Static Voltage Collapse Studies In Power Systems. D. Vijaya Kumar, B.Manmadha Kumar, I.Ramesh, A.Jagannadham

Size: px
Start display at page:

Download "Static Voltage Collapse Studies In Power Systems. D. Vijaya Kumar, B.Manmadha Kumar, I.Ramesh, A.Jagannadham"

Transcription

1 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl Statc oltage Collapse Stues In ower Systems D. jaya Kumar, B.Manmaha Kumar, I.Ramesh, A.agannaham Abstract- Ths paper concentrates on the statc voltage stablty stues on power systems. The behavor of the system when subjecte to graual an steay ncrease n system loang s stue. The tool le contnuaton loa flow usng the moal analyss technque s use n a systematc way so as to prect the system behavor at fferent operatng contons. The metho evse s a worthy tool to use n power system plannng stues from the vew pont of voltage stablty. The man objectve s to evce sutable computer programs so as to conuct plannng stues on a power system from the vew pont of voltage stablty. To o the loa flow an entfy the wea buses n the system usng Egen value analyss. Inex Terms Moel analyss technque oltage stablty stues, Newton- Raphson Metho, an Branch artcpaton, Egen value analyss. I INTRODUCTION Once a reactve power source has reache ts maxmum ORE an more voltages relate problems are beng lmt, t can no longer regulate the voltage. Therefore, experence by moern power systems n Ina as well sustane loa growth results n accelerate voltage ecay Mas n other foregn countres. It s well nown that the an hence greater reactve power requrements. Ths may voltage problems are closely relate to the management of force other voltage regulatng evces to ther lmts, wth reactve power resources an flows n the system. It has been subsequent further acceleratons n the rate of eclne of establshe that qute a few of the gr falures experence by oltage. If loa s ncrease further, the pont of voltage fferent electrc utltes have been cause by the voltage collapse woul soon be reache. Ths phenomenon has come collapse phenomenon [10]. The stuy of a system for voltage to be nown as voltage collapse. nstablty/collapse contons wll have to be one both from A voltage collapse process may consst of the followng the plannng as well as from the operaton vewponts [13]. steps: [10] The present stuy manly concentrates on the plannng a) The crtcal sturbance by ncreasng transmsson lne aspects. loang woul evelop an untenable ncrease of seres Lac of aequate reactve power resources n a power system s a major contrbutng factor to the process of voltage collapse. As loas n a power system ncrease, voltage across the networ tens to ecrease an reactve power, losses ncrease. The ncrease reactve power eman woul be supple by voltage regulatng evces such as generators or reactve power losses I X. b) Ths woul cause a sharp voltage reucton at a number of transmsson loa substatons. c) By reucng loas an provong over exctaton n surrounng unts, the voltage reucton woul create an ntate stablty. statc var compensators, f possble [1]. However, ue to ) But the voltage reucton woul also ntate a powerful physcal lmtatons, such evces cannot supply unlmte establzng force, automatc on-loa transformer tap amounts of reactve power. Often sustane loa growth changng, whch woul progressvely ncrease the loas, an wll result n some source of reactve power, or perhaps a number of such sources, encounterng lmts,.e. reachng a physcal lmtatons n the amount of reactve power that they can supply. may even provoe loa overshoot. e) Ths loa ncrease cause by each tap changng step woul progressvely reuce the transmsson voltage levels. f) Each voltage reuctons woul ncrease seres reactve power losses nversely to the voltage cube. g) Ths changng stuaton coul only mantan stablty untl the frst unts over exctatons protecton functons. Djaya Kumar s rofessor n Department of E.E.E, Atya Insttute of h) Once ths occurs, the voltage falls so sharply that Technology an Management, Teal, Anhra raesh, Ina. system collapse s nevtable. B.Manmaha Kumar s Senor Assstant rofessor n Department of ) The sustane excess, reactve eman woul srupt E.E.E, Atya Insttute of Technology an Management, Teal, A., Ina. Emal.ID: bomann@yahoo.co.n nter unt co-ornatons so leang to angle nstablty as the fnal cause of breaown. I.Ramesh an A.agannaham are Assstant rofessors n Department of E.E.E, Atya Insttute of Technology an Management, Teal, A., Ina.

2 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl MATHEMATICAL MODELLING FOR OLTAGE STABILITY ANALYSIS The objectve of ths paper s to evelop the necessary bacgroun for the analyss of statc voltage collapse problem, establshng the concepts of -/Q curves (nose curves). oltage senstvty to reactve power, number of solutons at fferent loa levels, the pont of collapse (oc) an the conton whch occur at voltage collapse n a smple, sngle lne loss-less power system, an then to generalze to a multbus system. The ssues of senstvty of voltage to loa power on the upper an lower sectons of the nose curve an the change of number of solutons as the loa power s change s explore n ths paper. Conser a sngle lne, loss-less system wth constant loa an fxe senng en voltage, E. Ths assumpton of fxe senng en voltage amounts to lmt-less reactve power supply from the generator to eep the generator termnal voltage fxe at E at fferent loa contons. Ths secton wll establsh the nose curves, voltage Senstvty to reactve power, number of solutons at fferent loa levels an the pont of collapse n the two-bus system. ) Solutons for < max ) 1 Soluton at max ) Soluton for > max Fg.1. Lossless Two System The actve an reactve power balance equatons are: c E Sn θ (1) X E Q Q + Cos θ () X X From euqaton (1) E Sn θ X E max X at θ 0 45 Fg.. Dagram (3) (4) The Fg. llustrates the followng eas. a) Senstvty: 1 < 0 Ths shows that an ncrease n at 1 wll cause a ecrease n voltage an a ecrease n wll cause an ncrease n voltage. Ths s an expecte behavor n normal power system operaton an s usually terme as stable soluton, upper branch soluton or hgh voltage soluton.[1, ]. > 0 The senstvty of to at soluton pont s opposte to that at 1. Ths s calle an unstable soluton, lower branch soluton or low voltage soluton. b) Number of Solutons: It coul be seen that the number of solutons varous as s ncrease. It can be vsualze from fgure that there wll be: c) ont of Collapse (o C): The pont ( max, C) on the agram, s the ont of Collapse Ths ncates that voltage s nfntely senstve to at c. Smlar results can be obtane for Q also. ) oltage Stablty Crtera: For a sngle lne networ, the crteron for voltage stablty s state as follows > 0 Q > 0 (5) Where - an Q -Q. The pont (Qmax, C) s the oc on Q agram. The conton for voltage collapse s thus; Q (or) Q 0 (or) 0 Thus an alternate statement for voltage collapse can be gven as: A ower system n steay state s at a pont of voltage collapse f some Δ j s unboune as Q tens to zero.

3 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl OWER FLOW EQUATIONS Usng bus frame of reference, the bus current at th bus s expresse as [3]: I n 1 Y ; For 1,,... n (6) The complex power at th bus * * * S I Y ; For 1,,... n (7) efne e jѳ ; θ θ - θ ; Y G + jb; S S + jq S Then [ G [ Cos(θ θ ) + B sn(θ θ )] (8) 3 OLTAGE COLLASE CONDITION IN MULTI- BUS SYSTEMS The power flow equaton n the case of mult-bus system can be wrtten as (θ,, λ) ((θ, ) S λ * 0 (14) Q(θ,, λ) Q((θ, ) Q S λ Q* 0 (15) Where λ s the loang parameter an * p p an Q * λ λ Lnearzaton of equatons (14) an (15) yels, D p θ + q v Where s gven by λ λ 0 (16) p * λ λ λ (17) q Q * Qλ λ Therefore t gves the recton of loang from equaton (16) [ ] λ (18) θ 1 v λ So λ can be ncrease untl becomes sngular. The pont of voltage collapse therefore correspons to the sngularty of,.e.,et 0 OLTAGE SENSITIITY (x) The lnearse power flow equaton s re-wrtten n a mofe form as: Q (x) G Sn(θ θ ) B sn(θ θ )] Δp θ Δθ For 1,,3, n. (19) Δq Δ qθ Q Defne msmatch vector for real an reactve power as: (x) (x) - S Usng equaton (16) an assumng that there s no angular (9) nstablty,.e., et θ 0 Q(x) Q(x) - Q S (10) If λ s set equal to E, the generator termnal voltage Equatons (9) an (10) can be expresse n compact form as: - QS -1 (Qe - Qθ θ -1 e) E (0) p(x) f (x) q 0 (11) Where Qe an q(x) e E E If λ s set equal to b, the susceptance of SC at the loa bus Soluton of f(x) 0 by Newton Raphson Metho (Q -b ) an Let X Xe + Δx, then by Taylor seres expanson. QS -1 (Qb - Qθ θ -1 b) b - QS -1 Qb b (1) F(x) f(xe +Δx) f(xe)+(xe)δx + hgher orer terms (1) q Choose Δ x such that f(x) 0 an gnorng the hgher orer As pb 0 an G b b b terms of the expanson, Thus, n sngle lne case, n aton to the conton gven by Δx - -1 (xe) f(xe) (13) equaton (5) for voltage stablty, the followng are also to be Where (xe) the acoban evaluate at Xe, Expresse as an satsfe. teratve scheme, the next estmate of state vector s X+1 X + ΔXI, the teratve metho of soluton contnues untl msmatch > 0, > 0 () functons satsfy a pre-etermne tolerance between E b successve teratons. In a mult bus system the suffcent conton for voltage stablty s that all elements of Qs -1, -( Qe - Qθ θ -1 e) an (Qb - Qθ θ -1 b) are postve when there s no angular stablty problem. Angle Senstvty to Change n arameter The relatonshp between voltage senstvty to parameter λ, A smlar relatonshp can be establshe between θ an λ. Usng equaton (15): O θ λ + Q0 Q v qλ λ 0 (3) From equaton (3)

4 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl Q -1 (Qθ θ + Qλ λ) (4) θ - (S -1 (λ Q -1 Qλ) λ (5) If et Q 0, then et 0 mples et S 0 an equaton (5) shows that angular senstvty to parameter λ s nfnte when et 0. Thus t s seen that n general angle an voltage stablty ssues are nterrelate. 4 MODEL ANALYSIS FOR OLTAGE STABILITY STUDIES A ower system s voltage stable, at a gven operatng conton, f for every bus n the system, bus voltage magntue ncreases as reactve power njecton at the same bus s ncrease. A system s voltage unstable f, for at least one bus n the system, bus voltage magntue ecreases as the reactve power njectons at the same bus s ncrease. In other wors, a system s voltage stable f -Q senstvty s postve for every bus an unstable f -Q senstvty s negatve for at least one bus. The lnearse steay state system power voltage equatons are gven by equaton (19) Δ θ Δθ (6) Q θ Qv Δ Where Δ ncremental change n bus real power ncremental change n bus reactve power njecton. Δθ ncremental change n bus voltage angle. Δθ1max maxj 1j, Δ ncremental change n bus voltage magntue. Δθgmax Max g, System voltage stablty s affecte by both & Q. However, at each operatng pont s ept constant an voltage stablty s evaluate by conserng the ncremental relatonshp between Q an. Although ncremental changes n are neglecte n the formulaton, the effects of change n system loa or power transfer levels are taen nto account by stuyng the ncremental relatonshp between Q an at fferent operatng contons. let Δ 0 then, (qv - qθ -1 pθ pv) Δ (7) R Δ An Δ -1 R (8) R s calle the reuce acoban matrx of the system; R s the matrx whch rectly relates the bus voltage magntue an bus reactve power njectons. Elmnatng the real power an angle part from the system steay state equatons allows one to concentrate on the stuy of the reactve eman an supply problem of the system as well as to mnmze computatonal efforts. ARTICIATION FACTORS artcpaton Factor:- The relatve partcpaton of bus n moe s gven by bus partcpaton factor. ζ η Where ncates the contrbuton of the th egen value to the _ Q senstvty at bus. The bgger the value of, the more λ contrbutes n etermnng Q senstvty at bus. For all the small egen values, bus partcpaton factors etermne the areas close to voltage nstablty. partcpaton factors etermne the areas assocate wth each moe. The sze of the bus partcpaton n a gven moe ncates the effectveness of remeal actons apple at that bus n stablzng the moe. The sum of all the bus partcpaton for each moe s equal to unty. Branch artcpatons:- When the change n reactve power njectons n Δ Qm, the resultng voltage varatons s Δm an the moel angle varaton s, Δθm - -1 pθ pv Δm Wth Δ an Δθ nown, the lnearse reactve loss varaton across transmsson branch 1j, 1j, an the lnearse reactve power output varaton at generator g, g, can be calculate, Let, The partcpaton factor of branch j to moe I s efne as, 1j 1j 1max (9) Branch artcpatons thus ncate, for each moe, branches consume the most reactve power for a gven for a ncremental change s reactve loa. Branches wth hgh 1j are those whch cause moe I to be wea. The branch partcpaton thus proves valuable nformaton regarng.. Remeal actons n terms of transmsson branch enhancement an restrbutng the power flow to allevate the loang on that branch,. Crtera for contngency selecton, The partcpaton factor of generator g to moe s efne as, ncremental change n system reactve loang.e g (30) gmax Generator partcpatons prove mportant nformaton s regarng proper strbuton of reactve reserves among all

5 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl machnes n orer to mantan an aequate voltage stablty margn. 5 TEST SYSTEM AND RESULTS A Computer program has been evelope to conuct the moal analyss of the system. The program s teste wth the small system shown n Fg. 3 the test s conucte n such a way that, the operatng ponts are vare by mplementng a step change n reactve power at bus 3 (n steps of 0.05 p.u), startng from 0 p.u an ncrementng untl, the loa flow fals to converge. REFERENCES [1].Kunur, ower Systems stablty an Control, Mc.Graw Hll Inc. Fg.3. Four Two Generator Test System New Yor (Boo). [] C.W. Taylor, ower system voltage stablty, Mc.Graw Hll Internatonal Etons; New Yor, 1994 (Boo) The results obtane at fferent operatng contons are [3] A.R. Bergen, ower System Analyss, rentce Hall Inc. presente n the Table.1. Englewoo Clffs, New ersey 0763, 1986 (Boo) [4] I.A. Hsens, D..Hll, Energy Functons, transent stablty an OERATING OINT voltage behavor n power systems wth non-lnear loas, IEEE TABLE I Moel Analyss Results at Dfferent Operatng onts Q pu Q pu oltage Senstvty oltage Senstvty BUS BUS BUS BUS Egen alue Egen alue Egen alue Egen alue BUS ARTICIIATION BUS ARTICIIATION art. art. art. art BRANCH ARTICIIATION BRANCH ARTICIIATION. art. art. art. art CONCLUSION The funamental am behn ths paper s to evelop some tools whch help n prectng the behavor of a complex system wth respect to system we voltage relate performance as the loang on encounter ther lmts. The thess wor one establshng of effect of reactve power on the voltage stablty of a power system. The wor one s establshe on a sample 4 bus test system. The Egen value analyss metho normally nown as the moal analyss s use for ths stuy. It s observe that as an when the reactve power s ncrease on a Q bus, the mnmum value of the Egen values s ecreasng whch ncates that the stablty of the system s ecreasng an when the system s unstable the Egen value becomes zero. The stuy was supporte by many other factors such as the bus an branch partcpaton factor an voltage senstvty whch gves a measure of the system stablty. Trans on ower Systems, ol.4,.4, Oct 1989, [5].A. Lof, et.al., Fast calculatons of a voltage stablty nex, IEEE Trans. On ower Systems, ol. 7,.1 February, 199. [6] B.Scott, Revew of loa flow calculatons methos, IEEE roceengs ol. 6.7, pp , uly [7] B.Gao, G.K.Marrson,.Kunur, oltage Stablty Evaluaton usng moal Analyss, IEEE Trans an power systems, ol.7,. 4, pp , vember, 199. [8] oltage stablty of power systems: Concepts analytcal tools an nustry experence, Report prepare by IEEE worng group on voltage stablty, 1990(Boo). [9] K.Walve, Moellng of power systems components at severe sturbances, CIGRE report 38-18, ars, August, 7-September,4, [10] W.R.Lachs, oltage Collapse n EH ower Systems, IEEE paper A 78057, 1978 IEEE/ES Wster meetng, New Yor, an/feb [11].Ajarappu an C. Chrsty, The Contnuaton ower Flow: A tool for steay state voltage stablty analyss, IEEE ICA conference proceengs, pp , May, [1] N. Flatabo, R.Ogeneal, an T. Carlsen, oltage Stablty contons n a power transmsson systems calculate by senstvty methos, IEEE Trans. On power systems, ol. 5,.4, pp , vember, [13] Y.Tamura, H.Mor an S. Iwamoto, Relatonshp between voltage nstablty an multple an flow solutons n electrc power

6 Internatonal ournal of Scentfc & Engneerng Research, olume 5, Issue 4, Aprl systems;, IEEE Trans. On power systems. ol. AS10,.5, pp, , May,

Chapter - 2. Distribution System Power Flow Analysis

Chapter - 2. Distribution System Power Flow Analysis Chapter - 2 Dstrbuton System Power Flow Analyss CHAPTER - 2 Radal Dstrbuton System Load Flow 2.1 Introducton Load flow s an mportant tool [66] for analyzng electrcal power system network performance. Load

More information

ELE B7 Power Systems Engineering. Power Flow- Introduction

ELE B7 Power Systems Engineering. Power Flow- Introduction ELE B7 Power Systems Engneerng Power Flow- Introducton Introducton to Load Flow Analyss The power flow s the backbone of the power system operaton, analyss and desgn. It s necessary for plannng, operaton,

More information

On the Coordinated Control of Multiple HVDC Links: Modal Analysis Approach

On the Coordinated Control of Multiple HVDC Links: Modal Analysis Approach R. Erksson an V. Knazkns / GMSARN nternatonal Journal 2 (2008) 15-20 On the Coornate Control of Multple HVDC Lnks: Moal Analyss Approach Robert Erksson an Valerjs Knazkns Abstract There are several possbltes

More information

EEE 241: Linear Systems

EEE 241: Linear Systems EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they

More information

Inductance Calculation for Conductors of Arbitrary Shape

Inductance Calculation for Conductors of Arbitrary Shape CRYO/02/028 Aprl 5, 2002 Inductance Calculaton for Conductors of Arbtrary Shape L. Bottura Dstrbuton: Internal Summary In ths note we descrbe a method for the numercal calculaton of nductances among conductors

More information

SIMPLIFIED MODEL-BASED OPTIMAL CONTROL OF VAV AIR- CONDITIONING SYSTEM

SIMPLIFIED MODEL-BASED OPTIMAL CONTROL OF VAV AIR- CONDITIONING SYSTEM Nnth Internatonal IBPSA Conference Montréal, Canaa August 5-8, 2005 SIMPLIFIED MODEL-BASED OPTIMAL CONTROL OF VAV AIR- CONDITIONING SYSTEM Nabl Nassf, Stanslaw Kajl, an Robert Sabourn École e technologe

More information

Field and Wave Electromagnetic. Chapter.4

Field and Wave Electromagnetic. Chapter.4 Fel an Wave Electromagnetc Chapter.4 Soluton of electrostatc Problems Posson s s an Laplace s Equatons D = ρ E = E = V D = ε E : Two funamental equatons for electrostatc problem Where, V s scalar electrc

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

ENGI9496 Lecture Notes Multiport Models in Mechanics

ENGI9496 Lecture Notes Multiport Models in Mechanics ENGI9496 Moellng an Smulaton of Dynamc Systems Mechancs an Mechansms ENGI9496 Lecture Notes Multport Moels n Mechancs (New text Secton 4..3; Secton 9.1 generalzes to 3D moton) Defntons Generalze coornates

More information

Chapter Newton s Method

Chapter Newton s Method Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

ADVANCED PROBABILISTIC POWER FLOW METHODOLOGY

ADVANCED PROBABILISTIC POWER FLOW METHODOLOGY ADVANCED ROBABILITIC OWER FLOW METHODOLOY eorge tefopoulos, A.. Melopoulos an eorge J. Cokknes chool of Electrcal an Computer Engneerng eorga Insttute of Technology Atlanta, eorga 333-5, UA Abstract A

More information

SIO 224. m(r) =(ρ(r),k s (r),µ(r))

SIO 224. m(r) =(ρ(r),k s (r),µ(r)) SIO 224 1. A bref look at resoluton analyss Here s some background for the Masters and Gubbns resoluton paper. Global Earth models are usually found teratvely by assumng a startng model and fndng small

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

1 GSW Iterative Techniques for y = Ax

1 GSW Iterative Techniques for y = Ax 1 for y = A I m gong to cheat here. here are a lot of teratve technques that can be used to solve the general case of a set of smultaneous equatons (wrtten n the matr form as y = A), but ths chapter sn

More information

A Hybrid Variational Iteration Method for Blasius Equation

A Hybrid Variational Iteration Method for Blasius Equation Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method

More information

Determining Transmission Losses Penalty Factor Using Adaptive Neuro Fuzzy Inference System (ANFIS) For Economic Dispatch Application

Determining Transmission Losses Penalty Factor Using Adaptive Neuro Fuzzy Inference System (ANFIS) For Economic Dispatch Application 7 Determnng Transmsson Losses Penalty Factor Usng Adaptve Neuro Fuzzy Inference System (ANFIS) For Economc Dspatch Applcaton Rony Seto Wbowo Maurdh Hery Purnomo Dod Prastanto Electrcal Engneerng Department,

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

More information

Review of Taylor Series. Read Section 1.2

Review of Taylor Series. Read Section 1.2 Revew of Taylor Seres Read Secton 1.2 1 Power Seres A power seres about c s an nfnte seres of the form k = 0 k a ( x c) = a + a ( x c) + a ( x c) + a ( x c) k 2 3 0 1 2 3 + In many cases, c = 0, and the

More information

VOLTAGE SENSITIVITY BASED TECHNIQUE FOR OPTIMAL PLACEMENT OF SWITCHED CAPACITORS

VOLTAGE SENSITIVITY BASED TECHNIQUE FOR OPTIMAL PLACEMENT OF SWITCHED CAPACITORS VOLTAGE SENSITIVITY BASED TECHNIQUE FOR OPTIMAL PLACEMENT OF SWITCHED CAPACITORS M. Rodríguez Montañés J. Rquelme Santos E. Romero Ramos Isotrol Unversty of Sevlla Unversty of Sevlla Sevlla, Span Sevlla,

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

Proceedings of the 10th WSEAS International Confenrence on APPLIED MATHEMATICS, Dallas, Texas, USA, November 1-3,

Proceedings of the 10th WSEAS International Confenrence on APPLIED MATHEMATICS, Dallas, Texas, USA, November 1-3, roceedngs of the 0th WSEAS Internatonal Confenrence on ALIED MATHEMATICS, Dallas, Texas, USA, November -3, 2006 365 Impact of Statc Load Modelng on Industral Load Nodal rces G. REZA YOUSEFI M. MOHSEN EDRAM

More information

2016 Wiley. Study Session 2: Ethical and Professional Standards Application

2016 Wiley. Study Session 2: Ethical and Professional Standards Application 6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

AGC Introduction

AGC Introduction . Introducton AGC 3 The prmary controller response to a load/generaton mbalance results n generaton adjustment so as to mantan load/generaton balance. However, due to droop, t also results n a non-zero

More information

State Estimation. Ali Abur Northeastern University, USA. September 28, 2016 Fall 2016 CURENT Course Lecture Notes

State Estimation. Ali Abur Northeastern University, USA. September 28, 2016 Fall 2016 CURENT Course Lecture Notes State Estmaton Al Abur Northeastern Unversty, USA September 8, 06 Fall 06 CURENT Course Lecture Notes Operatng States of a Power System Al Abur NORMAL STATE SECURE or INSECURE RESTORATIVE STATE EMERGENCY

More information

x i1 =1 for all i (the constant ).

x i1 =1 for all i (the constant ). Chapter 5 The Multple Regresson Model Consder an economc model where the dependent varable s a functon of K explanatory varables. The economc model has the form: y = f ( x,x,..., ) xk Approxmate ths by

More information

Army Ants Tunneling for Classical Simulations

Army Ants Tunneling for Classical Simulations Electronc Supplementary Materal (ESI) for Chemcal Scence. Ths journal s The Royal Socety of Chemstry 2014 electronc supplementary nformaton (ESI) for Chemcal Scence Army Ants Tunnelng for Classcal Smulatons

More information

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor Taylor Enterprses, Inc. Control Lmts for P Charts Copyrght 2017 by Taylor Enterprses, Inc., All Rghts Reserved. Control Lmts for P Charts Dr. Wayne A. Taylor Abstract: P charts are used for count data

More information

Chapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise.

Chapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise. Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where y + = β + β e for =,..., y and are observable varables e s a random error How can an estmaton rule be constructed for the

More information

Static Voltage Stability Assessment Using Probabilistic Power Flow to Determine the Critical PQ Buses

Static Voltage Stability Assessment Using Probabilistic Power Flow to Determine the Critical PQ Buses Majles Journal of Electrcal Engneerng Vol. 8, o. 4, December 4 Statc Voltage Stablty Assessment Usng Probablstc Power Flow to Determne e Crtcal PQ Buses Farkhonde Jabar, Behnam Mohammad Ivatloo - Department

More information

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc

More information

Georgia Tech PHYS 6124 Mathematical Methods of Physics I

Georgia Tech PHYS 6124 Mathematical Methods of Physics I Georga Tech PHYS 624 Mathematcal Methods of Physcs I Instructor: Predrag Cvtanovć Fall semester 202 Homework Set #7 due October 30 202 == show all your work for maxmum credt == put labels ttle legends

More information

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient 58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),

More information

POWER FLOW IN COMPLEX FORM BASED LOADABILITY ASSESSMENT

POWER FLOW IN COMPLEX FORM BASED LOADABILITY ASSESSMENT 54 Power flow n complex form base loaablty assessment POWER FLOW I COMPLEX FORM BASED LOADABILITY ASSESSMET PhD Iu. Axente PhD prof. I. Stratan nversty of Western Ontaro Lonon Techncal nversty of Molova

More information

A Robust and Efficient Power Series Method for Tracing PV Curves

A Robust and Efficient Power Series Method for Tracing PV Curves A Robust and Effcent Power Seres Method for Tracng PV Curves Xaomng Chen, Davd Bromberg, Xn L, Lawrence Plegg, and Gabrela Hug Electrcal and Computer Engneerng Department, Carnege Mellon Unversty 5000

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

(1) L. are all the parameter variables in the polynomials above. Wu Elimination intends to reduce the number of

(1) L. are all the parameter variables in the polynomials above. Wu Elimination intends to reduce the number of Wu Elmnaton Method Appled n Statc Analyss of the Power System QING ZHANG, and CHEN CHEN Department of Electrcal Engneerng Shangha Jao Tong Unversty 800 Dong Chuan oad, Shangha 0040 CHINA chchen@sjtu.edu.cn

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

CHAPTER 4d. ROOTS OF EQUATIONS

CHAPTER 4d. ROOTS OF EQUATIONS CHAPTER 4d. ROOTS OF EQUATIONS A. J. Clark School o Engneerng Department o Cvl and Envronmental Engneerng by Dr. Ibrahm A. Assakka Sprng 00 ENCE 03 - Computaton Methods n Cvl Engneerng II Department o

More information

New Liu Estimators for the Poisson Regression Model: Method and Application

New Liu Estimators for the Poisson Regression Model: Method and Application New Lu Estmators for the Posson Regresson Moel: Metho an Applcaton By Krstofer Månsson B. M. Golam Kbra, Pär Sölaner an Ghaz Shukur,3 Department of Economcs, Fnance an Statstcs, Jönköpng Unversty Jönköpng,

More information

Visualization of 2D Data By Rational Quadratic Functions

Visualization of 2D Data By Rational Quadratic Functions 7659 Englan UK Journal of Informaton an Computng cence Vol. No. 007 pp. 7-6 Vsualzaton of D Data By Ratonal Quaratc Functons Malk Zawwar Hussan + Nausheen Ayub Msbah Irsha Department of Mathematcs Unversty

More information

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites 7 Asa-Pacfc Engneerng Technology Conference (APETC 7) ISBN: 978--6595-443- The Two-scale Fnte Element Errors Analyss for One Class of Thermoelastc Problem n Perodc Compostes Xaoun Deng Mngxang Deng ABSTRACT

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

Topic 5: Non-Linear Regression

Topic 5: Non-Linear Regression Topc 5: Non-Lnear Regresson The models we ve worked wth so far have been lnear n the parameters. They ve been of the form: y = Xβ + ε Many models based on economc theory are actually non-lnear n the parameters.

More information

On the Multicriteria Integer Network Flow Problem

On the Multicriteria Integer Network Flow Problem BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 5, No 2 Sofa 2005 On the Multcrtera Integer Network Flow Problem Vassl Vasslev, Marana Nkolova, Maryana Vassleva Insttute of

More information

PHZ 6607 Lecture Notes

PHZ 6607 Lecture Notes NOTE PHZ 6607 Lecture Notes 1. Lecture 2 1.1. Defntons Books: ( Tensor Analyss on Manfols ( The mathematcal theory of black holes ( Carroll (v Schutz Vector: ( In an N-Dmensonal space, a vector s efne

More information

PERFORMANCE OF HEAVY-DUTY PLANETARY GEARS

PERFORMANCE OF HEAVY-DUTY PLANETARY GEARS THE INTERNATIONAL CONFERENCE OF THE CARPATHIAN EURO-REGION SPECIALISTS IN INDUSTRIAL SYSTEMS 6 th edton PERFORMANCE OF HEAVY-DUTY PLANETARY GEARS Attla Csobán, Mhály Kozma 1, 1 Professor PhD., Eng. Budapest

More information

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

The equation of motion of a dynamical system is given by a set of differential equations. That is (1) Dynamcal Systems Many engneerng and natural systems are dynamcal systems. For example a pendulum s a dynamcal system. State l The state of the dynamcal system specfes t condtons. For a pendulum n the absence

More information

A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS

A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS HCMC Unversty of Pedagogy Thong Nguyen Huu et al. A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS Thong Nguyen Huu and Hao Tran Van Department of mathematcs-nformaton,

More information

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

More information

A Modified Approach for Continuation Power Flow

A Modified Approach for Continuation Power Flow 212, TextRoad Publcaton ISSN 29-434 Journal of Basc and Appled Scentfc Research www.textroad.com A Modfed Approach for Contnuaton Power Flow M. Beragh*, A.Rab*, S. Mobaeen*, H. Ghorban* *Department of

More information

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor Taylor Enterprses, Inc. Adjusted Control Lmts for U Charts Copyrght 207 by Taylor Enterprses, Inc., All Rghts Reserved. Adjusted Control Lmts for U Charts Dr. Wayne A. Taylor Abstract: U charts are used

More information

e i is a random error

e i is a random error Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where + β + β e for,..., and are observable varables e s a random error How can an estmaton rule be constructed for the unknown

More information

ECONOMICS 351*-A Mid-Term Exam -- Fall Term 2000 Page 1 of 13 pages. QUEEN'S UNIVERSITY AT KINGSTON Department of Economics

ECONOMICS 351*-A Mid-Term Exam -- Fall Term 2000 Page 1 of 13 pages. QUEEN'S UNIVERSITY AT KINGSTON Department of Economics ECOOMICS 35*-A Md-Term Exam -- Fall Term 000 Page of 3 pages QUEE'S UIVERSITY AT KIGSTO Department of Economcs ECOOMICS 35* - Secton A Introductory Econometrcs Fall Term 000 MID-TERM EAM ASWERS MG Abbott

More information

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth

More information

High-Order Hamilton s Principle and the Hamilton s Principle of High-Order Lagrangian Function

High-Order Hamilton s Principle and the Hamilton s Principle of High-Order Lagrangian Function Commun. Theor. Phys. Bejng, Chna 49 008 pp. 97 30 c Chnese Physcal Socety Vol. 49, No., February 15, 008 Hgh-Orer Hamlton s Prncple an the Hamlton s Prncple of Hgh-Orer Lagrangan Functon ZHAO Hong-Xa an

More information

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems Chapter. Ordnar Dfferental Equaton Boundar Value (BV) Problems In ths chapter we wll learn how to solve ODE boundar value problem. BV ODE s usuall gven wth x beng the ndependent space varable. p( x) q(

More information

Global Sensitivity. Tuesday 20 th February, 2018

Global Sensitivity. Tuesday 20 th February, 2018 Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values

More information

Indeterminate pin-jointed frames (trusses)

Indeterminate pin-jointed frames (trusses) Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all

More information

Note 10. Modeling and Simulation of Dynamic Systems

Note 10. Modeling and Simulation of Dynamic Systems Lecture Notes of ME 475: Introducton to Mechatroncs Note 0 Modelng and Smulaton of Dynamc Systems Department of Mechancal Engneerng, Unversty Of Saskatchewan, 57 Campus Drve, Saskatoon, SK S7N 5A9, Canada

More information

Second Order Analysis

Second Order Analysis Second Order Analyss In the prevous classes we looked at a method that determnes the load correspondng to a state of bfurcaton equlbrum of a perfect frame by egenvalye analyss The system was assumed to

More information

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force.

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force. Secton 1. Dynamcs (Newton s Laws of Moton) Two approaches: 1) Gven all the forces actng on a body, predct the subsequent (changes n) moton. 2) Gven the (changes n) moton of a body, nfer what forces act

More information

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification E395 - Pattern Recognton Solutons to Introducton to Pattern Recognton, Chapter : Bayesan pattern classfcaton Preface Ths document s a soluton manual for selected exercses from Introducton to Pattern Recognton

More information

November 5, 2002 SE 180: Earthquake Engineering SE 180. Final Project

November 5, 2002 SE 180: Earthquake Engineering SE 180. Final Project SE 8 Fnal Project Story Shear Frame u m Gven: u m L L m L L EI ω ω Solve for m Story Bendng Beam u u m L m L Gven: m L L EI ω ω Solve for m 3 3 Story Shear Frame u 3 m 3 Gven: L 3 m m L L L 3 EI ω ω ω

More information

#64. ΔS for Isothermal Mixing of Ideal Gases

#64. ΔS for Isothermal Mixing of Ideal Gases #64 Carnot Heat Engne ΔS for Isothermal Mxng of Ideal Gases ds = S dt + S T V V S = P V T T V PV = nrt, P T ds = v T = nr V dv V nr V V = nrln V V = - nrln V V ΔS ΔS ΔS for Isothermal Mxng for Ideal Gases

More information

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram Adabatc Sorpton of Ammona-Water System and Depctng n p-t-x Dagram J. POSPISIL, Z. SKALA Faculty of Mechancal Engneerng Brno Unversty of Technology Techncka 2, Brno 61669 CZECH REPUBLIC Abstract: - Absorpton

More information

Week 11: Differential Amplifiers

Week 11: Differential Amplifiers ELE 0A Electronc rcuts Week : Dfferental Amplfers Lecture - Large sgnal analyss Topcs to coer A analyss Half-crcut analyss eadng Assgnment: hap 5.-5.8 of Jaeger and Blalock or hap 7. - 7.3, of Sedra and

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased

More information

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin Proceedngs of the 007 Wnter Smulaton Conference S G Henderson, B Bller, M-H Hseh, J Shortle, J D Tew, and R R Barton, eds LOW BIAS INTEGRATED PATH ESTIMATORS James M Calvn Department of Computer Scence

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

4DVAR, according to the name, is a four-dimensional variational method.

4DVAR, according to the name, is a four-dimensional variational method. 4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and

More information

Term Project - select journal paper and outline. Completed analysis due end

Term Project - select journal paper and outline. Completed analysis due end EE 5200 - Lecture 30 Fr ov 4, 2016 Topcs for Today: Announcements Term Project - select journal paper and outlne. Completed analyss due end of Week 12. Submt va e-mal as mn-lecture.ppt wth voce narraton.

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

More information

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information

FUZZY GOAL PROGRAMMING VS ORDINARY FUZZY PROGRAMMING APPROACH FOR MULTI OBJECTIVE PROGRAMMING PROBLEM

FUZZY GOAL PROGRAMMING VS ORDINARY FUZZY PROGRAMMING APPROACH FOR MULTI OBJECTIVE PROGRAMMING PROBLEM Internatonal Conference on Ceramcs, Bkaner, Inda Internatonal Journal of Modern Physcs: Conference Seres Vol. 22 (2013) 757 761 World Scentfc Publshng Company DOI: 10.1142/S2010194513010982 FUZZY GOAL

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

Chapter 9: Statistical Inference and the Relationship between Two Variables

Chapter 9: Statistical Inference and the Relationship between Two Variables Chapter 9: Statstcal Inference and the Relatonshp between Two Varables Key Words The Regresson Model The Sample Regresson Equaton The Pearson Correlaton Coeffcent Learnng Outcomes After studyng ths chapter,

More information

Singular Value Decomposition: Theory and Applications

Singular Value Decomposition: Theory and Applications Sngular Value Decomposton: Theory and Applcatons Danel Khashab Sprng 2015 Last Update: March 2, 2015 1 Introducton A = UDV where columns of U and V are orthonormal and matrx D s dagonal wth postve real

More information

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations Physcs 171/271 -Davd Klenfeld - Fall 2005 (revsed Wnter 2011) 1 Dervaton of Rate Equatons from Sngle-Cell Conductance (Hodgkn-Huxley-lke) Equatons We consder a network of many neurons, each of whch obeys

More information

3. MODELING OF PARALLEL THREE-PHASE CURRENT-UNIDIRECTIONAL CONVERTERS 3. MODELING OF PARALLEL THREE-PHASE CURRENT-

3. MODELING OF PARALLEL THREE-PHASE CURRENT-UNIDIRECTIONAL CONVERTERS 3. MODELING OF PARALLEL THREE-PHASE CURRENT- 3. MOEING OF PARAE THREE-PHASE URRENT-UNIIRETIONA ONERTERS 3. MOEING OF PARAE THREE-PHASE URRENT- UNIIRETIONA ONERTERS Ths chater eelos the moels of the arallel three-hase current-unrectonal swtch base

More information

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA 14 th Internatonal Users Conference Sesson: ALE-FSI Statstcal Energy Analyss for Hgh Frequency Acoustc Analyss wth Zhe Cu 1, Yun Huang 1, Mhamed Soul 2, Tayeb Zeguar 3 1 Lvermore Software Technology Corporaton

More information

V.C The Niemeijer van Leeuwen Cumulant Approximation

V.C The Niemeijer van Leeuwen Cumulant Approximation V.C The Nemejer van Leeuwen Cumulant Approxmaton Unfortunately, the decmaton procedure cannot be performed exactly n hgher dmensons. For example, the square lattce can be dvded nto two sublattces. For

More information

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Solutions to exam in SF1811 Optimization, Jan 14, 2015 Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable

More information

CHAPTER 2 MULTI-OBJECTIVE GENETIC ALGORITHM (MOGA) FOR OPTIMAL POWER FLOW PROBLEM INCLUDING VOLTAGE STABILITY

CHAPTER 2 MULTI-OBJECTIVE GENETIC ALGORITHM (MOGA) FOR OPTIMAL POWER FLOW PROBLEM INCLUDING VOLTAGE STABILITY 26 CHAPTER 2 MULTI-OBJECTIVE GENETIC ALGORITHM (MOGA) FOR OPTIMAL POWER FLOW PROBLEM INCLUDING VOLTAGE STABILITY 2.1 INTRODUCTION Voltage stablty enhancement s an mportant tas n power system operaton.

More information

Introduction. - The Second Lyapunov Method. - The First Lyapunov Method

Introduction. - The Second Lyapunov Method. - The First Lyapunov Method Stablty Analyss A. Khak Sedgh Control Systems Group Faculty of Electrcal and Computer Engneerng K. N. Toos Unversty of Technology February 2009 1 Introducton Stablty s the most promnent characterstc of

More information

Module 3: Element Properties Lecture 1: Natural Coordinates

Module 3: Element Properties Lecture 1: Natural Coordinates Module 3: Element Propertes Lecture : Natural Coordnates Natural coordnate system s bascally a local coordnate system whch allows the specfcaton of a pont wthn the element by a set of dmensonless numbers

More information

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS)

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS) Some Comments on Acceleratng Convergence of Iteratve Sequences Usng Drect Inverson of the Iteratve Subspace (DIIS) C. Davd Sherrll School of Chemstry and Bochemstry Georga Insttute of Technology May 1998

More information

Math1110 (Spring 2009) Prelim 3 - Solutions

Math1110 (Spring 2009) Prelim 3 - Solutions Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.

More information

Electrical Circuits II (ECE233b)

Electrical Circuits II (ECE233b) Electrcal Crcuts (ECE33b SteadyState Power Analyss Anests Dounas The Unersty of Western Ontaro Faculty of Engneerng Scence SteadyState Power Analyss (t AC crcut: The steady state oltage and current can

More information

Hierarchical State Estimation Using Phasor Measurement Units

Hierarchical State Estimation Using Phasor Measurement Units Herarchcal State Estmaton Usng Phasor Measurement Unts Al Abur Northeastern Unversty Benny Zhao (CA-ISO) and Yeo-Jun Yoon (KPX) IEEE PES GM, Calgary, Canada State Estmaton Workng Group Meetng July 28,

More information

IV. Performance Optimization

IV. Performance Optimization IV. Performance Optmzaton A. Steepest descent algorthm defnton how to set up bounds on learnng rate mnmzaton n a lne (varyng learnng rate) momentum learnng examples B. Newton s method defnton Gauss-Newton

More information