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第三版目录。7 f: U$ ]! Z. U- M
1 Introduction 1
( i: l( [7 n- `: j6 e1.1 Purpose of the Course / 1
: d, }, k5 q9 |8 |& E1.2 Course Scope / 2
, h1 W2 {6 o7 Z1 d1.3 Economic Importance / 2& G, B' g* W9 s3 ?) z( ~
1.4 Deregulation: Vertical to Horizontal / 3
/ g) ]: m# p6 Z* k1.5 Problems: New and Old / 3
( M, q9 `; O- V; C. {1.6 Characteristics of Steam Units / 6
- p! ]) [8 L2 {" a% F2 z9 y1.6.1 Variations in Steam Unit Characteristics / 10
! ]" I9 j: ]& A( m7 G$ W! u1.6.2 Combined Cycle Units / 134 q& c; _" J4 a# _
1.6.3 Cogeneration Plants / 14 ?. l7 J' y2 H! V; n0 ?
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
& u' L8 L6 O) x, r# \. `6 R' A3 u* _1.6.5 Hydroelectric Units / 184 i' p0 s7 e7 x$ G& o/ d9 p
1.6.6 Energy Storage / 21( ^& c3 }, _5 x! N
1.7 Renewable Energy / 22- R# `8 b2 m# }. Z6 P. d! q/ O
1.7.1 Wind Power / 23; w4 y* A' F9 Z7 Q, ]- N% {
1.7.2 Cut-In Speed / 23
: @# ^ O1 h' ]3 ^; ^9 z1.7.3 Rated Output Power and Rated Output Wind Speed / 243 A; @: u7 m, p" U4 C( R( D) f
1.7.4 Cut-Out Speed / 24/ C2 z8 W+ Y$ T# o9 D1 m
1.7.5 Wind Turbine Efficiency or Power Coefficient / 241 V* e7 {. ^9 h ^8 A
1.7.6 Solar Power / 25
; r& u7 f: W. \3 }1 ^APPENDIX 1A Typical Generation Data / 26% y) p$ }6 ?2 o. e6 N) e
APPENDIX 1B Fossil Fuel Prices / 28, C% E+ T& Q3 e& W) {. I {
APPENDIX 1C Unit Statistics / 29
6 l) N# u1 H: m3 ]$ c$ C, aCONTENTS
7 l' ^5 ^0 @# p& c1 v h% ^; mviii contents" ?! L, G% F( W! B
References for Generation Systems / 31" t6 T, m0 a# d5 p8 J2 l
Further Reading / 31
, }* J( q9 M( y! W' Z: ~2 Industrial Organization, Managerial Economics, and Finance 35. s9 A* G/ q8 b* F
2.1 Introduction / 35% P5 V9 M% D% w. Q
2.2 Business Environments / 36
7 u* [8 n/ t4 i+ \* c& h2.2.1 Regulated Environment / 37
: l! P2 J- Y* m# m2.2.2 Competitive Market Environment / 38
6 r. Q4 k5 W ?9 y2.3 Theory of the Firm / 40) i4 N' t: F% `# E* b
2.4 Competitive Market Solutions / 426 V# o4 e0 L$ i) d! h. h
2.5 Supplier Solutions / 45/ l' |2 q C* P
2.5.1 Supplier Costs / 46# h5 [3 S7 y4 @
2.5.2 Individual Supplier Curves / 467 P j* x8 ]1 @/ e7 {$ E7 ]
2.5.3 Competitive Environments / 47
5 v( V2 c$ J+ @! I0 r2.5.4 Imperfect Competition / 51! v- h \" J p4 ~* {
2.5.5 Other Factors / 525 b/ p1 Z; b: L, M: ^9 K( V F
2.6 Cost of Electric Energy Production / 53' H2 q A ~" J2 c8 M
2.7 Evolving Markets / 546 {; x" w" z( W- V9 i
2.7.1 Energy Flow Diagram / 57
# ^, s [' l- [& M$ D: X9 N2.8 Multiple Company Environments / 58
. q- [; @9 ]( q) K+ ?2.8.1 Leontief Model: Input–Output Economics / 58/ b; k% w. N& c; c1 \
2.8.2 Scarce Fuel Resources / 60
& G* ]* H; e" _$ n, N4 I0 Q2.9 Uncertainty and Reliability / 61
! n6 g2 o* A1 Q. p3 OPROBLEMS / 61
5 M$ _6 d( @" iReference / 626 U D( b. @* t1 e# Q. {( q' ~
3 Economic Dispatch of Thermal Units and Methods of Solution 63
' w N0 p; f0 T, e3.1 The Economic Dispatch Problem / 63
) T* I9 [# \0 l3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68/ Q* m, q. Q$ U$ ]6 K8 M1 ]$ z$ y, E7 `
3.3 LP Method / 69! O% t+ r5 Q4 O/ i, Y: f* K% E
3.3.1 Piecewise Linear Cost Functions / 69% o, N3 `& j! n6 e: P0 [) D! L) f
3.3.2 Economic Dispatch with LP / 71$ x E3 Q, n7 p" n+ n7 x
3.4 The Lambda Iteration Method / 73
2 x/ n; X9 g# O0 b0 f9 F3.5 Economic Dispatch Via Binary Search / 76
_6 i4 c# g, v o% L/ n3.6 Economic Dispatch Using Dynamic Programming / 783 E8 a% j2 K9 G" R
3.7 Composite Generation Production Cost Function / 81
" ^: ^7 d$ d. P5 _3.8 Base Point and Participation Factors / 854 T3 g" _) U4 t& W# F/ m
3.9 Thermal System Dispatching with Network Losses, T/ y+ `, s: c+ _3 Z# u: Y
Considered / 889 b& `" ^1 t o5 p, U$ W/ j9 y
contents ix
0 M4 r8 Q; L; N" n* W9 Z0 c7 O3.10 The Concept of Locational Marginal Price (LMP) / 92
6 y) J5 D/ S. K x0 i& r7 s( i3.11 Auction Mechanisms / 95& s: Y4 o; ^3 v: G" v
3.11.1 PJM Incremental Price Auction as a
f' Z% c! [8 JGraphical Solution / 95
1 H- `/ ?1 d& t: k8 n$ @& ^7 y" @3.11.2 Auction Theory Introduction / 98
6 R& R5 h( W9 H, P% v% }3.11.3 Auction Mechanisms / 100& \9 A1 |9 J- j+ z. A0 W* Y
3.11.4 English (First-Price Open-Cry = Ascending) / 101, X2 r8 g& X2 O: F+ j. c
3.11.5 Dutch (Descending) / 103
' N; \# @2 s$ c( _9 f3.11.6 First-Price Sealed Bid / 104
8 Y1 V! ?2 \& L( x) O3.11.7 Vickrey (Second-Price Sealed Bid) / 105. @ K& g+ C1 v6 K. }7 w1 a& b1 N S2 l
3.11.8 All Pay (e.g., Lobbying Activity) / 105$ d- Q. x& x5 b' n3 L: w
APPENDIX 3A Optimization Within Constraints / 1060 C; t( x/ q+ d% J0 s# S
APPENDIX 3B Linear Programming (LP) / 117) S0 ~3 b+ U& {" X0 f
APPENDIX 3C Non-Linear Programming / 1286 R4 V2 ]% J, Q, w0 C
APPENDIX 3D Dynamic Programming (DP) / 128
2 G, L5 H% G% w1 Y" @8 G* DAPPENDIX 3E Convex Optimization / 1358 |( Z- l0 |/ n" R5 ?
PROBLEMS / 138' ~, d1 ?! S& \- q% Y* ]
References / 146
+ z( G- s a0 K0 f5 ~" K7 X4 Unit Commitment 147
" D0 H4 j7 M9 X4 K+ K+ u4.1 Introduction / 147
- _7 E5 f( d% v: U: q: V0 E4.1.1 Economic Dispatch versus Unit Commitment / 147
7 j+ X2 y, M* Z0 e. |3 s4 `4.1.2 Constraints in Unit Commitment / 152
0 Z- o/ q: X0 G( r7 |6 ]& u2 p" j3 J! a4.1.3 Spinning Reserve / 152+ E* P# o' Q) q- T* M: B/ K
4.1.4 Thermal Unit Constraints / 153' |2 g$ P2 {. H2 i7 s' C' A
4.1.5 Other Constraints / 155+ ~3 q% W2 N2 W" X9 H
4.2 Unit Commitment Solution Methods / 155! C' q3 T' R9 O$ n' }) V2 H
4.2.1 Priority-List Methods / 156
, g- W# d& X [0 E) S( S1 C4.2.2 Lagrange Relaxation Solution / 157
% T, |0 l( w+ W4.2.3 Mixed Integer Linear Programming / 166& j- I( t. R3 s) u
4.3 Security-Constrained Unit Commitment (SCUC) / 167
$ a6 w1 w3 V. Y8 e' k& m3 e+ W4.4 Daily Auctions Using a Unit Commitment / 1671 e; i0 C* R' J
APPENDIX 4A Dual Optimization on a Nonconvex
& M+ o3 ~; K. `% O$ HProblem / 167
" o0 `! c" Z1 o- t" j' B' fAPPENDIX 4B Dynamic-Programming Solution to% Y# j3 X7 Y. M0 }# {2 _9 \
Unit Commitment / 173
% |+ e) v/ q q+ M. Q4B.1 Introduction / 173
5 W p; u1 S' b# W/ {4B.2 Forward DP Approach / 1740 T& ]: I- j8 l: q! s* N
PROBLEMS / 182
7 W+ c* ?! x7 |) c8 Rx contents
/ H. M0 c( E& g8 |, |; ~, w5 Generation with Limited Energy Supply 187
% Y6 }5 @0 \1 Q4 z7 Y$ N6 m5.1 Introduction / 187* Z' v5 ]& W! J+ `' |& `
5.2 Fuel Scheduling / 188
0 `! ]/ Y- Y3 Q% D+ ]' S5.3 Take-or-Pay Fuel Supply Contract / 188) ]- M R# j- M4 P. @7 F7 l# _; O
5.4 Complex Take-or-Pay Fuel Supply Models / 194
% h* ]$ A3 Q$ H; @+ j8 q5.4.1 Hard Limits and Slack Variables / 194
, ?/ N. d4 ~% g; J) c4 T5.5 Fuel Scheduling by Linear Programming / 195
. z m8 H, }3 D' j* \: I# N8 r5.6 Introduction to Hydrothermal Coordination / 202
8 Q$ G7 V9 h% x0 ?+ r5.6.1 Long-Range Hydro-Scheduling / 203
8 C+ x5 N8 b% s5.6.2 Short-Range Hydro-Scheduling / 204
. ~9 A1 l7 q' A1 A L5.7 Hydroelectric Plant Models / 204
$ K- s1 v7 y/ _. r) _5.8 Scheduling Problems / 207% O b7 n; C+ E% I
5.8.1 Types of Scheduling Problems / 207' w4 ^* g% c8 W0 a1 T0 \- O
5.8.2 Scheduling Energy / 207: Z7 u! g! v* A5 D @
5.9 The Hydrothermal Scheduling Problem / 211
: k( I% C) t3 ~! ~+ C0 I5.9.1 Hydro-Scheduling with Storage Limitations / 211
% A% G F2 d) ~) J, Q* w0 M, v7 x5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216/ H: g( L. \$ |- Y {9 a
5.9.3 Pumped-Storage Hydroplants / 218
$ s' S% e3 Z; a( Y5.10 Hydro-Scheduling using Linear Programming / 222
3 d- g3 n1 s' D* s# f- e$ KAPPENDIX 5A Dynamic-Programming Solution to hydrothermal
9 D% q9 e4 P o1 M! T; {Scheduling / 225" P% M; I+ E) S
5.A.1 Dynamic Programming Example / 2275 f% ^! a; e* S- ?
5.A.1.1 Procedure / 2282 Q/ i4 `9 z) X+ s1 h7 A
5.A.1.2 Extension to Other Cases / 231
2 y( u* D% k) z) P% ]5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
1 E1 m6 t7 n& B: u! O$ jProblem / 232
( l" g$ i2 t ]9 ]PROBLEMS / 234
+ L; h% i1 @- I; J# j* i6 Transmission System Effects 243
, U: N6 g0 x& O/ A1 X. ?& r6.1 Introduction / 243
& R! @7 u& f4 T- g# j0 l& q6.2 Conversion of Equipment Data to Bus and Branch Data / 247# u; k! l1 W" s$ ~# U. Z' Z7 V
6.3 Substation Bus Processing / 248
, e+ r6 M0 ]1 \5 u6.4 Equipment Modeling / 248; R' y% k: l) v7 v; x
6.5 Dispatcher Power Flow for Operational Planning / 251
$ g5 x9 A* p: Z6.6 Conservation of Energy (Tellegen’s Theorem) / 2522 [- K, G9 ]. P* M2 l
6.7 Existing Power Flow Techniques / 253# r: w8 T6 @4 } d, g& y4 n+ c
6.8 The Newton–Raphson Method Using the Augmented( L0 R' g" Z9 z+ ]
Jacobian Matrix / 2548 T3 N0 O$ V& k- w; l" {& z
6.8.1 Power Flow Statement / 254
$ \8 n L1 K0 p' e% Q$ _* @6.9 Mathematical Overview / 257
4 h% w: k# L: W! E' Vcontents xi
) @" F' a: C* Z* ^( ~1 G6.10 AC System Control Modeling / 259$ k O. h5 P" R3 M3 i
6.11 Local Voltage Control / 2597 q7 x3 u1 G a
6.12 Modeling of Transmission Lines and Transformers / 259/ }! C* Z N2 n1 [. R
6.12.1 Transmission Line Flow Equations / 2595 p& l4 n D! p) j8 I2 y
6.12.2 Transformer Flow Equations / 2606 a# P7 z; k5 Y( B
6.13 HVDC links / 2615 F4 r+ U" }4 W, O8 S# q n+ E2 j
6.13.1 Modeling of HVDC Converters! c) W# Q& {& T
and FACT Devices / 2641 L) ?- r; r% N' n' n" N* u
6.13.2 Definition of Angular Relationships in
3 A) D9 A, L9 v! \HVDC Converters / 264& S8 C/ g. c' O, _5 W- ~
6.13.3 Power Equations for a Six-Pole HVDC+ I d: Q3 G- W: A: N
Converter / 264
% J! \ h: F' X6.14 Brief Review of Jacobian Matrix Processing / 267
+ e$ g' i$ t4 i6.15 Example 6A: AC Power Flow Case / 269: V k' }4 R2 g. r; ~* _
6.16 The Decoupled Power Flow / 271
F! D/ S0 e9 ^0 c: u X6.17 The Gauss–Seidel Method / 275
2 z/ f* G# g9 B; |" w6.18 The “DC” or Linear Power Flow / 277( n) i: s6 p* x- g5 Z8 h! _( K
6.18.1 DC Power Flow Calculation / 277& o) }+ H* l1 o$ e& r8 k) ?
6.18.2 Example 6B: DC Power Flow Example on the
# L; W5 e' q: t& `; hSix-Bus Sample System / 278$ _! h* W1 ^2 V) G4 p
6.19 Unified Eliminated Variable Hvdc Method / 278, ~* ]5 q2 w8 h+ N
6.19.1 Changes to Jacobian Matrix Reduced / 2792 j: ?$ T; b r) Z$ K0 V8 C
6.19.2 Control Modes / 2801 h4 p( Z0 B' a) v
6.19.3 Analytical Elimination / 280
) n$ `$ R6 H0 M8 l) i" Q6.19.4 Control Mode Switching / 283" P2 Y5 h, A* q; q9 D. [
6.19.5 Bipolar and 12-Pulse Converters / 283 }! J4 Z2 E1 v* S4 K
6.20 Transmission Losses / 284
' t. M4 y. O2 W x9 p G+ I" Y! ~# h8 [6.20.1 A Two-Generator System Example / 284
+ E( {# q2 w7 O( b! W6.20.2 Coordination Equations, Incremental Losses,
0 J6 W$ Q& J! kand Penalty Factors / 286
3 F1 W; q4 c. K& D& t6.21 Discussion of Reference Bus Penalty Factors / 288
- R! B+ p% d6 _ E7 O: b6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
) P x$ o" Y+ J5 A7 {! BPROBLEMS / 291) H6 W; o7 S* H
7 Power System Security 296 L w7 F8 H2 W2 _: F9 }
7.1 Introduction / 296
2 z3 F/ e+ n- }7 I- j7.2 Factors Affecting Power System Security / 301
& |; y/ E- v+ t) B0 [) H7.3 Contingency Analysis: Detection of Network Problems / 301' w Q" V: S4 `: j3 F; R
7.3.1 Generation Outages / 301
7 X9 Q+ R) t7 S& ~, E7.3.2 Transmission Outages / 3028 m: o- c0 K% k t K( s
xii contents8 O; w8 E) s# N
7.4 An Overview of Security Analysis / 306$ e5 T8 A1 }3 p
7.4.1 Linear Sensitivity Factors / 307: _7 G. J( B- V' ` w
7.5 Monitoring Power Transactions Using “Flowgates” / 3139 O3 ]% b1 m! _2 I2 A/ N
7.6 Voltage Collapse / 315
$ ^5 H* A0 y U! B1 c* w/ x+ j8 j7.6.1 AC Power Flow Methods / 3170 x: H0 `$ `- P6 p7 H6 f& ^
7.6.2 Contingency Selection / 320" S6 {( z# A0 L9 P, H! Z# l
7.6.3 Concentric Relaxation / 323
- d# g: \/ ~) J% e7.6.4 Bounding / 3257 q2 s. }: o% F) K0 o# }$ x$ ?
7.6.5 Adaptive Localization / 3254 ~0 g. ~7 T4 \' d' B; w! X: o
APPENDIX 7A AC Power Flow Sample Cases / 327
( j! N2 ^7 m! x) ^2 X$ }& L5 dAPPENDIX 7B Calculation of Network Sensitivity Factors / 336
9 N3 `/ {/ N" |4 K7B.1 Calculation of PTDF Factors / 336
% [9 R! ?$ z" r }9 |# ~, l+ ~7B.2 Calculation of LODF Factors / 339/ u8 [* Z$ S }) G4 t' h5 R
7B.2.1 Special Cases / 341
! u: y" P# v6 M+ i$ I; p7B.3 Compensated PTDF Factors / 3435 U$ m O4 ^9 l! K- \
Problems / 343
* N0 l4 I( e8 _1 U) P) D, aReferences / 3490 A J! W( F3 \& `% b0 N. o
8 Optimal Power Flow 350# [" Y# P" o# b7 A8 ^3 {' i! J
8.1 Introduction / 350$ q7 e U. W \& n
8.2 The Economic Dispatch Formulation / 351+ s4 E% W7 r% m' X' t3 P4 a
8.3 The Optimal Power Flow Calculation Combining
$ v2 a( T8 O% Y; g1 FEconomic Dispatch and the Power Flow / 352 j9 A, t6 S7 X3 b* _
8.4 Optimal Power Flow Using the DC Power Flow / 354
$ x4 C& w. }! f7 Y/ c/ ?8.5 Example 8A: Solution of the DC Power Flow OPF / 3563 O$ ~$ T) W2 b5 n7 M! P. g
8.6 Example 8B: DCOPF with Transmission Line
8 S4 Q0 j1 y/ m* ELimit Imposed / 361) N& U) B: J I# m
8.7 Formal Solution of the DCOPF / 365
( T8 x5 r4 S8 Q( r6 Z6 h6 e' w9 g8.8 Adding Line Flow Constraints to the Linear* H5 p7 J- `. e2 a
Programming Solution / 365
2 { M+ F% o j8.8.1 Solving the DCOPF Using Quadratic Programming / 367
( t$ Q4 i) v) d# X8.9 Solution of the ACOPF / 368
/ L7 W& H" a$ u& V |8.10 Algorithms for Solution of the ACOPF / 369
* r+ ]0 R3 c4 p' X8.11 Relationship Between LMP, Incremental Losses,
" v; X) F) N% P1 E- J9 H. Sand Line Flow Constraints / 3760 ~: p8 g1 g/ Y! k; R
8.11.1 Locational Marginal Price at a Bus with No Lines
& D8 A) {7 r, W; Q1 x# L6 E. jBeing Held at Limit / 3775 F. ?0 G1 R- K ?# X
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378; Q8 z1 ]3 w) ?" b
contents xiii/ ]5 _0 L9 y' P5 K+ s* Y
8.12 Security-Constrained OPF / 382; Y7 m9 ^# K1 Z: h7 Z8 z2 S9 X
8.12.1 Security Constrained OPF Using the DC Power Flow6 K9 ~0 P+ x: @5 u' B( y
and Quadratic Programming / 384
3 o: B2 q$ s6 }( L0 f* I* j8.12.2 DC Power Flow / 3850 d8 S4 f/ k9 i! ?! f3 j. h1 S, Q
8.12.3 Line Flow Limits / 385
" ~5 ~+ L. s; T, a0 o. b8.12.4 Contingency Limits / 3862 y5 s6 s5 r9 C! c1 d% |5 A: w
APPENDIX 8A Interior Point Method / 391* c1 U p$ B1 ?) ~
APPENDIX 8B Data for the 12-Bus System / 393
& l5 p3 i; `8 Q7 B8 S, _/ {6 RAPPENDIX 8C Line Flow Sensitivity Factors / 395* B8 I3 M8 n- t
APPENDIX 8D Linear Sensitivity Analysis of the6 f: e' c7 N. c) ^% e* L0 P
AC Power Flow / 397
- f, r- Y( Q7 T# Y" IPROBLEMS / 3993 `+ Z. A& ^) [9 {/ M# i3 V
9 Introduction to State Estimation in Power Systems 4037 q! y/ c* |) A" o& x) D5 u
9.1 Introduction / 403
, P2 } a$ I5 h2 N# x+ V8 d4 {9.2 Power System State Estimation / 404
5 T* W8 T% V5 C4 `/ E2 b" l9.3 Maximum Likelihood Weighted Least-Squares; t z. l+ {7 l* J
Estimation / 408
8 d9 N: }, M: b9 }: P$ X9 K9.3.1 Introduction / 408$ y1 U1 t0 C$ o. @6 h0 F$ V
9.3.2 Maximum Likelihood Concepts / 410
0 E# `8 ?, Z4 O" i1 ?0 p9.3.3 Matrix Formulation / 414" {/ V5 `$ m& w, A I& y
9.3.4 An Example of Weighted Least-Squares
1 {& }$ g" |' g! b: `% q2 M' VState Estimation / 4178 g0 t( b8 T' n* j
9.4 State Estimation of an Ac Network / 421
! t+ X0 _9 U! y* J7 Z) J9 P9.4.1 Development of Method / 4214 [3 o2 ~+ x6 D3 d$ r
9.4.2 Typical Results of State Estimation on an
0 q: D) @3 X% z7 C8 N* H7 mAC Network / 424
% i- a; b6 r' d4 _* F7 a9.5 State Estimation by Orthogonal Decomposition / 428; U. x9 d% s1 K! \
9.5.1 The Orthogonal Decomposition Algorithm / 431' o ~( w; y! h
9.6 An Introduction to Advanced Topics in State Estimation / 435
! e1 m- k" K" g' H' ]6 N9.6.1 Sources of Error in State Estimation / 435
9 k% P: v9 V/ J5 w* r9.6.2 Detection and Identification of Bad Measurements / 436/ {0 g- m2 h# c" _0 k( x: G+ _' h" I
9.6.3 Estimation of Quantities Not Being Measured / 443
$ b2 @1 F, x2 Q; ~# x8 `9.6.4 Network Observability and Pseudo-measurements / 4449 T. n$ z' T# b( q6 ?
9.7 The Use of Phasor Measurement Units (PMUS) / 447% P0 b' o+ I6 x: u' D2 g
9.8 Application of Power Systems State Estimation / 4516 b1 P a! k2 E6 [1 W! X
9.9 Importance of Data Verification and Validation / 454
5 c/ I) g! r% E# y" l6 Y2 r9.10 Power System Control Centers / 454* D* w( Q/ y8 a
xiv contents4 j1 y, ` L3 P3 g# Y
APPENDIX 9A Derivation of Least-Squares Equations / 456
- W- `! a; T. t1 E9A.1 The Overdetermined Case (Nm > Ns) / 457
0 S# {4 [, Q+ j" h' J1 u+ H9A.2 The Fully Determined Case (Nm = Ns) / 462
9 M1 a& A0 _+ A6 s# g* E9A.3 The Underdetermined Case (Nm < Ns) / 462
0 Y* L. K0 x: J3 J0 }PROBLEMS / 464
- }+ _9 X( H9 N! _10 Control of Generation 468
9 H5 y1 e. N. H8 a10.1 Introduction / 468
( j* J4 A7 ^$ j1 n, u10.2 Generator Model / 470
* g6 x) m; M- t. N* {10.3 Load Model / 473* ^+ B" f: o0 h8 }% y) ]3 {
10.4 Prime-Mover Model / 475
" ^! _1 D# @ m10.5 Governor Model / 476
]! s0 ]! N& ?. X3 g10.6 Tie-Line Model / 4814 E' G$ w" j7 R5 g1 t9 t* l
10.7 Generation Control / 4853 |" K- D) t0 V/ i g
10.7.1 Supplementary Control Action / 485
; t$ d& t/ t% K' E$ ?: u10.7.2 Tie-Line Control / 486$ U; R6 }* O' ?- o) P
10.7.3 Generation Allocation / 489
# ?8 h0 T& V0 x- b) r. t( [% A [10.7.4 Automatic Generation Control (AGC)6 l+ M1 B4 d+ _1 Q& d/ `& S
Implementation / 4919 O" w- Z$ M, _8 C& u* i& G
10.7.5 AGC Features / 495# n$ z6 T) V8 |" X( m# E6 P" u
10.7.6 NERC Generation Control Criteria / 496
1 Q& y, E- T' pPROBLEMS / 497" A( p) C& c# f: \# I5 S
References / 500; P u0 Q1 n- P7 A
11 Interchange, Pooling, Brokers, and Auctions 501+ Z% ~0 o5 _( }5 B
11.1 Introduction / 5019 K1 _) s* ~1 J0 }% O# A- m8 H& w5 e& r
11.2 Interchange Contracts / 504' d3 z" m) H& Z5 g! o% i" s, V
11.2.1 Energy / 504
" W2 H4 E. ~9 ]8 Q3 b' k; M/ ?11.2.2 Dynamic Energy / 506 R6 \. O9 Q; g
11.2.3 Contingent / 506' x" Y; O, ^& P2 K, _1 P
11.2.4 Market Based / 507$ c% M9 b6 u% I7 F$ t2 J1 l" ~4 |/ ]
11.2.5 Transmission Use / 508
& `. i/ \9 S9 O/ _) f+ H11.2.6 Reliability / 5177 Z6 Z4 E$ ?3 o$ W5 Q1 Y$ ^0 `# i/ {
11.3 Energy Interchange between Utilities / 517
0 c) p& X& t$ c# r0 a7 O11.4 Interutility Economy Energy Evaluation / 521' x( n5 }( R6 S& O
11.5 Interchange Evaluation with Unit Commitment / 522
D# n! N9 }3 l- H- b' O11.6 Multiple Utility Interchange Transactions—Wheeling / 5238 ?, \: f) P% E" C$ k
11.7 Power Pools / 526
: X9 B, O0 v6 X f2 lcontents xv
3 }# R1 l# C; R2 g3 a2 ]11.8 The Energy-Broker System / 5290 {7 i* @% z* q# j3 d0 z; d6 C/ X( t
11.9 Transmission Capability General Issues / 5332 A6 S9 a) F* e1 y& k$ {, \
11.10 Available Transfer Capability and Flowgates / 535& g) n) f4 j, D0 P. c" B$ X/ `
11.10.1 Definitions / 536! D, q: a3 ~4 [: Y
11.10.2 Process / 5399 r5 j; _& z0 k& S6 t+ a2 W5 S3 f
11.10.3 Calculation ATC Methodology / 540
4 t3 `, n6 w% Y L- d11.11 Security Constrained Unit Commitment (SCUC) / 5500 W. T4 [/ F2 H R& s# T$ s
11.11.1 Loads and Generation in a Spot Market Auction / 550
6 p* h3 a& q: T4 d+ d; n2 Y5 m11.11.2 Shape of the Two Functions / 5521 t& P* K X% L: U8 w$ \
11.11.3 Meaning of the Lagrange Multipliers / 553
3 L! V4 H/ Q" u7 a/ E m7 e11.11.4 The Day-Ahead Market Dispatch / 5543 R7 v# [' |# I% I
11.12 Auction Emulation using Network LP / 555# n3 x8 {+ H$ g
11.13 Sealed Bid Discrete Auctions / 555& Y1 T& g( r. C% p7 u: y$ ]
PROBLEMS / 5607 w& u' K3 z, k( q. N
12 Short-Term Demand Forecasting 566* }4 o% k0 v1 }$ a+ Z
12.1 Perspective / 566
& P9 z' E6 J8 ~, S) D: ?12.2 Analytic Methods / 569
9 j6 k) a# o6 c ^9 |12.3 Demand Models / 571
' s2 Y# ^/ ^$ [& ?12.4 Commodity Price Forecasting / 5726 k3 h/ [- v$ ?/ V
12.5 Forecasting Errors / 573
" a, U6 Y G& F- f# m/ d! c12.6 System Identification / 573: s* E4 k Q& Y3 L5 T* O
12.7 Econometric Models / 574
3 A- x1 d% i/ t12.7.1 Linear Environmental Model / 5742 h0 _! J) R1 Q- f: M
12.7.2 Weather-Sensitive Models / 5766 f9 a( M9 N4 E/ I
12.8 Time Series / 5787 n" u0 \6 n7 X: V: E
12.8.1 Time Series Models Seasonal Component / 5786 ]/ M. r; b2 \2 R, x' W: W' j
12.8.2 Auto-Regressive (AR) / 580
( {2 F* L' c+ a/ B. ]5 G: T5 E12.8.3 Moving Average (MA) / 581( v8 e% R M; _" d- Z
12.8.4 Auto-Regressive Moving Average (ARMA):. V0 D4 _3 h8 T* S+ j! q2 I9 }5 D
Box-Jenkins / 582 R& X9 I: L( |# j& ]
12.8.5 Auto-Regressive Integrated Moving-Average
( x0 d7 `1 M) S$ D6 T(ARIMA): Box-Jenkins / 584
3 y+ R5 D3 l6 t12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585 U8 ?% ^; n3 P( i/ E6 ^& f/ z
12.9 Time Series Model Development / 5853 M+ |: [! l" r! W" [
12.9.1 Base Demand Models / 586+ k; J; D, d( t5 h0 m1 N9 o. I# J
12.9.2 Trend Models / 586
% X( \; p( h$ |( H: `( k. |7 N12.9.3 Linear Regression Method / 586
& E) e7 `! A, u3 L, yxvi contents
& S0 O: {. N- G6 Q0 O/ Q12.9.4 Seasonal Models / 588
# g' \' i: y! j) T12.9.5 Stationarity / 588
" s% N5 d$ r, P# K0 H2 d8 [12.9.6 WLS Estimation Process / 590
! R7 f/ E8 S9 ]7 u) p5 m4 d2 b12.9.7 Order and Variance Estimation / 591) b! A# w; @" p* T. j0 e8 ]
12.9.8 Yule-Walker Equations / 592
0 m- O/ A0 g& `- `# ^# M. m12.9.9 Durbin-Levinson Algorithm / 5952 U$ i7 e y7 @+ R+ i( A! |: Q3 B
12.9.10 Innovations Estimation for MA and ARMA- }* t: ]6 L: O( u- u% \
Processes / 598
! Z; g( v+ X8 \ r f$ @12.9.11 ARIMA Overall Process / 600
' t9 a( F) \4 [. \12.10 Artificial Neural Networks / 603
5 K0 `- W0 J' q, ~12.10.1 Introduction to Artificial Neural Networks / 604
/ b0 A9 {/ u8 x: r12.10.2 Artificial Neurons / 605% Q s: O: J2 `8 J: E
12.10.3 Neural network applications / 606
3 g2 c, X$ e) h12.10.4 Hopfield Neural Networks / 606
5 [: Z1 n# e" G. F12.10.5 Feed-Forward Networks / 6072 \ [' x5 [$ ~8 L
12.10.6 Back-Propagation Algorithm / 610
9 E+ U6 \6 M" F- r) A7 I12.10.7 Interior Point Linear Programming Algorithms / 613
# @, y/ F: ~8 i* v3 {! _7 U12.11 Model Integration / 614
6 h6 \* {+ K2 C3 F- ^4 }: w% Q2 f7 p! I; c12.12 Demand Prediction / 6142 Y/ z1 F2 A7 G# i( i
12.12.1 Hourly System Demand Forecasts / 615
: l5 t7 A5 [! ~5 ^5 Y12.12.2 One-Step Ahead Forecasts / 615
5 ^9 B( K# u) C; u: ?& u12.12.3 Hourly Bus Demand Forecasts / 616; _1 o9 @$ \( P! f; H' @! x
12.13 Conclusion / 616* I5 |1 W3 @, x
PROBLEMS / 617 |
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