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第三版目录。1 U9 u4 v; Y+ m6 k4 n1 x
1 Introduction 1
% p" q$ c: R& ~9 t/ G' ^1.1 Purpose of the Course / 1' \( I$ Q& b$ z Q/ [3 E. P
1.2 Course Scope / 2
1 G: w8 r( W3 Y/ L ]5 }- G1.3 Economic Importance / 2
6 Q; d, h1 T5 k t3 N. |( K1.4 Deregulation: Vertical to Horizontal / 3
& p8 |8 d0 X; c6 N. Y' }& P1.5 Problems: New and Old / 3
4 \* u: c4 O% @# O( w1.6 Characteristics of Steam Units / 6
! W. i8 J! M* C! J; ^* f1.6.1 Variations in Steam Unit Characteristics / 10- g1 A4 Y7 @( i7 y# C
1.6.2 Combined Cycle Units / 13
6 H6 G4 D B: W' p8 J2 |7 T; L1.6.3 Cogeneration Plants / 141 U/ a6 n; ]+ R
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17! w4 @1 p: ?/ ], Q8 m6 Q4 G
1.6.5 Hydroelectric Units / 18
; }3 O% O+ z8 Y3 i) {1.6.6 Energy Storage / 21) Q1 z$ R& B. S
1.7 Renewable Energy / 22/ k8 T4 i+ P' s& P# [: S
1.7.1 Wind Power / 23+ j. [; u6 j9 z: K! H- y) V
1.7.2 Cut-In Speed / 23) e0 ~! z& m* o0 ?: |% Y1 t
1.7.3 Rated Output Power and Rated Output Wind Speed / 247 ^; v: V3 F- E% _5 f/ B9 {6 j8 B3 F
1.7.4 Cut-Out Speed / 24" m6 T; M7 O2 T. c% Z# M
1.7.5 Wind Turbine Efficiency or Power Coefficient / 24
0 d' h1 h9 m; E$ p# b, Y- u1.7.6 Solar Power / 25
0 j1 [, h1 u" L+ i, {APPENDIX 1A Typical Generation Data / 26/ U. I) I) p: o( r& c9 r" {2 f
APPENDIX 1B Fossil Fuel Prices / 28
& q5 n4 b, G" d6 x+ mAPPENDIX 1C Unit Statistics / 29/ Y, F2 M$ H. L* R. T( w' ~7 m
CONTENTS
* e- K8 w2 d9 T% eviii contents1 N# o7 D2 y$ U. }& e/ I3 z
References for Generation Systems / 31
, f$ {: v, M( aFurther Reading / 31
7 \! J; v* n, G9 H$ C0 j8 m2 Industrial Organization, Managerial Economics, and Finance 35! N( K2 u U: F8 ^
2.1 Introduction / 35
' M& b* {* N0 [* B# F, D2.2 Business Environments / 36
; R& _- n/ l, M+ Y" T2.2.1 Regulated Environment / 375 n* c* c' L2 X8 O& U
2.2.2 Competitive Market Environment / 38# u0 A& q5 U. b( S& Y6 Z. ?
2.3 Theory of the Firm / 40
% M+ Z, G- B+ W2 j$ z7 p. G. P& y$ I2.4 Competitive Market Solutions / 42+ s. |# r5 b& Z( G8 W
2.5 Supplier Solutions / 45
+ L2 m; Y& x' r1 i/ }- z3 g2.5.1 Supplier Costs / 46
8 j5 u9 c) b/ M2.5.2 Individual Supplier Curves / 46
" B& K& W/ f! _2.5.3 Competitive Environments / 471 D9 M6 i) d; g7 T' I
2.5.4 Imperfect Competition / 51- ~' L9 T6 d1 J9 }2 J, C" I6 D7 w
2.5.5 Other Factors / 52
8 d0 ^. d q/ T1 q$ q9 H2 ]2.6 Cost of Electric Energy Production / 53: I# j! s- s- Y5 A3 L2 r
2.7 Evolving Markets / 549 h. _. [' t& }- {; y% d5 p! F6 B
2.7.1 Energy Flow Diagram / 57, Z5 \3 r% J) ~9 |
2.8 Multiple Company Environments / 58' q; H1 Z0 R$ m( J" I6 ?& z
2.8.1 Leontief Model: Input–Output Economics / 58
$ @1 `' B6 Z/ u$ A2 w6 _3 u2.8.2 Scarce Fuel Resources / 60
' ~# ^9 \/ A& X2.9 Uncertainty and Reliability / 61
$ X! `9 o( K8 ^PROBLEMS / 61
3 S+ F+ E# _7 `0 CReference / 62$ c6 L; F0 I" Y
3 Economic Dispatch of Thermal Units and Methods of Solution 63
; V! \" G7 b5 [1 q3 Y0 G3.1 The Economic Dispatch Problem / 63
) b( L& j& I; Y' P1 D& A3.2 Economic Dispatch with Piecewise Linear Cost Functions / 685 ?3 h6 @7 P9 C! W
3.3 LP Method / 69
; o& ?' v( \5 q3.3.1 Piecewise Linear Cost Functions / 699 C2 F1 x7 g% p3 S& r6 J
3.3.2 Economic Dispatch with LP / 71
( ^5 ~7 R8 }2 _' C; w3.4 The Lambda Iteration Method / 73' q! V) l' i0 l+ { o( w7 d5 O1 l
3.5 Economic Dispatch Via Binary Search / 76
" G& V7 A, T; N) ]6 H3.6 Economic Dispatch Using Dynamic Programming / 78. V3 L0 W( v5 L4 q+ a* H
3.7 Composite Generation Production Cost Function / 815 z; r" ]3 \9 b: \* R7 _3 }( o0 `0 R
3.8 Base Point and Participation Factors / 85
& U6 H+ _' d) X, F) ~8 U3.9 Thermal System Dispatching with Network Losses4 x: e1 x6 T9 X I
Considered / 880 v6 c. ?) Q B" S% c8 j/ f4 @
contents ix
( j/ Q0 L1 p7 L# S$ ^5 I$ \$ r3.10 The Concept of Locational Marginal Price (LMP) / 92& F* ^* ?6 a7 Z3 [
3.11 Auction Mechanisms / 951 F, C8 y7 g3 E. E: b
3.11.1 PJM Incremental Price Auction as a
$ G: v0 h. F3 a& }; n/ IGraphical Solution / 95# h3 M. j, u/ f, S2 ~% i' H
3.11.2 Auction Theory Introduction / 98
6 A' a" M1 y* Q3.11.3 Auction Mechanisms / 100! X$ W1 y) J! p- R, V
3.11.4 English (First-Price Open-Cry = Ascending) / 101
9 _% \1 v' h/ j& |3.11.5 Dutch (Descending) / 103" E8 T$ V- g1 f. p" m ^* Q* l
3.11.6 First-Price Sealed Bid / 104( }& w) {5 l! M7 n2 o, H
3.11.7 Vickrey (Second-Price Sealed Bid) / 105
& [8 H% C# _1 O' L7 U3.11.8 All Pay (e.g., Lobbying Activity) / 1058 v7 [/ V3 q$ v
APPENDIX 3A Optimization Within Constraints / 106
" \8 D" c& l. lAPPENDIX 3B Linear Programming (LP) / 117' V) R7 ^ J$ G$ S
APPENDIX 3C Non-Linear Programming / 128; a& F. k8 [6 P$ Q4 s
APPENDIX 3D Dynamic Programming (DP) / 128
: ]+ V" _! l: [9 c3 }4 t- E7 ?% Y$ I! o% TAPPENDIX 3E Convex Optimization / 1352 W; |: |! g% T* o$ s
PROBLEMS / 1389 c0 K/ b( H" p9 G
References / 146$ Q% k) n% K) p1 {
4 Unit Commitment 147
+ k8 I3 d! w* O. w" T; M# ~! K! s4.1 Introduction / 147* W5 W' U8 N5 E- T
4.1.1 Economic Dispatch versus Unit Commitment / 147
: ]2 x) _. W7 \% t4.1.2 Constraints in Unit Commitment / 152
D. w% H; U3 p7 y4.1.3 Spinning Reserve / 152* |6 ^, f) x7 d, F6 h5 T
4.1.4 Thermal Unit Constraints / 153+ U+ I: S. L6 Z
4.1.5 Other Constraints / 155% J3 ~- w: y. y$ g( v
4.2 Unit Commitment Solution Methods / 155
* C. M6 L: @; U7 D. f4.2.1 Priority-List Methods / 156! K" p3 B# r, u7 p
4.2.2 Lagrange Relaxation Solution / 157" F7 |6 k7 [4 P$ O
4.2.3 Mixed Integer Linear Programming / 1660 f' l4 l/ z8 `6 |
4.3 Security-Constrained Unit Commitment (SCUC) / 167
" P7 C* i* O6 P, b# i+ {4 H& y4.4 Daily Auctions Using a Unit Commitment / 167, E( s. D5 x1 S; c$ w; ^9 P
APPENDIX 4A Dual Optimization on a Nonconvex
' b& Q+ O& l- N- H H( N# J1 x6 |Problem / 167
- s6 V/ a% r. X, S& ]APPENDIX 4B Dynamic-Programming Solution to: A3 B1 X& C8 {& d
Unit Commitment / 173
( r& B, @7 E& b8 l2 E# r4B.1 Introduction / 173
* a3 B9 z" x! b5 i% b) h' l/ c7 U4B.2 Forward DP Approach / 174
/ r- g/ D+ [( e5 fPROBLEMS / 182 z5 z$ _) Z; x) k9 ]' @4 C% v
x contents; _) G; H( f6 o- L$ {2 o& Z
5 Generation with Limited Energy Supply 187/ R( }: v; t" P) {3 M9 B
5.1 Introduction / 187/ \5 s( X4 A9 K" {
5.2 Fuel Scheduling / 188
9 u, Z7 Q3 `1 W2 E6 F5 Q5.3 Take-or-Pay Fuel Supply Contract / 188
_% T% [4 @; f5.4 Complex Take-or-Pay Fuel Supply Models / 194, M' L) |) F# Z
5.4.1 Hard Limits and Slack Variables / 1943 _( `) N" }5 j2 J3 n
5.5 Fuel Scheduling by Linear Programming / 1950 m% P+ b* t- y; d4 |0 }- l1 B1 L
5.6 Introduction to Hydrothermal Coordination / 202
, t; T7 u5 _& V @7 W5.6.1 Long-Range Hydro-Scheduling / 203
0 {! J3 k" I3 x+ k& D% f5.6.2 Short-Range Hydro-Scheduling / 204
1 n: F0 H8 ?; p: K R) P( m% h5.7 Hydroelectric Plant Models / 204
7 ?# y* F, Z; g) d( ~$ c1 |5.8 Scheduling Problems / 207
4 }+ L& D# N2 D; N* Q/ d- |5 @/ e! @5.8.1 Types of Scheduling Problems / 2076 h, }$ @6 B9 a6 |3 M9 C
5.8.2 Scheduling Energy / 207" k) |+ G# G7 b0 b8 s
5.9 The Hydrothermal Scheduling Problem / 211. f) p& {4 F! V! Y* S
5.9.1 Hydro-Scheduling with Storage Limitations / 2115 h8 g+ D$ c5 E2 r
5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216
. }& o% N, v* p7 o5 k, o2 b/ T5.9.3 Pumped-Storage Hydroplants / 218
7 g- ~5 i2 c- F/ J5.10 Hydro-Scheduling using Linear Programming / 222$ Y( h3 h) a% i
APPENDIX 5A Dynamic-Programming Solution to hydrothermal3 W/ c6 e$ r, Y" Q+ \7 X( |6 v1 |6 |
Scheduling / 225# R5 b( n' ]" w3 R1 z4 [# O. B
5.A.1 Dynamic Programming Example / 2274 |( s x% V2 U S+ E8 C
5.A.1.1 Procedure / 2281 B! @6 @2 {+ D
5.A.1.2 Extension to Other Cases / 231! J7 O( R+ r5 q0 R& [/ j
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant* D* @" u7 N! c
Problem / 232
% `$ n' a* K/ p5 }3 n v9 }PROBLEMS / 234
7 E# H! B! G( k0 j6 m9 L* a6 Transmission System Effects 243
1 _' f. v5 g+ g6.1 Introduction / 243
- _; ]& S' X' K0 ]6.2 Conversion of Equipment Data to Bus and Branch Data / 247# O! e" L/ {% k+ a, b& a( X7 N
6.3 Substation Bus Processing / 248* G. |+ c" B9 f; O
6.4 Equipment Modeling / 2480 y' B! ~ J; z2 _- R% D
6.5 Dispatcher Power Flow for Operational Planning / 251$ I. I0 s% E* y
6.6 Conservation of Energy (Tellegen’s Theorem) / 252# ~& N5 V+ M& n- h( n& a" g
6.7 Existing Power Flow Techniques / 2535 ?5 G/ }/ k( I1 Z# a9 c+ _2 {8 J! r
6.8 The Newton–Raphson Method Using the Augmented
7 k% {% |* I: c0 l, r* rJacobian Matrix / 254/ t# _5 Q# f9 z9 \1 L! _5 ]7 I
6.8.1 Power Flow Statement / 254
* U: \4 }3 f7 W+ \% S/ U6.9 Mathematical Overview / 2578 a( ]# O$ ^3 a0 `/ M4 Y5 Q% d- H
contents xi
7 l% ?1 R* w4 a& l) c& B0 T6.10 AC System Control Modeling / 259* E* i$ i6 J3 k! n( y
6.11 Local Voltage Control / 259
% H- i% w+ }# @. A- C; }5 O' L4 b, U6.12 Modeling of Transmission Lines and Transformers / 2594 F+ M: B( q& W1 [" r9 ~0 r3 [
6.12.1 Transmission Line Flow Equations / 259
& \2 p3 l- E( D& s x" ~6.12.2 Transformer Flow Equations / 260 E$ u3 |2 J1 Z; a F: W$ _
6.13 HVDC links / 2619 ?4 R" ^) s. C1 C& t
6.13.1 Modeling of HVDC Converters
- r+ M+ M# W9 S2 Dand FACT Devices / 264
7 l- A z: x. ]" ]6.13.2 Definition of Angular Relationships in) }' w- g% J0 h1 W4 I
HVDC Converters / 264: v( {. C( m) e
6.13.3 Power Equations for a Six-Pole HVDC
* \ S1 r. E6 X+ C8 CConverter / 264
$ f* N6 a! O: g" G6 v- _6.14 Brief Review of Jacobian Matrix Processing / 267
9 @" |, X: u4 X" \1 v* ^- I8 c' K6.15 Example 6A: AC Power Flow Case / 269
# _; y: O1 e2 {. T$ G1 a6.16 The Decoupled Power Flow / 271" H5 q5 L6 \! m1 Y/ g# ?
6.17 The Gauss–Seidel Method / 275
3 P$ ?1 P3 Y* Q3 _7 f& D/ e6.18 The “DC” or Linear Power Flow / 277
0 o* f1 S' ^* C9 t% h9 i) }, b8 x# h6.18.1 DC Power Flow Calculation / 2772 O; s( M" g! j6 c" }
6.18.2 Example 6B: DC Power Flow Example on the3 m- }% _" t1 [. T9 y
Six-Bus Sample System / 278
* w& {# x6 S3 T4 [! N+ {4 z6.19 Unified Eliminated Variable Hvdc Method / 2785 L5 H: y# L; n1 f: a( E( B
6.19.1 Changes to Jacobian Matrix Reduced / 279
X$ [5 K# `5 y/ A7 Y" `+ ]9 a) {6.19.2 Control Modes / 280
H; U% [8 e, g& T6.19.3 Analytical Elimination / 2808 t9 P$ f3 F8 E
6.19.4 Control Mode Switching / 283" x8 i/ l$ b, { Z. K1 O$ ~( e
6.19.5 Bipolar and 12-Pulse Converters / 283+ U; w& o U9 y
6.20 Transmission Losses / 284
4 f1 i, n5 `- s+ c/ x6.20.1 A Two-Generator System Example / 2843 x! B, {, k0 |" A
6.20.2 Coordination Equations, Incremental Losses,
r; ? ]6 m5 w' l2 o# H7 z+ {and Penalty Factors / 286
0 h1 E0 [6 X" z- `6.21 Discussion of Reference Bus Penalty Factors / 2880 v; X" m# E. T+ G5 i. @* `
6.22 Bus Penalty Factors Direct from the AC Power Flow / 289+ }' i- y( l9 d, X* p; o) N: p: {
PROBLEMS / 291% I. s9 ?/ g5 M% l
7 Power System Security 296
2 C- k* V$ z. y7 }0 j7.1 Introduction / 296
$ ^; I" E( H4 T# R7.2 Factors Affecting Power System Security / 3017 W/ T8 m3 X, V8 O# o8 z
7.3 Contingency Analysis: Detection of Network Problems / 301
0 } d v; Z' B& E b, ~3 r7.3.1 Generation Outages / 3011 J* U$ P/ N. x4 d5 a
7.3.2 Transmission Outages / 3025 B# C: o- D- n+ j3 U) ?
xii contents/ b+ p; }- [+ h% C
7.4 An Overview of Security Analysis / 306+ l L8 Z- v2 u2 p+ j1 [/ F; _
7.4.1 Linear Sensitivity Factors / 307
- E- R# i) B% [/ ?0 S1 A. c7.5 Monitoring Power Transactions Using “Flowgates” / 313
( h- c# d }+ H& |2 F- R. o7.6 Voltage Collapse / 315& x+ w9 B+ H- h x- w
7.6.1 AC Power Flow Methods / 317$ L/ i) x0 e/ F; @1 J
7.6.2 Contingency Selection / 320
q4 `$ j! R! l6 z7.6.3 Concentric Relaxation / 323. `" a W0 o8 _. C
7.6.4 Bounding / 325) H* ?9 {. _: }, I( v# ]' T
7.6.5 Adaptive Localization / 325
* o5 P) Z1 m5 S- ?/ E% N" t- nAPPENDIX 7A AC Power Flow Sample Cases / 327" _. r9 T4 W* K/ {+ k
APPENDIX 7B Calculation of Network Sensitivity Factors / 3363 O7 y% R! e2 |& `
7B.1 Calculation of PTDF Factors / 336
0 {" P% N ~- u( P1 j# P0 t, L7B.2 Calculation of LODF Factors / 3394 S; ]6 F. V4 M: T3 g
7B.2.1 Special Cases / 341$ B# T, f! X$ M7 Y
7B.3 Compensated PTDF Factors / 3435 y/ s% o8 S% |) z8 J' [3 h
Problems / 343
) z* m/ K5 {% r/ h. h8 IReferences / 349
3 V' I6 I' B, Q2 u; u4 w5 e8 Optimal Power Flow 350
; t2 ?% R) d2 ~8.1 Introduction / 350
0 W/ M; _# g3 F( O8.2 The Economic Dispatch Formulation / 351
/ j* L* q0 n$ Q8.3 The Optimal Power Flow Calculation Combining5 D8 i6 X1 K0 K+ H0 A& e4 b+ e" a
Economic Dispatch and the Power Flow / 352
# e3 j* v X6 `$ C+ t8.4 Optimal Power Flow Using the DC Power Flow / 354' X. j4 i1 A8 q0 A$ Z
8.5 Example 8A: Solution of the DC Power Flow OPF / 356
9 @4 Z! p" m; J5 h5 S8.6 Example 8B: DCOPF with Transmission Line. X5 @. Y$ F5 h @+ g! [
Limit Imposed / 361
& t' O D- j* N8.7 Formal Solution of the DCOPF / 365& q/ R+ Q+ _' s! w3 _/ o
8.8 Adding Line Flow Constraints to the Linear/ P7 X2 \2 P2 S4 j! m, R; S7 n
Programming Solution / 365- o$ k% r% k9 g; b- g! J
8.8.1 Solving the DCOPF Using Quadratic Programming / 367
9 w( E; a! d$ z' e# E( [8.9 Solution of the ACOPF / 368
4 E8 X0 y7 X6 y2 @; q% ^8.10 Algorithms for Solution of the ACOPF / 369
2 X0 p: o, J/ d. [) N/ d0 `! z8.11 Relationship Between LMP, Incremental Losses,
% v$ \# C, |# F9 U0 @6 oand Line Flow Constraints / 376! _4 }4 y* h8 H1 ?' F9 F/ q# A, c
8.11.1 Locational Marginal Price at a Bus with No Lines" K9 A9 x2 M" d5 I4 n$ L
Being Held at Limit / 377* j/ x, m+ P5 k7 ?; v8 P$ H
8.11.2 Locational Marginal Price with a Line Held at its Limit / 378
3 k2 E }: s* A4 M/ H1 z9 n vcontents xiii8 W0 X) c2 O! H/ s1 z
8.12 Security-Constrained OPF / 382) T* @$ o9 u i& D7 T3 R
8.12.1 Security Constrained OPF Using the DC Power Flow3 P0 h' v9 R2 D- n- d5 f
and Quadratic Programming / 384. n% t9 }6 O" J3 m3 I. `" M
8.12.2 DC Power Flow / 385
. i! N1 Y# m) X* f% }8.12.3 Line Flow Limits / 385! x( x9 R v" K- W6 o' h
8.12.4 Contingency Limits / 3867 L% }- i8 G* l2 @# X
APPENDIX 8A Interior Point Method / 391
7 O6 O2 t- E2 z M: y, lAPPENDIX 8B Data for the 12-Bus System / 393& j9 ?, Q3 y* R
APPENDIX 8C Line Flow Sensitivity Factors / 395
6 J3 L* M: q$ n2 \+ a( M) yAPPENDIX 8D Linear Sensitivity Analysis of the# f4 x; n) f4 K7 {# i
AC Power Flow / 397
: Z7 O/ ?& m& c$ s: jPROBLEMS / 3996 D) d7 a5 \) p
9 Introduction to State Estimation in Power Systems 4035 s3 \+ z# }% C, N2 V$ Q
9.1 Introduction / 403
8 K* e, j) W8 i+ p) s/ I" t) n9.2 Power System State Estimation / 404% T {$ ], w' ~* v4 B9 Q {
9.3 Maximum Likelihood Weighted Least-Squares$ g/ \4 F {( d! h/ C" H
Estimation / 408
* K- I6 x( L: r, d5 n9.3.1 Introduction / 408
8 S! B' `; p! J# j( v( ]9 F9.3.2 Maximum Likelihood Concepts / 410
* z' P6 k' z$ f; m9.3.3 Matrix Formulation / 414
5 L4 N# J3 A; T+ v9.3.4 An Example of Weighted Least-Squares+ A* ]+ v/ Q9 E
State Estimation / 417& C( e- D# f4 E* L3 `
9.4 State Estimation of an Ac Network / 421
. l; a/ a, r' _, A5 V9.4.1 Development of Method / 421/ `3 s$ a6 P& |, F6 j. o& d; t+ k
9.4.2 Typical Results of State Estimation on an9 D' y; B* z. H: s
AC Network / 424
- I @, o$ ]; o1 ^0 [9.5 State Estimation by Orthogonal Decomposition / 428 l0 m: Q4 {( G7 L! x
9.5.1 The Orthogonal Decomposition Algorithm / 431
7 g7 t" ^: a; X8 d9.6 An Introduction to Advanced Topics in State Estimation / 435
) P2 ?! d/ q. G- g6 Z( `9 M1 Q9.6.1 Sources of Error in State Estimation / 435& ?" R$ i' G7 b5 B# h6 j
9.6.2 Detection and Identification of Bad Measurements / 436& r+ E# D% t/ h: p0 H) _
9.6.3 Estimation of Quantities Not Being Measured / 443# c+ \5 J9 A- F# w. D9 o& H( s; d$ e! d+ q
9.6.4 Network Observability and Pseudo-measurements / 444& e+ P8 `* f/ V
9.7 The Use of Phasor Measurement Units (PMUS) / 447/ a5 q4 Q% r( S5 x% H
9.8 Application of Power Systems State Estimation / 4519 T* }2 B8 d8 V8 \* B7 n
9.9 Importance of Data Verification and Validation / 454
% W5 T6 p$ v, N: Q9.10 Power System Control Centers / 454: u) g8 Q5 v( u4 Z |
xiv contents+ k! e+ ~$ }: `; a, i$ v
APPENDIX 9A Derivation of Least-Squares Equations / 456* t. J- B, N, y1 e$ D2 S+ |% N8 {
9A.1 The Overdetermined Case (Nm > Ns) / 457
1 {" m7 G1 b: c' `5 _) ~7 |9A.2 The Fully Determined Case (Nm = Ns) / 462
" W+ Y9 B d9 t: c1 V6 a9A.3 The Underdetermined Case (Nm < Ns) / 462" s" A. {0 E+ R6 A1 `3 G* u
PROBLEMS / 464
, x7 F( T! i9 h" R' [* z10 Control of Generation 468
) b f' Y$ r: i2 W0 N10.1 Introduction / 468
" t( B4 }: c! I10.2 Generator Model / 4700 Q5 ]1 [2 ^: t
10.3 Load Model / 473
2 W% F- d, S; g. O' Q10.4 Prime-Mover Model / 475
: M& i5 J4 i& E; e" m10.5 Governor Model / 4760 w1 \) z: c( g& p- l( Y
10.6 Tie-Line Model / 4818 `. s% h. A5 ~" R; c8 `
10.7 Generation Control / 485
: _' `1 X: p; ?9 r2 c& j10.7.1 Supplementary Control Action / 485
& P i4 i6 j9 O' T7 f10.7.2 Tie-Line Control / 486
1 B) c/ A; z3 f; g0 B: X; E10.7.3 Generation Allocation / 489+ a8 G7 D* R& l' P2 m
10.7.4 Automatic Generation Control (AGC)6 A9 W* R- C$ X, L
Implementation / 4914 m2 D1 A8 R6 ]6 G8 I; F+ i
10.7.5 AGC Features / 495: e/ ~: P, e3 a, O
10.7.6 NERC Generation Control Criteria / 496. y$ o! d4 Q% \9 t8 V
PROBLEMS / 497
- m0 f/ ?; @0 G: d, U; I) _References / 500
' c; p7 ]0 O& E! v% b$ ]! L11 Interchange, Pooling, Brokers, and Auctions 501* | Q8 J# L i2 Z2 d1 |
11.1 Introduction / 501
9 q+ F# c G K9 n11.2 Interchange Contracts / 504* G$ l6 H8 f$ f F
11.2.1 Energy / 504
7 ?7 T0 E3 M7 }: e1 d. o% W X' {11.2.2 Dynamic Energy / 506! g) W, O: F) r: T# ^7 H
11.2.3 Contingent / 5062 ~% U) T# X3 P; ~$ } \5 I8 d
11.2.4 Market Based / 507
' Z/ ], K" F9 ^- `/ ~5 F6 c# ?7 Y11.2.5 Transmission Use / 508% ^$ M% {5 F$ a9 w/ f6 y: O' Y
11.2.6 Reliability / 5179 h4 i8 L2 M1 K: `7 O+ T+ c: t
11.3 Energy Interchange between Utilities / 5172 b" ^- j, v- D) s4 {$ Q; o- }% O
11.4 Interutility Economy Energy Evaluation / 5211 U4 V6 ~8 \) ^- y# @+ F% K
11.5 Interchange Evaluation with Unit Commitment / 5220 [* @ H3 F7 u
11.6 Multiple Utility Interchange Transactions—Wheeling / 523
. z/ [# E$ N1 L6 B: ^% |11.7 Power Pools / 526
- |+ M3 H- u. i( ?" S0 Wcontents xv
' n: ^3 R. B8 Q7 i I' j. D( N/ \8 o11.8 The Energy-Broker System / 5291 h/ u) _. B! w. X3 x$ ?
11.9 Transmission Capability General Issues / 533/ I: b& ]2 k. {) Q+ Q5 J3 ^
11.10 Available Transfer Capability and Flowgates / 5354 _4 R* m8 _. K2 Q) v' F& T3 t
11.10.1 Definitions / 536
% G; l$ h1 J( e( i/ k11.10.2 Process / 539- ]; t" n8 ~( Y7 ~2 M
11.10.3 Calculation ATC Methodology / 540
0 O. F2 p5 D8 f, Q# a# l11.11 Security Constrained Unit Commitment (SCUC) / 550$ [1 Y/ ?! r9 q9 u, G- t
11.11.1 Loads and Generation in a Spot Market Auction / 5509 Z/ d& i2 t, F: k
11.11.2 Shape of the Two Functions / 5524 X& U% z) u2 a) {& A# g1 s G
11.11.3 Meaning of the Lagrange Multipliers / 5538 T. f5 W( p5 F0 o. W
11.11.4 The Day-Ahead Market Dispatch / 5540 D9 [. g) o, d9 K e
11.12 Auction Emulation using Network LP / 555) H' B) T6 ~8 `6 `8 I! l
11.13 Sealed Bid Discrete Auctions / 555# i7 R, I$ Q1 x% B P. I+ H
PROBLEMS / 5605 X' r" @- f6 Z9 N
12 Short-Term Demand Forecasting 566$ u: u$ b6 O; e9 j
12.1 Perspective / 5661 U! f7 m+ D( ?
12.2 Analytic Methods / 569
- |/ O& B. ]( U. L12.3 Demand Models / 571+ {, e5 S; _. [7 L0 f) ^0 [
12.4 Commodity Price Forecasting / 5723 V7 A5 L7 F1 e* B$ g
12.5 Forecasting Errors / 573
4 s! _2 y' ^) j2 u; ` M# S2 J12.6 System Identification / 573
* `9 J+ ], c# K. x% s- T( z12.7 Econometric Models / 574
- K, u3 L1 H; @0 H& m, D12.7.1 Linear Environmental Model / 574! L$ R5 ?" b7 l. u. l e9 q/ A
12.7.2 Weather-Sensitive Models / 5763 x* F5 r" [4 M. e7 \: N1 p
12.8 Time Series / 578& C2 y Z% F2 j6 P. i, {, a
12.8.1 Time Series Models Seasonal Component / 578: m L6 C+ }- E! ?/ I
12.8.2 Auto-Regressive (AR) / 580
& T8 N- @4 x# F1 M, y6 }$ G0 A12.8.3 Moving Average (MA) / 5811 }$ g7 m! W, g! J, p
12.8.4 Auto-Regressive Moving Average (ARMA):4 w! \% x; s/ w. H* k7 |
Box-Jenkins / 582
4 N' D" @, _$ i; v0 {12.8.5 Auto-Regressive Integrated Moving-Average1 T! v% F' k5 M, ^0 k7 G
(ARIMA): Box-Jenkins / 584+ o' s( j/ x3 K7 h9 x% [" N
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585
) y7 U* ^" J. P! D4 }3 D5 j12.9 Time Series Model Development / 585
1 r, Z1 y& d9 Q; K) [12.9.1 Base Demand Models / 586
( W- a4 C J+ ]2 d6 P. z( A12.9.2 Trend Models / 586# f6 ^ O- H2 J- n
12.9.3 Linear Regression Method / 586! o4 Q2 |) a! e! l5 ]
xvi contents3 f" r8 H& j* |$ `9 e
12.9.4 Seasonal Models / 588
; B+ \2 {& a$ j3 [/ i; d12.9.5 Stationarity / 588) _: Q5 f+ I: c+ B
12.9.6 WLS Estimation Process / 590
/ S5 y2 B: i: ]! l8 ~# k* P12.9.7 Order and Variance Estimation / 591% V! C( C8 ` L& k2 a+ |
12.9.8 Yule-Walker Equations / 592
: z$ L8 j3 l- w. @( N2 s; u12.9.9 Durbin-Levinson Algorithm / 595/ M3 a! o" i1 ^; x1 {( L
12.9.10 Innovations Estimation for MA and ARMA: R* a0 E3 ]: f8 \
Processes / 598* D, s& U' A. I
12.9.11 ARIMA Overall Process / 600
* R! N! y& Q7 B1 W ]12.10 Artificial Neural Networks / 603- A5 b- C/ e* b
12.10.1 Introduction to Artificial Neural Networks / 6040 j% [$ x `& q) U$ K) N/ }: P2 o
12.10.2 Artificial Neurons / 605
' \5 c( W, g2 q12.10.3 Neural network applications / 606 E" P) b* d6 m6 U
12.10.4 Hopfield Neural Networks / 6067 }1 O' |8 e H2 z2 J3 e3 B
12.10.5 Feed-Forward Networks / 607, s! g0 r0 _$ O
12.10.6 Back-Propagation Algorithm / 610- b$ I, {3 K. k0 e/ ]! a
12.10.7 Interior Point Linear Programming Algorithms / 6133 }+ p3 w# X7 B$ b9 c' M
12.11 Model Integration / 614- i; G' y+ `" j5 K2 Q! G8 S
12.12 Demand Prediction / 614
c7 M( R7 V* j e; Y$ D8 ]12.12.1 Hourly System Demand Forecasts / 615. u* f% n9 X. F4 @/ k
12.12.2 One-Step Ahead Forecasts / 6150 j8 x: o9 k& e& }- u5 ^0 g% I3 c( V
12.12.3 Hourly Bus Demand Forecasts / 616
( @# e' [7 R6 e+ X. ~0 \/ X12.13 Conclusion / 616* x" e# Y3 z+ L8 w9 [4 K
PROBLEMS / 617 |
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