Contents & References of Network reactive power planning considering load uncertainty using an evolutionary method
List:
Table of Contents
Abstract:.. 1
Chapter One.. 2
1-1 Introduction.. 2
1-2 Topic Plan.. 3
1-3 Report Structure.. 3
Chapter Two Reactive Power, Supply Devices and Its Planning. 5
2-1 General definition of reactive power.. 5
2-2 Reactive power generation devices.. 5
2-2-1 Synchronous generators.. 6
2-2-2 Synchronous condensers.. 6
2-2-3 Synchronous motors.. 6
2-2-4 Capacitor.. 6
2-2-5 Capacitor installation location.. 10
2-2-6 Capacitor placement to reduce losses. 11
2-3 Reasons for increasing the need for capacitors in Iran's networks. 12
2-4 Background of reactive power planning. 13
2-5 methods used to solve the reactive power planning problem. 19
2-5-1 Analytical methods (AM).. 20
2-5-2 Numerical programming methods (NP). 20
2-5-3 heuristic methods (HM). 24 2-6-1 Algorithm (PSO) Leaping.. 28
2-6-2-5 Decoding.. 28
2-7 Training-learning based optimization algorithm (TLBO). 29
2-7-1 Teacher phase.. 29
2-7-2 Learner phase.. 30
2-8 Classification of presented works.. 30
The third chapter of PSO algorithm.. 33
3-1 Overview of PSO algorithm.. 33
3-2 Types of particle topology.. 34
3-2-1 star topology.. 34
3-2-2 ring topology.. 34
3-2-3 wheel topology.. 35
3-3 process of PSO algorithm.. 35
3-4 steps of PSO algorithm implementation.. 37
3-5 checking the effects of parameters PSO.. 38
3-5-1 Acceleration constants.. 38
3-5-2 Number of particles.. 38
3-5-3 Maximum speed.. 39
3-5-4 Inertia weight.. 39
Chapter four.. 41
4-1 Introduction.. 41
4-2 Performance framework of beneficial owner in capacitor planning problem. 41
4-3 scenario reduction.. 46
4-4 scenario reduction regression algorithm.. 48
4-5-Mathematical formulation of the problem of stochastic planning of capacitors. 49
4-6 analytical studies.. 58
Chapter five:.. 85
5-1 conclusion.. 85
5-2 suggestions.. 87
English sources.. 88
English abstract.. 94
List of tables
Table (2-1) classification of articles.. 7
List of forms
Figure (2-1) Vector representations for a circuit with delayed power factor. 9
Figure (2-2) a general view of the methods used to solve the reactive power planning problem. 23
Figure (2-3) the movement path of a particle in two consecutive repetitions. 25
Figure (2-4) genetic algorithm flowchart.. 27
Figure (4-1) owner-operator and future decision variables. 42
Figure (4-2) structure of capacitor planning problem. 43
Figure (4-3) structure of random programming problem. 44
Figure (4-4) Random programming scenario tree. 45
Figure (4-5) cost of three-stage capacitor.. 50
Figure (4-6) schematic of tap trans model.. 52
Figure (4-7) 30 bus standard network.. 58
Figure (4-8) 57 bus standard network.. 59
Figure (4-9) 118 standard network Base.. 60
Figure (4-10) Expected cost according to the number of scenarios in the 30 base network. 61
Figure (4-11) Expected cost according to the number of scenarios in the 57 bus network. 61
Figure (4-12) Expected cost according to the number of scenarios in the 118 bus network. 62
Figure (4-13) scenario tree of active load of 30 buses. 63
Figure (4-14) reduced scenario tree of active load of 30 buses. 63
Figure (4-15) active load scenario tree of 57 buses. 64
Figure (4-16) reduced scenario tree of active load of 57 buses. 64
Figure (4-17) 118 bus active load scenario tree. 65
Figure (4-18) reduced scenario tree of active 118 bus load. 65
Figure (4-19) Reactive load scenario tree of 30 bases. 66
Figure (20-4) reduced scenario tree66
Figure (20-4) reduced scenario tree of reactive 30-base load. 66
Figure (4-21) Reactive load scenario tree 57 Basse. 67
Figure (4-22) reduced scenario tree of Reactive 57 Basse load. 67
Figure (4-23) Reactive load scenario tree of 118 bases. 68
Figure (4-24) reduced scenario tree of 118-base reactive load. 68
Figure (4-25) scenario tree of active power price. 69
Figure (4-26) reduced scenario tree of active power price. 69
Figure (4-27) reactive power price scenario tree. 70
Figure (4-28) reduced scenario tree of reactive power price. 70
Figure (29-4) Expected cost according to the 30-basis risk criterion. 72
Figure (30-4) Expected cost according to the risk criteria of 57 Basse. 74
Figure (4-31) Expected cost according to the risk criteria of 118 bases. 74
Figure (4-32) capacitor capacity according to the risk criteria in the 30 bus network. 75
Figure (4-33) capacitor capacity according to the risk criteria in the 57 bus network. 76
Figure (4-34) capacitor capacity according to the risk criteria in the 118 bus network. 77
Figure (4-35) Expected reactive power according to 30-basis risk criteria. 78
Figure (4-36) Expected reactive power according to the risk criteria of 57 Basse. 79
Figure (4-37) Expected reactive power according to the risk criterion of 118 bases. 80
Figure (38-4) 30 bus network voltage fluctuations according to value. 82
Figure (4-39) voltage fluctuations of the 57-base network in terms of value. 83
Figure (4-40) voltage fluctuations of 118 bus network according to value. 84
Source:
English sources
[1] K.R.C. Mamundar, R.D. Chenweth, "Optimal control of reactive power flow for improvements in voltage profiles and for real power loss minimization", IEEE Trans. Power App. and Systems, vol. 7, pp. 3185-3194, Jul. 1981.
[2] 2012-18 - IEEE Standard for Shunt Power Capacitors, Revision of IEEE Std 18-2002 (Revision of IEEE Std 1992-18), Feb. 2013.
[3] 2004-824 - IEEE Standard for Series Capacitor Banks in Power Systems, Revision of IEEE Std 824-1994, 01 August 2005.
[4] 2004-824 - IEEE Standard for Series Capacitor Banks in Power Systems, Revision of IEEE Std 824-1994, 22 May 2012.
[5] J. Fang, Z. Bo, "Modeling of on-load tap-changer transformer with variable impedance and its application", Proceedings of Energy Management and Power delivery, 1998.
[6] R. Marconato, “Electric Power Systems – Vol.1: Background and Basic Components”, Second Edition, 2002, Edited by: CEI–Italian Electrotechnical Committee, Milan, Italy.
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[10] IEEE Guide for the Application of Shunt Power Capacitors, 978-0-7381-6492-2, 30 March 2012.
[11] EN 50160 standard, "Voltage characteristics in public distribution networks".
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