Design and Control Strategies of an Induction-Machine-Based ...

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Design and Control Strategies of an Induction-Machine-Based Flywheel Energy Storage System Associated to a Variable-Speed Wind Generator Gabriel Cimuca, Stefan Breban, Member, IEEE, Mircea M. Radulescu, Senior Member, IEEE, Christophe Saudemont, and Benoit Robyns, Member, IEEE

Abstract—Flywheel energy storage systems (FESSs) improve the quality of the electric power delivered by wind generators, and help these generators contributing to the ancillary services. Presently, FESSs containing a flux-oriented controlled induction machine (IM) are mainly considered for this kind of application. The paper proposes the direct torque control (DTC) for an IM-based FESS associated to a variable-speed wind generator, and proves through simulation and experimental results that it could be a better alternative. This DTC application entails two specific aspects: 1) the IM must operate in the flux-weakening region, and 2) it must shift quickly and repeatedly between motoring and generating operation modes. DTC improvement for increasing the FESS efficiency, when it operates at small power values, is discussed. Some aspects concerning the flywheel design and the choice of the filter used in the FESS supervisor are also addressed. Index Terms—DC-link voltage regulation, direct torque control (DTC), flywheel energy storage, flux-oriented controlled (FOC), induction machine (IM), power flow supervision, variable-speed wind generator (VSWG).

I. INTRODUCTION HE LIBERALIZATION of the European electricity market and the development of the decentralized electricity production reveal new scientific and technical problems related to the new type of electricity sources, as well as to the structure and control of power grids [1].

T

Manuscript received April 18, 2007; revised December 7, 2007; accepted October 22, 2008. Date of current version May 21, 2010. This work was supported in part by the Romanian Ministry of Education and Research. The test bench development was supported by the Regional Council Nord-Pas de Calais, by the European Regional Development Fund, by the Technological Research National Center, Lille, by the Forclum Ing´enierie Verquin, Innovelect, and by the Ecole des Hautes Etudes d’Ing´enieur. Paper no. TEC-00121-2007. G. Cimuca is with the Powertrain Control Group, Renault Technologie Roumanie, Bucharest 077190, Romania (e-mail: [email protected]). S. Breban and M. M. Radulescu are with the Department of Electric Machines and Special Electric Machines and Light Electric Traction Group, Technical University of Cluj-Napoca, Cluj-Napoca 400020, Romania (e-mail: [email protected]; [email protected]). C. Saudemont and B. Robyns are with the Laboratoire d’Electrotechnique et d’Electronique de Puissance de Lille, Ecole des Hautes Etudes d’Ing´enieur, Lille C´edex 59046, France (e-mail: [email protected]; [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TEC.2010.2045925

The actual decentralized electricity sources cannot participate in the ancillary services of the power grid (voltage and frequency control, black start, and islanding operation). From the viewpoint of the power grid, these sources are like negative charges, i.e., they do not consume the electric energy but generate it, without participating in the ancillary services. The mains voltage and frequency control is always reported to the classical generators. Hence, the penetration rate (i.e., the ratio of the generated power to the consumed power) of the decentralized electricity production is restricted in order to keep the power grid’s stability. This is particularly right for the renewable energy sources, whose primary energy source is very fluctuant and unpredictable. The wind generators belong to this category of energy sources, and to give them the possibility to participate in the ancillary services, a generating system, which is able to feed isolated loads or to be integrated in the network, has to be considered. In order to reach these objectives, an energy buffer is needed for controlling the power flow between the wind generator and the power grid [2]–[9]. In this paper, the energy buffer is represented by a flywheel energy storage system (FESS). During the past decade, FESSs have been rediscovered by the industry due to their advantages in comparison with other energy storage systems. FESSs have thus found a specific application in enhancing the electric power quality, as far as voltage and frequency are kept within preset limits. By virtue of their high dynamics, long lifetime, and good efficiency, FESSs are well suited for short-term storage systems, which are generally sufficient to improve the electric power quality [10]–[12]. In this paper, a low-speed FESS coupled to a variable-speed wind generator (VSWG) is investigated. Fig. 1 provides a block diagram of the VSWG–FESS assembly under study. By means of power electronic converters, the energy generation and storage systems can be coupled via a dc-link circuit. In such a configuration, the FESS ensures the dc-link voltage control [3], [4], thus contributing to the generation/consumption balance of energy. The power converter connected to the network can then be concerned with the mains voltage and frequency control, and the wind generator can contribute to the ancillary services. The FESS contains an induction machine (IM) for which the direct torque control (DTC) is proposed as an alternative to the flux-oriented control (FOC) reported in [3]–[9]. Besides, experimental results with an FESS coupled to a VSWG and

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CIMUCA et al.: DESIGN AND CONTROL STRATEGIES OF AN INDUCTION-MACHINE-BASED FLYWHEEL ENERGY STORAGE SYSTEM

Fig. 1.

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VSWG–FESS assembly under study. Fig. 2.

controlled by both techniques (FOC and DTC) are presented further in this paper, emphasizing the advantages of the DTC. In the proposed IM control strategy, the flux reference is determined as a function of the IM electromagnetic torque. By accounting for torque variations due to wind power fluctuations, the flux reference enables to reduce IM iron losses, and thus, increase the efficiency. It is to be noted that the DTC is achieved under flux weakening, and the IM continuously shifts between motor and generator operation modes. The experimental results were obtained with a 3-kW laboratory test bench for an IM-based FESS built at the Ecole des Hautes Etudes d’Ing´enieur (HEI) Lille, France. The test bench emulates an FESS associated to a VSWG and generates electric power into the laboratory power grid. It is fully described in [12] and [15]. The next two sections deal with the flywheel design and the control of the FESS. In Section IV, the choice of the filter constant for the FESS supervisor is addressed. Section V presents the IM DTC and FOC strategies. A method to increase the IM efficiency is also discussed. Comparative simulation and experimental results are then reported. Finally, Section VI makes a comparison between energy-efficiency performances of FOC and DTC. II. FLYWHEEL DESIGN CONSIDERATIONS The mechanical part of the FESS is represented by the flywheel itself. When designing a flywheel for an FESS, two constraints must be taken into account: 1) the maximum revolution speed and 2) the energy-storage capacity. Fig. 2 presents an ordinary flywheel with its geometrical parameters. The flywheel design must begin by choosing the inner radius ri . It depends on the mechanical shaft, which must support the flywheel weight, ensure the coupling between the flywheel and the electric machine, and bear the maximum torque of the electric machine. The highest revolution speed of the flywheel Ωfly is proportional to the maximum speed of the electric machine Ωm ax by a safety coefficient k (greater than unity) Ωfly = kΩm ax .

(1)

The outer radius ro of the flywheel can take any value from the interval ri < ro ≤ rom ax with rom ax calculated as follows:
σadm 1 ro m ax = (2) Ωfly ρ

Flywheel geometry.

or, more accurately, as follows:  4σadm 1−µ 2 r − ro m ax = 2 (3 + µ)ρΩfly 3+µ i

(3)

where σadm is the admissible stress of the flywheel material, ρ is the flywheel density, and µ is the Poisson coefficient. The inertia of the flywheel of Fig. 2 is expressed by  ρπh  4 ro − ri4 . (4) 2 The thickness h of the flywheel is chosen as a function of the maximum energy Em ax , which must be stored in it, and can be calculated as follows: J=

h=

4Em ax . ρπΩ2m ax (ro4 − ri4 )

(5)

Other different approaches to flywheel design aspects are given in [17]–[19]. III. CONTROL OF THE FESS The wind generators are considered as negative charges for the power grid, since they do not consume, but generate the electric energy, without participating in the ancillary services. The drawback of such generators is due to their primary energy source: the wind. As well known, the wind speed is very fluctuant, and therefore, the wind generator will deliver a variable electric power. To overcome this drawback, following two main alternatives are available: 1) acting on the mechanical system or 2) acting on the electric system. The first one is largely used in the actual wind farm, and provides satisfactory results when the wind generators are supplying a very strong grid. Nevertheless, for a weak grid or an isolated load, this type of control is no more useful. In such cases, a faster and better control must be implemented on the wind systems. This is the reason for choosing the second alternative for the power regulation. An energy buffer is needed in order to achieve a good power regulation [2]–[9]. Fig. 3 gives a graphical explanation of the control strategy. The FESS has to accomplish the following control tasks: 1) to regulate the dc-link voltage and 2) to regulate the power flow on the grid or on an isolated load. For dc-link voltage regulation, a proportional-integral (PI) voltage controller is used, and gives the value of the power ∆P necessary to keep this voltage at its reference value Vdc ref . If

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speed Ωm ax , while the electric machine operates at rated power Prat . For this case, the following expression can be written:   J Ω2m ax − Ω2b (8) τ Prat = 2 where τ is the filter constant. From (8), two expressions can be derived for the filter constant and the flywheel inertia, respectively, which are as follows:   J Ω2m ax − Ω2b τ= (9) 2Pnom Fig. 3.

Graphical representation of the FESS’ control strategy.

J=

Fig. 4.

(10)

It is obvious that the filter constant depends on the flywheel inertia. Moreover, the rated power of the FESS must be related to the filter constant. Greater the filter constant, larger Pref variations are, thus more powerful electric machine is needed.

Block diagram of the supervisor.

Preg is the power required from the FESS-VSWG assembly, and Pwg is the active power generated by the VSWG, the reference value of the active power exchanged between FESS and dc-link circuit is determined as follows: Pref = Preg − Pwg − ∆P.

2τ Pnom . (Ω2m ax − Ω2b )

(6)

From (6), the IM reference torque can be computed as follows: Pref + BΩ + Ts (7) Ω where Ω is the flywheel speed, B is the viscous friction coefficient, and Ts is the load torque. The Pref value must be limited at the IM-rated power, otherwise, the torque reference can exceed the IM torque capability; moreover, by using the DTC in generator operation mode and flux-weakening region, the IM flux cannot be regulated and falls to zero [9]. The IM used on the test bench has four pole pairs. The flywheel speed range is from 800 to 3000 r/min, the high-speed limit being imposed by mechanical constraints. Hence, the IM must operate in the flux-weakening region over an extended flywheel speed range. A fuzzy-logic-based supervisor imposes the value of the power delivered to the power grid, i.e., the value of Preg in (6). The supervisor prevents the flywheel speed from reaching its upper limits and, depending on the supervisory method and the flywheel capacity, the power delivered to the grid is much more smoothed than the wind-generated power. Fig. 4 shows the diagram of this supervisor, whose description is given in [12]. Tref =

IV. CHOICE OF THE FILTER CONSTANT The aforementioned supervisor uses filtered values of the generated power Pwgf as input. The choice of the filter constant is of paramount importance for the FESS design, being related to the flywheel capacity. This constant can be determined for the highest charging (or discharging) rate of the FESS, i.e., the flywheel is accelerated from the base speed Ωb to the maximum

V. DTC AND FOC FOR THE FESS IM A. DTC Principle In the DTC, IM torque and stator-flux amplitudes are controlled by means of two independent hysteresis controllers (see Fig. 5), and the feedback signals (T ∗ and Ψ∗ ) are calculated from IM stator voltages and currents. ∗ The stator-flux space vector Ψ is obtained from the stator voltage equation  ∗ ∗ Ψ = (V s − Rs I s )dt (11) where Rs is the stator resistance, I s is the stator-current space ∗ vector. The stator-voltage space vector V s is computed using the dc-link voltage Vdc and the inverter switch gating signals Sa , Sb , and Sc 2Vdc (Sa + e2π j /3 Sb + e4π j /3 Sc ). (12) 3 The stator-current space vector is derived from the measured currents ia , ib , and ic ∗

Vs =

2 (ia + e2π j /3 ib + e4π j /3 ic ) (13) 3 and the IM electromagnetic torque results from the dot product ∗ of I s and Ψ : Is =

3p ∗ (I s · jΨ ) (14) 2 where p is the IM pole-pair number. The power converter can deliver only eight voltage vectors, which are selected with reference to the flux sector and the hysteresis controllers’ outputs. Fig. 6 shows the variations of the stator flux corresponding to the first sector, and Table I provides all the possible voltage-vector selections. The principle of the two hysteresis controllers is presented in Fig. 7, and it can be seen that the torque controller is a three-level comparator, while the flux controller is a two-level comparator. T∗ =

CIMUCA et al.: DESIGN AND CONTROL STRATEGIES OF AN INDUCTION-MACHINE-BASED FLYWHEEL ENERGY STORAGE SYSTEM

Fig. 5.

Fig. 6.

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FESS control scheme using DTC for the IM.

Fig. 7.

Hysteresis controllers for (a) torque and (b) flux.

Fig. 8.

Operation of a discrete hysteresis controller.

IM stator-flux variations in sector 1. TABLE I SELECTION OF THE VOLTAGE VECTORS IN THE BASIC DTC

The analog hysteresis controllers have the well-known disadvantage of a variable switching frequency. However, it can be avoided by using discrete hysteresis controllers; in contrast with its analog counterpart, the discrete controller operates at fixed sampling time Ts , involving a constant switching frequency [19]. Fig. 8 shows the operation mode of the discretehysteresis torque controller. B. FOC Principle In the FOC, the d–q reference frame is locked to the rotor-flux vector. Hence, the flux and torque can be separately controlled

by the stator direct-axis current id and the quadrature-axis current iq , respectively (see Fig. 9). The q-axis stator-current reference is computed from the torque reference as follows: iq ref =

Tref L∗r pM ∗ Ψref

(15)

where M ∗ and L∗r are the estimated mutual and rotor inductances, respectively, and Ψref is the rotor-flux reference value. The d-axis stator-current reference id ref is obtained using a flux controller (see Fig. 9), and the rotor-flux position results

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Fig. 9.

IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 25, NO. 2, JUNE 2010

FESS control scheme using FOC for the IM.

from the rotor speed ωm and slip frequency ωsl  θr = (ωm + ωsl ) dt

(16)

and ωsl =

M ∗ Rr∗ iq ref L∗r Ψref

(17)

where Rr∗ is the estimated rotor resistance. As readily seen, the aforementioned equations refer to a particularly case of the FOC, i.e., the rotor flux-oriented control. C. Flux Reference Determination for the DTC From (7), the torque reference of the IM is a function of FESS’ reference power and flywheel speed. In the case of the classical DTC, the stator-flux reference is computed as follows:  Ψrat , if |Ω| ≤ Ωb Ωb (18) Ψref1 = , if |Ω| > Ωb Ψrat |Ω| where Ωb is the IM base speed and Ψrat is the IM-rated stator flux. This strategy offers good results when the IM’s load is close to the rated load. However, as it can be seen from Fig. 3, the IM’s load is steadily changing, and the IM frequently operates below its rated load. If the IM is under-load, a smaller flux is sufficient for its operation; moreover, a smaller flux yields less core losses in the IM. Based on this observation, the following method for determining the stator-flux reference is proposed:  Tp.u.  , if |Ω| ≤ Ωb  Ψrat Ψp.u. (19) Ψref2 =   Ψrat Ωb Tp.u. , if |Ω| > Ωb |Ω| Ψp.u.

where Tp.u. is the IM reference torque and Ψp.u. is the IM’s stator flux, both expressed in p.u. It should be noted that the stator-flux reference has a lower limit at 0.3 Wb; this is due to the fact that when the IM flux is too small, the IM operation becomes unstable. Simulation and experimental results clearly showed that using (19) for the stator-flux reference computation, a notable improvement of the energy efficiency is obtained when the IM’s load is much smaller than the rated load; however, if the IM’s load is closer to the rated load, the classical method of the flux reference computation leads to better IM efficiency. By combining the advantages of both methods, a real-time dynamic selection of the stator-flux reference was adopted Ψref = kΨref 1 + (1 − k)Ψref 2

(20)

where k = Tref Ω/PIM and PIM is the IM-rated power. Further in the paper, the DTC using (20) will be called “energy-efficient DTC” to distinguish it from the “classical DTC,” which uses (18). Simulations were performed in MATLAB/Simulink environment to validate the proposed method for computing the IM flux reference. As the rated power of the IM is 3 kW, the simulations were performed for 11 different power values from 500 W to 3 kW, with a step of 250 W. Therefore, the IM operates at constant power and accelerates the flywheel from 1500 to 3000 r/min (charging mode). After reaching the speed of 3000 r/min, the flywheel decelerates to 1500 r/min (discharging mode). In order to evaluate the FESS efficiency, simulations were performed for a charge/discharge cycle (CDC). By measuring the input/output energy, the FESS efficiency can be determined for each CDC [8]. The FESS efficiency results obtained from simulations are given in Fig. 10 and Table II.

CIMUCA et al.: DESIGN AND CONTROL STRATEGIES OF AN INDUCTION-MACHINE-BASED FLYWHEEL ENERGY STORAGE SYSTEM

Fig. 10. Simulation results of FESS efficiency for one CDC with IM operating at constant power in flux-weakening region.

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Fig. 12. Experimental results of FESS efficiency for one CDC with IM operating at constant power in flux-weakening region.

TABLE II FESS EFFICIENCIES FOR ONE CDC—SIMULATION RESULTS

Fig. 13.

Fig. 11.

FESS simulated energies when IM power is 500 W. TABLE III FESS EFFICIENCIES FOR ONE CDC—EXPERIMENTAL RESULTS

FESS measured energies when IM power is 500 W.

powers, the FESS efficiency obtained through simulations is greater than that resulting from experiments; this is due to the simplifications adopted in the simulation model (e.g., core losses were disregarded, albeit they increase with the stator-flux level). Lastly, it should be noted that the IM always operates in the flux-weakening region, at a speed ranging from 1500 to 3000 r/min. D. Flux Reference Determination for the FOC In the FOC case, the rotor-flux reference was computed from the IM power equation as follows: PIM ≈ Tem IM ΩIM = p

Simulation results in Fig. 11 reveal 18% efficiency improvement in the case of energy-efficient DTC, for the IM power operated at 500 W. Experiments were carried out on the test bench in order to check the simulation results. The same conditions were set, but for IM power values ranging from 500 to 1750 W; this is because the IM encounters a power step twice of reference power, when the FESS is changing its operation modes, for example, if the IM operates at 1750 W and the FESS shifts from the charging mode to the discharging one, the IM power suddenly drops to −1750 W; therefore, the IM must bear a 3.5-kW power shock, which will cause notable dc-link voltage variations. Table III and Fig. 12 provide experimental results for FESS efficiency during one CDC, and Fig. 13 displays the measured FESS energy outcome for IM operating at 500 W. By comparing Figs. 10 and 12, it can be observed that 18% efficiency improvement at 500 W is gained in both simulation and experiment, thus validating the energy-efficient method for stator-flux reference computation. Nevertheless, for higher IM

M Ψr d isq ΩIM Lr

(21)

where PIM is the IM output power, Tem IM is the IM electromagnetic torque, ΩIM is the IM mechanical speed, p is the pole-pair number, M is the mutual inductance, Lr is the rotor inductance, and Ψr d is the d-axis rotor-flux component. From (21), the rotor-flux reference value can be calculated as follows: Ψref (ΩIM ) =

1 PIM rat L∗r ∗ pM isq m ax ΩIM m es

(22)

where PIM rat is the IM rated power and ΩIM m es is the IM measured speed. In (22), the IM parameters marked with asterisk define the estimated parameters. The experimental results have proven that PIM rat value has a notable influence on the FESS efficiency [8]. VI. EXPERIMENTAL RESULTS Fig. 14 provides the wind speed, which was measured in the northern part of France, where a wind farm was installed. These wind speed values were used to control a wind turbine emulator (WTE) that drives the VSWG [12].

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Fig. 14.

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Wind speed. Fig. 18.

Fig. 15.

Flywheel speed for the FOC case.

Speed of the wind generator, without FESS.

Fig. 19. (Continuous curve) Generated power and (pointed curve) delivered power for the DTC case.

Fig. 16.

Power delivered into the power grid, without FESS.

Fig. 20.

Flywheel speed for the DTC case.

Fig. 21.

DC-link voltage for the FOC.

Fig. 17. (Continuous curve) Generated power and (pointed curve) delivered power for the FOC case.

Fig. 15 provides the speed of the VSWG, which is similar to the WTE speed, and Fig. 16 shows the power delivered by the VSWG to the power grid. It can be seen from Fig. 16, that the power grid receives a variable power. The aim of the FESS is to smooth this power. Figs. 17–22 present some experimental results obtained with the two IM control methods. By comparing the powers delivered to the grid (see Figs. 17 and 19) as well as the flywheel speeds (see Figs. 18 and 20), better efficiency in the case of the DTC can be observed; this can be partly attributed to the flux-reference improved computation by means of (20).

Fig. 23 clearly emphasizes that, in the DTC case, more power is delivered to the network, thus proving again that DTC could be a better choice for controlling the IM of the FESS. Moreover, the DTC needs a sample time of 125 µs when using dSPACE control card, while the FOC needs 250 µs. The difference is due to the fact that FOC method, being more complex, needs additional time to make all the computations during a sampling period, in contrast with the simpler DTC method

CIMUCA et al.: DESIGN AND CONTROL STRATEGIES OF AN INDUCTION-MACHINE-BASED FLYWHEEL ENERGY STORAGE SYSTEM

Fig. 22.

DC-link voltage for the DTC case.

Fig. 23. Electric power delivered by the VSWG-FESS assembly into the power grid for the two IM control methods.

requiring less computation. About 40 µs from both sample times are used for implementing the supervision strategy. Another aspect to be pointed out concerns the switching frequency. It is well known that the FOC operates at constant frequency, while the classical DTC operates with a variable frequency. This apparent disadvantage of the DTC can be removed by using discrete hysteresis controllers [9] and [13]. For the experiments reported in this paper, the DTC has been operated at 8 kHz, while the FOC at 9.5 kHz. VII. CONCLUSION Simulation and experimental results for an IM-based FESS associated to a VSWG have been presented. Two IM control strategies, i.e., DTC and FOC, have been implemented. It has been emphasized that the DTC is a better choice for this kind of application. An energy-efficient method to compute the IM stator-flux reference value has been incorporated in the DTC, and its effectiveness has been validated through simulations and experiments.

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[5] L. Leclercq, B. Robyns, and J. M. Grave, “Control based on fuzzy logic of a flywheel energy storage system associated with wind and diesel generators,” Math. Comput. Simul., vol. 63, pp. 271–280, 2003. [6] L. Leclercq, A. Ansel, and B. Robyns, “Autonomous high power variable speed wind generator system,” presented at the 10th Eur. Conf. Power Electron. Appl. (EPE 2003), Toulouse, France, Sep., CD-ROM. [7] L. Leclercq, C. Saudemont, B. Robyns, G. Cimuca, and M. M. Radulescu, “Flywheel energy storage system to improve the integration of wind generators into a network,” Electromotion, vol. 10, no. 4, pp. 647–652, 2003. [8] G. Cimuca, M. M. Radulescu, C. Saudemont, and B. Robyns, “Performance analysis of an induction machine-based flywheel energy storage system associated to a variable-speed wind generator,” in Proc. 9th Int. Conf. Optim. Electr. Electron. Equip. (OPTIM 2004, Brasov, Romania, May, vol. II, pp. 319–326. [9] G. Cimuca, M. M. Radulescu, C. Saudemont, and B. Robyns, “DTC vs. FOC of an IM-based flywheel energy storage system associated to a variable-speed wind generator,” presented at the 8th Int. Conf. Model. Simul. Electric Mach., Convert. Syst. (ELECTRIMACS 2005), Hammamet, Tunisia, Apr. 17–20, 2005, CD-ROM. [10] R. Hebner, J. Beno, and A. Walls, “Flywheel batteries come around again,” IEEE Spectr., vol. 39, no. 4, pp. 46–51, Apr. 2002. [11] R. G. Lawrence, K. L. Craven, and G. D. Nichols, “Flywheel UPS,” IEEE Ind. Appl. Mag., vol. 9, no. 3, pp. 44–50, May/Jun. 2003. [12] G. Cimuca, C. Saudemont, B. Robyns, and M. M. Radulescu, “Control and performance evaluation of a flywheel energy storage system associated to a variable-speed wind generator,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1074–1085, Aug. 2006. [13] G. Cimuca, S. Breban, M. M. Radulescu, C. Saudemont, and B. Robyns, “Energy-optimized direct torque control of an induction machine-based flywheel energy storage system associated to a variable-speed wind generator,” Electromotion, vol. 13, no. 1, pp. 80–86, 2006. [14] G. Cimuca, S. Breban, M. M. Radulescu, C. Saudemont, and B. Robyns, “DTC vs. FOC for an induction machine-based flywheel energy storage system associated to a variable-speed wind generator – Experimental results,” presented at the 17th Int. Conf. Electr. Mach. (ICEM 2006), Chania, Greece, Sep. 2–5, 2006, CD-ROM. [15] C. Saudemont, B. Robyns, G. Cimuca, and M. M. Radulescu, “Grid connected or stand-alone real-time variable speed wind generator emulator associated to a flywheel energy storage system,” presented at the 11th Eur. Conf. Power Electron. Appl. (EPE 2005), Dresden, Germany, Sep. 11–14, 2005, CD-ROM. [16] R. C. Thompson, J. H. Beno, and T. T. Pak, “Advanced flywheel technology for space applications,” in Proc. 37th Intersoc. Energy Convers. Eng. Conf. (IECEC 2002), Jul. 29–31, 2004, pp. 153–156. [17] V. Babuska, S. M. Beatty, B. J. de Blonk, and J. L. Fausz, “A review of technology developments in flywheel attitude control and energy transmission systems,” in Proc. IEEE Aerosp. Conf., Mar. 6–13, 2004, vol. 4, pp. 2784–2800. [18] M. Poloujadoff, C. Rioux, and M. M. Radulescu, “On the flywheel design for energy storage systems,” Electromotion, vol. 13, no. 4, pp. 271–275, 2006. [19] G. S. Buja and M. P. Kazmierkowski, “Direct torque control of PWM inverter-fed AC motors—A survey,” IEEE Trans. Ind. Electron., vol. 51, no. 4, pp. 744–757, Aug. 2004.

REFERENCES ´ [1] M. Crappe, Commande et R´egulation des R´eseaux Electriques. Paris: Herm`es Science, 2003. [2] F. Hardan, J. A. M. Bleijs, R. Jones, and P. Bromley, “Bi-directional power control for flywheel energy storage system with vector-controlled induction machine drive,” in Proc. IEE Conf. Publ., 1998, pp. 456–477. [3] R. Cardenas, R. Pena, G. Asher, and J. Clare, “Control strategies for enhanced power smoothing in wind energy systems using a flywheel driven by a vector-controlled induction machine,” IEEE Trans. Ind. Electron., vol. 48, no. 3, pp. 625–635, Jun. 2001. [4] R. Cardenas, R. Pena, G. Asher, J. Clare, and R. Blasco-Gim´enez, “Control strategies for power smoothing using a flywheel driven by a sensorless vector-controlled induction machine operating in a wide speed range,” IEEE Trans. Ind. Electron., vol. 51, no. 3, pp. 603–614, Jun. 2004.

Gabriel Cimuca received the M.S. degree from the Technical University of Cluj-Napoca, Cluj-Napoca, Romania, in 2001, and the Ph.D. degree jointly from the Technical University of Cluj-Napoca and the Ecole Nationale Sup´erieure d’Arts et M´etiers de Lille, Lille, France, in 2005, both in electrical engineering. Between March 2006 and April 2007, he was in the Powertrain Department, Siemens VDO Automotive, Timisoara, Romania. Since April 2007, he has been with the Powertrain Control Group, Renault Technologie Roumanie, Bucharest, Romania. He is author or coauthor of more than 15 technical papers and reports.

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IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 25, NO. 2, JUNE 2010

Stefan Breban (M’09) received the M.S. degree from the Technical University of Cluj-Napoca, ClujNapoca, Romania, in 2005, and the Ph.D. degree jointly from the Technical University of Cluj-Napoca and the Ecole Nationale Sup´erieure d’Arts et M´etiers de Lille, Lille, France, in 2008, both in electrical engineering. He is currently an Assistant Lecturer in the Department of Electric Machines, Technical University of Cluj-Napoca, where he is also a Researcher in the Special Electric Machines and Light Electric Traction Group.

Mircea M. Radulescu (M’94–SM’99) received the Dipl.Ing. (with Hons.) degree from the Technical University of Cluj-Napoca, Cluj-Napoca, Romania, in 1978, and the Ph.D. degree from the Polytechnic University of Timisoara, Timisoara, Romania, in 1993, both in electrical engineering. Since 1983, he has been with the Faculty of Electrical Engineering, Technical University of ClujNapoca, where he is currently a Full Professor in the Department of Electric Machines and also the Head of the Special Electric Machines and Light Electric Traction Group. He was an Invited Professor at Helsinki University of Technology, Espoo, Finland, in 1997, Rheinisch-Westf¨alische Technische Hochschule Aachen, Aachen, Germany, in 1999, University of Akron, Akron, OH, in 1999 and 2001, the Universit´e “Pierre et Marie Curie” (Paris VI), Paris, France, in 2002, Universit´e de Picardie “Jules Verne” Amiens, France, in 2003, and Ecole Centrale de Lille, Lille, France, in 2006, 2007, and 2008. He is an Associate Editor of the international scientific quarterly Electromotion. He is author or coauthor of more than 100 published scientific papers in refereed technical journals and international conference and symposium proceedings. His research interests include computer-aided design of electromechanical devices, field analysis of electromagnetic structures, design and control of small electric motors, actuators and mechatronic drives, light electric traction systems. Prof. Radulescu is a member of the International Steering Committee of several conferences and symposia in the field of electric motor drives and electric traction. His biography is listed in several editions of “Who’s Who in the World” and “Who’s Who in Science and Engineering.”

Christophe Saudemont received the Ph.D. degree in electrical engineering from the Universit´e des Sciences et Technologies de Lille, Lille, France, in 1999. Since 2001, he has been in the Electrical Engineering Department, Ecole des Hautes Etudes d’Ingenieur, Lille. Since 2002, he has also been a Researcher with the Laboratoire d’Electrotechnique et d’Electronique de Puissance de Lille, Lille. His current research interests include the renewable energies, decentralized electric energy production, and integration of dispersed renewable energy sources. Dr. Saudemont is a member of the Soci´et´e Franc¸aise des Electriciens et des Electroniciens.

Benoit Robyns (M’96) received the Ing´enieur Civil Electricien and Docteur en Sciences Appliqu´ees degrees from the Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium, in 1987 and 1993, respectively, and the Habilitation a` Diriger des Recherches degree from the Universit´e des Sciences et Technologies de Lille, Lille, France, in 2000. From 1988 to 1995, he was an Assistant in the Laboratory of Electrotechnics and Instrumentation, Faculty of Applied Sciences, Universit´e Catholique de Louvain. Since 1995, he has been with the Ecole des Hautes Etudes d’Ing´enieur, Lille, where he is currently the Director of Research. Since 1998, he has been a Researcher in the Laboratoire d’Electrotechnique et d’Electronique de Puissance de Lille, Lille, and is currently the Head of the Electrical Networks and Power Systems research team. He is the author or coauthor of more than 150 papers and one book in the fields of digital control of electric machines, renewable energies, and distributed generation. Prof. Robyns is a member of the Soci´et´e Franc¸aise des Electriciens et des Electroniciens, the Soci´et´e Royale Belge des Electriciens, and the European Power Electronics Association.