Power Generation Using Permanent Magnet Synchronous

Power Generation Using Permanent MagnetSynchronous Generator (PMSG) Based

Variable Speed Wind Energy ConversionSystem (WECS): An Overview

Anjana Jain1,∗, S. Shankar1 and V. Vanitha2

1Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India2Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, IndiaE-mail: [email protected]∗Corresponding Author

Received 11 December 2017; Accepted 14 March 2018;Publication 27 March 2018

Abstract

In the recent time, Permanent-Magnet Synchronous-Generator (PMSG) basedvariable-speed Wind-Energy Conversion-Systems (WECS) has become veryattractive to many researchers. The research aim is to analyse differentsynchronous machine and compare them based on their maximum powergeneration. This paper reviews various aspects of PMSG such as topologieswith controlled and uncontrolled rectifier, grid-connected and standalonemode of operation with various control methods of PMSG based WECS andrecent optimization approaches. The performance analysis of PMSG can beenhanced by adopting a number of control mechanisms with the benefit ofadvanced optimization techniques.Acomparative analysis is carried out basedon the techniques used and their corresponding advantages and drawbacks arediscussed.

Keywords: PMSG, WECSs, power generation, synchronous generator, grid-connected PMSG, standalone mode of PMSC, grid side converter (GSC),machine side converter (MSC).

Journal of Green Engineering, Vol. 7 4, 477–504.doi: 10.13052/jge1904-4720.742This is an Open Access publication. c© 2018 the Author(s). All rights reserved.

478 Anjana Jain et al.

List of Abbreviations

PMSG – Permanent Magnet Synchronous GeneratorWECS – Wind Energy Conversion SystemsBESS – Battery Energy Storage SystemSG – Synchronous GeneratorPM – Permanent MagnetWT – Wind TurbineHAWT – Horizontal Axis Wind TurbineVAWT – Vertical Axis Wind TurbineGSC – Grid Side ConverterMSC – Machine Side ConverterCSC – Current Source InverterMPPT – Maximum Power Point TrackingRAPS – Remote Area Power SupplyPLL – Phase Locked LoopPCC – Point of Common CouplingFLC – Fuzzy Logic ControllerAFLC – Adaptive Fuzzy Logic ControllerANN – Artificial Neural NetworkDTC – Direct Torque ControlPSO – Particle Swarm OptmizationGA – Genetic AlgorithmBFO – Bacterial-Foraging-Optimization

1 Introduction

Nowadays, PMSGs are most popular for power-generation, as they have highefficiency [1–5]. For instance, the electrical efficiency of PMSGs is higherthan the synchronous-generators (SGs) in the moderate-size power marinediesel gen-sets [6]. As PMSG don’t comprise excitation control, voltage-regulation in island-operation is challenging. The flux-density of permanentmagnet (PM) reduces with the rise in temperature, so voltage-control becomecomplicates. Some of the difficulties of PMs are high cost and handling whilemanufacturing [7]. The variable-speed operation of the WECS is essential forextracting maximum wind power.Amodern control based tracking of power ortorque helps to achieve best utilization of wind-energy [8, 9]. Control strategiesare developed based on wind-velocity to acquire required shaft speed. Theseschemes involve high cost and reduced reliability for a small scale WECS. Thecurrent-vector of an interior type PMSG optimizes the operation at variable

Power Generation Using Permanent Magnet Synchronous Generator (PMSG) 479

wind-velocity, which needs control of six active switches [10]. Switch-moderectifier is also designed for PMSM [11]. For standalone operation, load-side converter voltage needs to be controlled in terms of amplitude andfrequency [12]. Grid connected PMSG based WECSs are also proposed andimplemented. Probability to attain less pole-pitch permits the machine to runat low speed and removes the gearbox or allows using single-stage gear formore compact design. This paper reviews various PMSG techniques with theaim of maximum power generation [13, 14].

The objective of this paper is to discuss different methods and approachesfor control of PMSG based WECS. In Section 2 of the paper, discussion aboutWECS and modelling of PMSG is carried out. Section 3 is presenting varioustopologies for the converters used for PMSG based WECS. In Section 4,method of control of grid connected pmsg based WECS are discussed.Section 5 presents discussion about standalone mode of operation of PMSGbased WECS. In Section 6 some advanced control methods of PMSG basedWECS are discussed. Section 7 presents recent optimization approaches forthe system. Section 8, includes the conclusion with a comparative analysis ofthe diffenent methods and apporoaches discussed in the previous sections.

2 Wind Energy Conversion System (WECS)and Modelling

Non-conventional means of energy has become an alternative and or anadditive for the conventional source of energy. With endless potential of windenergy and environmental-merits, it has become the most popular source ofrenewable energy. The WECS based on the wind-turbine (WT) is categorisedas fixed and variable speed system. Initially fixed-speed WECS was popularone. Nowadays, variable speed generators are more effective. PMSG is moreeffective and efficient as compared to other generators and are best suitedfor WECS due to its high torque to size ratio, less maintenance required,omission of slip-rings, reduced overall-cos. Permanent magnets(PM) insteadof electromagnets makes the stator direct-flux constant [65]. The modellingof wind based power generation system is discussed below.

2.1 Modelling of the Wind Turbine

The rotor-blades of WT converts the kinetic-energy of the windinto mechanical-energy. Then generator as an electrical-sytem transformmechanical-power into the electrical-power. WTs generally used for WECS


are vertical-axis-wind-turbine (VAWT) and horizontal-axis-wind-turbine(HAWT). HAWT shows listed below advantages than VAWT.

• it offers flexible blade-pitch so that blades can operate at optimum-angleof attack, for extracting more wind-energy.

• it always captures efficient wind-energy from during the whole rotationas blade’s rotation is perpendicular to the wind.

• it is self-starting, but VAWT needs initial starting-torque.

The kinetic energy, which is extracted from the wind, is penetrated on to theturbine blade area.

According to the principle of energy-mass conservation in wind, themaximum extracted wind power is given as [65];

Pwind=12

ρAv3w (1)

Where vw is wind velocity, ρ is density of air,Ais swept-area of turbine-blades.Cp, power coefficient is defined as the ratio of turbine power to the

extracted wind power.

Cp=Turbine power (Pturbine)

Power obtained from wind (Pwind)

Hence the turbine-power is given by:

Pturbine= PwindCp=12ρAv3

wCp (2)

The turbine-power wrt wind transients is given by

Pturbine= PwindCp=12ρAv3

wCp (λ, β) (3)

Where λ is the tip-speed ratio of the turbine:

λ=rotational speed of rotor (ωr) ∗radius(r)

wind velocity (vw)(4)

Where

Cp (λ, β) =C1

(C2

λi−C3β−C4

)e

−C5λi +C6λ (5)

λi=(

1λ+0.08β

−0.035β3+1

)(6)


Figure 1 Power coefficient Cp(λ, β) vs tip speed ratio λ.

Where β stands for the blade pitch angle.The coefficient C1 to C6 are: C1 = 0.5176, C2 = 116, C3 = 0.4, C4 = 5,

C5 = 21, C6 = 0.0068.Figure 1 show the relationship between the power coefficient Cp and tip

speed ratio λThe governing formula for directly-coupled PMSG for the mechanical-

analysis is given as,

dωm

dt=

(1J

)(Tm − Tgen − Bωm) (7)

ωe = Pωm (8)

Also ∫ωe dt = θe (9)

Where, θe = electrical angle (is required for abc↔d-q transformation),Tm = generated turbine mechanical-torque (Nm), Tgen (=Te) = generatedelectromagnetic-torque (Nm), P = pole-pairs ωm = the rotor mechanical speed(rad/sec), ωe= rotor electrical speed in elec. rad/sec, J = inertia-moment(Kgm2), B = viscous-friction coefficient (can be ignored for small WT).

2.2 Modelling of the PMSG

Figure 2 shows the d-q axes ‘park’ model. In PMSG rotor is made up of PM,not fed by external source for producing magnetic-field. Hence rotor voltage-equation need not be be developed as variation in rotor flux wrt time is not


Figure 2 PMSG model (a) d (direct)-axis, (b) q (quadrature)-axis.

there. Stator voltageiequations are as follows [65]:

Vsd = RsIsd +dφsd

dt− ωeφsq (10)

Vsq = RsIsq +dφsq

dt+ ωeφsd (11)

The stator fluxes are given by,

φsd = LdIsd + φm (12)

φsq = LdIsq + φm (13)

Where, Rs = stator-winding resistance, Ld = d-axis stator-inductance, Lq =q-axis stator-inductance, φm = flux linkage, Vsd & Isd = d-axis stator voltage& current, Vsq & Isq = q-axis stator voltage & current. From Equations 10–13:

Vsd = RsIsd + LddIsd

dt− ωeLqIsq (14)

Vsq = RsIsq + LqdIsq

dt+ ωeLdIsd + ωeφm (15)

The electromagnetic-torque can be written as:

Te =(

32

)P (φmIsq + (Ld − Lq)IsdIsq) (16)

For surface-seated PMSG, we can assume Ld = Lq. Then Te can bewritten as:

Te =(

32

)P (φmIsq) (17)


For steady-state condition, real power Ps and reactive power Qs of PMSG areas follow:

Ps = VsdIsd + VsqIsq (18)

Qs = VsqIsd − VsdIsq (19)

3 Converter Topologies for Permanent MagnetSynchronous Generator (PMSG) BASED WindEnergy Conversion System (WECS)

PMSG is more popular among the synchronous and asynchronous generatorsdue to its lower weight & size, self-excitation. Low maintenance-cost andno gearbox give high efficiency and power factor compare to wound-rotorsynchronous generator (WRSG), squirrel-cage induction generator (SCIG),and doubly-fed induction generator (DFIG). DFIGs are the promising choicedue to high wind power extraction capability with low converter losses [69].PMSG with diode-bridge rectifier (AC/DC), boost-converter (DC/DC) &inverter (DC/AC) were proposed for power extraction. The DC/DC convertercontrols the machine’s voltage. Cost and control complexity is reduced bydiode-bridge rectifier [66]. Due to effect of diode commutation at morewind velocity and discontinuous- operation of DC/DC-converter at lowwind-velocity, the extracted wind-power decreases. Therefore, for power inthe range of 10s kW, back-to-back converter is the better choice, whichleads to 5%–15% rise in power [67]. Various techniques are proposedand implemented by the researchers to enhance the performance of PMSGconnected to variable speed WECS, such as PMSG with controlled anduncontrolled rectifier for grid connected or stand-alone system. Figure 3(a)shows a grid-connected PMSG through AC/DC-boost-DC/AC converters andFigure 3(b) shows a grid-connected PMSG through bidirectional (back-to-back) converter. Bidirectional-converter consists of 2 VSI-PWM convertersand a dc-link capacitor. The MSC works as controlled-rectifier and grid-side-converter as inverter. Dc-link voltage can be made constant by controllingpower flow of the GSC. MSC is controlled to suit the magnetization & the ref-erence speed/torque. This topology provides decoupling-effect MSC & GSCthrough capacitor. Decoupling-effect helps for independent converters-controlwith some protection [68].

Figure 4(a) shows the schematic diagram for controlled rectifier basedMSC, Figure 4(b) shows the MPPT control, and Figure 4(c) shows the phsedlocked loop (PLL) to find angular velovity. Dynamic modelling of PMSG


Figure 3 (a) WECS with uncontrolled diode rectifier, boost-converter, VSC; (b) WECS withcontrolled rectifier and VSC.

based WECS, and MPPT based controller design using fuzzy-logic con-troller (FLC) is presented for constant and variable wind conditions [16].An Artificial-Neural-Network (ANN) based Reinforcement-Learning (RL)MPPT algorithm is proposed. Initially, MPPT-algorithm learns the ideal linkamong the rotor-speed & electrical-power of PMSG by the integration ofANN and Q learning algorithm. MPPT-algorithm is changed from the online-RL to relation-based online-MPPT. The online-learning scheme permitsWECS to perform like an intelligent-agent (with memory) to learn from itsspecific knowledge, therefore enhancing the learning efficiency. The onlineRL algorithm is reenergised whenever genuine optimal-relationship divergesfrom the learned-one due to system aging [17]. Figure 5 [17] shows theSchematic diagram of the ANN-based RL algorithm. The major problem in aseries-connected current-source-converter (CSC) is the insulation level, dueto monopolar operation. Bipolar operation gives a half insulation requirement,is investigated to solve the degradation of the system. Paths for dc-link currentproduces a concern for appropriate operation of the bipolar system. Bipolaroperation with the support of the optimized dc-link current control characteriselower insulation, higher reliability, efficiency and flexibility[18]. An inclusiveanalysis on power converter topologies with technical details for MW rangePMSG-WECS, fault-ride-through compliance approaches and digital controlapproaches are presented in [19]. In WECS, traditional frequency-controltechniques are imposing a severe stress on the system. Enhanced frequency-response scheme for PMSG-based WECS to control the frequency of Remote


Figure 4 (a) Controlled rectifier based machine side converter, (b) MPPT control, (c) PLL.


Figure 5 Schematic diagram of the ANN-based reinforcement learning (RL) algorithm.

Area Power Supply (RAPS) system with its combined ultra-capacitors isproposed [20]. Here frequency-response scheme is based on droop-controland virtual-inertial methods. It efficiently controls RAPS frequency with highrate of change of power. A Medium-Frequency Transformer (MFT) basedWECS for offshore wind farms is proposed using current source converters[21]. This configuration includes a medium-voltage PMSG which is connectedto a low-cost passive rectifier, onshore current source inverter and MFT-basedcascaded converter. Both simulation and experimental results are achievedbetter performance is shown compared with conventional methods.

In [22], robust & reliable power system is proposed having a combinationof a machine-side 3-switch buck-rectifier and a grid-side Z-source inverter as abridge among the grid and the machine. Figure 6 shows the schemetic diagramof PMSG based WECS with Z-source converter. Space-vector modulation andZ-source network operation principles in utilized to develope the modulationscheme. Two control approaches such as unity-power-factor control and rotor-flux-orientation control are considered to develop the optimized proposedcontrol. Decoupled active and reactive-power control is attained indepen-dently. MPPT is achieved through control of shoot-through duty cycles ofZ-source network.

Figure 6 Schematic diagram of PMSG based WECS with Z-source converter.


In [23] the solutions based on diode rectifiers are found wrt the wave-forms of electrical & mechanical quantities, efficiency, torque ripple, withvarious connections (6-pulse & 12-pulse rectifier). Rectifier with high no.of pulses can be utilized without using special shifter-transformers, makesthem very useful for low-medium power applications. A scheme comprisingof 3 individual thyristors and two 3-φ diode bridge is implemented forhigh-power variable speed PMSG [24]. Here each of diode bridge recti-fiers is supplied by a 3-φ power-source and their outputs are connectedin parallel. Three individual thyristors connects the corresponding inputphases of the rectifiers. The rectifier’s dc output voltage is equal to theoutput of a single diode bridge, if thyristors are off. The outputs of thetwo diode bridges are cascaded and total dc voltage becomes double, ifthe thyristors are controlled and turned on. This rectifier consists someimportant properties such as low power loss, low cost, simple control,and more efficient [24]. The effect of Vienna-rectifier voltage-vectors onPMSG torque & stator-flux are derived by Direct torque control (DTC) [25].In [26], operational challenges of 3-φ surface-mount PMSG connected toa diode-rectifier are evaluated and by using analytical steady-state modelof the system, maximum power transfer is obtained. In [27] a linearizedaverage dynamic-model of the WECS including PMSG, diode-rectifier, boost-converter is presented. Also relationship between electromagnetic torque &converter current is extracted; then system’s control-loops are developedusing linearized model. Then small signal stability of the overall system ispresented. Here the effect of speed-controller on the stability of the systemis observed theoretically and with simulations. In [28] a novel schemewith fuzzy fractional order proportional integral + I (FFOPI+I) controllerfor grid-connected PMSG based variable-speed WECS is proposed. Thecontroller is employed to control system with nonlinear load through abidirectional-converter. The MSC aims to extract maximum-power underfluctuating wind speed. The controller develops a FLC in parallel withFractional Order PI (FOPI) and conventional PI controllers. The initialparameters of FFOPI+I controller is computed using a frequency approachto produce a search space then particle-swarm-optimization (PSO) algorithmis applied to choose optimal-parameters. The performance evaluation ofFFOPI+I controller is estimated under the steady-state and transient condi-tions. The simulation results demonstrate the effectiveness of FFOPI+I overFOPI and enhancing the grid-side power factor for a wide range of wind speed.Figure 7 shows the schematic diagram of the control scheme with FFOPI+Icontroller [28].


Figure 7 Schematic diagram of the control scheme with FFOPI+I controller.

4 Grid Connected Permanent Magnet SynchronousGenerator (PMSG) Based Wind Energy ConversionSystem (WECS)

In [29], intelligent controllers are proposed for a Switched-Reluctance Gener-ator (SRG) based WECS to obtain the maximum-power. These controllersare based on of fuzzy-logic (FL) controller and ANN techniques. Con-troller adjusts WT rotational-speed by fixing the turn-on angle and varyingthe turn-off angle of SRG. Simulation results shows the effectiveness ofANN-controller in terms efficiency & accuracy than FL-controller. In [30]a model-predictive-control is proposed, which provides better dynamic-response and permits flexible-operation of parallel-connected generators byremoving the dependency of voltage & frequency synchronization. Schemeshows operational-ability of the micro grid under islanding from distribution-grid. An enhanced rapid dynamic-system for regulating Matrix-Converter(MC) is proposed with modified-hysteresis-current-controller and optimal-tuning-PI-controller in [31]. Also enhanced Bacterial-Foraging-Optimization(BFO) algorithm is applied for active & reactive currents control of PMSGto achieve maximum-power. Using BFO, active & reactive powers can besupplied to the grid at normal and fault situations. Dynamic limiter with


BFO-controller controls the injected reactive-power to grid and improves thesystem stability. Also pitch angle controller with rate limiter is developed forWECS protection from mechanical-damage. An overall control technique forhybrid-wind/PV distributed generation system is presented [32].

Various energy sources are integrated using DC bus into the utility grid.Meta-heuristic Firefly algorithm (FA) based controller is utilised for voltage &frequency control at point of common coupling (PCC). The gains of PI & PIDcontrollers are concurrently improved by powerful FAand their performance isevaluated. The dynamic responses of PID controller shows the better perfor-mance compare to PI controller. A Maximum-Power-Extraction Algorithm(MPEA) is proposed for a grid-connected PMSG based WECS and it isfeasible to implement in practical without any mechanical sensors for WECSvia a PMSG [33]. Comprehensive models have been proposed to analysepower & voltage fluctuations, which depends on the grid-parameters. Flickeremissions can be reduced by activating the developed voltage regulationloop [34]. The q & d axis current controls the active & reactive powerrespectively. Utility-voltage phase-angle is identified by software PLL insynchronous-reference-frame. This method provides high quality & low costpower conversion for WECS [35]. Figure 8 shows the control scheme of agrid connected PMSG system.

Figure 8 Control scheme of grid side converter (GSC).


In [36], two control schemes, based on sliding-mode control and classicalPI controllers, to control both MSC & GSC for wind farms (WF) using PMSGconnected to a DC-bus system are proposed. Control scheme integrates a pitchcontrol method and MPPT to achieve more power from WF. In [37], hardwareimplementation of 3-parallel connected PMSGs based WECS is proposed,which minimizes the converters rating, shows better performance comparedto traditional schemes.

5 Standalone Permanent Magnet Synchronous Generator(PMSG) Based Wind Energy Conversion System (WECS)

Figure 9 shows a PMSG based standalone WECS. Here PMSG is con-nected to a load via a 3-phase ac/dc converter, BESS, and a 3-phase dc/acconverter. Generally standalone WECS are supported by BESS and orsuper-capacitor/ultra-capacitor.

In [38] an Effective-Energy-Management algorithm for standalone PMSGusing dc link voltage is proposed. Here variable-speed WECS with PMSGincludes battery, dump load and fuel cell. By maintaining constant dc-linkvoltage to its reference value, constant inverter output is gained. An effectivecontrol scheme developed based on PWM-technique provides balanced linevoltages at PCC for unstable load also. Also, control method for battery withDC/DC converter is developed to minimize the torque-pulsation of machine.Scheme maintains MPPT. In [39], controller for voltage & frequency isimplemented using a battery-energy-storage-system (BESS). BESS controlsthe frequency and provide load levelling for varying wind velocity. Machinevoltage control is achieved by supplying reactive power at variable loads &wind velocity. The performance of the system is verified as a harmonic com-pensator, a load-balancer & leveller and a voltage & frequency controller. Anadaptive-control method based on Neural-network-identifier (NNI) for MPPT

Figure 9 PMSG based Standalone WECS.


Figure 10 PMSG based standalone WECS with BESS and supercapacitor [41].

of stand-alone PMSG based WECS is proposed [40]. This method providesaccurate mechanical torque signal and off-line training is not required toacquire its optimal-parameter-values.Ablock-back-stepping controller is alsoproposed to attain optimal rotor-speed. In [41], energy-management-algorithm(EMA) for enhancing the performance of hybrid-energy-storage-system alongwith super-capacitor is discussed. Figure 10 shows a PMSG based standaloneWECS with BESS and supercapacitor. Synchronous-condenser offer reactive-power and inertial-aid to the system. Here developed coordinated-controlmanages the active & reactive power flow between system elements. Theresults achieved with the robust voltage and frequency regulation, effectivemanagement and maximum wind-power extraction.

In [42], a hybrid system is proposed which includes PMSG & DFIG inte-grated with a battery-storage. The simulation results varifies both the systemscapabilities of voltage & frequency control. In [43] a parameter-independent-intelligent-power-management-controller, includes MPPT & power-limit-search (PLS) algorithm for standalone PMSG, is proposed. PLS algorithmhelps to reduce surplus-energy production and minimize the heat-dissipationneeds by finding optimal operating resulting required-power at the place ofmaximum-power.

6 Advanced Control Technique for Permanent MagnetSynchronous Generator (PMSG) Based Wind EnergyConversion System (WECS)

In [44], a systematic formula of loss using quadrature-direct axis currentand speed and evaluation of loss model of high-speed PMSG is proposed.Total loss is concave function based on d-axis current and speed. There-fore, the mathematical derivation of solving the extreme value is employed


and then the explicit expression of the two independent variables directaxis current and speed for the minimum-loss-point is accomplished. Asthe effect of the maximum current limitation of the circuit on the systemspeed operation mode, the minimum loss speed and direct current com-bined control strategy are raised. Proposed algorithm enhances the efficiencyby 16.91% compared to conventional algorithms. Next, a power-controltechnique for PMSG based WECS is proposed. At sub-synchoronos speed,with rotor dynamic-characteristics, optimal reference-torque is found withoutwind velocity sensors. At super-synchronous speed, with flux-weakeninghelps to use maximum-torque under specific current & voltage. SVM-baseddirect-torque-control (SVM-DTC) helps to generate the torque angle &flux references [45]. Direct-model-predictive-control (DMPC), without extra-modulator, takes care of power converter’s switching-non-linearity. Its natureof one-switching-vector/control-interval causes big ripples in the control-variables. To overcome this issue, multiple-vector-direct-model-predictive-power-control (MV-DMPPC) is presented for GSC based on FPGA [46].Here, MV-DMPPC shows improved performance than DMPPC with duty-cycle-optimizations. Three methods of current control for MSC are presentedbased on rotor-flux-oriented-control [47]. Integral-sliding-mode-controller(ISMC), consist of two integral-switching-functions for stator d-q axiscurrents and controls the currents in synchronous-reference-frame. Thenfinite-control-set-model-predictive-control (FCS-MPC) controls the stator-currents and replaces ISMC. In FCS-MPC, switching action reduces apredefined-cost-function required for next sampling. At last, conventionalPI is developed to evaluate new controllers. In [48] a feedback-linearizationbased partical swarn optimization (PSO) for selecting optimal working forMPPT of WECS based on PMSG is proposed and verified. A Vienna-rectifier based MPC, measures the possible eight voltage-vectors of therectifier and enhance the performance of the WECS based on PMSG[49]. Cost-function measures the optimized voltage-vector, used for ripple-minimization. Selection of final switching-set is based on neutral-pointvoltage-unbalancing issue consideration. Output-power smoothing in low &high-frequency regions, based on coordinated-control of DC-link-voltageand pitch-angle of a WT is proposed [50]. WT blade-stress is alleviatedas the pitch-action for high-frequency less and for low frequency; DC-link-capacitor size is reduced without its charge/discharge action. A newmethod for voltage & frequency control for a stand-alone WECS handlingvariable load is proposed [51]. Scheme controls GSC for maximum powerextraction from wind. Dynamic illustration of dc bus and small-signal


analysis is also obtained. In [52], predictive-current-control for the predic-tion of the generator-behaviour using a mathematical-model is proposed.These parameters may differ from their actual values, leads to inaccurateprediction, so deteriorate predictive algorithm. Extension of the proposedalgorithm to enhance the prediction accuracy is presented, which decreasesthe current-ripple and improves robustness of the system against parameteruncertainties. A new sliding-mode-observer (SMO) to obtain the sensorlesscontrol of PMSG is proposed in [53]. An observer is constructed basedon back EMF model and accuracy of estimation of rotor-position & speedis achieved. In [54], the output-power-control based on combined high-order-sliding-mode (HOSM) controller is proposed for PMSG based WECSintegrating a stand-alone hybrid-generation-system with BESS and someother generation-subsystems. Figure 11 shows the control scheme proposed.Controller presents chattering-free behavior, simplicity & robustness wrtdisturbances.

In [55], direct-current based d–q vector control method integrating fuzzy,adaptive and conventional PID control is proposed, which enhances the systemoptimal-performance. A PMSG-control based on dc-vector-control-processfor MSC & GSC is proposed to gain maximum-power from wind [56]. Thissystem achieves excellent performance under various conditions.A integratedpower-control is presented for PMSG based WECS operating in various grid

Figure 11 Schematic diagram for combined high-order-sliding-mode (HOSM) control [54].


conditions [57]. The designed scheme is more quicker and accuracy powerresponses than the variable structured control scheme that is advantageous tothe grid recovery. A prototype version of the mechanical sensorless controltechnique of a 20-kW PMSG for maximum power tracking is proposed [58].

7 Optimization Approach for Permanent MagnetSynchronous Generator (PMSG) Based WindEnergy Conversion System (WECS)

Intelligent techniques, using two AFLC and PSO, to enhance DTC per-formance of PMSG based-WECS are proposed in [59]. AFLC replacesthe traditional-comparators & switching-table and regulates real time PI-parameters. PSO keeps switching frequency constant, is used as an alternativeto regulate PI parameters. Controllers help to reduce flux & torque ripplesand improves dynamic & steady state efficiency. Pitch-control along withoptimization, delay-perturbation-approximation, and signal-compensationmethods is proposed [60]. Direct-search-optimization based controller pro-vides delay-free pitch model. Delay-estimator calculates the perturbationdue to delay. Signal-compensation method eliminates the effect from delay-perturbation to the turbine output. A multi-physics design optimization of

Figure 12 Flowchart of optimum design process.


PMSG is proposed, where goal is to reduce cost [61]. Multi-physics machinemodel, cost, and loss models are considered under design. Converter’scontrol scheme, affects the system cost, is analysied. Here, optimizationleads to describe the phase-angle of the generator-current. Fuzzy-sliding-mode loss-minimization control and an efficient on-line-training radial-basis-function-network (RBFN) for turbine-pitch-angle-control is presented [62].MPPT algorithms for optimal wind energy capture using RBFN and torque-observer-MPPT-algorithm is proposed [63]. Here, efficient RBFN (based onback-propagation) and a modified-PSO regulates the controller for a sensorlesscontrol of PMSG. In [64] an optimum design procedure for parametersof PI controllers of frequency-converter using genetic-algorithms (GAs) ispresented. Figure 12 shows the control algorithm for GA. GA enhaces thefault-ride-through also.

8 Conclusion

In this paper, various PMSG topologies such as with controlled & uncontrolledrectifier, grid connected operation; stand-alone operation, different controlalgorithms, and optimization technique for PMSG have been discussed basedon their maximum power generation. Each technique is determined accordingto the required specification in terms of the parameters used.Also, comparativeanalysis of various PMSG based variable-speed WECS techniques is studiedwith advantages and future recommendations and is shown in Table 1.This comparison table provides advantages and research gap of each glitchreduction technique. The performance measure of PMSG can be enhancedby adopting several control mechanism with the aid of advanced optimizationtechniques. This research study helps as an advantageous knowledge for futureresearch direction.

Table 1 Comparative analysis of PMSG techniquesSl.No. Paper Title

TopologyUsed Outcomes Research Gap

1 A medium-frequencytransformer-basedWECS used forcurrent-sourceconverter-basedoffshore windfarm [18].

PMSG withcontrolled &uncontrolledrectifier

Low power loss, lowcost, simple control,and more efficientAchieved betterperformance.

Morecomplexity

(Continued )


Table 1 ContinuedSl.No. Paper Title

TopologyUsed Outcomes Research Gap

2 Experimentalenhancement of fuzzyfractional order PI+Icontroller of gridconnected variablespeed wind energyconversion system [28].

GridconnectedPMSG

Improved thegrid-side powerfactor for a widerange of wind speed.

Average costand highcomplexity.

3 A novel online trainingneural network-basedalgorithm for windspeed estimation andadaptive control ofPMSG wind turbinesystem for maximumpower extraction [40].

Stand-alonePMSG

It provides goodaccuracy.

More timeconsumptiondue to trainingphase in neuralnetworks.

4 A Control Approach forSmall-ScalePMSG-based WECS inthe whole wind speedrange [45].

controltechniques

10 kW wind turbinefor commercialapplications.

High cost.

5 A comparativeexperimental study ofdirect torque controlbased on adaptive fuzzylogic controller andparticle swarmoptimization algorithmsof a PMSG [59].

Optimizationapproach

Keeps a constantswitching frequencywhich enhances thePMSM drive systemcontrol performance.

More timeconsumption.

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Biographies

Anjana Jain has completed her BE in EEE in the year 2001 and ME inControl Systems in the year 2005 from Jabalpur Engineering College,Jabalpur, RDVV, MP, India. She is currently working as Assistant Professorat the dept. EEE, Amita Vishwa Vidyapeetham, Bengaluru and pursuing PhD.She has 13 years of total teaching experience and her areas of researchinclude Renewable Energy (Wind Generation), Power Electronics.


Dr. S. Shankar has completed his BE in Instrumentation Technology in theyear 2005 from KNS Institute of Technology, Bangalore, Karnataka, India andMTech in Power Electronics in the year 2008 from RV College of Engineering,Bangalore, Karnataka, India. He has received his PhD degree from IIT Delhi,India in the year 2014 and currently working in the dept. of EEE, AmritaVishwa Vidyapeetham, Bengaluru, India. He has total teaching and industryexperience of 6 years. His areas of research include Renewable Energy (wind,solar), Power Electronics.

Dr. V. Vanitha has received her BE in EEE in 1992 from Madurai Kama-raj University, Madurai, India and ME in Power Systems in 1993, fromBharathidasan University, India. She has received her PhD degree from AnnaUniversity, Chennai, India and currently working in the dept. of EEE, AmritaSchool of Enginnering, Coimbatore. She has totally 17 years of teachingexperience. Her research interests are in the areas of Power System, ElectricalMachines, Renewable Energy Sources and Power Quality.

Documents

Power Generation Using Permanent Magnet Synchronous