” or Linear Power Flow / 277
% D$ P5 I6 e M. Q% B3 K6.18.1 DC Power Flow Calculation / 277
9 y) A j% l7 h+ t5 T8 \6.18.2 Example 6B: DC Power Flow Example on the
4 ?/ t5 K) }; E$ N2 PSix-Bus Sample System / 278, r i7 O( O' Q7 [- `& t
6.19 Unified Eliminated Variable Hvdc Method / 278
1 \; Z/ _; a3 `5 T/ B/ b3 Q) S5 I6.19.1 Changes to Jacobian Matrix Reduced / 279
4 L3 ^ u4 m) n9 [6.19.2 Control Modes / 280
9 r% O' \$ D. r1 H4 v, Y% b7 A6.19.3 Analytical Elimination / 2802 u [' ]! t7 }5 R
6.19.4 Control Mode Switching / 283
8 \: @; O( I' n, @8 \$ d6.19.5 Bipolar and 12-Pulse Converters / 283
# K/ |& \) A6 f3 @1 F) i* ]6.20 Transmission Losses / 284
: U: A. ~; P! ]6.20.1 A Two-Generator System Example / 284
" \4 C2 f3 k% X# C6.20.2 Coordination Equations, Incremental Losses,& v5 N. d+ K9 r( b: q2 Y
and Penalty Factors / 286
/ c% M) R* m. i0 q& H( }6 m# ?3 j6.21 Discussion of Reference Bus Penalty Factors / 288
2 ]* u1 r$ E. B- t6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
9 O! `3 d B: g, O# N/ K4 S. PPROBLEMS / 2915 ]- I2 @2 i0 N: X' B
7 Power System Security 296" J' O# l2 T7 W8 a6 W- v& l
7.1 Introduction / 296
5 g8 r0 h7 P! |) y" s% t [9 }7.2 Factors Affecting Power System Security / 301
7 }7 u& _0 J4 x: u1 v- B( Q: P7.3 Contingency Analysis: Detection of Network Problems / 301
7 l, y' G- ^+ \; k+ ]. O7.3.1 Generation Outages / 3010 @; a9 v! k1 E
7.3.2 Transmission Outages / 302
' ^$ j+ m: E+ j3 v# c! u" w" ixii contents
% a6 \6 R! c! ^* A3 g t7.4 An Overview of Security Analysis / 306
$ T6 f0 p Q* ]9 K7.4.1 Linear Sensitivity Factors / 3070 z' N( L/ p9 |! V
7.5 Monitoring Power Transactions Using “Flowgates” / 313
2 n; g4 O3 O3 A2 r8 D: \7.6 Voltage Collapse / 315
; d) S3 P) q4 G! p$ w$ R7.6.1 AC Power Flow Methods / 3174 ]( O; y( N! w
7.6.2 Contingency Selection / 3200 M5 ?0 P5 @$ f- {
7.6.3 Concentric Relaxation / 323
$ U' n ~7 ?/ `7.6.4 Bounding / 325
0 V4 X7 D+ [" l. Q7.6.5 Adaptive Localization / 325
5 [& j2 n, Q4 R# b; y" ?- E2 gAPPENDIX 7A AC Power Flow Sample Cases / 3277 f0 b' L. ?7 \
APPENDIX 7B Calculation of Network Sensitivity Factors / 336
0 }# C& b+ f- b' o7B.1 Calculation of PTDF Factors / 336/ n6 {; S3 C5 a. J2 A$ L
7B.2 Calculation of LODF Factors / 339: v2 X8 @# o. r- b3 F; p
7B.2.1 Special Cases / 341" |! ^: i! W; C% R2 l* b1 @
7B.3 Compensated PTDF Factors / 343
" W* K; w7 w' m2 p# i0 dProblems / 343
+ S( X& j" a' ?! ]References / 349# f3 o& u: m2 d; t5 b! w2 T$ A
8 Optimal Power Flow 350' R1 ?! T- [! P. ?# r& t9 _, f
8.1 Introduction / 350
( u) i$ w- K0 ^+ K' W+ s& ~1 ?8.2 The Economic Dispatch Formulation / 351
& W' I) t$ K& p6 |% O8.3 The Optimal Power Flow Calculation Combining
! _+ u$ h" u! `/ n% b# F G' C8 v+ YEconomic Dispatch and the Power Flow / 352$ V* N6 f8 `& p" N3 Z
8.4 Optimal Power Flow Using the DC Power Flow / 354
/ q* A, q: b" ?* V1 n6 K( u6 L8.5 Example 8A: Solution of the DC Power Flow OPF / 356' o( C2 D6 t8 ?; E% n1 a9 M% X
8.6 Example 8B: DCOPF with Transmission Line9 s3 l: T6 F. E% I. @! J
Limit Imposed / 3610 m% c" S O: p V) P& c" p
8.7 Formal Solution of the DCOPF / 365
5 U0 k' [; C% E8.8 Adding Line Flow Constraints to the Linear
, E* x) B/ j% v6 x% y3 S$ b6 l% v+ n$ UProgramming Solution / 365
, P" ?9 Y0 e8 q8.8.1 Solving the DCOPF Using Quadratic Programming / 367
% o1 n$ m8 [1 ?! d& X- B' C8.9 Solution of the ACOPF / 368
& y' a* B# I5 |+ f- `8.10 Algorithms for Solution of the ACOPF / 3693 V% L; {, k# V X+ w
8.11 Relationship Between LMP, Incremental Losses,
# ?) y+ s% s; s: dand Line Flow Constraints / 376
5 r, y7 {1 V2 z8 h4 B) P5 h8.11.1 Locational Marginal Price at a Bus with No Lines
8 h5 m, B+ j/ Y4 ^0 qBeing Held at Limit / 377
2 J' L4 S5 T" K4 {5 ~( a8.11.2 Locational Marginal Price with a Line Held at its Limit / 378' }/ C! p* B6 f4 {. ~
contents xiii* V: V: p$ K$ E4 x0 O4 n
8.12 Security-Constrained OPF / 382! q( k+ M% R5 y0 Y3 ~' l: D
8.12.1 Security Constrained OPF Using the DC Power Flow
2 Z, L, b, n3 f3 B$ mand Quadratic Programming / 384
& O7 v! {8 ~5 z* C8.12.2 DC Power Flow / 3852 ~ u% d1 _3 H7 k
8.12.3 Line Flow Limits / 385: Z0 W6 N# b5 i/ H! |
8.12.4 Contingency Limits / 386
' M5 m. ^( C2 z9 @APPENDIX 8A Interior Point Method / 3918 d3 R* I: ~! o+ i7 R% y) x
APPENDIX 8B Data for the 12-Bus System / 393
3 G5 {6 C: O7 ^" F+ k2 aAPPENDIX 8C Line Flow Sensitivity Factors / 395$ G+ f0 v/ q8 u' A7 L7 F% `7 a
APPENDIX 8D Linear Sensitivity Analysis of the
$ W+ o3 F+ Z$ q3 {AC Power Flow / 397
1 m7 x8 F! O8 v$ N W; t( Z! T/ Q; J cPROBLEMS / 399 F3 ~. \3 i% F6 C# U3 y, ^' K
9 Introduction to State Estimation in Power Systems 4038 F+ n$ G" L, [$ w
9.1 Introduction / 403
% z- U2 C2 Z8 f. [7 E+ V9.2 Power System State Estimation / 404* f9 N/ E8 K; l8 Z
9.3 Maximum Likelihood Weighted Least-Squares) E: b- ^) L7 {
Estimation / 408
7 i: L4 w$ n0 f9.3.1 Introduction / 408% C* R* p% V6 \" k |
9.3.2 Maximum Likelihood Concepts / 410/ @6 Y8 W7 T( s! h" ?5 X$ E
9.3.3 Matrix Formulation / 414
- V3 }: i. h; ]0 \9 r9.3.4 An Example of Weighted Least-Squares- H; d, C+ P& L+ c0 P' |2 a
State Estimation / 4173 S n( ^2 }5 X
9.4 State Estimation of an Ac Network / 4213 Q$ u; K I3 M& P/ Y. E
9.4.1 Development of Method / 4218 G/ B) w" V2 p9 }! P* X; i+ K
9.4.2 Typical Results of State Estimation on an
( K1 m& H- L8 a9 k7 I+ U. K0 S" S& uAC Network / 424
2 l& [9 @) @( y$ g, f" H9 l9.5 State Estimation by Orthogonal Decomposition / 428
7 ]- h/ G3 M* {! z" a: O" \0 e9.5.1 The Orthogonal Decomposition Algorithm / 431& R& D2 _- n- M7 x. p! `
9.6 An Introduction to Advanced Topics in State Estimation / 435
9 C$ W8 P5 d; T. b; Y9.6.1 Sources of Error in State Estimation / 435: ~" }0 B. D1 p5 q/ S& e6 u4 M x5 h
9.6.2 Detection and Identification of Bad Measurements / 436
: @, W, A* O2 J+ o+ p9.6.3 Estimation of Quantities Not Being Measured / 443
* m! {; x9 H2 n) f9.6.4 Network Observability and Pseudo-measurements / 444
, ^: w6 t8 D7 Q( E/ j9.7 The Use of Phasor Measurement Units (PMUS) / 4474 Q& Q0 q3 e$ d l$ v
9.8 Application of Power Systems State Estimation / 451
+ V+ f7 y4 B3 }9.9 Importance of Data Verification and Validation / 454
/ W! k! R# m8 K" I9.10 Power System Control Centers / 454
7 ~" [& \) u& ^5 ^xiv contents9 D' M5 R( I7 O" @
APPENDIX 9A Derivation of Least-Squares Equations / 456) I* ]% I; A$ U: W0 |" L
9A.1 The Overdetermined Case (Nm > Ns) / 457
9 D; {+ U6 B0 `! ~& Q/ M9A.2 The Fully Determined Case (Nm = Ns) / 4621 C. i4 z1 N2 X! s
9A.3 The Underdetermined Case (Nm < Ns) / 462& c% X: V7 W/ r9 A3 i6 p; C
PROBLEMS / 464
T$ i. N2 N2 e1 B' C, H0 v10 Control of Generation 468
( K9 S% c r: P2 T5 J; P7 D$ h; d10.1 Introduction / 468
/ v/ E2 {, d6 `$ A10.2 Generator Model / 470
' X L9 y! \' p10.3 Load Model / 473( Y, f6 s2 n( j9 k5 d1 y" H
10.4 Prime-Mover Model / 4758 U8 ^( ^, L. F0 c& C. q, J
10.5 Governor Model / 476
0 @1 O4 d# r$ h0 H- k$ `0 j10.6 Tie-Line Model / 481# O7 ?! S: | L8 ]% d1 s
10.7 Generation Control / 485
, m( g2 M/ [# l a10.7.1 Supplementary Control Action / 485
+ m A% C# f2 Q: E! Y' n10.7.2 Tie-Line Control / 4860 P6 h( O' Y7 q3 C9 n" J
10.7.3 Generation Allocation / 489
. { V$ _+ J; x* Q# Z10.7.4 Automatic Generation Control (AGC)
; ?$ ?3 `4 N3 v3 r' L* ?1 E# tImplementation / 491
! a* e* t8 _7 V6 @10.7.5 AGC Features / 4957 B! }% E' W7 {0 M4 V4 N! c5 ^
10.7.6 NERC Generation Control Criteria / 4967 V* F( b, U8 `. g7 j. P
PROBLEMS / 497
. i4 W" { o% k9 b- U1 p& o7 S |3 xReferences / 5008 q" X4 b8 O" p' I7 h: ^
11 Interchange, Pooling, Brokers, and Auctions 5019 K$ N c: R5 N* ?
11.1 Introduction / 501- R v' ?+ p+ h
11.2 Interchange Contracts / 504
2 z: I& K, `8 v: w5 C) y11.2.1 Energy / 504
: ]1 t" j( ~ Y% q4 w' L11.2.2 Dynamic Energy / 506
2 D$ c* n4 V0 A1 A) C1 H11.2.3 Contingent / 506
3 A- Q3 W4 @. A; G5 O k11.2.4 Market Based / 507- m/ d& D& b! I
11.2.5 Transmission Use / 508/ v0 c, c9 r' D, V' W" K1 c
11.2.6 Reliability / 5174 W; N4 R7 \6 H' y
11.3 Energy Interchange between Utilities / 517
, q5 R5 f3 Q7 _0 D3 h11.4 Interutility Economy Energy Evaluation / 521
' Q7 p) Q- b- i" M Q: ?& ~11.5 Interchange Evaluation with Unit Commitment / 522
$ I% O( ]! \+ B' n8 L& ^ P6 }11.6 Multiple Utility Interchange Transactions—Wheeling / 5237 `( X( ^* P$ L% K
11.7 Power Pools / 526
6 Q3 B8 q* U# e$ ]! Gcontents xv0 b) h) c% |* H, G5 @
11.8 The Energy-Broker System / 529
& x+ F. A- i2 @5 w11.9 Transmission Capability General Issues / 533) {0 R3 M* P5 k( e4 {
11.10 Available Transfer Capability and Flowgates / 5354 X7 B$ Z+ l$ d F3 Z9 O0 n$ H
11.10.1 Definitions / 536
* _; N) G( n2 C. S+ O; f" M' u11.10.2 Process / 539
2 D+ A1 b/ m1 y, m( P11.10.3 Calculation ATC Methodology / 540, e# G1 M7 L) u6 b7 e) F
11.11 Security Constrained Unit Commitment (SCUC) / 5501 ~4 F" o- x; w( n8 k' m2 }
11.11.1 Loads and Generation in a Spot Market Auction / 550( M5 I2 l% Y8 E0 V* E8 r
11.11.2 Shape of the Two Functions / 552, R. p0 Q# r# f# P
11.11.3 Meaning of the Lagrange Multipliers / 553/ M9 E7 d+ K2 r( n
11.11.4 The Day-Ahead Market Dispatch / 5543 ?, O6 i7 w! p' l' h" R
11.12 Auction Emulation using Network LP / 555) v( g: W2 L$ R7 _. E, p2 e% S
11.13 Sealed Bid Discrete Auctions / 555 ?0 o9 n5 S& Z* w" s* H7 ]
PROBLEMS / 5606 N. L I% a5 j9 @
12 Short-Term Demand Forecasting 566* |6 l5 ]2 x& s7 u4 S; q
12.1 Perspective / 566) m4 f% X C% k9 b9 X+ m
12.2 Analytic Methods / 569
2 c# i' ^3 @1 U4 c2 y5 q! v12.3 Demand Models / 571
+ a, B- x7 [( F1 ~12.4 Commodity Price Forecasting / 572
3 h4 n1 w" G' D5 |" W9 K$ p12.5 Forecasting Errors / 573
Z! n Z" g- f! A5 N6 |12.6 System Identification / 5739 e( X9 n& O8 @ `1 z% n
12.7 Econometric Models / 574
) |4 ~1 T) v5 R3 j: q5 ]- n12.7.1 Linear Environmental Model / 574
' W: N7 f- k# g5 {, J/ Q12.7.2 Weather-Sensitive Models / 576
" l$ _" z7 i F% o. I/ |( k5 n' f12.8 Time Series / 578+ E& C, d( ^) p( _1 E: X! N. |6 v% D
12.8.1 Time Series Models Seasonal Component / 578! g& f7 z" P; w/ z8 t5 l
12.8.2 Auto-Regressive (AR) / 5806 m& C7 V$ R N
12.8.3 Moving Average (MA) / 581( y9 J6 Q1 J: x6 h# H) S
12.8.4 Auto-Regressive Moving Average (ARMA):
0 m ^1 T1 Z: R7 o, eBox-Jenkins / 582
8 n8 o G- e. A$ A12.8.5 Auto-Regressive Integrated Moving-Average
+ O+ j) T) J* ~; G+ W2 [2 |7 _(ARIMA): Box-Jenkins / 584+ \" y1 j a, a- C1 d, }) R
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585
6 @. W5 H1 N( ~8 T. Y9 m12.9 Time Series Model Development / 585
- G( d0 ^) n. B( a6 R+ V4 ^12.9.1 Base Demand Models / 586
( K; @! J! c Z: k! Y! O. ~12.9.2 Trend Models / 586' a* L! `( X2 {! y$ `) B
12.9.3 Linear Regression Method / 586
6 k# T1 {' T0 exvi contents
" h- Q$ {5 y9 @$ G2 v12.9.4 Seasonal Models / 588
; m j% j' H+ k% U- X0 ^" A" X12.9.5 Stationarity / 588
* g* h3 e y0 N% h12.9.6 WLS Estimation Process / 590
! @$ _0 H+ s; Z# z12.9.7 Order and Variance Estimation / 591
- O/ h! o& y$ O12.9.8 Yule-Walker Equations / 592& A! u8 G4 n( { q
12.9.9 Durbin-Levinson Algorithm / 595
# d% o% ?1 I, V; F6 y12.9.10 Innovations Estimation for MA and ARMA
" h& |7 \% n: h$ z5 ~( a1 C9 _Processes / 598' X* U( Z# N6 \) A' |+ d: ]
12.9.11 ARIMA Overall Process / 600: X3 q) E- L0 W9 B
12.10 Artificial Neural Networks / 603
: U8 i& @- c) k$ H- Y& @0 T12.10.1 Introduction to Artificial Neural Networks / 604
; Q) Z8 w0 G* ~7 z9 T% _, F' l X3 {; e v12.10.2 Artificial Neurons / 605
8 ^8 H) u e8 b" H2 i4 t; Y0 T12.10.3 Neural network applications / 606
$ K( P2 a% [% `# e. \- Q- {12.10.4 Hopfield Neural Networks / 606
/ o) D7 a2 r3 _2 }. B% w12.10.5 Feed-Forward Networks / 6079 i9 I6 {2 f( q% O
12.10.6 Back-Propagation Algorithm / 6104 a; t& |% U6 i; J! {
12.10.7 Interior Point Linear Programming Algorithms / 613* |8 [2 _$ [% Y. }
12.11 Model Integration / 614
9 l+ @4 q0 ]0 O- J3 J+ l% V12.12 Demand Prediction / 614
$ ?- O% p7 g9 y _3 B8 {12.12.1 Hourly System Demand Forecasts / 6151 \+ T) w+ i/ `) n9 |
12.12.2 One-Step Ahead Forecasts / 615
% V" Z, d5 H5 ]6 x12.12.3 Hourly Bus Demand Forecasts / 616$ Y* q, N% V: B; {7 i' C1 G: ~
12.13 Conclusion / 616
8 ?9 m& J9 Q: O2 G; ePROBLEMS / 617 |
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