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第三版目录。5 G5 N7 }, y+ Z7 u a
1 Introduction 1
, {/ \0 s- w$ B q' ^1 R4 q1.1 Purpose of the Course / 1
% z! j* Q0 u$ ^8 Q Z! ~1.2 Course Scope / 2
, W# c/ V N3 I$ c- c0 S, ~5 ]' T1.3 Economic Importance / 2
* l2 l- T4 B8 i1 D1 h: n: b3 g9 b; k1.4 Deregulation: Vertical to Horizontal / 3! I1 T9 f% ]1 P# {3 Y$ \
1.5 Problems: New and Old / 3
1 }' ? D3 D1 t8 f. \7 ?% }2 I! T1.6 Characteristics of Steam Units / 6
" s6 F' E9 @7 U; s( x) g7 z1.6.1 Variations in Steam Unit Characteristics / 10. s; b" P0 o/ ?, T
1.6.2 Combined Cycle Units / 139 A) `8 W6 b7 h' u( ]
1.6.3 Cogeneration Plants / 140 E# V9 g, e+ ]2 e9 N) j
1.6.4 Light-Water Moderated Nuclear Reactor Units / 17+ t3 K A. [( R8 f. Y
1.6.5 Hydroelectric Units / 18
2 U' t+ {: \/ K1 Z8 u3 ]1.6.6 Energy Storage / 21
h1 w1 m& ^+ u k: w' J3 O. z1.7 Renewable Energy / 22; n* A: t9 w. M, H
1.7.1 Wind Power / 23$ k- g, g! C4 }* O
1.7.2 Cut-In Speed / 23
$ J+ B4 x/ \) ?# ~- H6 o% D/ ?1.7.3 Rated Output Power and Rated Output Wind Speed / 24
" k. K) x1 n, F8 {4 O, v1.7.4 Cut-Out Speed / 240 ]; {0 U' ~- q" ~) u
1.7.5 Wind Turbine Efficiency or Power Coefficient / 24
$ d/ u9 n: a1 K5 ] E: E1.7.6 Solar Power / 25
) \ ?9 v. p6 X2 z9 dAPPENDIX 1A Typical Generation Data / 26* {6 o8 t9 I% k2 ~; s
APPENDIX 1B Fossil Fuel Prices / 28
# M' N0 k8 a: I7 b2 p1 O) B- ?APPENDIX 1C Unit Statistics / 29
1 Q f9 }& C. `CONTENTS3 s2 \0 |2 h- ~/ B; ]8 }6 N8 Y# c6 X% [
viii contents
% ?, _& q+ T* A6 v$ [References for Generation Systems / 31
( g; w$ I. c I+ \2 ~+ s' v U+ [2 pFurther Reading / 31
8 L( h. n, G/ A: q2 Industrial Organization, Managerial Economics, and Finance 35
5 ~: c+ p$ P3 n; j: `1 S" J% K, q2.1 Introduction / 35
# w1 U0 N4 F* n! F' {+ g2.2 Business Environments / 36
, o( ?1 g) K4 w- y& f8 R2.2.1 Regulated Environment / 37" H5 e0 h$ [% M- J6 k
2.2.2 Competitive Market Environment / 38. \. }& [7 e2 k3 @9 M$ S3 J" T" I4 n5 W1 J
2.3 Theory of the Firm / 40% s" i+ ?/ V- o: a
2.4 Competitive Market Solutions / 42
! m& N. x/ b: @( E; j7 v) w2.5 Supplier Solutions / 45! \, ~( F4 P, l
2.5.1 Supplier Costs / 46. e. r; V4 q4 V, h& [" N
2.5.2 Individual Supplier Curves / 46* S% I- T" j' v) @# m
2.5.3 Competitive Environments / 47; e# i$ `- h" B2 B, S' ?
2.5.4 Imperfect Competition / 51
+ ^! R3 I2 R0 E' M: p2.5.5 Other Factors / 52
. c' ^4 |7 ^/ g- U5 R. _+ I) `2.6 Cost of Electric Energy Production / 53
4 A$ x v& f5 J8 E4 m" ~8 \" e2.7 Evolving Markets / 54
8 Y8 z( ^/ o2 n, m+ s2 r2.7.1 Energy Flow Diagram / 57
, K1 B1 Q5 Q4 H: M2.8 Multiple Company Environments / 587 |1 e3 ]5 }0 x
2.8.1 Leontief Model: Input–Output Economics / 58
; y. n( \8 z/ Z S2.8.2 Scarce Fuel Resources / 60; [% m8 r2 h" B2 Z! q ~
2.9 Uncertainty and Reliability / 61
+ j6 j7 d0 \# p8 _ W: k" nPROBLEMS / 615 K: u3 J5 g& }& ?, ]
Reference / 62
: w3 ~4 n: C( f2 Y0 y3 Economic Dispatch of Thermal Units and Methods of Solution 635 z3 g* D0 _' d! Z3 f0 C/ k
3.1 The Economic Dispatch Problem / 635 B4 p% F- H% d4 C" t+ h
3.2 Economic Dispatch with Piecewise Linear Cost Functions / 68
. q0 v6 _4 k+ k1 g- ^: s3.3 LP Method / 694 H* {/ F) e* s* |
3.3.1 Piecewise Linear Cost Functions / 69
: [, o; Q# T' d- ?2 J( ^' y3.3.2 Economic Dispatch with LP / 717 Z$ ?/ q+ N% e' p! ]: d0 q7 c
3.4 The Lambda Iteration Method / 73! ]) i" I3 f4 D4 O
3.5 Economic Dispatch Via Binary Search / 762 R" P% n8 U2 X# b1 p) p @
3.6 Economic Dispatch Using Dynamic Programming / 78- |0 A, A1 `$ Q& t! u; L
3.7 Composite Generation Production Cost Function / 81
1 c9 Y' l7 x0 I; F- t8 S, V5 R3.8 Base Point and Participation Factors / 85
; \2 Z4 g! Q1 w3 a* W) O3.9 Thermal System Dispatching with Network Losses
, i/ q6 q5 T4 e( O! IConsidered / 88! `8 s2 X4 V3 r- v. a
contents ix
2 W' h# T& V1 ?% I- p3.10 The Concept of Locational Marginal Price (LMP) / 92
* a( q( q. ^# T9 ?3.11 Auction Mechanisms / 959 t$ i: k; ^ l$ t
3.11.1 PJM Incremental Price Auction as a
/ z2 |3 t4 Y4 M o" \Graphical Solution / 95
8 g- N# ]$ h1 y) O n+ |3.11.2 Auction Theory Introduction / 98
% I' n, C* a) z/ \3.11.3 Auction Mechanisms / 100
7 O$ \/ B' c) m3 m* e3.11.4 English (First-Price Open-Cry = Ascending) / 101. l% m4 X, g" \+ w2 e7 B5 J
3.11.5 Dutch (Descending) / 103+ x, z; i" }1 W$ ^; r8 P
3.11.6 First-Price Sealed Bid / 104; V( {5 M* i8 r( R3 l
3.11.7 Vickrey (Second-Price Sealed Bid) / 105
, Y; k" Y" F, J3.11.8 All Pay (e.g., Lobbying Activity) / 105/ n5 r; f, r4 D- m$ ] s
APPENDIX 3A Optimization Within Constraints / 1062 O7 O( j ?; W$ U$ a6 V# r
APPENDIX 3B Linear Programming (LP) / 117
4 Y) A6 a0 N- ~, ^1 r; y, E/ ]% AAPPENDIX 3C Non-Linear Programming / 128
. J3 C- _# x2 |. Z# T' {APPENDIX 3D Dynamic Programming (DP) / 128+ g$ R$ y6 L- E9 J3 b! A' W1 k9 X, q, j
APPENDIX 3E Convex Optimization / 135
5 J- Q5 J, v. r8 _" Y: _PROBLEMS / 1384 R5 o; }6 t0 V* w0 C8 N7 ^
References / 146
# n* \* c; X/ O+ ]& w. w2 H7 v8 p9 U4 Unit Commitment 147) u6 @$ G9 s6 B5 [7 r1 u% B
4.1 Introduction / 147
2 J$ R2 ~* M7 }& @4 C4.1.1 Economic Dispatch versus Unit Commitment / 147
* e L& L! K# j4.1.2 Constraints in Unit Commitment / 152
) v: k3 Q: a% t" T1 n6 B4 Q3 n4.1.3 Spinning Reserve / 152
3 u, z5 P# r# f) h% Y* h# e4.1.4 Thermal Unit Constraints / 153
7 e/ S: F& e8 `+ y! k) P7 g" I ]9 M4.1.5 Other Constraints / 155
% i# o+ X) e7 D/ T- F: {4.2 Unit Commitment Solution Methods / 155. v0 T8 h9 P5 J p& m
4.2.1 Priority-List Methods / 156; _, r+ @, W1 f( q; I0 c) Q
4.2.2 Lagrange Relaxation Solution / 157
) g. g! m& Q! ~. q \" F+ ~9 H+ M4.2.3 Mixed Integer Linear Programming / 166! A! M' {+ r* I1 G1 ~5 b
4.3 Security-Constrained Unit Commitment (SCUC) / 167
2 {3 P/ P J) H# |4.4 Daily Auctions Using a Unit Commitment / 167 O6 l* r* E; q/ _% M' H, X- N
APPENDIX 4A Dual Optimization on a Nonconvex C4 c* W% m9 J7 V
Problem / 167
; k- x, z( L2 f4 n5 p& j6 D( j$ K; ZAPPENDIX 4B Dynamic-Programming Solution to
5 T4 B% `' d! h0 F5 ?Unit Commitment / 1736 s% h% ~7 e/ |8 w0 o
4B.1 Introduction / 173
& r5 R1 K* y6 T0 a5 X9 `* W: G4B.2 Forward DP Approach / 174
* @. g2 F* A+ e1 }. oPROBLEMS / 1828 h) e+ Y$ S |: h" ^ N8 a( ]
x contents) B+ ]* A! ?: @6 N1 O
5 Generation with Limited Energy Supply 187
! K, E5 W/ D; P+ a9 [! r. |) s6 Z5.1 Introduction / 187
3 g! s* t* k* Y# A7 G: J6 _; s5.2 Fuel Scheduling / 1886 ^, i1 ~2 t( }
5.3 Take-or-Pay Fuel Supply Contract / 1884 B9 P) q/ a _" c8 E, t* c
5.4 Complex Take-or-Pay Fuel Supply Models / 194
& R$ `2 D/ E3 K) q C5.4.1 Hard Limits and Slack Variables / 1940 A* c8 M' N3 F9 |: S: B
5.5 Fuel Scheduling by Linear Programming / 195( }) S' i3 l2 W# o4 b8 E
5.6 Introduction to Hydrothermal Coordination / 202
9 N- ?6 Y' m6 l5.6.1 Long-Range Hydro-Scheduling / 2031 g+ J& |4 C# |& q
5.6.2 Short-Range Hydro-Scheduling / 2044 x+ V" q. E* Q; Y7 ^
5.7 Hydroelectric Plant Models / 2041 M7 O# F' o2 ^" j& a
5.8 Scheduling Problems / 207
9 f x- B# r5 J, G5.8.1 Types of Scheduling Problems / 207
3 `; f5 `( B& `% m( m; L! {0 `! B5.8.2 Scheduling Energy / 207" O! ?- O) R q. [3 {
5.9 The Hydrothermal Scheduling Problem / 211/ \% J/ I) T u6 w0 g& {
5.9.1 Hydro-Scheduling with Storage Limitations / 211
+ ~0 e6 X% }4 Q. |0 }6 u. u5.9.2 Hydro-Units in Series (Hydraulically Coupled) / 216( X: }2 ]3 p, r% m
5.9.3 Pumped-Storage Hydroplants / 2187 \0 i, F0 r4 K- ~) Q7 L8 x, x
5.10 Hydro-Scheduling using Linear Programming / 222
3 j, [: q# i% @# d3 Q7 TAPPENDIX 5A Dynamic-Programming Solution to hydrothermal* s% l4 {# [ J$ A
Scheduling / 225
1 n) c. k" t" m# w0 Q7 h+ d) G5.A.1 Dynamic Programming Example / 227+ C6 f. {/ c6 R; L7 y y
5.A.1.1 Procedure / 228
7 ]- X/ a" v- S8 N1 R$ \( K& r5.A.1.2 Extension to Other Cases / 231' I1 Y3 W O$ F* R
5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant
# q$ y& ]& l/ V. T" GProblem / 232/ Z1 }- F+ P2 m
PROBLEMS / 234, ], U3 O; P( v+ r8 \) u" B+ T; V
6 Transmission System Effects 243+ z1 F: [6 x& T( W3 ]4 v$ u% ~2 x
6.1 Introduction / 243
7 x, g% F* N$ X" w) \0 [5 h6.2 Conversion of Equipment Data to Bus and Branch Data / 2478 ?4 P# A( J& P6 F; ?
6.3 Substation Bus Processing / 248$ r; l, ^ j( A2 D" X
6.4 Equipment Modeling / 248
+ L4 x7 @" y8 `" M F1 `- U6.5 Dispatcher Power Flow for Operational Planning / 251$ I3 v( D5 a- j6 c/ h8 r
6.6 Conservation of Energy (Tellegen’s Theorem) / 252. _. H: g6 n2 n9 ]$ j. u+ w5 B7 x t& G9 j
6.7 Existing Power Flow Techniques / 253$ w2 i% T: A* O' |; Z# V) |% I
6.8 The Newton–Raphson Method Using the Augmented
4 D/ ^+ O1 h7 tJacobian Matrix / 254
2 ?* A- ^+ m8 X6.8.1 Power Flow Statement / 254! v" x0 v# p. x3 J$ g) v3 N' Q
6.9 Mathematical Overview / 257
# o; m5 d- w, a8 J+ H$ }# Ycontents xi. j% Z" M/ `2 w* n) z2 Y
6.10 AC System Control Modeling / 259
* z* l. P9 p* t6 E. }$ O6.11 Local Voltage Control / 259
7 N5 J9 j$ r$ a T6.12 Modeling of Transmission Lines and Transformers / 2595 i2 h( [# N/ ^3 {. u
6.12.1 Transmission Line Flow Equations / 259
) r0 ~7 x8 j( M9 S6.12.2 Transformer Flow Equations / 260" A% p% O' O' `- @# R% [! G% ~: c6 ]
6.13 HVDC links / 2610 z* b3 y% E) L
6.13.1 Modeling of HVDC Converters
) A" r& H! K, g6 xand FACT Devices / 264
) g9 q B' L% X% o2 Z7 K6.13.2 Definition of Angular Relationships in
0 m: I9 f" B6 E8 L( X6 }HVDC Converters / 264
% p' ?! G, W+ L% y* z, q6.13.3 Power Equations for a Six-Pole HVDC
" T4 R; F3 L5 iConverter / 264- D6 W5 J8 H R
6.14 Brief Review of Jacobian Matrix Processing / 267
, S6 X$ }, h+ d v' I' `6.15 Example 6A: AC Power Flow Case / 269% c6 y% |% }" q3 L6 ~ }
6.16 The Decoupled Power Flow / 271
+ U0 c! ^" c9 q! w3 Y4 N6.17 The Gauss–Seidel Method / 275
+ F' F* z z/ U- x6.18 The “DC” or Linear Power Flow / 277* m; @ s1 T! W
6.18.1 DC Power Flow Calculation / 277
9 b1 f2 Q! O/ t7 D2 ]6.18.2 Example 6B: DC Power Flow Example on the
' i- Y" ]2 b- W/ T( nSix-Bus Sample System / 2787 w/ [) }9 y/ K
6.19 Unified Eliminated Variable Hvdc Method / 278
& E- x) }; ^) [7 I, k/ s6.19.1 Changes to Jacobian Matrix Reduced / 279
+ `3 l. y. M: t6 d- m$ \) {6.19.2 Control Modes / 280
& b+ [" y7 O: D) R/ S h, Q6.19.3 Analytical Elimination / 280
7 H( u/ c7 ?& i/ X; {6.19.4 Control Mode Switching / 283
9 j% S4 J. X+ l6 | ~6.19.5 Bipolar and 12-Pulse Converters / 283
$ a O; [5 b" c3 r% h1 Q! i* m% \6.20 Transmission Losses / 2846 Y, {5 e* m! @6 r0 Z* g( _+ f
6.20.1 A Two-Generator System Example / 284* p! X/ X( ^! A9 o" s! U
6.20.2 Coordination Equations, Incremental Losses,
$ z/ c; a( q: ]9 i/ l& Sand Penalty Factors / 286& K9 |/ O; w, e& R( S7 [2 j) ?
6.21 Discussion of Reference Bus Penalty Factors / 288
' X1 T6 f( G6 {$ u6.22 Bus Penalty Factors Direct from the AC Power Flow / 289# d; O3 e, W5 ]+ z( S7 |; p
PROBLEMS / 291; C1 T) O# e' T; Q. j) B; T
7 Power System Security 296
: d9 u- o9 M$ e) I7.1 Introduction / 296
5 u5 B( z: g8 y/ _' N! A. l. m7.2 Factors Affecting Power System Security / 301
- ~% m- E x) d8 c. g8 ?7.3 Contingency Analysis: Detection of Network Problems / 301) r9 [6 j5 p9 U1 e1 @
7.3.1 Generation Outages / 3014 D" y7 c1 F e0 B* m
7.3.2 Transmission Outages / 3026 J8 T- i5 ~; L' X6 v' _- u
xii contents
7 v4 d) z6 D% r% u9 N7.4 An Overview of Security Analysis / 306
) I; }7 V7 c/ n+ r: P5 u7.4.1 Linear Sensitivity Factors / 307
' g( {/ h5 P- c7.5 Monitoring Power Transactions Using “Flowgates” / 313% j! \! H8 X* Q9 h6 }2 c
7.6 Voltage Collapse / 315
+ s0 b) W: T3 t- ~( ?7.6.1 AC Power Flow Methods / 317* s* R' H! m! t
7.6.2 Contingency Selection / 320
8 F6 j- D8 d$ }) s5 p; ^5 E" {7.6.3 Concentric Relaxation / 323+ {4 D9 G7 Y* ~9 ^6 A. j2 }) N
7.6.4 Bounding / 325
& a( O3 W; e! d5 G0 i2 {7.6.5 Adaptive Localization / 325
+ {4 S" H: u. X+ O ?' yAPPENDIX 7A AC Power Flow Sample Cases / 327& s; Y2 y% v: e b
APPENDIX 7B Calculation of Network Sensitivity Factors / 336) j* t, P* ^( q) O; W9 g; P& M
7B.1 Calculation of PTDF Factors / 3361 K: U) g$ T1 b T+ ], u1 P
7B.2 Calculation of LODF Factors / 3391 s& }0 Z8 i1 g/ u w. [# p! M( ?2 S
7B.2.1 Special Cases / 341
1 f$ A' m4 y& g+ K( V7B.3 Compensated PTDF Factors / 343: [# D8 |2 T8 W3 C) a9 u
Problems / 343
7 s' C6 ^8 V1 L" I8 q5 K" X5 C+ uReferences / 349' r3 q s$ r) K C% E" i
8 Optimal Power Flow 350" r$ X6 t* q/ M P
8.1 Introduction / 350
% e i9 C& C* p8.2 The Economic Dispatch Formulation / 351
7 [7 W/ R l7 h7 p: D/ R7 t7 U2 Y* u8.3 The Optimal Power Flow Calculation Combining5 m0 b8 d* F- X" V/ b
Economic Dispatch and the Power Flow / 352
% M ^# Y' B1 }# K+ j, {8.4 Optimal Power Flow Using the DC Power Flow / 354
5 a0 _7 M9 v! \% b5 p, ^( g. h8.5 Example 8A: Solution of the DC Power Flow OPF / 356* x- x& m! D/ _. v- T
8.6 Example 8B: DCOPF with Transmission Line
7 u+ u6 i$ O8 c. M8 Y( ?9 WLimit Imposed / 361
, j* }' ^7 `5 y( v+ `! X5 q8.7 Formal Solution of the DCOPF / 365
9 k ~7 x# o7 M! U p$ \8.8 Adding Line Flow Constraints to the Linear' a: @ q6 ?' n1 y6 f* u
Programming Solution / 365
I: [' J; I \9 k8.8.1 Solving the DCOPF Using Quadratic Programming / 367 S; [* K# x* }2 l
8.9 Solution of the ACOPF / 368
1 N" s7 Y* N& a4 M8 m8.10 Algorithms for Solution of the ACOPF / 369
0 D& R8 n- ?8 p$ H8.11 Relationship Between LMP, Incremental Losses,8 w d5 F1 u7 G$ @
and Line Flow Constraints / 376
2 y: E9 S" B: P+ z. U2 O8 M) Y8.11.1 Locational Marginal Price at a Bus with No Lines
4 `) Z- U1 C7 m* H; u$ @7 Z& |Being Held at Limit / 377
P7 F: ?# f8 c1 G& p& t1 ~8.11.2 Locational Marginal Price with a Line Held at its Limit / 378* M2 l5 l" \! C7 |, R5 C& G( C
contents xiii$ b* _2 i& N. f, ^! {- p( r d
8.12 Security-Constrained OPF / 382
Z* l$ t: O# x8.12.1 Security Constrained OPF Using the DC Power Flow
+ m( c% @. J7 W2 land Quadratic Programming / 3847 \8 F3 z1 j% b3 |
8.12.2 DC Power Flow / 385
1 O8 V3 K" I- n8.12.3 Line Flow Limits / 385
5 M/ t) F R# a7 L2 y3 E8.12.4 Contingency Limits / 386
. J% T0 W1 Q; [. ?. T: tAPPENDIX 8A Interior Point Method / 391
: [! m8 ~: e/ O, fAPPENDIX 8B Data for the 12-Bus System / 393
+ c1 w5 I5 k2 N& ^) w9 pAPPENDIX 8C Line Flow Sensitivity Factors / 395: v0 S6 L% C0 c/ u4 g+ P0 l4 C
APPENDIX 8D Linear Sensitivity Analysis of the0 |7 k; h+ Y. A% g9 P5 {4 w
AC Power Flow / 3976 O/ i4 l* E# E( r
PROBLEMS / 399
3 c6 h( w2 `% l5 B9 y9 [9 Introduction to State Estimation in Power Systems 403
; N; g( E; S/ ^* `+ V9.1 Introduction / 403
' v+ k: E8 G$ {9 d9.2 Power System State Estimation / 404) p% K* Q/ S0 y, A' t% S
9.3 Maximum Likelihood Weighted Least-Squares. `- f' t9 X6 C/ g3 e0 t1 |1 S! z
Estimation / 408
+ z7 m& S. E n1 o! y7 @3 Z9.3.1 Introduction / 408/ o: ~5 C7 \- M* p k$ f
9.3.2 Maximum Likelihood Concepts / 4109 ?: M3 Y5 ~+ \( y/ a
9.3.3 Matrix Formulation / 414
0 `5 X6 ?8 W7 |( O9.3.4 An Example of Weighted Least-Squares
4 `( q0 R4 J2 u T0 u! }! MState Estimation / 4170 t& ?' Q; ~$ m& }8 @+ n. L4 D/ C
9.4 State Estimation of an Ac Network / 4210 k( q: Y! g/ v3 A: c
9.4.1 Development of Method / 4217 B k% y/ n* `* y6 c2 Z, c. |
9.4.2 Typical Results of State Estimation on an4 M* @9 \* `( m0 z
AC Network / 424
$ p" U# x* Z+ i8 C$ I* ]% i: n$ ^9.5 State Estimation by Orthogonal Decomposition / 428
: e& W# |5 H/ z @9 S+ ]9.5.1 The Orthogonal Decomposition Algorithm / 431
7 J% E5 j( f8 C! v- F( a1 |9.6 An Introduction to Advanced Topics in State Estimation / 435
' t. B9 F, H. B q9 R9.6.1 Sources of Error in State Estimation / 435
- j. R- q% ?5 \9.6.2 Detection and Identification of Bad Measurements / 436
4 ]$ x' d2 K6 r3 d9.6.3 Estimation of Quantities Not Being Measured / 443
3 e0 ^7 H& s& {/ {1 [- M! X9.6.4 Network Observability and Pseudo-measurements / 4441 F* K# M+ h! `3 m5 y, v3 B
9.7 The Use of Phasor Measurement Units (PMUS) / 447
4 P) D0 n0 K5 E/ ?3 t# N9.8 Application of Power Systems State Estimation / 451* f8 M" H) m$ \3 J. j
9.9 Importance of Data Verification and Validation / 454
8 r$ G b: I$ f4 A$ C9.10 Power System Control Centers / 454
9 v4 t; w% n7 z9 t7 v6 B! {xiv contents
# j6 S9 e/ {$ Z/ X, \" RAPPENDIX 9A Derivation of Least-Squares Equations / 456$ ]) Q {$ ~% L
9A.1 The Overdetermined Case (Nm > Ns) / 457' C# P( H2 l1 x9 m. }, r
9A.2 The Fully Determined Case (Nm = Ns) / 462" W/ d8 ^" g% e+ F' `8 v- C
9A.3 The Underdetermined Case (Nm < Ns) / 4623 {$ [6 m$ L$ z& K6 Z A
PROBLEMS / 464
) i6 L; w9 d2 P9 U8 F- x; j10 Control of Generation 4683 @1 s- f; x1 z; u4 s
10.1 Introduction / 468* {- G5 M. r; R9 j
10.2 Generator Model / 470
' a% w& d. g- Y' D. K& o: H3 f2 N' W$ q10.3 Load Model / 473
5 P0 }* P8 d! E/ M" b10.4 Prime-Mover Model / 4752 b0 G1 Z" x, ^+ e3 G0 L6 U
10.5 Governor Model / 476
( z+ b% d" V) J+ i! E `10.6 Tie-Line Model / 481% n8 N) H$ i' w) i; D
10.7 Generation Control / 485" m) C f) O/ O5 v
10.7.1 Supplementary Control Action / 485
2 W+ j8 g g$ m1 v10.7.2 Tie-Line Control / 486
+ B3 q. Q: J5 w, R! K10.7.3 Generation Allocation / 489
3 v: _, i6 J( M, S2 f10.7.4 Automatic Generation Control (AGC)! k. g- Z: F0 x9 F
Implementation / 491" X( x( n5 b7 U+ \- K* ~9 o
10.7.5 AGC Features / 495: j. ]( Z# e1 w K% V& K% y
10.7.6 NERC Generation Control Criteria / 496
1 Y. ^6 I9 d/ j4 I$ KPROBLEMS / 4975 V6 E1 B6 Y9 q9 l! i
References / 500
! S( \% L6 P+ q" q2 G |" T! n11 Interchange, Pooling, Brokers, and Auctions 501
) V* K: r+ B' ]" u& h3 m, ]11.1 Introduction / 501
7 M J6 R, k: O3 `6 Y9 P. q11.2 Interchange Contracts / 504
5 r4 U N4 R$ ~11.2.1 Energy / 5047 t# f8 }9 L) v: @& q8 c: k+ \
11.2.2 Dynamic Energy / 506
" H# ~7 C" y' m8 q5 S% _. u( @8 A11.2.3 Contingent / 506
8 ~7 _/ A- \+ y% y) h11.2.4 Market Based / 507
3 W2 R0 X; r* m% Y11.2.5 Transmission Use / 508
/ q) e! n' g3 F: M11.2.6 Reliability / 517. @% H0 b) u' b |
11.3 Energy Interchange between Utilities / 517
; j+ [( D7 ?" M1 [0 m/ @11.4 Interutility Economy Energy Evaluation / 521' y5 s! [8 X8 u6 ?3 P$ e5 B$ F
11.5 Interchange Evaluation with Unit Commitment / 5221 E& n- m; M' W+ ?
11.6 Multiple Utility Interchange Transactions—Wheeling / 523- o1 F$ m' v( @( d, C0 b
11.7 Power Pools / 5261 d. j; C' }3 @2 s8 z3 S5 R! n8 i
contents xv! D+ W9 H+ f# q; c/ E4 v
11.8 The Energy-Broker System / 529
1 p( U' K8 X; T5 j$ I4 B% ^11.9 Transmission Capability General Issues / 533
: w+ \, M3 r0 E! {" n11.10 Available Transfer Capability and Flowgates / 535& Z" w1 R' N- i/ e
11.10.1 Definitions / 5362 X; G( Y3 @& H- `0 y8 \
11.10.2 Process / 539! X& P) D8 w( I0 x
11.10.3 Calculation ATC Methodology / 540
2 b) m' c4 w4 [4 U; l11.11 Security Constrained Unit Commitment (SCUC) / 550
/ R& O/ t) I7 [8 e11.11.1 Loads and Generation in a Spot Market Auction / 550: Z0 k( F/ u6 h" E1 W6 s$ q
11.11.2 Shape of the Two Functions / 552, d b8 o& S1 A, u! R" I
11.11.3 Meaning of the Lagrange Multipliers / 553! r1 A, t4 `0 g$ c
11.11.4 The Day-Ahead Market Dispatch / 554# J/ G" C; b9 i6 S/ U4 ?2 {1 ^
11.12 Auction Emulation using Network LP / 555: {. P8 g6 G6 w1 h
11.13 Sealed Bid Discrete Auctions / 555
% P8 p5 h' R6 d0 HPROBLEMS / 560/ w/ g' b- P& w& U1 c6 s
12 Short-Term Demand Forecasting 566
- c% h C/ T9 c! O$ n12.1 Perspective / 5664 K1 W/ x. E& }0 b
12.2 Analytic Methods / 569' y& q3 `& b/ i8 G' y7 ]
12.3 Demand Models / 5716 q# O% P: w! {" d/ Y6 {
12.4 Commodity Price Forecasting / 572
( b" j+ \7 }1 \1 ]) c |, M12.5 Forecasting Errors / 573. i0 l9 K( o/ z; z, g
12.6 System Identification / 573
& x: O) J \: N L12.7 Econometric Models / 574+ r1 A( U1 i o/ T0 P. g6 R0 L1 i
12.7.1 Linear Environmental Model / 574# {, y/ e2 r6 J8 e# M8 p& C c
12.7.2 Weather-Sensitive Models / 5764 u& L& k$ L& v! w3 L% z8 Y J9 k
12.8 Time Series / 578, `; g j0 Y. K$ o6 L- ~' }) f
12.8.1 Time Series Models Seasonal Component / 578+ I- O9 ]& k, Y8 ?
12.8.2 Auto-Regressive (AR) / 580
# L5 K0 i' R! n2 I- Y12.8.3 Moving Average (MA) / 581* l. r0 [5 M3 e. d" e: l0 k; L
12.8.4 Auto-Regressive Moving Average (ARMA):
+ Z$ M. f) ?7 Y$ V j! L7 MBox-Jenkins / 582
# r* Z, M U4 P2 C8 e12.8.5 Auto-Regressive Integrated Moving-Average+ V. O+ D0 e) c( B
(ARIMA): Box-Jenkins / 5845 B$ `5 c1 }4 d+ M! b
12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) / 585/ i6 ~0 m1 c' [0 Y* S. w
12.9 Time Series Model Development / 5852 ?# ]4 u f3 V6 ~" Q
12.9.1 Base Demand Models / 586
, S3 v6 R/ E7 U) I/ I; B12.9.2 Trend Models / 586
6 q5 I. r+ `, g+ {12.9.3 Linear Regression Method / 586
@3 r: h3 r# `& g# G1 ixvi contents
! G6 a( b) q6 j% R12.9.4 Seasonal Models / 588: X1 ]7 s: b" {! g1 D
12.9.5 Stationarity / 588
: ]1 S& s. T) s3 M12.9.6 WLS Estimation Process / 590
$ C" d2 i. |: l4 q! Y* M3 |0 Y$ }7 l12.9.7 Order and Variance Estimation / 5916 A; I3 }; h" e- I' C$ o J
12.9.8 Yule-Walker Equations / 592
3 e( Y9 Q% T2 [/ O/ y: Q: D12.9.9 Durbin-Levinson Algorithm / 595
0 j$ L9 E" e+ k6 z* } }) @1 F( h12.9.10 Innovations Estimation for MA and ARMA
& n6 {9 j7 z8 y2 \( l* M. R: X, FProcesses / 598
+ Q/ _7 o6 n4 V3 D8 S# w: {12.9.11 ARIMA Overall Process / 600 X: i2 k8 k* G& a
12.10 Artificial Neural Networks / 603' {+ U: Y, q5 r8 U1 D; r
12.10.1 Introduction to Artificial Neural Networks / 604
9 F1 [! |7 ]9 Y3 e12.10.2 Artificial Neurons / 605+ [+ @4 g! v" ]) S2 u& ~& m
12.10.3 Neural network applications / 6063 ^$ l& l! R: m* h! O% U& E
12.10.4 Hopfield Neural Networks / 606- N6 |' X: j4 q) I, T2 h3 x# y) q
12.10.5 Feed-Forward Networks / 607
9 f' |6 ~& _$ j# O( Q* g) V12.10.6 Back-Propagation Algorithm / 610- J4 I* N: R! ^2 V* y
12.10.7 Interior Point Linear Programming Algorithms / 613, K+ m1 i' v& v8 z
12.11 Model Integration / 614
2 u1 m' V4 E! L$ a( r3 E7 Y- d12.12 Demand Prediction / 614
7 K" ]$ ^, k. F) _8 R/ o( w12.12.1 Hourly System Demand Forecasts / 6155 O- ~0 \& ?+ Y& D- A' u$ m7 J$ p k
12.12.2 One-Step Ahead Forecasts / 6153 W4 M; e! r. n6 l$ `" [* i
12.12.3 Hourly Bus Demand Forecasts / 616
( ~, v7 ~- S- H% l+ d* L12.13 Conclusion / 616
# E. ~$ b: z7 ZPROBLEMS / 617 |
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