TA的每日心情 | 开心 2020-3-1 21:18 |
|---|
签到天数: 1 天 连续签到: 1 天 [LV.1]初来乍到 累计签到:2 天 连续签到:1 天
|
楼主 |
发表于 2014-6-10 16:45:26
|
显示全部楼层
第三版目录。
4 ~" G# j4 V7 N4 u- j0 ?+ @- P1 Introduction 14 B/ `8 w8 u# N7 A% ^
1.1 Purpose of the Course / 1
* _" E9 t2 h* h0 S1.2 Course Scope / 2, O* R* Q; a; _4 R7 ]# U
1.3 Economic Importance / 2, t* i4 d' Y3 w. d/ g
1.4 Deregulation: Vertical to Horizontal / 3
. Y; P6 y8 L' r- B; v6 u Y4 y+ q1.5 Problems: New and Old / 3. L* q/ o" B$ O9 ^+ }" N0 R
1.6 Characteristics of Steam Units / 6
! B8 Z9 N4 {+ G" T1.6.1 Variations in Steam Unit Characteristics / 10& G5 G+ m- C# f7 j4 q% S0 P
1.6.2 Combined Cycle Units / 136 N& O% U- p$ F# u% @
1.6.3 Cogeneration Plants / 14
% [; a& J5 P1 \4 `/ O' ~5 m1.6.4 Light-Water Moderated Nuclear Reactor Units / 17$ a8 N& ]1 J! t0 ^; M
1.6.5 Hydroelectric Units / 18
{3 b" O0 A: y$ o1 a2 B1.6.6 Energy Storage / 21
8 ?- z1 x4 K8 S: Y: Q* V1.7 Renewable Energy / 22
% k/ ]3 V7 A% C1 I1.7.1 Wind Power / 236 Q* @3 g: N8 B' s$ h1 {9 {
1.7.2 Cut-In Speed / 231 c( d1 g6 s. w( z, F0 e% b
1.7.3 Rated Output Power and Rated Output Wind Speed / 24. t) j# ^; I- c4 K( ]
1.7.4 Cut-Out Speed / 24
/ x3 C) h! m3 S: K1.7.5 Wind Turbine Efficiency or Power Coefficient / 240 {) Q1 \2 J* e- C! F, J, U
1.7.6 Solar Power / 25
& w9 m! C) H7 n" p! V* \APPENDIX 1A Typical Generation Data / 26
" N0 O5 s! x- V, O5 Y4 B+ C: P; bAPPENDIX 1B Fossil Fuel Prices / 28
( K# M+ |& @# k# O& uAPPENDIX 1C Unit Statistics / 29
" v4 M4 l# i1 N2 OCONTENTS
$ Y$ L( Z' t; C! O8 `8 @5 Dviii contents
0 w+ X7 m4 w" h7 E, y/ ?, {References for Generation Systems / 319 y p1 k! P7 z4 J5 L; ^6 E
Further Reading / 31 s; N5 q ?5 G6 l# F% @9 R8 P
2 Industrial Organization, Managerial Economics, and Finance 35
: o( x1 Y) E3 F2.1 Introduction / 35
( m% s2 j% l+ n9 S1 h5 h2.2 Business Environments / 36
+ }, p; G, a9 C* O2.2.1 Regulated Environment / 37$ k+ \: r5 N. S: o6 a) j; ~3 a
2.2.2 Competitive Market Environment / 383 r! b7 D+ e+ p
2.3 Theory of the Firm / 40
- F- s9 u' X' y3 c2.4 Competitive Market Solutions / 428 i; Z7 q( C/ K; P! R2 D ^+ z2 z
2.5 Supplier Solutions / 45; k, T1 R& [5 k7 |8 C/ [2 A
2.5.1 Supplier Costs / 46& f3 R8 `; Q6 U9 E/ Z6 `) B5 G. m
2.5.2 Individual Supplier Curves / 46
3 a2 Z- F u! O2 ]2.5.3 Competitive Environments / 478 l8 R) |& o+ M. j! t; y, w: {, U
2.5.4 Imperfect Competition / 51
/ ?' |" E4 [, o8 u# c% X2.5.5 Other Factors / 52: M( B8 x \5 e3 w, A
2.6 Cost of Electric Energy Production / 53
3 {8 u# R4 g7 [8 v5 a6 j2.7 Evolving Markets / 54
- ^4 y' v/ y% V2.7.1 Energy Flow Diagram / 57
9 c2 f: y+ k5 B! F, _2.8 Multiple Company Environments / 58
" I3 |5 s0 l5 Z) _' o- w2.8.1 Leontief Model: Input–Output Economics / 58
$ @$ n: E7 N+ U2.8.2 Scarce Fuel Resources / 60
. [; ~8 x) ?! K6 m. B& k8 T2.9 Uncertainty and Reliability / 61( D, a" p! G6 m5 }. D, B
PROBLEMS / 61/ R9 n; V$ Q5 G
Reference / 62
5 B7 ]' Y; K0 B. H3 Economic Dispatch of Thermal Units and Methods of Solution 633 u* c; s$ V% l5 i- @9 m$ y% B3 |
3.1 The Economic Dispatch Problem / 63) t3 _. G9 y9 g4 o q( o
3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68" |0 H5 j V3 x/ V) w4 a
3.3 LP Method / 69( _ j. w* Y1 X' O
3.3.1 Piecewise Linear Cost Functions / 69
% _/ t0 p6 _) G' h1 M5 }" U3.3.2 Economic Dispatch with LP / 71
: t. N" E6 {) B' v) d3.4 The Lambda Iteration Method / 73
! K; J' J. V/ u) l, Y3.5 Economic Dispatch Via Binary Search / 76
- E7 G% q, M# k6 Q0 y3.6 Economic Dispatch Using Dynamic Programming / 78
( t) v5 O* ?1 P2 I% F% }# h3.7 Composite Generation Production Cost Function / 81
& J" |+ f; @, |9 p9 y7 \: Z6 _3.8 Base Point and Participation Factors / 85
D6 b# G+ [$ |3.9 Thermal System Dispatching with Network Losses, ?6 S* a, z, F0 W# ]' G: F a# C
Considered / 880 G) A0 _0 k: ]$ M8 |6 n* p/ N% B3 x
contents ix+ u7 j3 e* R. i9 I3 _
3.10 The Concept of Locational Marginal Price (LMP) / 92
* l2 n& @' M7 i) R3.11 Auction Mechanisms / 95
3 ?% {# ~6 R' Z$ O3.11.1 PJM Incremental Price Auction as a& z4 a$ g+ p, K$ k3 V8 _
Graphical Solution / 95- Z% m7 U& ?1 c+ c% s
3.11.2 Auction Theory Introduction / 98
V% g' c" C/ |# `3.11.3 Auction Mechanisms / 1009 |8 ?1 }- F5 y& A( J m
3.11.4 English (First-Price Open-Cry = Ascending) / 101
2 C# d! R# Z8 R+ R" E- X3.11.5 Dutch (Descending) / 103
3 P$ U7 d! q# c4 q% N1 ?- i* u# z3.11.6 First-Price Sealed Bid / 104" n4 x* S1 l; R3 x9 p; u6 [4 ^
3.11.7 Vickrey (Second-Price Sealed Bid) / 105
+ d) L! E, {" g0 t$ v1 ^) V3 W3.11.8 All Pay (e.g., Lobbying Activity) / 105; @1 B# e/ i2 j, ^9 s
APPENDIX 3A Optimization Within Constraints / 106
8 u' ]' I( i* z, E+ |APPENDIX 3B Linear Programming (LP) / 117
) q9 E- ]3 z+ jAPPENDIX 3C Non-Linear Programming / 128
, H- }/ ], t' p+ j2 W+ xAPPENDIX 3D Dynamic Programming (DP) / 128
5 D" _( F( ?. y& PAPPENDIX 3E Convex Optimization / 135" J& j2 w ]" A- y1 i2 ^
PROBLEMS / 138
) i* z( [0 n7 l! S( KReferences / 1464 a1 Y: ^7 X2 O% S
4 Unit Commitment 147
( Z. @6 `+ `9 I& T" K4.1 Introduction / 147! R; s/ F! g. g, ?1 X' E
4.1.1 Economic Dispatch versus Unit Commitment / 147
- i. ]& U. L( y. F! L4.1.2 Constraints in Unit Commitment / 152
: k6 R" _* p0 y( \! {, B4.1.3 Spinning Reserve / 152
1 C% e3 w* M6 N5 T/ {4.1.4 Thermal Unit Constraints / 153
# I5 h' e/ d& P+ l( D2 k3 h7 M4.1.5 Other Constraints / 155
8 X4 ~! w# \8 S: u2 ^3 p i# e4.2 Unit Commitment Solution Methods / 155
4 s' X: J! b- G) ]" I' L% \4.2.1 Priority-List Methods / 156, Z6 a/ O3 K% i: j" \
4.2.2 Lagrange Relaxation Solution / 157
8 B& c" Z2 N! ^" ~4 r4.2.3 Mixed Integer Linear Programming / 166
$ x9 @. M) C" a I6 T4.3 Security-Constrained Unit Commitment (SCUC) / 167' i+ B- V1 q3 _
4.4 Daily Auctions Using a Unit Commitment / 167
& R# y' u, @. v0 G! L7 {APPENDIX 4A Dual Optimization on a Nonconvex% m+ v/ r7 l( H7 F
Problem / 167- F! I! \: q# `6 k
APPENDIX 4B Dynamic-Programming Solution to5 J3 ?0 M2 n( s1 [: g
Unit Commitment / 173
- k0 G3 c& }( G$ n4B.1 Introduction / 173( ]3 y, A. r [
4B.2 Forward DP Approach / 174' P* [1 p% J6 X# Z s% A2 h7 C
PROBLEMS / 182* P5 n I! v3 S
x contents
: s6 A$ w$ Y' Y3 r M: i5 Generation with Limited Energy Supply 187
9 }1 [/ _, q$ i5.1 Introduction / 187
7 q' ~# M! H7 X9 C: E( ?5.2 Fuel Scheduling / 188
: m _$ ~- M$ x- n/ N5.3 Take-or-Pay Fuel Supply Contract / 188
, ~! v$ a4 E/ A: a/ T5.4 Complex Take-or-Pay Fuel Supply Models / 194
/ h( a6 P8 [' |2 n$ r5.4.1 Hard Limits and Slack Variables / 194
$ u9 x6 u% V6 W# o) M) P- M, S1 N5.5 Fuel Scheduling by Linear Programming / 195/ X0 h5 r% W* b" c; |
5.6 Introduction to Hydrothermal Coordination / 202) @- ?7 w# O+ L, \: n3 m
5.6.1 Long-Range Hydro-Scheduling / 203
) s3 K: T, m) c Q5.6.2 Short-Range Hydro-Scheduling / 2040 X0 o+ p% i% r+ m$ v$ Z, i
5.7 Hydroelectric Plant Models / 204
7 \, M, F, f8 e: l3 i1 F5.8 Scheduling Problems / 207$ l$ N* ?. \& D7 ~
5.8.1 Types of Scheduling Problems / 207
9 q, s" U$ i( E" S! s- z* V6 u9 h- B5.8.2 Scheduling Energy / 2070 [8 @; z! t [; z
5.9 The Hydrothermal Scheduling Problem / 211 Z7 P! H* E6 D% d+ Y
5.9.1 Hydro-Scheduling with Storage Limitations / 211) _: O& l$ ]% i& K
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
% k) ~6 J" D7 P Z% Z: [5.9.3 Pumped-Storage Hydroplants / 218 W+ l1 q, a; l
5.10 Hydro-Scheduling using Linear Programming / 222
0 o5 J, @, k+ ^5 l. X1 jAPPENDIX 5A Dynamic-Programming Solution to hydrothermal7 g$ G& C6 z% ^1 Y4 X
Scheduling / 225
' i# I) H3 M* o0 z4 D K5.A.1 Dynamic Programming Example / 227
3 k$ T9 S0 ?& m; F8 D. g# g! R$ n1 O5.A.1.1 Procedure / 228
. ^7 n! m" v1 e# K: D& z5.A.1.2 Extension to Other Cases / 231
6 v, t* r' I2 f+ i5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant- \! x+ V7 |' l @/ r
Problem / 232, y% z0 F5 F: ^4 b; f& \0 C$ s
PROBLEMS / 234, e' k' M. p2 i% x! D5 b- E3 g
6 Transmission System Effects 243
/ m" ]" n1 h9 [- e. g+ x6.1 Introduction / 243
6 S$ P5 I' ?5 ~( \6 h6.2 Conversion of Equipment Data to Bus and Branch Data / 247, C/ q2 ?( _' G
6.3 Substation Bus Processing / 248
2 F9 r1 \, H3 ~4 Y; o1 l6.4 Equipment Modeling / 248 J" P# L, K! H( B
6.5 Dispatcher Power Flow for Operational Planning / 2516 b' I8 X2 F Z# K9 z P' ]8 b
6.6 Conservation of Energy (Tellegen’s Theorem) / 252
8 o5 w% f; Z' D6.7 Existing Power Flow Techniques / 253
& j0 ]& @& z% Q, w$ k4 G0 x6.8 The Newton–Raphson Method Using the Augmented+ l% w7 q, ^. b0 f8 \5 I& A. U
Jacobian Matrix / 254
- [. W, m) t1 T, M7 W8 O% ]8 v6.8.1 Power Flow Statement / 254; b2 ` y2 Q L, z
6.9 Mathematical Overview / 257
( T; e& R* D% \% Zcontents xi
. E/ `# l$ q O0 Y j6.10 AC System Control Modeling / 2595 b) b$ F( `+ s* y* _/ f
6.11 Local Voltage Control / 259
3 [8 m4 S- ]/ }, R8 H6.12 Modeling of Transmission Lines and Transformers / 2599 L- y o; |- w' M H
6.12.1 Transmission Line Flow Equations / 259/ y. h. C& s6 R# O; ~- r* u
6.12.2 Transformer Flow Equations / 2600 j( a2 _, M& R. N8 Y; T1 L, X& _
6.13 HVDC links / 261
* w& X7 E& I0 a0 Q$ @& U1 T6.13.1 Modeling of HVDC Converters U& u& Y; l- N1 a3 z4 B* m
and FACT Devices / 264
6 g+ ]* J3 J+ R: X6.13.2 Definition of Angular Relationships in9 R$ o3 y g2 o/ T! ?
HVDC Converters / 264
4 r7 y1 F1 o# @" }) ?, g$ X7 C6.13.3 Power Equations for a Six-Pole HVDC
1 N1 @9 H! i7 |0 y1 E9 g: k: J! m2 oConverter / 2645 L8 r- u- C Z' A( k r- x
6.14 Brief Review of Jacobian Matrix Processing / 267
2 ?3 E0 U6 @% x5 k) a0 Y2 E3 D$ V& H! w6.15 Example 6A: AC Power Flow Case / 269+ S) Z) r1 s/ L8 ]) l3 g
6.16 The Decoupled Power Flow / 271
& s* k, d2 B9 I6.17 The Gauss–Seidel Method / 275
& u9 V5 B' g2 B5 W6.18 The “DC” or Linear Power Flow / 277# G: Q' z" C: s2 K9 [5 p
6.18.1 DC Power Flow Calculation / 277
" `' W8 I5 l* K1 l. m9 a1 F$ A6.18.2 Example 6B: DC Power Flow Example on the7 }5 \/ ?" C0 S: y4 P0 S5 h
Six-Bus Sample System / 278; s5 V. q! O% X# ]0 X' w# w
6.19 Unified Eliminated Variable Hvdc Method / 278: N- s* d8 \- o& D, `. r! Q, i/ z
6.19.1 Changes to Jacobian Matrix Reduced / 279
7 P& h. U9 H# x- n6 h/ ?0 s6.19.2 Control Modes / 280
$ M+ J$ i8 G6 }0 `9 x- P1 Q6.19.3 Analytical Elimination / 2805 g' ~$ y' X9 a7 p& T6 F4 W/ f
6.19.4 Control Mode Switching / 2832 O: v V" J+ z* Z% t) ?$ {2 d4 ^
6.19.5 Bipolar and 12-Pulse Converters / 283
g, B* w% Z, j( _' V7 i6.20 Transmission Losses / 284
( |* p; _% r2 O; U& Y9 a1 G6.20.1 A Two-Generator System Example / 284* R/ ~1 R! V' Z @1 k, O/ @
6.20.2 Coordination Equations, Incremental Losses,
6 y" y" b( U; m1 W7 pand Penalty Factors / 286
. K% Q( d' s, Z4 y) J6.21 Discussion of Reference Bus Penalty Factors / 288
/ ~6 E# @3 s5 h# w+ m" v6.22 Bus Penalty Factors Direct from the AC Power Flow / 289
/ M# ? e! k+ J$ Q4 y2 J+ c# [4 g; s$ @PROBLEMS / 2914 }2 z. n- Y& Z; X" W8 V1 p. w
7 Power System Security 296' B" b* Z& P% j4 S& Z5 b, U8 x
7.1 Introduction / 296
8 S0 R1 Q8 A% d3 U, D5 H7.2 Factors Affecting Power System Security / 301: x1 h) C) {) F- C
7.3 Contingency Analysis: Detection of Network Problems / 301
( r4 ]4 ^3 m; t7.3.1 Generation Outages / 301" I/ P) U/ M& H9 W% ^$ T
7.3.2 Transmission Outages / 302. f4 @* e. @% {& |
xii contents- y* p$ e" e: }% J7 q2 k
7.4 An Overview of Security Analysis / 306
9 ~" G! D, A: _5 o; X$ \1 H7.4.1 Linear Sensitivity Factors / 3074 x i4 A2 G9 Y, B+ k2 @, p
7.5 Monitoring Power Transactions Using “Flowgates” / 313; h' `& K% F0 A O. O5 |
7.6 Voltage Collapse / 315' {5 s' \6 P: w* X3 k
7.6.1 AC Power Flow Methods / 317
# }5 Q- E1 e6 n% \7.6.2 Contingency Selection / 320: {3 {$ J9 U( V, J
7.6.3 Concentric Relaxation / 323$ @4 O5 T3 r6 H" W* ^; z, a
7.6.4 Bounding / 325
: O* E4 c" y, K4 N. Y7.6.5 Adaptive Localization / 3257 g9 B) a" v* m
APPENDIX 7A AC Power Flow Sample Cases / 327
Z2 g. \; j" w' dAPPENDIX 7B Calculation of Network Sensitivity Factors / 336
K; G1 Y6 B+ G1 q7B.1 Calculation of PTDF Factors / 336
' r, ?: N& o4 x; _7B.2 Calculation of LODF Factors / 339; S, z9 G# }+ D
7B.2.1 Special Cases / 3419 } |& m7 G# p7 ~" s$ l
7B.3 Compensated PTDF Factors / 3432 T( T6 n& M' E6 V2 U9 t
Problems / 343
6 g8 k0 ^" a& @5 {References / 349( L6 U& \- u4 R
8 Optimal Power Flow 350
! i/ y# f) y3 Z8.1 Introduction / 350
0 T+ H( W; k q/ H& y8.2 The Economic Dispatch Formulation / 3516 c' @, G. A+ y8 H' e( _
8.3 The Optimal Power Flow Calculation Combining
% r: o% q/ F p; |# m3 j5 M9 g" OEconomic Dispatch and the Power Flow / 3523 \; k1 Y! H0 y4 H+ W+ e
8.4 Optimal Power Flow Using the DC Power Flow / 354
! N" [% u( I% S8.5 Example 8A: Solution of the DC Power Flow OPF / 356
7 x* [3 f" x; _# A2 {0 D+ y8.6 Example 8B: DCOPF with Transmission Line) L# ^ F5 l) Q- b
Limit Imposed / 361% R! g% _* E$ x) S
8.7 Formal Solution of the DCOPF / 365
a6 U6 c% k8 Y' L1 T2 a8.8 Adding Line Flow Constraints to the Linear0 W' ]. ~0 B. L9 S0 \3 }
Programming Solution / 365. v: d, [! o7 D0 k/ R
8.8.1 Solving the DCOPF Using Quadratic Programming / 367' z) ], X' X7 Q: O
8.9 Solution of the ACOPF / 368: ]& {) ^# K8 \+ ]' _4 B
8.10 Algorithms for Solution of the ACOPF / 369
; M4 d7 ]* {$ i, K: T6 Z! D8.11 Relationship Between LMP, Incremental Losses,1 b3 i2 I: ]1 s3 L+ g ~
and Line Flow Constraints / 376; n5 `, I8 i8 b
8.11.1 Locational Marginal Price at a Bus with No Lines
; t) O( O, `9 k$ M2 h9 sBeing Held at Limit / 3779 [. I) L+ ^: s' E) Q4 R2 t0 D- d
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
% D G/ V$ [+ P ^8 {3 xcontents xiii
" K- w2 u h, }, b7 u& e/ f1 W8.12 Security-Constrained OPF / 382. [ g, o y' _7 q& u. Q: c
8.12.1 Security Constrained OPF Using the DC Power Flow
7 C8 J e( v- G( oand Quadratic Programming / 3840 ?: v& k9 s$ o3 Q% o! B
8.12.2 DC Power Flow / 385 v& i9 Z9 j+ h5 X
8.12.3 Line Flow Limits / 385" g% b# g( p- S
8.12.4 Contingency Limits / 386
+ X8 q% d9 k6 ] B% yAPPENDIX 8A Interior Point Method / 391
1 H; e) T& B: O2 V3 v8 @APPENDIX 8B Data for the 12-Bus System / 393# y8 |. S4 _+ b8 b
APPENDIX 8C Line Flow Sensitivity Factors / 395# ]7 G1 i8 `: f! ?
APPENDIX 8D Linear Sensitivity Analysis of the
$ \5 E, L. s4 TAC Power Flow / 397
4 E. p! X8 k& W$ mPROBLEMS / 3995 s% w" k+ y$ W9 F1 h6 L; J+ h
9 Introduction to State Estimation in Power Systems 403
7 e8 n% v# Y3 _3 C9 X# G( Z9.1 Introduction / 403
; ]) h0 q" |# C" L9 b& J: O9.2 Power System State Estimation / 404
- G9 A$ J. E }2 i+ A9.3 Maximum Likelihood Weighted Least-Squares
& s3 g' b1 r3 u! l& t4 A J. rEstimation / 408
' |. f+ M. p# ], S6 [9.3.1 Introduction / 408. ]+ O6 f7 @2 [# ^7 \* U; Z
9.3.2 Maximum Likelihood Concepts / 410
5 n& n- w$ ?3 `7 \1 v; z# c9.3.3 Matrix Formulation / 4140 b1 C6 A2 k) i/ c. ]! I
9.3.4 An Example of Weighted Least-Squares
9 ?2 ^1 j z* T1 e# K* `State Estimation / 4170 e! Z& Q' n! G4 v& e
9.4 State Estimation of an Ac Network / 421
0 R2 Z- U9 c. H9.4.1 Development of Method / 421
0 b7 g5 v7 d4 i9.4.2 Typical Results of State Estimation on an
: U, h6 v" L+ W( o( b* CAC Network / 424/ X0 F( t- C1 _
9.5 State Estimation by Orthogonal Decomposition / 428
" K; ]( g* I6 _6 N- V7 _9.5.1 The Orthogonal Decomposition Algorithm / 431
; o, p4 f9 T9 Q" _' x( C8 c9.6 An Introduction to Advanced Topics in State Estimation / 435- |$ D/ u; I( O& ~9 g: Y/ ~
9.6.1 Sources of Error in State Estimation / 435
+ h- P$ D. z$ l/ [7 A1 O9.6.2 Detection and Identification of Bad Measurements / 436
s4 o4 F, G: P9.6.3 Estimation of Quantities Not Being Measured / 443
# O2 ^ `5 s [& Z" j8 e9.6.4 Network Observability and Pseudo-measurements / 444
. B! x7 l& x6 E ], x' w# K% }9.7 The Use of Phasor Measurement Units (PMUS) / 447
; b; j3 g6 S$ c6 z+ h* O1 a5 ^9.8 Application of Power Systems State Estimation / 451- y; T5 M; r6 F0 |1 [- c
9.9 Importance of Data Verification and Validation / 454- P* f+ Y' E5 e. r7 K; S
9.10 Power System Control Centers / 4546 ]/ J3 O, c0 e
xiv contents
. i0 n& K# Y. ]( P9 f4 v$ |APPENDIX 9A Derivation of Least-Squares Equations / 4564 S1 c" J! M" y5 Y: @/ ^$ X
9A.1 The Overdetermined Case (Nm > Ns) / 457
9 k% t! `* G( U, C2 H( h, K9A.2 The Fully Determined Case (Nm = Ns) / 462$ g% E9 M0 B) S1 v7 [
9A.3 The Underdetermined Case (Nm < Ns) / 462
( e( o, ^9 x1 Z5 R5 ]3 HPROBLEMS / 4647 S5 B0 K* L) e2 X9 {% Q5 p
10 Control of Generation 468
# w7 g( _0 E. s/ k. E10.1 Introduction / 468* B+ ~/ R' n! q) l
10.2 Generator Model / 470
3 `' y7 f( _! z- Y* o+ E10.3 Load Model / 473
* K; A6 k- J8 S2 B% F. y8 B8 a; K10.4 Prime-Mover Model / 475
1 E- e! H7 t$ N8 @* f) ^* P% _10.5 Governor Model / 476
' V7 f+ |" {) _& {10.6 Tie-Line Model / 4814 ]3 c4 B8 E5 o4 \
10.7 Generation Control / 485
- F$ Q- Y7 L u! x( R10.7.1 Supplementary Control Action / 485( k I2 c5 {- C1 T9 ?5 H1 i
10.7.2 Tie-Line Control / 486- _9 {( M& E1 i- N7 X+ n
10.7.3 Generation Allocation / 489* q4 |1 r2 Z3 n! Q+ ?2 o
10.7.4 Automatic Generation Control (AGC)/ W# T0 N# f' S
Implementation / 491
$ ]5 F5 K; _; Y( z _10.7.5 AGC Features / 4954 C) ?( J& O: i! o
10.7.6 NERC Generation Control Criteria / 496- e. ~- S+ G6 t `4 s( X
PROBLEMS / 497* \3 u6 [$ R+ w3 X: q4 u! W! L
References / 500- g [- [' O- y. ?
11 Interchange, Pooling, Brokers, and Auctions 501& R& n) p. C4 e/ Q) ]
11.1 Introduction / 501
4 \; k" ?0 u2 K11.2 Interchange Contracts / 504, F9 f$ t. ~" r- j7 D
11.2.1 Energy / 504
7 h$ ~, Z5 Q1 y! s# Z11.2.2 Dynamic Energy / 506
( K }5 p: k, s11.2.3 Contingent / 506
3 f0 t t6 F% k! C6 @6 x8 I/ F" c11.2.4 Market Based / 507
) e5 B9 O9 ^7 l4 l% }5 ]9 Y11.2.5 Transmission Use / 508
; A6 }% w N4 V, r. w+ M11.2.6 Reliability / 517$ W! G6 c, u! k
11.3 Energy Interchange between Utilities / 5178 m) v8 m5 B) S+ V0 F, i1 ?( S
11.4 Interutility Economy Energy Evaluation / 521
$ j4 }' F& q) E8 h11.5 Interchange Evaluation with Unit Commitment / 522" }+ {$ o* ^# `9 e( b
11.6 Multiple Utility Interchange Transactions—Wheeling / 523
/ Y2 G7 |# p9 {8 [. U; G& T11.7 Power Pools / 526$ M `( ^: ?' b" ]/ [7 f) |; ^, T( v
contents xv
8 M5 n- H7 k" H11.8 The Energy-Broker System / 529
0 |* N; ]9 {* C11.9 Transmission Capability General Issues / 533; d. B+ F9 K, l0 k z" x
11.10 Available Transfer Capability and Flowgates / 535
- W3 o; Z, a. \2 t9 y, S. O( Z1 O11.10.1 Definitions / 536" e8 G% \6 E& ]
11.10.2 Process / 539# V% z9 x$ _. _0 [0 M
11.10.3 Calculation ATC Methodology / 540
2 H2 o) K$ L( L11.11 Security Constrained Unit Commitment (SCUC) / 550
: b) ?% O0 l6 Y, p( l11.11.1 Loads and Generation in a Spot Market Auction / 550
: Z% y3 n# T0 y4 W3 p11.11.2 Shape of the Two Functions / 5529 ~9 p' p( o! G; r. y$ r" k/ T
11.11.3 Meaning of the Lagrange Multipliers / 553
6 T. r' P( B* O% E9 j8 }! E11.11.4 The Day-Ahead Market Dispatch / 554" ~& H5 R/ ?, R( l. F
11.12 Auction Emulation using Network LP / 555. E- d, e6 u5 t" ?. d6 a {* B1 k
11.13 Sealed Bid Discrete Auctions / 5550 }# a; h" j; [: s3 w1 x- P
PROBLEMS / 560; z) ?/ Q: K+ ]* o1 S( F7 m) X
12 Short-Term Demand Forecasting 566* k( z! \! C2 k. ~
12.1 Perspective / 566
' w4 X7 q' j1 d l) w9 }12.2 Analytic Methods / 569
1 o4 q: u- L* C, n/ F12.3 Demand Models / 571
% j! g9 `1 b1 o+ T6 A) {12.4 Commodity Price Forecasting / 572; u( ^6 Q# f p3 w
12.5 Forecasting Errors / 573
; k; l3 v2 B( ^( g9 C3 Z# ~12.6 System Identification / 5737 I X$ N0 w7 c8 ^2 H
12.7 Econometric Models / 574+ Y; p( n/ {: }8 h
12.7.1 Linear Environmental Model / 574
9 ?" {- m; I: k+ H12.7.2 Weather-Sensitive Models / 576
6 {! j2 L7 n9 o4 U1 M2 o. Z0 h1 ^12.8 Time Series / 578, } ]8 o8 m/ I6 |5 f
12.8.1 Time Series Models Seasonal Component / 578
2 s* w+ y0 r, j; {3 c7 d$ G- k12.8.2 Auto-Regressive (AR) / 580: g1 c" P$ A i; p# g, P6 O
12.8.3 Moving Average (MA) / 581
# Y- J# H- z9 Q8 H( j9 n) L2 [9 A+ c12.8.4 Auto-Regressive Moving Average (ARMA):2 H* k$ \7 ?* [ m z0 j9 W: X
Box-Jenkins / 582
4 r9 X+ a9 o4 O% c& v" x12.8.5 Auto-Regressive Integrated Moving-Average& Q0 r+ W5 w2 k" }
(ARIMA): Box-Jenkins / 584
2 Z( p: w6 i! S/ e( F1 i12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585& M) E }6 J' [; \
12.9 Time Series Model Development / 585
/ v7 S1 x) g) X( q12.9.1 Base Demand Models / 586/ Z# L0 b( o1 p# F/ {3 T9 _
12.9.2 Trend Models / 586( D2 b' n- P0 K- H" a' {
12.9.3 Linear Regression Method / 5867 N1 \$ x% D" [! w% I
xvi contents, e- V E- {2 Y: ?) Q# p# J
12.9.4 Seasonal Models / 588
) _( u0 A5 h! b4 D' A/ a12.9.5 Stationarity / 588
. c, L* o5 W3 R7 D9 ^* A- s; ?12.9.6 WLS Estimation Process / 590
5 V/ M# _0 x0 l' N/ s* A2 g12.9.7 Order and Variance Estimation / 591
% b5 Y. i% _4 y1 t12.9.8 Yule-Walker Equations / 592
% a# B1 C0 A' W. _* B( i12.9.9 Durbin-Levinson Algorithm / 5953 {& A. G1 {1 E- L3 c, Y) [/ M
12.9.10 Innovations Estimation for MA and ARMA
& b; y. W8 h4 U+ AProcesses / 598
) I1 N5 }0 v) t) i: i. m6 k6 A2 ?12.9.11 ARIMA Overall Process / 600
1 G- d6 v: b! z: X12.10 Artificial Neural Networks / 6032 }9 ]; C% e- l5 \" b) E9 b, r
12.10.1 Introduction to Artificial Neural Networks / 604# \; N' l% ^+ A9 I3 P
12.10.2 Artificial Neurons / 605# [8 ~2 Y$ M% t/ {9 w5 s+ ]
12.10.3 Neural network applications / 606( V* e- j' p1 S
12.10.4 Hopfield Neural Networks / 606
5 E2 H. t/ f# `& W: E1 G12.10.5 Feed-Forward Networks / 607
- r) ]) ?: M# O( B! X12.10.6 Back-Propagation Algorithm / 610! n$ n, |* Y$ S( n6 R# b
12.10.7 Interior Point Linear Programming Algorithms / 613( a7 [0 N, N, W" K2 j5 q; f
12.11 Model Integration / 6148 v; `0 n" m/ g1 e& [5 N
12.12 Demand Prediction / 614
0 j2 l7 V; R% T, A. X: P12.12.1 Hourly System Demand Forecasts / 6157 n& r. o9 w0 |# J9 G9 L B6 g9 L' G8 }9 T+ F
12.12.2 One-Step Ahead Forecasts / 6153 L/ p$ Y( |0 F- _
12.12.3 Hourly Bus Demand Forecasts / 616 F5 j: s2 }0 j% R# D$ T
12.13 Conclusion / 616
8 q' k% ^' V) z# b$ r8 |PROBLEMS / 617 |
|