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第三版目录。2 q+ y5 }4 Y0 q, `" H
1 Introduction 1
' o0 t! m* K$ f. B6 M1.1 Purpose of the Course / 1( A# \) u2 }- E# {3 b
1.2 Course Scope / 2
+ t5 c( W2 J+ @/ o- y& _0 X$ D1.3 Economic Importance / 2
4 c6 l$ O& b% h% b: I1.4 Deregulation: Vertical to Horizontal / 3* H1 U/ p% J+ S0 h' e1 v+ a
1.5 Problems: New and Old / 3
2 j- @/ n* y: Y: k' D( k. l5 V1.6 Characteristics of Steam Units / 6
) J0 Y* @7 n; S# M$ D" _1.6.1 Variations in Steam Unit Characteristics / 10- @( d" g6 M {/ q' O
1.6.2 Combined Cycle Units / 13
% O& w6 m- O3 ~( I1.6.3 Cogeneration Plants / 14- w6 _; `4 R+ A- Q
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17
1 r: m/ {5 N8 ^8 C1.6.5 Hydroelectric Units / 18$ M% R! N5 ~% ]. j
1.6.6 Energy Storage / 21
6 Y- u. V5 X0 j- Y. q1.7 Renewable Energy / 22
0 e$ w- {2 i9 F/ z5 z1.7.1 Wind Power / 23' ?/ f- T9 O2 ^ C' s
1.7.2 Cut-In Speed / 23" C; r2 V) C& E8 A n
1.7.3 Rated Output Power and Rated Output Wind Speed / 24
! z! A' G: N. j$ d. n: Y1.7.4 Cut-Out Speed / 241 h0 ?. @ F @4 j0 q; S
1.7.5 Wind Turbine Efficiency or Power Coefficient / 24, A3 J0 ^! L) _) Z7 b% k
1.7.6 Solar Power / 25+ N; [* m; n. ^2 |" ]- _9 E: `; L
APPENDIX 1A Typical Generation Data / 260 W' ^2 i, M* A2 b0 I- t2 |
APPENDIX 1B Fossil Fuel Prices / 28
0 H' s- ]1 L; |. d& S: CAPPENDIX 1C Unit Statistics / 29
( C5 U- z) J( G6 vCONTENTS# F* ]- k; |( D2 e/ u& U4 q1 D9 o
viii contents; U2 f5 D5 _9 t6 X* o+ n
References for Generation Systems / 31
; v( V7 Z; V' F- ]. o0 T; QFurther Reading / 31
. k& G. x" e# _. V: _2 Industrial Organization, Managerial Economics, and Finance 35: M* s! G \6 p6 s
2.1 Introduction / 35
8 t, D8 _2 k5 @$ p* X2.2 Business Environments / 36
2 Y; q* ^! \7 E4 f- }% s* v9 Y2.2.1 Regulated Environment / 37
9 b7 O+ h' U" J! ]2.2.2 Competitive Market Environment / 38, v9 Z k5 R9 C
2.3 Theory of the Firm / 40
/ V: ?# |9 u( u2.4 Competitive Market Solutions / 42
) k) u g4 c. H3 ? B/ i2.5 Supplier Solutions / 457 r, c& E: g+ I# I8 ]
2.5.1 Supplier Costs / 46
( \4 b" }$ s2 S7 }5 b2.5.2 Individual Supplier Curves / 46
! \8 q; V1 R+ K2.5.3 Competitive Environments / 474 o1 z- Q8 d$ j A/ x$ f; w
2.5.4 Imperfect Competition / 51
6 J! {& U% O, l+ ~& E/ Y8 c; e2.5.5 Other Factors / 52
* w. v5 b& J( Z, q3 x/ m5 C, A/ ?; a2.6 Cost of Electric Energy Production / 53
- G* f, r& _) {1 p6 ?- Z# ? o2.7 Evolving Markets / 54) Q2 W2 l) I% l) {5 v6 b
2.7.1 Energy Flow Diagram / 57
+ z' z: q0 |6 n1 N2.8 Multiple Company Environments / 58
. h0 E& ]0 i' m( {2.8.1 Leontief Model: Input–Output Economics / 58
J& Z3 k% F, O% ]1 t* U, `2.8.2 Scarce Fuel Resources / 607 @! F0 E, ?5 b8 o. B# a E
2.9 Uncertainty and Reliability / 616 c3 y) u d1 |
PROBLEMS / 61
. t- d3 J- Y7 YReference / 62* b& i& h8 S4 y6 {& @" R8 T7 V
3 Economic Dispatch of Thermal Units and Methods of Solution 63
H8 q& w: ?- b+ r' l9 w3.1 The Economic Dispatch Problem / 633 m0 Z+ t# f" E( q# ~* S7 K Y
3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68, `( @7 ~: ~ V3 ~+ v) T/ t7 S
3.3 LP Method / 69( J( y# ?3 k% `% u
3.3.1 Piecewise Linear Cost Functions / 69# z. a- U& a4 G7 `
3.3.2 Economic Dispatch with LP / 71
+ e$ U, q+ Q6 k3 X# T/ @. F0 C3.4 The Lambda Iteration Method / 73
& u( f% V& w) w6 m: W3.5 Economic Dispatch Via Binary Search / 76
8 n1 R, @3 M+ Y- X8 o) d/ v3.6 Economic Dispatch Using Dynamic Programming / 78
7 n# C0 i! S; ]; B4 u2 V5 ^: Y/ p0 K4 ~3.7 Composite Generation Production Cost Function / 811 ]; t' x% h% ?" c% C
3.8 Base Point and Participation Factors / 85: z& H) K0 X$ m
3.9 Thermal System Dispatching with Network Losses+ P. w/ h+ c8 W% j; I
Considered / 88* @0 b1 A1 i2 E4 x+ `3 b
contents ix
0 O: d2 i. R5 I* J3.10 The Concept of Locational Marginal Price (LMP) / 92
) o3 J' `. L9 C8 K3 S3.11 Auction Mechanisms / 95
. P- k3 @8 h4 O2 p( A4 S3.11.1 PJM Incremental Price Auction as a
4 r8 K. k1 D0 r4 J( C& c: V( ]$ HGraphical Solution / 95
- T$ ~( U M, S4 r9 Y" ]6 R3.11.2 Auction Theory Introduction / 983 B( d- u5 I* J! d$ ~' @5 |
3.11.3 Auction Mechanisms / 1004 Z# Y1 C6 u* w; a' r
3.11.4 English (First-Price Open-Cry = Ascending) / 1016 s& W% Z* M, L" L
3.11.5 Dutch (Descending) / 103
- }1 c3 v( }; c9 r3.11.6 First-Price Sealed Bid / 104
/ M4 \0 w6 M; R) L3.11.7 Vickrey (Second-Price Sealed Bid) / 105% v9 j/ {0 O6 l! I7 ]
3.11.8 All Pay (e.g., Lobbying Activity) / 105
' j4 p1 ?% c1 i. J0 A6 R @APPENDIX 3A Optimization Within Constraints / 106
# l1 e6 l2 D# H- ~( gAPPENDIX 3B Linear Programming (LP) / 117
2 J- C4 E7 f- P2 q+ `APPENDIX 3C Non-Linear Programming / 1285 E6 @, b* P/ P- @: Q0 a
APPENDIX 3D Dynamic Programming (DP) / 128, N8 W. ]: |2 o+ A' n. p6 }5 Z4 [
APPENDIX 3E Convex Optimization / 135
5 p/ _) M3 Y) b; W9 RPROBLEMS / 138, l0 v- U( u# z% }
References / 146
$ w1 S1 z8 }- ~2 F" m$ N6 z( Y4 Unit Commitment 1475 A* x* j3 \' p
4.1 Introduction / 147
8 E Z: D' N! U4.1.1 Economic Dispatch versus Unit Commitment / 147
6 M# f4 \8 d+ p6 n/ F1 n4.1.2 Constraints in Unit Commitment / 152' v/ L0 Y, A) ?. s
4.1.3 Spinning Reserve / 152
' L; J7 \9 H" X/ z* I4.1.4 Thermal Unit Constraints / 153
$ s! ^9 Z _- V0 g4.1.5 Other Constraints / 155
% X9 K q- U, u3 |" N7 I8 C4.2 Unit Commitment Solution Methods / 155
. e2 Q2 [$ r/ L9 Y- l. B' R- b& u" @4.2.1 Priority-List Methods / 156
( {- @: k5 W" n, u3 n: @, h4.2.2 Lagrange Relaxation Solution / 157
, y2 ~' _; Z0 {2 h! R: p/ g' z4.2.3 Mixed Integer Linear Programming / 166+ r. H+ q! |( ^: c% E* V
4.3 Security-Constrained Unit Commitment (SCUC) / 167
+ W1 d: ?9 p+ o' n A8 q* ]4.4 Daily Auctions Using a Unit Commitment / 167
4 h4 e$ p6 R% I# Q4 O. s7 l& m5 ?APPENDIX 4A Dual Optimization on a Nonconvex
4 S# b5 p7 m. n! D* RProblem / 167- `0 ` b" M: D9 w- I
APPENDIX 4B Dynamic-Programming Solution to4 y5 k; U' @1 U- u# w- A7 w
Unit Commitment / 1736 c1 Y6 N1 |/ ?. |# ]
4B.1 Introduction / 173' w( s% P7 a* K' j
4B.2 Forward DP Approach / 174 C1 _, b0 ?- t7 v7 f4 u' n
PROBLEMS / 182: `5 z$ b& ~5 |7 c) g0 z7 t
x contents
: M2 |+ j7 w+ w: m7 ~8 N* ~9 z5 Generation with Limited Energy Supply 187
& d9 l) O1 U3 Y( e- j' q5.1 Introduction / 187
; S* o4 D, j4 K+ c5.2 Fuel Scheduling / 188
( ^: H: U4 Q8 p' O5.3 Take-or-Pay Fuel Supply Contract / 1884 s9 j' t; _0 \: F2 }; [
5.4 Complex Take-or-Pay Fuel Supply Models / 194
( ]1 l& j8 H) |' h6 o9 L* ^5.4.1 Hard Limits and Slack Variables / 194) G- S- U! \! f8 a
5.5 Fuel Scheduling by Linear Programming / 195
7 y( u; P' j' b! H% a7 U5 d5.6 Introduction to Hydrothermal Coordination / 202% `" p B: r% ]! b4 _
5.6.1 Long-Range Hydro-Scheduling / 203
( n. A K+ K1 V+ X3 M' q5.6.2 Short-Range Hydro-Scheduling / 204. u4 A, Y) z3 B$ \
5.7 Hydroelectric Plant Models / 2045 q5 Y* ]# r" C: R' c. C
5.8 Scheduling Problems / 207# D* c, x- V6 ]1 V7 M0 S
5.8.1 Types of Scheduling Problems / 2078 V( _2 Y5 u! z- i \# y. |* s: K% Q4 L
5.8.2 Scheduling Energy / 207: ^+ p$ E( I! Q) S5 g, o9 V
5.9 The Hydrothermal Scheduling Problem / 211
$ x# L0 k: [# h' G; D6 @9 N4 E5.9.1 Hydro-Scheduling with Storage Limitations / 211
% H# L" O1 C3 Y0 n( y& Z9 [5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
6 A3 b: r/ ^4 g5.9.3 Pumped-Storage Hydroplants / 218
, G5 i; X3 W% \, [# b& ?8 ?8 u5 y5.10 Hydro-Scheduling using Linear Programming / 222
2 T2 j9 ?2 J5 W/ y+ `APPENDIX 5A Dynamic-Programming Solution to hydrothermal
- N# v8 U) ]4 [" P( i& mScheduling / 225! A+ \! {3 [+ L) W+ z
5.A.1 Dynamic Programming Example / 227( B- w, y. z o2 a2 e, \
5.A.1.1 Procedure / 2285 ~, N, {" U7 |: H
5.A.1.2 Extension to Other Cases / 2311 H7 q8 B T8 Q/ g, A* i6 \/ F8 t
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
% k) h f+ F: o( l7 jProblem / 232
+ o+ L# w+ u, y$ ePROBLEMS / 2343 L, {( m$ M, `% T0 T0 u
6 Transmission System Effects 243
1 x& L( ~& Q, p8 S: T8 Q ?9 A6 X6.1 Introduction / 243
$ z0 K) ]5 y0 i- c: N) K0 ?6.2 Conversion of Equipment Data to Bus and Branch Data / 247/ T* y) O* z& z0 U; I
6.3 Substation Bus Processing / 2480 L U: } f: j" s3 r
6.4 Equipment Modeling / 2482 L% D# J, C" d
6.5 Dispatcher Power Flow for Operational Planning / 251+ i- |- |. Q6 l
6.6 Conservation of Energy (Tellegen’s Theorem) / 252
6 l- H! e0 a$ I$ T. V+ X6.7 Existing Power Flow Techniques / 253
6 R: y7 g) @/ a' Y6.8 The Newton–Raphson Method Using the Augmented
( k3 b3 S6 R. P& ~$ wJacobian Matrix / 254
_! _! y! U0 J; t8 [* V0 f9 Q6.8.1 Power Flow Statement / 254
$ {6 @+ o" v6 @# k& ~- d6.9 Mathematical Overview / 257# k7 K& N/ c, y, |' S7 p
contents xi: b+ [, p. o }8 `% U
6.10 AC System Control Modeling / 259
E& @5 I/ d! w; c8 r, n6.11 Local Voltage Control / 259" W/ h/ V" G" I. F* S1 N8 Z
6.12 Modeling of Transmission Lines and Transformers / 259( f) @1 T0 C9 V6 G% E! y+ F3 K) G9 q5 n
6.12.1 Transmission Line Flow Equations / 259- A- ?" g* y/ Q Z- V
6.12.2 Transformer Flow Equations / 260* F6 K" @3 m+ T. I
6.13 HVDC links / 261
& s, o) \, y6 P* V$ a3 x' d7 q6.13.1 Modeling of HVDC Converters
+ H% w8 K6 H. ]% B1 ^1 Jand FACT Devices / 2640 u" j* o/ C- o- U5 U- m
6.13.2 Definition of Angular Relationships in
1 h: V$ c& V: I* r6 yHVDC Converters / 264. z" E. k4 u: r+ }
6.13.3 Power Equations for a Six-Pole HVDC3 e6 v, A7 P# z& \" |
Converter / 2649 z9 t6 }. y `6 u' v7 f5 W
6.14 Brief Review of Jacobian Matrix Processing / 267. w' \6 s( R" Y- [; l% z
6.15 Example 6A: AC Power Flow Case / 269
# R5 c3 p. W% ~, p s6.16 The Decoupled Power Flow / 271
7 e- R# ~' Y4 L$ p* T6.17 The Gauss–Seidel Method / 275& I% M: [* m0 Y
6.18 The “DC” or Linear Power Flow / 277) c5 p6 t3 C' _6 U
6.18.1 DC Power Flow Calculation / 277
9 q' T! H2 g7 J% {' v0 S2 }6.18.2 Example 6B: DC Power Flow Example on the
' G5 Q7 q% j/ pSix-Bus Sample System / 278
4 G+ z0 g; `; R6.19 Unified Eliminated Variable Hvdc Method / 2782 \5 x9 A# T* w: M
6.19.1 Changes to Jacobian Matrix Reduced / 279
: ?, r" r- k& R- ]6.19.2 Control Modes / 280
% _7 V2 b$ s+ `- W8 s) n6.19.3 Analytical Elimination / 280. e( i; l$ q+ O* \; L$ D% K4 ~
6.19.4 Control Mode Switching / 283
* r" Q5 x" ~- {- t8 P6.19.5 Bipolar and 12-Pulse Converters / 283( q1 I2 s. \' x# h: C8 @3 x5 D& q, q% b
6.20 Transmission Losses / 284
r& T+ U/ w( S& a \- {" n6.20.1 A Two-Generator System Example / 284! N4 o' [; Q9 l. \# d
6.20.2 Coordination Equations, Incremental Losses,
/ U$ e5 @& t \# G, Tand Penalty Factors / 286# q( r8 o6 P# t5 x/ I
6.21 Discussion of Reference Bus Penalty Factors / 288
j! A2 o! X1 d0 y- Z9 N6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
9 v3 D* u/ y$ `: P3 g8 fPROBLEMS / 291
) v/ [" b* P7 [% z1 e5 \7 X. b7 Power System Security 296
4 w/ r& M5 q" |; W* d/ Z# ^ g7.1 Introduction / 296' l: a" ?' q0 }, D6 `6 B
7.2 Factors Affecting Power System Security / 301+ n; V' \* D# m) P: ^! ^) b
7.3 Contingency Analysis: Detection of Network Problems / 3015 G2 n% p/ p; |. ~4 Z4 n9 i
7.3.1 Generation Outages / 301
" G# p, R- }7 O" g- N. H- X7.3.2 Transmission Outages / 302
$ K+ |2 p' \% }9 s! }! Fxii contents9 B/ ?# @# g* I' _* s
7.4 An Overview of Security Analysis / 306
; `$ u7 c7 A; S K7.4.1 Linear Sensitivity Factors / 307% \! @( Q2 d( W7 o( |
7.5 Monitoring Power Transactions Using “Flowgates” / 313" n5 n8 l& x$ f
7.6 Voltage Collapse / 315
5 q. \" b1 H, v7.6.1 AC Power Flow Methods / 317
, i# J( H, v( k! Q7.6.2 Contingency Selection / 3208 T$ `5 ]1 F- n, t2 c7 z: F
7.6.3 Concentric Relaxation / 3232 [& w. r+ ]: I5 ~! I1 U
7.6.4 Bounding / 325
- _3 J# C" n6 `* \7 q/ _0 q+ D5 a5 q7.6.5 Adaptive Localization / 325
$ t5 B! S1 D4 v, m6 O4 XAPPENDIX 7A AC Power Flow Sample Cases / 327" h6 Y P: r# H$ k2 L/ K$ ]) z1 U
APPENDIX 7B Calculation of Network Sensitivity Factors / 336
# E/ i, W; q9 m3 b7B.1 Calculation of PTDF Factors / 336, A" m8 Z) ]/ b$ S8 O7 R* Y. ~
7B.2 Calculation of LODF Factors / 339
# i$ u( S0 ^4 j* E/ K3 I9 G: S" y/ Y7B.2.1 Special Cases / 341
+ g# E- d8 y, N6 s7B.3 Compensated PTDF Factors / 343
) D: M3 X S8 G- ~Problems / 343
) V# t% q; S& t1 J& WReferences / 349
+ q2 O* {% S5 i9 \8 Optimal Power Flow 350% j1 o: v5 I; i/ L) S3 N! V
8.1 Introduction / 350* l; ]9 u! n8 b" k7 Q4 R9 C- e* ]
8.2 The Economic Dispatch Formulation / 351
1 b& w# e u, h4 M8 O. k8.3 The Optimal Power Flow Calculation Combining9 t/ W8 o, ^7 `# o
Economic Dispatch and the Power Flow / 352! r! N* ?2 x9 l7 W
8.4 Optimal Power Flow Using the DC Power Flow / 354
. S O9 _7 H7 h% `# {8.5 Example 8A: Solution of the DC Power Flow OPF / 356
! q) f1 d' r1 d+ I, z8.6 Example 8B: DCOPF with Transmission Line
2 P8 c* k5 u6 q& U! e8 @+ qLimit Imposed / 361; j$ g& W4 R8 D( O* k* j4 J
8.7 Formal Solution of the DCOPF / 365. E: p" X2 j" B7 l4 F4 m
8.8 Adding Line Flow Constraints to the Linear' g1 v, K. E) ?- T2 o
Programming Solution / 365
3 x2 ]3 w- p1 C! ~( x7 K( V8.8.1 Solving the DCOPF Using Quadratic Programming / 3675 U9 B0 o' ~) p
8.9 Solution of the ACOPF / 368) e% E, w% }5 @" X
8.10 Algorithms for Solution of the ACOPF / 369' w$ ~6 m. R+ j E8 s4 _* C' b( M
8.11 Relationship Between LMP, Incremental Losses, D& B" J8 m+ j# h) Y* C& g6 m8 j
and Line Flow Constraints / 376
' }; `& I) v( @: _5 V8.11.1 Locational Marginal Price at a Bus with No Lines
# J& z$ m8 q' o: X8 OBeing Held at Limit / 377, Z) D" t2 E T0 v. g
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378& f% ^9 B9 }+ _
contents xiii
! x- s# a6 u1 `, g: r; g8.12 Security-Constrained OPF / 382( @5 { y6 R0 T% i( M
8.12.1 Security Constrained OPF Using the DC Power Flow, q% k# U) a y) W" j
and Quadratic Programming / 384
; s6 I. ?1 n1 Q1 @5 p# Q8.12.2 DC Power Flow / 385" E- E5 X0 e- Y' V V! P
8.12.3 Line Flow Limits / 385
' X, D% | H8 ]" p( i7 g8.12.4 Contingency Limits / 386
, z$ ^9 f0 ^8 `/ N; G; H& @" dAPPENDIX 8A Interior Point Method / 391
: k! Z2 G- U1 ^3 o* @, N8 z+ BAPPENDIX 8B Data for the 12-Bus System / 393
! }& s( v" @2 J: g! l( BAPPENDIX 8C Line Flow Sensitivity Factors / 395
; c" S0 Q2 i" E( K; E4 OAPPENDIX 8D Linear Sensitivity Analysis of the
' r$ v' k) n* f ~* o) D: V$ FAC Power Flow / 397: G- ?( B. w% E, ?# V
PROBLEMS / 399! q" b# m4 a' R0 V: W& @% g$ i
9 Introduction to State Estimation in Power Systems 403& R1 ?; c% L8 s( x
9.1 Introduction / 4033 l+ I4 t: [5 [7 k5 U; J" }
9.2 Power System State Estimation / 404
; L% Y+ D4 k! S$ Z9 Q1 l9.3 Maximum Likelihood Weighted Least-Squares" f. q- l" D% f+ m1 {# s6 |" d
Estimation / 408# E+ i* A+ p* @" p& Z3 C
9.3.1 Introduction / 408
# k) W$ Z3 O3 z8 x+ J. w0 D" v v9.3.2 Maximum Likelihood Concepts / 410 p2 N q; ^( C9 i9 `3 _
9.3.3 Matrix Formulation / 414/ i3 x. ?, E3 r( c. G' g) a" u1 ?/ |3 x
9.3.4 An Example of Weighted Least-Squares& u5 G( v1 s2 @8 b! f% S
State Estimation / 417- k- o- r: j$ S6 d$ [% @4 H0 `" X
9.4 State Estimation of an Ac Network / 421! u* v3 P7 b- Z5 C$ o$ Q3 s
9.4.1 Development of Method / 421
' {5 a; [% m. v) M9.4.2 Typical Results of State Estimation on an
k& S4 C- ^ t# V3 M" M/ zAC Network / 424/ e# \3 ?3 z0 A! F% z5 \1 s
9.5 State Estimation by Orthogonal Decomposition / 428
1 p7 A2 S) K* }9 V/ f9.5.1 The Orthogonal Decomposition Algorithm / 431+ k0 `: U8 G+ a% N) I, n2 P
9.6 An Introduction to Advanced Topics in State Estimation / 4350 y7 ^6 Q9 c* W# B
9.6.1 Sources of Error in State Estimation / 435
. o) W0 a1 h. Y8 E# D) a9.6.2 Detection and Identification of Bad Measurements / 4360 W2 E: Q, P. q+ b& J( L
9.6.3 Estimation of Quantities Not Being Measured / 443
5 Y9 |$ D: L, X9.6.4 Network Observability and Pseudo-measurements / 4447 ~3 }- A! ]/ j* K
9.7 The Use of Phasor Measurement Units (PMUS) / 447
/ G% Y2 s1 Y F$ D2 n9.8 Application of Power Systems State Estimation / 451
8 G2 y- y9 A5 W I9.9 Importance of Data Verification and Validation / 454
' x9 p( Z, A) R8 o. ~# ~: Q7 w9.10 Power System Control Centers / 454
/ |# D0 N6 ^0 y. Wxiv contents
4 X1 z- C7 i4 N, LAPPENDIX 9A Derivation of Least-Squares Equations / 456) _( I: Q% A; L& p
9A.1 The Overdetermined Case (Nm > Ns) / 457
- N0 K% B( ?# E9 l, c9A.2 The Fully Determined Case (Nm = Ns) / 462) C1 U) O! c! A7 q/ ?
9A.3 The Underdetermined Case (Nm < Ns) / 462
, Y# c9 u& O- |9 B0 h# IPROBLEMS / 464
) b E* p3 {# K10 Control of Generation 468* H9 K& ~# G! i3 u) ~+ }0 n, M% D
10.1 Introduction / 468
0 L* v+ E- \' F. h% Y10.2 Generator Model / 470
+ p. x. B& I j1 L' Y; ~10.3 Load Model / 473
- F4 V0 J* {1 T/ T10.4 Prime-Mover Model / 4750 @. S- G s. `6 |5 c2 O
10.5 Governor Model / 4764 o$ ~( n2 _: {; Z6 |' w: @
10.6 Tie-Line Model / 481- K( A$ e6 K9 P1 U1 ~
10.7 Generation Control / 4852 M# U' o/ W* T4 _) a8 D, @
10.7.1 Supplementary Control Action / 485
+ q1 K. c- Q+ F" L' `" ~* d8 o% m$ u% T10.7.2 Tie-Line Control / 486
4 c' v4 m: m: U1 W" O10.7.3 Generation Allocation / 489* b) N6 q6 w) K* O' s
10.7.4 Automatic Generation Control (AGC)3 l& s# ?! ]4 ]) X) f" o) M3 U
Implementation / 491
: E6 h' X) V. v& ?10.7.5 AGC Features / 495
: \+ t7 q/ D+ J8 g* D7 ^4 Y10.7.6 NERC Generation Control Criteria / 496+ ] R: P$ F( n K5 c7 u/ B* S4 L/ ]
PROBLEMS / 497
' f) Z' H2 i# P2 f RReferences / 5003 O5 |$ t8 m# Q. C# [5 d* o
11 Interchange, Pooling, Brokers, and Auctions 501. i+ X4 M6 G- L9 c1 b
11.1 Introduction / 501 p7 O0 {( s$ D4 a% p" ?
11.2 Interchange Contracts / 504
; Z4 Y. l! X1 Q* K) [11.2.1 Energy / 504. `& y# ]# A* ~- W7 W
11.2.2 Dynamic Energy / 506' N1 J4 v( L7 ]; ~6 b
11.2.3 Contingent / 5060 T+ c* X& A4 c$ T3 K+ l
11.2.4 Market Based / 507
& d( I% F$ [5 D11.2.5 Transmission Use / 508
" w6 z0 R& Y$ c$ A4 Z3 f11.2.6 Reliability / 517" M! _3 y- b/ K; U4 W$ G9 ^
11.3 Energy Interchange between Utilities / 517
4 K+ z1 [# [' J) j$ {" V+ y11.4 Interutility Economy Energy Evaluation / 521
+ |2 P& E5 {' e+ ~11.5 Interchange Evaluation with Unit Commitment / 522
3 a R: G8 h) ]: }2 c2 ?11.6 Multiple Utility Interchange Transactions—Wheeling / 5234 v9 d7 R5 X" C* M ~0 p9 G4 T6 x0 B
11.7 Power Pools / 526# q, J' D8 |* p2 k: d8 G
contents xv. K' a* V% }2 I Y. S9 _( L
11.8 The Energy-Broker System / 529/ Y' u$ a$ \3 Y6 y. ^1 a6 F8 k; k5 D# u$ u
11.9 Transmission Capability General Issues / 533
& [2 B- H1 D% }8 W9 x11.10 Available Transfer Capability and Flowgates / 535 ~2 Y' i) N4 d
11.10.1 Definitions / 536
) }- E% [; N9 P3 ?# c11.10.2 Process / 539
" L _ l2 k! E1 P11.10.3 Calculation ATC Methodology / 5402 [* s% G+ v& l$ ~
11.11 Security Constrained Unit Commitment (SCUC) / 5502 t5 w1 {% Q I2 b
11.11.1 Loads and Generation in a Spot Market Auction / 5503 J# {; ~, c0 v! m
11.11.2 Shape of the Two Functions / 552+ |3 \, }- a% D- ~+ j: N
11.11.3 Meaning of the Lagrange Multipliers / 5536 M& E* m2 y" I/ C0 H1 x* b2 X
11.11.4 The Day-Ahead Market Dispatch / 554
- j$ \" p/ _3 A$ D9 a11.12 Auction Emulation using Network LP / 555" l! R6 l8 B0 Z% `
11.13 Sealed Bid Discrete Auctions / 555
3 w* a% @6 U0 _ {7 VPROBLEMS / 560
+ _# I) F8 ~4 a+ R0 s2 t( A12 Short-Term Demand Forecasting 5664 z4 p8 u$ e$ v
12.1 Perspective / 566
2 }" J# B5 I) D6 W+ T12.2 Analytic Methods / 5696 o3 P4 P. f& F4 K j0 Y/ t! j
12.3 Demand Models / 571/ E3 T6 W/ |. W* l1 J
12.4 Commodity Price Forecasting / 572
3 w2 b9 s# @3 Y8 m3 d12.5 Forecasting Errors / 573
; G% a, j8 s2 H6 z) V12.6 System Identification / 573
5 h8 A/ s- Z0 J" {/ a/ r12.7 Econometric Models / 574
9 F& X/ c: [( e5 a: ^' [4 g1 Z0 g/ Y3 T12.7.1 Linear Environmental Model / 574
2 Y' w" b2 d0 m7 j12.7.2 Weather-Sensitive Models / 576
8 V& C$ b: M+ t12.8 Time Series / 578
7 l4 N9 |. _# U( T+ O4 }' o12.8.1 Time Series Models Seasonal Component / 5782 `6 v5 `! U9 q# H( j$ j: e0 [
12.8.2 Auto-Regressive (AR) / 580& V6 B7 q7 ^: e: `; [/ ~1 P9 c0 b
12.8.3 Moving Average (MA) / 5811 k/ }0 s( `) N: C
12.8.4 Auto-Regressive Moving Average (ARMA):5 z P1 D7 N$ w/ i
Box-Jenkins / 582
3 T7 m5 Q8 F9 D" {2 r12.8.5 Auto-Regressive Integrated Moving-Average& M* l3 r* f' Y8 u i
(ARIMA): Box-Jenkins / 584$ u) `2 M. q1 J# B/ |( x9 c5 D
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585
" I5 F3 j2 x; p4 e3 _12.9 Time Series Model Development / 5851 ?2 ^ t9 {0 f! j
12.9.1 Base Demand Models / 586
& c' g% Z+ s% |0 x. Y" _- U12.9.2 Trend Models / 586, w. g, j( A" [$ g9 l
12.9.3 Linear Regression Method / 586
6 D9 j% V l3 `xvi contents
& [- O# B/ W3 ^4 O( Z% q y5 G12.9.4 Seasonal Models / 588
" a5 ~/ R# p: B5 z" m5 L2 T6 Q' }! [12.9.5 Stationarity / 588
# @" x2 d( _" y2 e, V7 u12.9.6 WLS Estimation Process / 590+ {( @9 `8 B% }9 V5 e" X
12.9.7 Order and Variance Estimation / 5911 r; a$ V7 n1 G7 L
12.9.8 Yule-Walker Equations / 592 A$ r7 ]; B! O+ H
12.9.9 Durbin-Levinson Algorithm / 595
8 q6 \+ M) ?7 S3 f b9 l9 S12.9.10 Innovations Estimation for MA and ARMA
0 w; I; G+ `6 l" ] }Processes / 598 y* F4 B/ q9 O
12.9.11 ARIMA Overall Process / 600& z$ k5 _8 Z* ?2 u) D: M
12.10 Artificial Neural Networks / 603
5 _1 G$ ]4 B/ |8 j3 f12.10.1 Introduction to Artificial Neural Networks / 604
1 L" ^$ n/ I! l12.10.2 Artificial Neurons / 6057 H& m2 j7 i& a8 }
12.10.3 Neural network applications / 606! H3 V& o! W0 r( i( D2 V
12.10.4 Hopfield Neural Networks / 606' z9 s* ] n! o' w0 f3 O1 Y
12.10.5 Feed-Forward Networks / 607) U3 X* R& ^) b% l+ o( {
12.10.6 Back-Propagation Algorithm / 610) j2 N6 l7 j, _, v2 t* F" w
12.10.7 Interior Point Linear Programming Algorithms / 613+ r0 Z" v2 C7 w' y. H
12.11 Model Integration / 614$ h% M! o" e- a
12.12 Demand Prediction / 614
0 F( t1 y; T' G7 M# o12.12.1 Hourly System Demand Forecasts / 615
1 R7 N. O0 M. ~3 ]: f- M* i2 h12.12.2 One-Step Ahead Forecasts / 615) W( C# w& z) S, |) T/ {
12.12.3 Hourly Bus Demand Forecasts / 616
' c$ F K- s2 B( n12.13 Conclusion / 616$ ?2 U. I- p( I: f, Z4 s
PROBLEMS / 617 |
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