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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 41, NO. 4, JULY/AUGUST 2005 1099

Dynamic Simulation and Analysis of ParallelSelf-Excited Induction Generators for

Islanded Wind Farm SystemsBhaskara Palle, M. Godoy Simões, Senior Member, IEEE, and Felix A. Farret

Abstract—In this paper, a dynamic mathematical model to de-scribe the transient behavior of a system of self-excited inductiongenerators (SEIGs) operating in parallel and supplying a commonload is proposed. Wind turbines with SEIGs are increasingly beingused to generate clean renewable energy in rural areas owing tomany economical advantages. Parallel operation of SEIGs isrequired where the size of the machine is a constraint. SEIGsconnected in parallel experience various transient conditions suchas generator/load/capacitor switching that are not easy to simulateusing conventional models. An automatic numerical solution topredict the steady-state and transient behavior of any number ofSEIGs connected in parallel is proposed in this paper. The genera-tors can be of different ratings and can have different prime moverspeeds. The performance of the proposed model when subjected tovarious dynamic scenarios is compared with experimental results.The simulation results are in good agreement with the experi-mental results, confirming the validity of the proposed model. Anaggregated model of a small wind power system is also proposed.This model was applied to a two-wind turbine case, which can beextended to simulate a complete wind generating system.

Index Terms—Induction generators, parallel machines,state-space methods, transient analysis.

NOMENCLATURE

, Stator and rotor voltage., Stator and rotor current., Load voltage and load current.

Magnetization current.Flux linkage.Rotor angular frequency.

, Stator ad rotor resistance., Stator and rotor leakage inductance.

Mutual inductance.Number of poles.

Paper ICPSD-05–04, presented at the 2004 Industry Applications SocietyAnnual Meeting, Seattle, WA, October 3–7, and approved for publication inthe IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Energy SystemsCommittee of the IEEE Industry Applications Society. Manuscript submittedfor review October 15, 2004 and released for publication March 19, 2005. Thiswork was supported by the Coordination for Improvement of Advanced Edu-cation Personal (CAPES) and by the National Science Foundation (NSF) underGrant ECS -0134130.

B. Palle and M. G. Simões are with the Engineering Division,Colorado School of Mines, Golden, CO 80401-1887 USA (e-mail:[email protected]).

F. A. Farret is with the Department of Electronics and Computation,Federal University of Santa María, Santa María 97015-003, Brazil (e-mail:[email protected]).

Digital Object Identifier 10.1109/TIA.2005.851040

Excitation capacitance., Load resistance and load inductance.

Wind turbine power.Air density.Wind speed.Propeller radius.Wind turbine power coefficient.Tip speed ratio.Wind turbine torque.Electromagnetic torque.Torque coefficient.Moment of inertia of the wind turbine.Viscous friction coefficient.

., – -axes quantities., Generator number., , Stator, rotor, and load quantities.

I. INTRODUCTION

ENVIRONMENTAL concerns and international poli-cies are supporting new interests and developments in

small-scale power generation during the last few years. Al-though the induction generator is mostly suitable for hydro andwind power plants, it can be efficiently used in prime moversdriven by diesel, biogas, natural gas, gasoline, and alcoholmotors. Induction generators have outstanding operation aseither motor or generator; they have very robust constructionfeatures, providing natural protection against short circuits, andhave the lowest cost with respect to other generators. Abruptspeed changes due to variations in load or primary source isusually expected in small power plants. An induction generator,with its solid rotor easily absorbs these variations and any surgein currents is damped by the magnetization path of its ironcore without fear of demagnetization, as opposed to permanentmagnet based generators. Therefore, the study of self-excitedinduction generators has re-gained importance, as they areparticularly suitable for generation below 15 kVA for wind andsmall hydro plants.

A stand-alone self-excited induction generator (SEIG) is un-likely to supply energy demand for ordinarily growing loads forlong time. Thus, multiple generators operating in parallel maybe required to harvest the maximum energy available at a site.Also, in the last few years, the trend has shifted from installinga few wind turbines to planning large wind farm installations

0093-9994/$20.00 © 2005 IEEE

1100 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 41, NO. 4, JULY/AUGUST 2005

Fig. 1. Induction machines supplying a common load.

with many induction generators connected electrically in par-allel [1]. Hybrid power plants that integrate wind farms with di-verse storage devices to allow for the control of the power outputof the ensemble further support the possibility of large-scale in-stallations [2]. With the resulting increased penetration of windpower into power networks, an accurate dynamic model of theoverall wind farm system is required to analyze the interactionbetween the wind farm and the power system. A system of par-allel-operated SEIGs in a wind or small hydro plant is subjectedto various transient conditions such as initial self-excitation,load transient and generator/capacitor switching. Transient in-teraction and resonant states may also be reasons for concernfor small power plants as they may create unstable oscillations,deteriorate mechanical elements and trigger protection circuits.Therefore, it is important to perform modeling and simulationanalysis of parallel-operated induction generators under tran-sient conditions. [3]–[5] developed a wind farm model that canbe used in power system dynamic simulations with steady-staterepresentation of the generator but does not deal with the tran-sient behavior of SEIGs. Understanding the transient behaviorof parallel SEIGs helps on the proper design of the power plant.Several papers [6]–[10] have been published on stand-alone op-eration of self-excited generators and only a few references areavailable on parallel-operation of SEIGs. Steady-state analysisof parallel-operated SEIGs has been discussed [11], [12] andprevious works related to transient analysis do not present clearnumerical modeling and experimental observations [13], [14].The current literature does not allow transient analysis of par-allel operation due to approximated representation of the induc-tion machine models. This paper proposes an algorithm that canbe used to simulate a wind generation system with SEIGs oper-ating in parallel.

With the proposed algorithm, any new generators can beadded or old generators can be removed from the existing par-allel generator model just by changing one variable in the statevariable matrix [15]. Fig. 1 shows wind turbines equippedwith SEIGs ready to be connected in parallel according to theload requirements or when more energy becomes available.The schematic shown in Fig. 1 seems to cope with the vastmajority of practical cases since it is always expected to havea new generator connected or disconnected from an alreadyexisting parallel association.

Section II gives a generalized model to simulate a wind gener-ation system with parallel SEIGs. Detailed models of SEIG and

Fig. 2. Aggregated model of parallel SEIGs.

Fig. 3. d–q axes equivalent circuit of an SEIG.

wind turbine are developed in Sections III and IV, respectively.The transient model developed for a stand-alone generator isextended to generators operating in parallel in Section V. Tovalidate the proposed model, simulation results of two induc-tion generators operating in parallel are compared with experi-mental results in Section VI. The proposed model is tested forvarious conditions normally encountered in a real wind genera-tion system.

II. MODEL OF A WIND GENERATION SYSTEM

One of the primary goals of this work is to develop a gen-eral model to represent parallel operated SEIGs in a wind farm.Fig. 2 shows a group of wind turbines equipped with SEIGs sup-plying an isolated load. Wind energy systems are usually com-posed of turbine, generator and load. Detailed models of eachof these components are developed in the following sections.These models are integrated to obtain the complete model of awind turbine driving an SEIG. It is shown that this aggregatedmodel could be extended to simulate multiple SEIGs connectedin parallel in a wind farm.

III. SEIG MODELING

Fig. 3 shows the – -axes equivalent circuit of a self-excitedinduction generator supplying an inductive load. The dynamicsof an induction machine can be expressed in a classic matrix

PALLE et al.: DYNAMIC SIMULATION AND ANALYSIS OF PARALLEL SEIGs SUPPLYING AN ISOLATED LOAD 1101

formulation using – -axes modeling [16] as shown in (1), atthe bottom of the next page. The representation includes theself and mutual inductances as coefficients, which are widelyused in machine theory. The following assumptions are made inthis analysis: 1) core and mechanical losses in the machine areneglected,; 2) all machine parameters except the magnetizinginductance are assumed to be constant; and 3) stator windings,self- excitation capacitors, and the load are star connected (al-though a common ground through delta connection is also ac-ceptable). Individual variation in the magnetizing inductance isincorporated in the analysis.

Traditional – -axes modeling of induction generators is notconvenient for the automatic building up of a general model ofparallel-operated induction generators. Every time a new gen-erator is switched on/off from the system, the set of differentialequations for that particular generator have to be added to/re-moved from the system, which might become cumbersome ifthe size of the system is large. Isolation of machine parame-ters from the self-excitation capacitor and load parameters is re-quired to make the process of simulating parallel operated gen-erators convenient. To isolate those parameters, (2), shown at the

bottom of the page, has been formulated using eight first-orderdifferential equations that relate the stator and rotor currents andvoltages. The matrix representation can be used for steady-stateas well as transient behavior of the parallel generator system.The simultaneous solution of this system of equations can be ob-tained using the Runge–Kutta fourth-order integration methodwith automatic adjustment of step, which gives the instanta-neous values of – -axes voltages and currents for stator androtor. See (1), shown at the bottom of the page. Equation (1) canbe expressed as a state variable matrix, which takes the form of(2), shown at the bottom of the page, which is in the form ofclassical state-space equation , or

(3)

where , , and refer, respectively, to the partition ofmatrix into matrices for the induction generator parameters,the self-excitation capacitance, and the load. Vector isthe transposed matrix and the submatrixes ,

and are defined as the set of equations shown at the

(1)

(2)


bottom of the page. The excitation vector of (3)is multiplied by the excitation parameter matrix , shownfollowing (therefore, defines the voltages correspondingto the residual magnetism in the machine core)

The variation of the magnetizing inductance is the mainfactor in the dynamics of the voltage build up and stabilizationin SEIGs. The relationship between magnetization inductance,

, and the magnetization current for each induction machinewas obtained experimentally. The nonlinear relationship be-tween magnetizing inductance and magnetizing current for thegenerator G1 used in the experimental setup is shown below

(4)

Fig. 4 shows the experimental and simulated plots of the tran-sient self-excitation process of a stand-alone SEIG. The terminalvoltage of the generator stabilizes when the machine reaches thesaturation level. The induction generator was operated at 1780r/min with a dc motor as prime mover. A capacitor bank of 160

F in star connection is supplying reactive power for the ma-chine and a 120- 22.5-mH star load was connected at 7.6 safter the generator was completely excited. Variation of speedobserved in the laboratory when load was applied is incorpo-rated in the numerical simulation as seen in Fig. 4(a). Remnant

Fig. 4. Self-exciatation and load response of a stand-alone SEIG. (a) Rotorspeed profile. (b) Variation in phase voltage measured during self-excitation andload switching on generator G1 (see Section V). (c) Variation in phase voltagesimulated using MATLAB.

magnetism in the machine core is also taken into account and isexplained below.

To begin the self-excitation process of the induction gener-ator, it is necessary that a certain amount of residual magnetismbe present. That is, it is a condition “sine qua non.” This effectmust also be taken into account in the simulation of the self-ex-citation process, without which it is not possible to start the nu-merical integration process. At the beginning of the integrationprocess of (2) and (4), an impulse function was used to repre-sent the transient existence of the residual magnetism that fadesaway after the first iterative step. Any other representation of theway the residual magnetism fades way may be acceptable. Thisobservation is vital in understanding the dynamics of self-exci-tation phenomenon because, it would justify the use of a smallvoltage source to the real machine for recovery of its active stateduring the occurrence of a fortuitous core de-excitation.

and


IV. MODEL FOR PARALLEL SEIGS

The model used for an isolated machine can be extended formultiple generators operating in parallel. The model to be pre-sented is according to the representation of SEIGs supplying acommon load as shown in Fig. 1. Equation (3) is generalized for

generators operating in parallel as explained below. Incominggenerators can be incorporated into the model by appending thegenerator parameter matrix ’ ’ diagonally as shown in (5). Thisis made possible by the isolating the generator, excitation capac-itance and load parameters. The matrix representation allows usto simulate the behavior of generators in parallel during theself-excitation process and in steady state, besides allowing usto analyze the transient performance under varying load condi-tions and generator switching. Equation (5) is also in the formof the classical state-space equation. State-space representationis very useful for eigenvalue and eigenvector analysis. It is alsoa powerful technique that provides deep insight into the systembehavior and greatly aid the system design

......

. . ....

...

. . . ...(5)

where

V. TURBINE MODEL

The power generated by the wind turbine is given by

(6)

where is the wind turbine power coefficient usually ex-pressed as a function of the tip speed ratio, ( ). Power coeffi-cient is not constant, but varies with the wind speed, rotationalspeed of the turbine, and turbine blade parameters. The torquegenerated by a turbine is given by

(7)

Fig. 5. Capacitance requirements of an SEIG supplying a load.

where is the torque coefficient and the electromag-netic torque generated by the induction generated is

(8)

The machine swing equation is given by

(9)

Equation (9) represents the wind turbine as a single lumped in-ertia. However, if required, (9) may be expanded to include themasses of the generator, gearbox and blades with the associatedparameters. Using an iterative process, the instantaneous primemover speed can be calculated.

VI. RESULTS AND DISCUSSION

Simulations in this paper have been developed in MATLAB®.Remnant magnetism in the machine is taken into account in thesimulation process without which it is not possible for the gen-erators to self-excite. As was said above, an impulse function isused to represent the remnant magnetic flux in the core. Fig. 5shows capacitance and speed requirements of a loaded SEIGneeded to sustain self-excitation. At lighter loads, speed andexcitation capacitance can vary over a wide range without thegenerator losing excitation. However, for heavy loads, highercapacitances are needed as SEIG absorbs more reactive powerand there are maximum and minimum speed limits for the gen-erator to produce self-excitation. The generator might collapseunder heavy loads when sufficient reactive power is not suppliedas depicted in Fig. 6. Other parameters remaining constant, themaximum load that the generator can supply is dictated by theexcitation capacitance.

Two similar induction machines driven by two dc motorswere used to investigate the proposed model experimentally.DC motors act as prime movers emulating wind-driven turbines.Variation in magnetizing inductance due to changes in load andprime mover speed has been taken into account by obtainingthe nonlinear relationship between air-gap voltage and magne-tizing current experimentally. The induction machine parame-


Fig. 6. Voltage collapse in a stand-alone SEIG under heavy load. (a) Rotorspeed profile. (b) Variation in phase voltage measured during collapse of G1.(c) Variation in phase voltage simulated.

TABLE IGENERATOR G1 RATINGS AND PARAMETERS

TABLE IIGENERATOR G2 RATINGS AND PARAMETERS

ters shown in Tables I and II are used for simulation. In additionto the stand-alone operation of an SEIG discussed in Section III,four other scenarios are discussed in this section.

First, the maximum load that an isolated SEIG can supplywith a fixed excitation capacitance was tested in the labora-tory. Load on the generator was increased until the machine canno longer supply the required load power. The generator wasexcited with a 160- F capacitance bank and a 45- 45.5-mHstar-connected inductive load was applied after the generatorwas fully excited at time s. Fig. 6 shows the experimentaland simulated plots of terminal voltage collapse of a stand-aloneSEIG (G1) when this heavy load was applied. Speed variationsobserved in the laboratory were taken into account for simula-tion, as illustrated in Fig. 6(a).

Dynamic model for parallel SEIGs presented in Section IVwas used to simulate parallel operation two SEIGs. The firstcase that was studied was the transient process of generatorswitching. Generator G1 was self-excited with 160- F capac-itance at 1800 r/min and a 130- 22.5-mH star-connected loadwas applied at time s. Drop in the terminal voltage of G1

Fig. 7. Parallel connection of two SEIGs with different voltage levels. (a)Rotor speed profile. (b) Variation in phase voltage of G1 measured. Load isapplied at t = 1:95 s and paralleling switch is closed at t = 3:85 s. (c)Simulated variation in phase voltage of G1. (d) Simulated variation in phasevoltage of G2.

Fig. 8. Parallel connection of two SEIGs with similar voltage levels. (a) Rotorspeed profile. (b) Variation in phase voltage of G1 measured. Load is applied att = 1:2 s and paralleling switch is closed at t = 4:6 s. (c) Simulated variationin phase voltage of G1. (d) Simulated variation in phase voltage of G2.

can be observed at this instant. Generator G2 which was previ-ously self-excited with 160 F at 1800 r/min was suddenly con-nected in parallel at time s. Fig. 7 shows the transientbehavior of the two generators during the generator switching.Sudden collapse in the phase voltages of the two generators canbe observed when the second generator is switched on. This isdue to the differences in phase voltages of the two generatorsat the paralleling instant. Full common voltage was recoveredat about time s. Also, from Fig. 7(a), a heavy dip in theoverall speed of the machines can be observed at the parallelinginstant. It can be noticed from Fig. 7 that the model is able tosuccessfully simulate the load and generator switching.

Synchronization techniques could be applied so as to switchthe generators when the phase voltages are at the same levels.The purpose of this result was to demonstrate the possibility ofrepresenting this worst case scenario using the proposed model.


Fig. 9. Simulation of two wind turbines operating in parallel. (a) Wind speedprofile. (b) Simulated phase voltage of G1. Load is applied at t = 36 s andparalleling switch is closed at t = 38 s. (c) Simulated phase voltage of G2.

Fig. 10. Simulation of two wind turbines operating in parallel. (a) Simulatedphase current of G1. (b) Simulated phase current of G2.

The next result (Fig. 8) shows the experimental and simu-lated plots of the transient generator switching process whenparallel connection was made between SEIGs operating at iden-tical voltage levels. As in the previous case, G1 was self-excitedwith 180- F capacitance and a 130- 22.5-mH star load wasapplied at time s. Generator G2 was already self-excitedwith 160 F and was connected in parallel at time s. Com-pared to the previous case, higher capacitance value was chosento excite G1, so that the two generators would be operating atsimilar voltage levels at the paralleling instant. No synchroniza-tion techniques were used. Full common voltage was recoveredat about time s. As the voltages were similar, there wasno collapse in the terminal voltages as observed in the previouscase and the voltage and speed dips are not very pronounced.

Fig. 9 shows the simulated plots of two 20-kW wind turbinesoperating electrically in parallel. The aggregated model shown

in Fig. 2 has been used to simulate the wind turbine with realwind conditions. This could be extended to simulate an entirewind farm with multiple wind turbines equipped with SEIGs.The wind speed profile of the two turbines is shown is Fig. 9(a).The simulated voltage variation closely follows the wind speed,thus confirming the validity of the turbine and the generatormodel. The generator begins to self-excite after the rotor hasreached a certain speed . The dip in voltage at correspondsto load switching. G2 is connected to G1 at to share the loadresulting in a slight increase in voltage.

Fig. 10 shows the simulated variation in phase currents ofgenerator G1 and G2 during the load and generator switchingprocess. The current surge experienced by the two machinesduring the switching of the second generator was very high (ap-proximately twice the rated current). However, it settled downin a few milliseconds; the system is able to sustain its excitation.

VII. CONCLUSION

This paper has presented an innovative algorithm for ana-lyzing the steady-state and transient performance of a windpower system with parallel-operated SEIGs. The approachpresented in this paper enhances previous works based onlyon steady-state conditions that cannot be used for transientanalysis. It has been shown that a new wind turbine or a gen-erator can be incorporated into the existing parallel generatormodel by appending the generator matrix simplifying thesimulation process. Performance of the parallel SEIG system isanalyzed during the initial self-excitation, load switching, andgenerator switching. Reactive power requirements and loaddemand limits are also analyzed. The simulation results closelymatch the experimental results validating the proposed matrixpartition scheme and opening new possibilities to incorporateadvanced control to monitor and optimize a parallel installationof SEIGs. A model for a wind turbine equipped with an SEIGwas presented. Simulations results for a two-wind turbine casewere presented that demonstrate the usefulness of the proposedmodel in modeling a small wind generating system.

REFERENCES

[1] F. P. de Mello and L. N. Hannett, “Large scale induction generatorsfor power systems,” IEEE Trans. Power App. Syst., vol. 100, no. 5, pp.2610–2618, May 1981.

[2] K. Strunz and E. K. Brock, “Hybrid plant of renewable stochastic sourceand multilevel storage for emission-free deterministic power genera-tion,” in Proc. CIGRE/IEEE PES Int. Symp. Electric Power DeliverySystems, Montreal, QC, Canada, Oct. 2003, pp. 214–218.

[3] A. D. Hansen, P. Sorensen, L. Janosi, and J. Bech, “Wind farm mod-eling for power quality,” in Proc. IEEE IECON’01, vol. 3, 2001, pp.1959–1964.

[4] A. E. Feijoo and J. Cidras, “Modeling of wind farms in the load flowanalysis,” IEEE Trans. Power Syst., vol. 15, no. 1, pp. 110–115, Feb.2000.

[5] J. G. Slootweg, S. W. H. de Haan, H. Polinder, and W. L. Kling, “Generalmodel for representing variable speed wind turbines in power systemdynamics simulations,” IEEE Trans. Power Syst., vol. 18, no. 1, pp.144–151, Feb. 2003.

[6] D. Seyoum, C. Grantham, F. Rahman, and M. Nagrial, “An insight intothe dynamics of loaded and free running isolated self-excited inductiongenerators,” in Proc. Int. Conf. Power Electronics, Machines and Drives,Jun. 2002, pp. 580–585.

[7] D. Seyoum, C. Grantham, and F. Rahman, “The dynamics of an isolatedself-excited induction generator driven by a wind turbine,” in Proc. IEEEIECON’01, Denver, CO, Dec. 2001, pp. 1364–1369.


[8] L. Wang and R. Y. Deng, “Transient performance of an isolated induc-tion generator under unbalanced excitation capacitors,” IEEE Trans. En-ergy Convers., vol. 14, no. 4, pp. 887–893, Dec. 1999.

[9] S. M. Alghuwainem, “Steady-state analysis of an isolated self-excitedinduction generator driven by regulated and unregulated turbine,” IEEETrans. Energy Convers., vol. 14, no. 3, pp. 718–723, Sep. 1999.

[10] D. Seyoum, M. F. Rahman, and C. Grantham, “Terminal voltage controlof a wind turbine isolated induction generator using stator oriented fieldcontrol,” in Proc. Eighteenth Annu. IEEE Power Electronics Conf. andExpo., vol. 2, Miami Beach, FL, Feb. 2003, pp. 846–852.

[11] C. Chakraborty, S. N. Bhadra, and A. K. Chattopadhyay, “Analysis ofparallel- operated self excited induction generators,” IEEE Trans. En-ergy Convers., vol. 14, no. 2, pp. 209–216, Jun. 1999.

[12] A. H. Al-Bahrani and N. H. Malik, “Steady state analysis of paralleloperated self-excited induction generators,” Proc. Inst. Elect. Eng., pt.C, vol. 140, no. 1, pp. 49–55, 1993.

[13] L. Wang and C. -H. Lee, “A novel analysis of parallel operated self-excited induction generators,” IEEE Trans. Energy Convers., vol. 13, no.2, pp. 117–123, Jun. 1998.

[14] L. Wang and C. H. Lee, “Dynamic analysis of parallel operated self-excited induction generators feeding an induction motor load,” IEEETrans. Energy Convers., vol. 14, no. 3, pp. 479–485, Sep. 1999.

[15] F. A. Farret, L. V. Canha, J. M. Correa, and M. Reckziegel, “Estudo sobrea associação de geradores de indução auto excitados usando espaço deestados,” in Proc. XII Brazilian Congr. Automation, vol. 1, Uberlandia,Brazil, 1998, pp. 105–109.

[16] N. N. Hancock, Matrix Analysis of Electrical Machinery, New York:Pergamon, 1974.

Bhaskara Palle was born in Hyderabad, India, in1980. He received the B.Tech. degree in electricaland electronics engineering from Jawaharlal NehruTechnological University, Hyderabad, India, in 2001.He is currently working toward the M.S. degreein engineering systems at the Colorado School ofMines, Golden.

His main areas of interest are power electronicsand power systems.

Marcelo Godoy Simões (S’89–M’95–SM’98)received the B.S. and M.Sc. degrees in electricalengineering from the University of São Paulo, SãoPaulo, Brazil, in 1985 and 1990, respectively, thePh.D. degree in electrical engineering from theUniversity of Tennessee, Knoxville, in 1995, and theLivre-Docência (D.Sc.) degree from the Universityof São Paulo in 1998.

He joined the faculty of the Colorado School ofMines, Golden, in 2000 and has been working to es-tablish research and education activities in the devel-

opment of intelligent control for high-power electronics applications in renew-able and distributed energy systems. He is the author of Renewable Energy Sys-tems: Design and Analysis with Induction Generators (Boca Raton, FL: CRCPress, 2004).

Dr. Simões is a recipient of a National Science Foundation (NSF)—FacultyEarly Career Development (CAREER) Award, which is the NSF’s mostprestigious award for new faculty members, recognizing innovative research ofyoung teachers/scholars. He is serving as the Program Chair for the 2005 IEEEPower Electronics Specialists Conference, General Chair of the 2005 PowerElectronics Education Workshop, Chair of the IEEE Power Electronics Chapterof the Denver Section, IEEE Power Electronics Society Intersociety Chairman,as Associate Editor for Energy Conversion, as well as Editor for IntelligentSystems, of the IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC

SYSTEMS, and as Associate Editor for Power Electronics and Drives of theIEEE TRANSACTIONS ON POWER ELECTRONICS. He is the Program Chair forPESC’05, the IEEE Power Electronics Specialists Conference, to be held inBrazil. He has been actively involved in the Steering and Organization Com-mittee of the IEEE/DOE/DOD 2005 International Future Energy Challenge.

Felix A. Farret received the B.E and M.Sc. degreesin electrical engineering from the Federal Univer-sity of Santa María, Santa María, Brazil, in 1972and 1986, respectively, the M.Sc. degree from theUniversity of Manchester, Manchester, U.K., andthe Ph.D.degree from the University of London,London, U.K.

Since 1974, he has taught in the Department ofElectronics and Computation, Federal Universityof Santa Maria. He works in an interdisciplinaryeducational background related to power electronics,

power systems, nonlinear controls, and integration of renewable energy. Hewas a Visiting Professor at the Engineering Division, Colorado School ofMines, Golden, during 2002–2003. He is currently committed to undergraduateand graduate teaching and research. Energy engineering systems are the focusof his present interests for industrial applications. He is the author of Use ofSmall Sources of Electrical Energy (santa maría, Brazil: UFSM Univ. Press,1999) and coauthor of Renewable Energy Systems: Design and Analysis withInduction Generators (Boca Raton, FL: CRC Press, 2004). In more recentyears, he has coordinated several technological processes in renewable sourcesof energy and transferred them to Brazilian enterprises, such as AES-SouthEnergy Distributor, Hydro Electrical Power Plant Generation of Nova Palma,RGE Energy Distributor, and CCE Power Control Engineering Ltd. Theseprocesses have been related to integration of micro power plants from distinctprimary sources, voltage and speed control by the load for induction generators,and low-power PEM fuel-cell applications and model development. Injectionof electrical power into the grid is currently his major interest. In Brazil, hehas been developing several intelligent systems for industrial applicationsrelated to integration, location, and sizing of renewable sources of energy fordistribution and industrial systems, including fuel cells, hydropower, windpower, photovoltaics, battery storage applications, and other ac–ac and dc–aclinks.

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