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A Control Strategy for Hybrid Autonomous PowerSystem with a Battery Management SchemeChellachi Kathiresan Aravinda, Ganesan Saravana Ilangoa, Chilakapati Nagamania &Maddikara Jaya Bharata Reddya

a Department of Electrical and Electronics Engineering, Power Converter ResearchLaboratory, National Institute of Technology, Tiruchirappalli, Tamilnadu, IndiaPublished online: 11 May 2015.

To cite this article: Chellachi Kathiresan Aravind, Ganesan Saravana Ilango, Chilakapati Nagamani & Maddikara Jaya BharataReddy (2015) A Control Strategy for Hybrid Autonomous Power System with a Battery Management Scheme, Electric PowerComponents and Systems, 43:8-10, 1159-1172, DOI: 10.1080/15325008.2015.1018457

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Electric Power Components and Systems, 43(8–10):1159–1172, 2015Copyright C© Taylor & Francis Group, LLCISSN: 1532-5008 print / 1532-5016 onlineDOI: 10.1080/15325008.2015.1018457

A Control Strategy for Hybrid Autonomous PowerSystem with a Battery Management SchemeChellachi Kathiresan Aravind, Ganesan Saravana Ilango, Chilakapati Nagamani, andMaddikara Jaya Bharata ReddyDepartment of Electrical and Electronics Engineering, Power Converter Research Laboratory, National Institute of Technology,Tiruchirappalli, Tamilnadu, India

CONTENTS

1. Introduction

2. System Description

3. Mathematical Modeling of Hybrid Power System

4. Coordinated Power Control Strategy for Hybrid Autonomous

Power System (HAPS)

5. Small Signal Analysis of Hybrid Autonomous Power System

6. Battery Management Scheme

7. Results and Discussion

8. Conclusion

References

Appendix

Keywords: Hybrid autonomous power system, battery energy storagesystem, battery management system, diesel generator, distributed generator,coordinated control

Received 17 June 2014; accepted 15 January 2015

Address correspondence to Dr. Maddikara Jaya Bharata Reddy, Departmentof Electrical and Electronics Engineering, National Institute of Technology,Tiruchirappalli, Tamil Nadu 620015, India. E-mail: jayabharat res@yahoo.co.inColor versions of one or more of the figures in the article can be found onlineat www.tandfonline.com/uemp.

Abstract—This article presents a coordinated control strategy for ahybrid autonomous power system to obtain a smooth power trans-fer between diesel generator and battery energy storage system undertransient conditions. In addition, a battery management scheme is alsodeveloped to maintain the battery state of charge around 70 to 80%to absorb/inject power under transient conditions and maintains thediesel generator power above 40% of its nominal value. Simulationstudies are carried out in MATLAB/Simulink and the performance ofthe controller is validated experimentally on a laboratory test setup. ATMS320LF2407A DSP controller is used to digitally implement thecontrol strategy and the overall scheme is verified with step changesin load. Moreover, the dynamic behavior of the system is also inves-tigated by directly connecting an induction motor.

1. INTRODUCTION

The present electricity infrastructure in most countries consistsof centrally located bulk power plants situated far away fromload centers. The generated electrical energy is transferred toconsumers through a highly meshed transmission network [1].In rural areas, with sparsely distributed lands and small popu-lation, extension of the existing grid could not be economicallypossible because of the high cost capital investment requiredfor transmission lines [2, 3]. A new trend is also developingtowards distributed energy generation in which energy genera-tion units of smaller sizes are situated closer to the consumers[4]. Nowadays, commercial and residential customers in urbanareas are also seeking this type of autonomous grid system.A diesel-engine-driven generator is the major source for theautonomous grid due to its reliability, ease of transportation,installation, and disconnection [5, 6]. Due to the considerablesource impedance of such a generator, the voltage distortionis more during the starting of induction motor loads and dur-ing load changes [7]. Further, the diesel generator is preferredto be operated above 40% of its nominal power to avoid wetstacking due to impartial burning of fuel [8]. The practice of in-tegrating renewable energy sources to the autonomous diesel

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1160 Electric Power Components and Systems, Vol. 43 (2015), Nos. 8–10

NOMENCLATURER = resistance (Ω)L = inductance (H)P = power (W)v = instantaneous voltage (V)rsh = shunt resistance per phase (Ω)ω = angular frequency rad/s (electrical)i = instantaneous current (A)Lmq = q-axis magnetizing inductance (H)Lsh = shunt leakage inductance per phase (H)

Lmd = d-axis magnetizing inductance (H)Llfd = field leakage inductance (H)ωe = angular speed of rotor rad/s (electrical)T = time delayK = system gainλ = flux linkage (wb-t)Kp = proportional gainKi = integral gain

First Subscripts

WG = wind generatorr = rotors = statorm = mutualDG = diesel generator

ls = stator leakagef = fieldp = phaset = terminalBESS = battery energy storage system

Second Subscripts

d = direct axisq = quadrature axis

ref = referenceinv = inverter

generator is becoming huge due to developments in powerelectronics technology [9, 10]. The hybrid system is not ex-tended to replace the diesel generator totally, but to minimizethe usage of diesel fuel and to use available renewable sources.In an autonomous grid system, the fluctuation in the voltageand frequency is due more to the dynamic changes in loadand changes in load sharing by the renewable energy sources[11, 12].

Various control strategies and topologies for an autonomoushybrid system have been reported in the literature. The oper-ation of energy storage systems in a hybrid power system isdiscussed in [13–23]. In an autonomous grid [13–15], a com-pressed air storage system and pumped energy storage are usedto compensate the mismatch between the generation and con-sumption. Here, the excess electrical energy is stored in theform of kinetic energy. This long-term energy storage manage-ment cannot be transferred back immediately to electric powerwhen it is needed and it is not feasible to all operating ar-eas. Reliability of the autonomous grid can be improved usinga battery storage system [16–22] and the power electronics-based battery storage systems have a fast response. Moreover,they are easily adaptable to the hybrid system. The sizing ofan energy storage system is very important where oversizeddimensions annihilate high economic profit [23]. In the liter-ature, a few papers [24–26] used PQ-based control and V/Fcontrol algorithms to control the voltage and frequency of theautonomous wind energy system, which increases the num-

ber of converters in the system. A few studies [27–29] dealtwith the coordination between the renewable energy sourcesand battery energy storage system. Zhang et al. [29] reportson the coordination between inertial control, rotor speed, andpitch angle control under low, medium, and high wind speedto mitigate the wind power fluctuations. Teleke et al. [28] inte-grated a wind generator with battery storage system and useda feedback-based control scheme to control the battery and re-duce the power fluctuations in wind farm. However, the papersof [28, 29] deal with coordinated control between renewableenergy source and battery energy storage system. Omine et al.[30] developed a H∞ control theory for deviation in windpower. In that study, the coordination is between wind powerand diesel generator for low power fluctuation and wind powerand battery for high load power fluctuation. In [31], coordina-tion between two solid oxide fuel cells (SOFCs), battery, and adiesel generator using a time domain simulation is described.In this article, a coordinated control strategy is developed forthe diesel generator and battery energy storage system, whichhelps to maintain the frequency and voltage of the autonomousgrid within a predefined limit. The dynamic behavior of dieselgenerator under step changes in load (induction motor) is in-vestigated. A battery management scheme is also developed tomaintain the battery state of charge (SOC) at around 70 to 80%limit to enable it to absorb/inject power from the autonomousgrid under transient conditions. The system is simulated usingthe MATLAB Simulink tool for preliminary validation and

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FIGURE 1. Block diagram of hybrid autonomous powersystem.

further tests are carried out on a laboratory prototype, whichemploys a TMS320LF2407A board to digitally implement thecontrol strategy.

2. SYSTEM DESCRIPTION

Figure 1 shows the block diagram of an autonomous power sys-tem, which consists of a diesel engine coupled synchronousgenerator (SG), battery energy storage system (BESS) withbidirectional converter, dump load, critical loads, and non-critical loads. A diesel generator is the main component ofan autonomous grid system, which is the primary source tomaintain the voltage magnitude and the frequency of the au-tonomous grid. A governor control is used to maintain thespeed of the diesel engine by adjusting the fuel flow accord-ing to the loading conditions. The function of BESS is toabsorb/inject the power during the transient operation and tomaintain the system frequency within the limits. Moreover, adump load is used to maintain the system frequency when thebattery SOC exceeds the predefined limits.

3. MATHEMATICAL MODELING OF HYBRIDPOWER SYSTEM

The mathematic model of the hybrid autonomous grid systemis described in this section.

3.1. Modeling of Synchronous Generator

The d-q model of the synchronous generator is developed inorder to eliminate the dependence of inductances on rotorposition. The d–q model should express both stator and rotorequations in rotor coordinate, aligned to rotor d and q axes.The d-q components of the synchronous generated voltage are

given by⎡⎣ vd

vq

vf

⎤⎦ =

⎡⎣−Rs Lqωe 0

−Ldωe −Rs Lqωe

0 0 Rf

⎤⎦

⎡⎣ id

iqif

⎤⎦

+⎡⎣−Ld 0 Lad

0 −Lq 0−Lad 0 Lf

⎤⎦ d

dt

⎡⎣ id

iqif

⎤⎦ , (1)

where

1. Lad = Llfd + Lmd;

2. Ld = Lls + Lmd;

3. Lq = Lls + Lmd.

3.2. Modeling of Bidirectional Converter

The differential equations for the bidirectional converter can bewritten in terms of d-q components considering the convertercurrent as the state variable.

diddt

= −rsh

Lshid + ωiq + 1

Lsh(Vpd − Vtd) , (2)

diqdt

= −rsh

Lshiq − ωid + 1

Lsh(Vpq − Vtq) . (3)

3.3. Modeling of Induction Generator

An asynchronous grid connected wind driven induction gen-erator is modeled in which the excitation is provided froman autonomous grid. The d-q axes model of the induction ma-chine is considered for the dynamic analysis where the d-axis isaligned with stator flux and q-axis is aligned with stator voltagespace vector. The currents are chosen as state variables, andthe equivalent model of induction generator in synchronousreference frame is expressed as:

d

dt

⎡⎢⎢⎣

ids

iqs

idr

iqr

⎤⎥⎥⎦

=(

1

σLsLr

) ⎡⎢⎢⎣

−RsLr ωmL2m + ωsσLsLr

−ωmL2m − ωsσLsLr −RsLr

RsLm −ωmLsLm

ωmLsLm RsLm

×RrLm ωmLmLr

−ωmLrLm RrLm

−RrLs −ωmLrLm + ωsσLsLr

ωmLrLm − ωsσLsLr −RrLs

⎤⎥⎥⎦

×

⎡⎢⎢⎣

ids

iqs

idr

iqr

⎤⎥⎥⎦ +

(1

σLsLr

)

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1162 Electric Power Components and Systems, Vol. 43 (2015), Nos. 8–10

×

⎡⎢⎢⎣

Lr 0 −Lm 00 Lr 0 −Lm

−Lm 0 Ls 00 −Lm 0 Ls

⎤⎥⎥⎦

⎡⎢⎢⎣

vds

vqs

00

⎤⎥⎥⎦ (4)

Equations (1)–(4) are used to develop the simulation modelfor analyzing the dynamic response of the autonomous powersystem.

4. COORDINATED POWER CONTROL STRATEGYFOR HYBRID AUTONOMOUS POWER SYSTEM(HAPS)

The schematic of the experimental setup of a hybrid au-tonomous power system (HAPS) developed in the laboratoryis shown in Figure 2. Figure 3 shows the coordinated controlstrategy for smooth coordination between a diesel generatorand a battery energy storage system. The controller topologyentails an elaborate and systematic control of the diesel gener-ator and BESS in the autonomous power system by sensing thespeed, voltage, and current signals from the diesel generator,the grid, and inverter. The sensed speed (ωact) is comparedwith the reference speed (ωref) to calculate the speed error ofthe diesel generator. Further, the speed error is fed to the pro-portional controller to obtain the real current reference (idd).However, when the diesel generator power goes below 40%of its rated capacity, the battery management scheme (BMS)controls the output reference current (ids) dependent upon thediesel generator current (idact) and set point (idmin). The in-crease in ids increases the reference current idref, which con-trols the power flow in the autonomous grid. The coordinationbetween the diesel generator and the BESS are maintained bythe actual system current id. Dependent upon the actual systemcurrent (id), the torque of the diesel generator (Tr) is smoothlycontrolled to maintain the power balance in the autonomousgrid.

idd = Lshω(ωref − ωact), (5)

idref = idd + ids. (6)

The real power flow (absorbed/injected) in the autonomousgrid depends on idref (6). To control the reactive power of thegrid, the reference voltage vref is compared with actual gridvoltage vact to calculate the voltage error and the differenceis fed to the proportional and integral controller (PI). Thecontroller outputs a reactive current reference iqref that can beused to control the reactive power that is absorbed from orinjected into the grid.

iqre f = Lshω(vre f − vact ) + rshω

s(vre f − vact ) (7)

FIGURE 2. Experimental setup of hybrid autonomous powersystem.

FIGURE 3. Schematic diagram of the coordinated controlstrategy.

The amount of reactive power injected/absorbed depends onthe reactive current reference (iqref). The actual system currentid and iq are compared with the reference iqref and idref current.These current errors are fed to the respective PI controller todetermine the control voltage in d-q quantities.

vpd = vtd − ωLshiq − Lshω(idre f − idact

)−rshω

s

(idre f − id

)(8)

vpq = vtq + ωLshiq − Lshω(iqre f − iqact

)−rshω

s

(iqre f − iq

)(9)

The system transfer functions are represented in a simplefirst-order system. The Kp and Ki values are selected to makethe closed loop system as stable by using R-H criteria.

id(s) = kLshωs + krshω

τ s2 + (1 + kLshω)s + krshωidre f (s) (10)

iq(s) = kLshωs + krshω

τ s2 + (1 + kLshω)s + krshωiqre f (s) (11)

5. SMALL SIGNAL ANALYSIS OF HYBRIDAUTONOMOUS POWER SYSTEM

The small signal models of a hybrid autonomous power sys-tem with coordinated control and without coordinated controlare shown in Figure 4. The proposed hybrid system is com-prised of a diesel generator and a wind generator along with

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a battery energy storage system. The transfer function of thediesel generator, wind generator, and BESS are modeled usinga simple linear first-order time delay system [32]. The systemis verified with and without coordinated control to observe theimpact and effectiveness of the coordinated control.

For instance, let the total load demand in the hybrid au-tonomous power system be 0.5 p.u. Considering that the windgenerator generates a power of 0.2 p.u. and the remainingpower demand is supplied by the diesel generator, the totalpower generated is determined by:

PT = PDG + PW G ± PB E SS (12)

�P L = PDG + PW G ± PB E SS − PL (13)

In case of a sudden change in load, the demand generationmismatch of the hybrid autonomous power system is controlledby the battery energy storage system. When a sudden loadof 0.2 p.u. is added to autonomous grid, the BESS suppliesthe surplus (insufficient) power to the hybrid system throughthe bidirectional inverter to balance the frequency since theresponse of BESS for load variation is very fast comparedto that of the diesel generator. However, in the absence ofcoordinated control, the BESS continuously supplies the powerto the grid and it does not allow the diesel generator to supplypower demand as shown in Figure 4(c).

In the system with a coordinated controller, the BESSsupplies the surplus (insufficient) power to the hybrid sys-tem through the bidirectional inverter in order to maintain thefrequency. The coordinated controller slowly transfers the ad-ditional power demand (which is taken by the BESS) to thediesel generator, to present the continuous discharge of batteryenergy.

6. BATTERY MANAGEMENT SCHEME

The state diagram for BMS is illustrated using Figure 5(a)and Table 1. In this HAPS, lead acid batteries are used as theenergy storage system. The predefined SOC limits of batteryand the diesel generator power determines the operating modeof the converter. The outer bands correspond to two outerSOC limits, i.e., lower threshold (SOCOLT = 40%) and upperthreshold (SOCOUT = 90%). Normally, the battery used forthe renewable applications has a limited range of depth ofdischarge (DoD) and is limited to 60 to 80%. In case of DoD,the value exceeds the specified limit and the battery suffersfrom over discharge and prolonged over discharge may result inpermanent damage to the battery. In this case the battery is wellcontrolled and SOC is limited to 40 to 90% in order to increasethe life of the battery. The battery is not allowed to chargeabove the upper threshold and it is not allowed to dischargebelow the outer lower threshold. Similarly, the inner bands of

FIGURE 4. Small signal analysis of HAPS: (a) block diagramwithout coordinated control, (b) block diagram with coordi-nated control, (c) output response without coordinated control,and (d) output response with coordinated control.

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1164 Electric Power Components and Systems, Vol. 43 (2015), Nos. 8–10

Case Battery SOC Diesel generator power (Pd) Previous state Next state

1 SOCOLT ≤ SOC ≤ SOCOUT Pdmin ≤ Pd ≤ Pdmax Idle Idle2 SOC < SOCOUT Pd < Pdmin Idle Charging3 SOC > SOCOLT Pd > Pdmax Idle Discharging4 SOC > SOCOUT Pd < Pdmin Idle Dump load5 SOC < SOCOLT Pd > Pdmax Idle Removal of non-critical load6 SOC < SOCOUT Pd < Pdmin Charging Charging7 SOC ≥ SOCIUT Pd > Pdmin Charging Idle8 SOC > SOCOUT Pd < Pdmin Charging Dump load9 SOC > SOCOUT Pd < Pdmin Dump load Dump load

10 SOC > SOCOLT Pd > Pdmax Discharging Discharging11 SOC < SOCILT Pd < Pdmax Discharging Idle12 SOC < SOCOLT Pd > Pdmax Discharging Removal of non-critical load13 SOC < SOCOLT Pd > Pdmax Removal of non-critical load Removal of non-critical load14 SOC < SOCOLT Pd < Pdmax Removal of non-critical load Charging15 SOC > SOCOUT Pd > Pdmin Dump load Discharging

TABLE 1. Control strategy for BMS

battery state of charge limits maintains the battery SOC withinnominal value (inner lower threshold (SOCILT = 70%) andinner upper threshold (SOCIUT = 80%)). Here, the repeatedshuttle of converters between any two modes of operation isavoided in such a way that the present modes decide the nextmode of converter operation. The transition from conductionmode to idle mode is dependent upon the inner band limitsof battery and diesel generator power, whereas the transitionfrom idle mode to conducting mode depends upon outer bandlimits of battery SOC and diesel generator power. Initially,the converter is in idle mode (case 2), when SOC < SOCOUT

and when Pd < Pdmin the converter is switched to chargingmode. And the reference current (ids) for the controller isdetermined by the difference in diesel generator minimum setcurrent (idmin) and actual current (id). This increase in referencecurrent increases the diesel generator power above 40% of itsrated capacity. The converter remains in charging mode untilSOC ≤ SOCOUT and is indicated in case 6. When the SOCreaches the SOCOUT limit and the Pd is less than Pdmin, thenthe rectifier mode is switched to the dump load (case 8) tobalances the excess power in the grid and maintains in thesame case up to Pd > Pdmin (case 9). When Pd > Pdmin, thebattery power is discharge up to SOC ≤ SOCILT to maintainthe battery SOC within the lower threshold. If the battery SOCis less than SOCILT and the diesel generator power is less thanPdmax, then the converter has to operate in idle mode (case 1).During idle mode, if the SOC is higher than SOCOLT and Pd >

Pdmax, then the converter operates as an inverter to dischargethe battery power to grid (case 10). During this mode the storedbattery power is supplied to the grid through the bidirectionalinverter. When the battery is in discharging mode, if the SOC

≤ SOCOLT and Pd > Pdmax, then the non-critical loads areremoved from the autonomous grid to avoid the overloadingof diesel generator (case 13) (see Figure 5(b)). This controlensures that the diesel generator will always run above 40% ofits rated capacity and the battery state of charge is maintainedwithin the predefined limits.

7. RESULTS AND DISCUSSION

The efficacy of the power control strategy and dynamics ofHAPS is evaluated in time domain using MATLAB/Simulinkenvironment and the experimental tests are carried out on aprototype unit built in the laboratory. The details of the ex-perimental setup are shown in Figure 2. The line frequencytransformer connects the diesel generator to the grid. A bat-tery is connected to the grid through a three-phase bidirectionalconverter, which is used to absorb/inject for balancing powerin the grid. Then consider that the wind generator is operat-ing at a constant wind velocity. The inverter is developed usingIGBT’s SKM100GB063D. The voltage transducers LV25P andcurrent transducers LA55P are used to measure the voltagesand the current. The parameters of the HAPS are given in theappendix. The control strategy is digitally implemented on aTMS320LF2407A DSP controller and the relevant results arepresented.

7.1. Dynamic Loading of HAPS

To investigate the dynamic response of the autonomous powersystem, HAPS is subjected to step change in the load. Fromthe simulation and experimental results shown in Figures 6

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Aravind et al.: A Control Strategy for Hybrid Autonomous Power System with a Battery Management Scheme 1165

FIGURE 5. Control strategy for battery management scheme:(a) operating modes of HAPS and (b) battery SOC under dif-ferent conditions.

and 7, it is notable that, initially, the HAPS has a load of 2 kW;at t = 12.5 sec, an additional load of 1 kW is introduced intothe autonomous system. The dynamic performance has beeninvestigated under the following three cases.

7.1.1. HAPS without BESS

From the investigation it is notable that the step increase inload of 1 kW to the HAPS decreases the speed of the dieselgenerator, which causes to reduce the system frequency to49 Hz (Figure 6(a)). Moreover, this increase in load decreasesthe line voltage and it creates oscillations in power as shownin Figure 7(a). Further, the diesel generator takes around 4 secto increase the mechanical torque to balance the load demand.This dip in frequency and voltage affects the sensitive loadsin the HAPS. From the experimental results (Figures 6(b) and7(b)) it is observed that, due to sudden loading of diesel gener-ator, the frequency of the HAPS reduces to 48 Hz and it takesaround 7 sec to settle to the nominal value. This deviation infrequency and voltage exceeds the IS: 1601:1960 standardslimit, which can affect the sensitive loads connected in thenetwork.

FIGURE 6. Voltage and frequency response of HAPS understep increase in load power: (a) load voltage and frequencywithout BESS (simulated), (b) load voltage and frequencywithout BESS (experimental), (c) load voltage and frequencywith BESS and without controller (simulated)

7.1.2. HAPS with BESS and without Coordinated Control

Figures 6(c) and 6(d) depict the waveform of the load voltageand the frequency waveform of the HAPS. When the load is

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1166 Electric Power Components and Systems, Vol. 43 (2015), Nos. 8–10

FIGURE 6. (continued) (d) load voltage and frequency withBESS and without controller (experimental), (e) load volt-age and frequency with BESS and controller (simulated),and (f) load voltage and frequency with BESS and controller(experimental).

changed from 2 to 3 kW, the voltage and frequency dip to412 V and 49.8 Hz, respectively. Further, during load change,the BESS responds quickly by injecting the required mismatchpower into the grid thus balancing the power generation and

FIGURE 7. Dynamic response of HAPS under step increasein load power: (a) output power without BESS (simulated), (b)output power without BESS (experimental), (c) output powerwith BESS and without controller (simulated)

power consumption. However, in the absence of coordinatedcontrol the BESS continuously supplies the power to the grid,and hence, the diesel generator does not take over the increasedload burden, even at a later installment. This is shown in

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Aravind et al.: A Control Strategy for Hybrid Autonomous Power System with a Battery Management Scheme 1167

FIGURE 7. (continued) (d) output power with BESS and with-out controller (experimental), (e) output power with BESS andcontroller (simulated), and (f) output power with BESS andcontroller (experimental).

Figure 7(c). From the test results (Figure 7(d)) a closer agree-ment with simulation results can be observed.

7.1.3. HAPS with BESS and Coordination Control

Figures 6(e) and 7(e) illustrates the dynamic response of theHAPS under sudden increase in load. Figure 6(e) indicates that

the frequency and voltage of the system is nearly constant andit is unaffected by step increase in load. Moreover, during thisstep increase in load, BESS responds very fast and injects themismatched power into the grid in order to balance the dif-ference in generation and consumption. This additional powerinjected by the BESS is slowly shifted to the diesel generatorover a time period of 7 sec, thereby preventing sudden stress tothe diesel generator. These results are experimentally verifiedwith the laboratory prototype model. From Figures 6(f) and7(f), it is observed that there is a smooth coordination in powertransfer between the diesel generator and BESS.

7.2. Dynamic Unloading of HAPS

To investigate the dynamic response of an autonomous powersystem during sudden removal of a load, the diesel generatoris subjected to step decrease in the load. From the simulationand experimental results shown in Figures 8 and 9, it is notablethat, initially, the HAPS has a load of 3 kW; at t = 20 sec, anadditional load of 1 kW is removed from the autonomoussystem. The dynamic performance of HAPS under unloadingis investigated with the following three cases.

7.2.1. HAPS without BESS

Figure 8(a) illustrates that a step decrease of 1 kW load fromthe HAPS increases the grid frequency to 51 Hz and the dieselgenerator takes around 5 sec to reduce the mechanical torqueto balance the load demand. This sudden increase in frequencyand load voltage affects the sensitive loads in the autonomousgrid. The sudden removal of load creates an oscillation in thewind power and diesel power and it is shown in Figure 9(a).Similar results are absorbed from the experimental test results(Figures 8(b) and 9(b)). This deviation in frequency and volt-age exceeds the IS: 1601:1960 standard limits, which can ad-versely affect the sensitive loads connected to the autonomoussystem.

7.2.2. HAPS with BESS and without Coordinated Control

Figures 8(c) and 9(c) depict the system response of the au-tonomous grid during step decrease in load power. When theload is changed from 3 to 2 kW, the voltage and frequencyare increased to 50.6 Hz and 430 V, respectively. Further, theBESS reacts quickly and absorbs the excess power in the au-tonomous grid. Moreover, it does not allow the diesel generatorto reduce the mechanical torque to reduce the excess power inthe grid as shown in Figure 9(c). From Figure 9(c) it is notablethat the sudden release of power creates an oscillation in thewind power for a short period of 2 sec. This situation is ex-perimentally verified and the output wave forms are shown inFigures 8(d) and 9(d).

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1168 Electric Power Components and Systems, Vol. 43 (2015), Nos. 8–10

FIGURE 8. Voltage and frequency response of HAPS understep decrease in load power: (a) load voltage and frequencywithout BESS (simulated), (b) load voltage and frequencywithout BESS (experimental, (c) load voltage and frequencywith BESS and without controller (simulated)

FIGURE 8. (continued) (d) load voltage and frequency withBESS and without controller (experimental), (e) load volt-age and frequency with BESS and controller (simulated),and (f) load voltage and frequency with BESS and controller(experimental).

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FIGURE 9. Dynamic response of HAPS under step decreasein load power: (a) output power without BESS (simulated), (b)output power without BESS (experimental), (c) output powerwith BESS and without controller (simulated)

7.2.3. HAPS with BESS and Coordination Control

The dynamic response of HAPS is verified with the sudden re-moval of a 1-kW load at t = 20 sec from the autonomous grid.During this step decrease in load, BESS responds very fastand absorbs the excess power in the grid to balance the gener-

FIGURE 9. (continued) (d) output power with BESS and with-out controller (experimental), (e) output power with BESS andcontroller (simulated), and (f) output power with BESS andcontroller (experimental).

ation and consumption. It is notable from Figures 8(e) and 9(e)that, during removal of load, the frequency and voltage of thesystem is nearly maintained constant and it is unaffected by

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FIGURE 10. Dynamic response during direct starting of in-duction machine (without BESS): (a) simulated output re-sponse without BESS, (b) experimental output response with-out BESS (experimental scale (speed = 200 rpm/div, current= 5 A/div))

the step decrease in load. During unloading the excess powerin the grid is smoothly transferred to the BESS to balancethe generation and consumption. This situation is experimen-tally verified with a prototype developed in the laboratory byapplying a sudden reduction in load (Figures 8(f) and 9(f)).The BESS with coordinated control ensures a good dynamicresponse under dynamic load changes as well.

7.3. Dynamics During Direct Starting of InductionMachine

To investigate the dynamic behavior of a diesel generator, a0.75-kW induction machine is directly connected to the dieselgenerator at an instant of t = 10 sec. The simulation results(Figure 10(a)) show that, with the start-up of induction ma-chine, the speed of the diesel generator fluctuates. This causes

FIGURE 10. (continued) (c) simulated output response withBESS, and (d) experimental output response with BESS (ex-perimental scale (speed = 200 rpm/div, current = 10 A/div,power = 1000 W/div).

the frequency of the grid to oscillate between 48 to 51.6 Hz,which exceeds the IS standards. The experimental results forthis test are in close agreement with the simulation results(Figure 10(b)).

The dynamic behavior of the autonomous grid during thedirect connection of induction motor is verified experimentallywith BESS and is found desirable (Figures 10(c) and 10(d)).During the direct starting of the induction machine, the BESSsupplies the required power to the autonomous grid therebyreducing the sudden stress to the diesel generator and alsoreducing the frequency oscillations.

8. CONCLUSION

This study presents the dynamic characteristics of a dieselgenerator with BESS in a hybrid autonomous power system.The system performance has been investigated under dynamic

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changes in load as well as under direct starting of an induc-tion motor. The proposed power control strategy ensures asmooth sharing of power between the diesel generator andBESS and also maintains the system frequency within the IS:1601:1960 standard. The battery power management schemeworks well as anticipated to maintain the battery SOC withinthe predefined limit. The efficacy of the scheme is validatedthrough time domain simulations and experimental studies on alaboratory prototype.

REFERENCES

[1] Rosas-Casals, M., “Power grids as complex networks: Topologyand fragility,” Complexity in Engineering, 2010 (COMPENG‘10), pp. 21–26, Rome, Italy, 22–24 February, 2010.

[2] Lhendup, T., “Rural electrification in Bhutan and a methodologyfor evaluation of distributed generation system as an alternativeoption for rural electrification,” Energy Sustainable Dev., Vol.12, No. 3, pp. 13–24, September 2008.

[3] Urmee, T., Harries, D., and Schlapfer, A., “Issues related to ru-ral electrification using renewable energy in developing coun-tries of Asia and Pacific,” Renew. Energy, Vol. 34, No. 2, pp.354–357, February 2009.

[4] Himri, Y., Boudghene Stambouli, A., Draoui, B., and Himri, S.,“Techno-economical study of hybrid power system for a remotevillage in Algeria,” Energy, Vol. 33, No. 7, pp. 1128–1136, July2008.

[5] Bajpai, P., and Dash, V., “Hybrid renewable energy sys-tems for power generation in stand-alone applications: A re-view,” Renewable Sustainable Energy Rev., Vol. 16, No. 5, pp.2926–2939, June 2012.

[6] Valente, O. S., da Silva, M. J., Pasa, V. M. D., Belchior, C. R. P.,and Sodre, J. R., “Fuel consumption and emissions from a dieselpower generator fuelled with castor oil and soybean biodiesel,”Int. J. Fuel, Vol. 89, No. 12, pp. 3637–3642, December 2010.

[7] Payne, M. G., “Motor starting on diesel generators,” ElectronicsPower, Vol. 23, No. 6, pp. 479–483, June 1977.

[8] Chen, Z., and Hu, Y., “A hybrid generation system using variablespeed wind turbines and diesel units,” Ind. Electron. Soc., Vol.3, pp. 2729–2734, November 2003.

[9] Carrasco, J. M., Franquelo, L. G., Bialasiewicz, J. T., Galvan,E., Guisado, R. C. P., Prats, Ma, A. M., Leon, J. I., and Moreno-Alfonso, N., “Power-electronic systems for the grid integrationof renewable energy sources: A survey,” IEEE Trans. Ind. Elec-tron., Vol. 53, No. 4, pp. 1002–1016, June 2006.

[10] Chakraborty, A., “Advancements in power electronics anddrives in interface with growing renewable energy resources,”Renewable Sustainable Energy Rev., Vol. 15, No. 4, pp.1816–1827, May 2011.

[11] Sharma, H., Islam, S., Pryor, T., and Nayar, C. V., “Power qualityissues in a wind turbine driven induction generator and dieselhybrid autonomous grid,” J. Elect. Electron. Eng., Vol. 21, No.1, pp. 19–25, 2001.

[12] Naimi, D., Bouktir, T., and Salhi, A., “Improvement of tran-sient stability of Algerian power system network with windfarm,” 2013 International Renewable and Sustainable Energy

Conference (IRSEC), pp. 251–256, Ouarzazate, Morocco,7–9 March, 2013.

[13] Le, H. T., and Santoso, S., “Operating compressed-air energystorage as dynamic reactive compensator for stabilising windfarms under grid fault conditions,” IET Proc., Renew. Power.Gen., Vol. 7, No. 6, pp. 717–726, November 2013.

[14] Brown, P. D., Peas Lopes, J. A., and Matos, M. A., “Optimizationof pumped storage capacity in an isolated power system withlarge renewable penetration,” IEEE Trans. Power Syst., Vol. 23,No. 2, pp. 523–531, May 2008.

[15] Cochran, A. M., Isles, D. E., and Pope, I. T., Development ofpumped storage in a power system,” Proc. Inst. Elect. Eng., Vol.126, No. 5, pp. 433–438, May 1979.

[16] Serban, I., and Marinescu, C., “Control strategy of three-phasebattery energy storage systems for frequency support in micro-grids and with uninterrupted supply of local loads,” IEEE Trans.Power Electron., Vol. 29, No. 9, pp. 5010–5020, September2014.

[17] Baalbergen, F., Bauer, P., and Ferreira, J. A., “Energy storageand power management for typical 4Q-load,” IEEE Trans. Ind.Electron., Vol. 56, No. 5, pp. 1485–1498, May 2009.

[18] Jayasinghe, S. S. G., Vilathgamuwa, D. M., and Madawala, U.K., “Direct integration of battery energy storage systems indistributed power generation,” IEEE Trans. Energy Convers.,Vol. 26, No. 2, pp. 677–685, June 2011.

[19] Sebastian R., “Modelling and simulation of a high penetrationwind diesel system with battery energy storage,” Elect. PowerEnergy Syst., Vol. 33, No. 3, pp. 767–774, March 2011.

[20] Sebastian R., “Reverse power management in a wind dieselsystem with a battery energy storage,” Elect. Power EnergySyst., Vol. 44, No. 1, pp. 160–167, January 2013.

[21] Sebastian, R., and Pena Alzola, R., “Simulation of an isolatedwind diesel system with battery energy storage,” Elect. PowerSyst. Res., Vol. 81, No. 2, pp. 677–686, February 2011.

[22] Goel, P. K., Singh, B., Murthy, S. S., and Kishore, N., “Iso-lated wind–hydro hybrid system using cage generators and bat-tery storage,” IEEE Trans. Ind. Electron., Vol. 58, No. 4, pp.1141–1153, April 2011.

[23] Mercier, P., Cherkaoui, R., and Oudalov, A., “Optimizing abattery energy storage system for frequency control applicationin an isolated power system,” IEEE Trans. Power Syst., Vol. 24,No. 3, pp. 1469–1477, August 2009.

[24] Jazaeri, M., and Chitsaz, H., “A new efficient scheme for fre-quency control in an isolated power system with a wind gen-erator,” Elect.PowerCompon.Syst., Vol. 40, No. 1, pp. 21–40,November 2011.

[25] Kasal, G. K., and Singh, B., “Voltage and frequency controllersfor an asynchronous generator-based isolated wind energy con-version system,” IEEE Trans. Energy Convers, Vol. 26, No. 2,pp. 402–416, June 2011.

[26] Sharma, S., and Singh, B., “Performance of voltage and fre-quency controller in isolated wind power generation for a three-phase four-wire system,” IEEE. Trans. Power Electron., Vol. 26,No. 12, pp. 3443–3452, December 2011.

[27] Adhikari, S., and Li, F., “Coordinated V-f and P-Q control ofsolar photovoltaic generators with MPPT and battery storagein microgrids,” IEEE Trans. Smart Grid, Vol. 5, No. 3, pp.1270–1281, May 2014.

Dow

nloa

ded

by [

UQ

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] at

12:

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[28] Teleke, S., Baran, M. E., Huang, A. Q., Bhattacharya, S., andAnderson, L., “Control strategies for battery energy storage forwind farm dispatching,” IEEE Trans. Energy Convers., Vol. 24,No. 3, pp. 725–732, September 2009.

[29] Zhang, Z.-S., Sun, Y.-Z., Lin, J., and Li, G.-J., “Coordinatedfrequency regulation by doubly fed induction generator-basedwind power plants,” IET Proc., Renew. Power Gen., Vol. 6, No.1, pp. 38–47, January 2012.

[30] Omine, E., Senjyu, T., Muhando, E. B., Yona, A., Sekine, H.,Funabashi, T., and Saber, A. Y., “Coordinated control of batteryenergy storage system and diesel generator for isolated powersystem stabilization,” IEEE Power and Energy Conference, pp.925–930, Johor Bahru, Malaysia, 1–3 December, 2008.

[31] Wang, L., and Lee, D.-J., “Load-tracking performance of anautonomous SOFC-based hybrid power generation/energy stor-age system,” IEEE Trans. Energy Convers., Vol. 25, No. 1, pp.128–139, March 2010.

[32] Ray, P. K., Mohanty, S. R., and Kishor, N., “Small-signal anal-ysis of autonomous hybrid distributed generation systems inpresence of ultra capacitor and the tie-line operation,” J. Elect.Eng., Vol. 61, No. 4, pp. 205–214, 2010.

APPENDIX

A1. Specifications of the induction machine: 3 �, 0.75 kW,four-pole, 50 Hz, 220 V, 3.8 A.

Machine parameters: rotor resistance (Rr): 12.08 Ω/ph; sta-tor resistance (Rs): 9.5 Ω/ph; rotor and stator leakage reactance(Xlr and Xls): 12 Ω/ph; moment of inertia: 0.02 kgm2.

A2. Specifications of the synchronous machine: 3 �, 3.7kW, four-pole, 50 Hz, 440 V, 3.8 A

Machine parameters: field resistance (Rf): 143.1 Ω; statorresistance (Rs): 2.7 Ω/ph; stator leakage reactance (Xls):12.78Ω/ph; rotor leakage reactance (Xlr): 212.89 Ω; moment of in-ertia: 0.02 kgm2.

A3. Specification of BESS: 120 V, 100 AhA4. Parameters for small signal analysis:

1. KWG = 1.0 and TWG = 1.5 sec

2. KDG = 1/300 and TDG = 2 sec

3. KBESS = −1/300 and TBESS = 0.1 sec

BIOGRAPHIES

Chellachi Kathiresan Aravind received the Diploma in Elec-trical and Electronics Engineering from Noorul Islam Poly-technic College, Nagercoil, India, a B.E degree from K.S.RGroup of Institution, Namakkal, India, and the M.Tech degreefrom VIT University, Vellore, India. From 2009 to 2011, he

was with the department of Electrical and Electronics Engi-neering, SASTRA University, Tanjore, India. He is currently aFull-time Research Scholar with the National Institute of Tech-nology, Tiruchirappalli, India. He is a Member of the IEEE. Hisareas of interest include power electronics, renewable energysystems and FACTS controllers.

Ganesan Saravana Ilango received the B.E. degree from theUniversity of Madras, Chennai, India, in 2000, the M.E. de-gree from Bharathidasan University, Tiruchirappalli, India, in2001, and the Ph.D. degree from the National Institute of Tech-nology, Tiruchirappalli. From 2001 to 2004, he was a Lecturerwith Noorul Islam College of Engineering, Kumaracoil, In-dia. Since 2006, he has been an assistant professor with theNational Institute of Technology. His area of interest includespower electronics, flexible AC transmission systems, and re-newable energy systems.

Chilakapati Nagamani received the B.Tech. degree from SriVenkateswara University College of Engineering, Tiruapati,India, the M.Tech. degree from the Indian Institute of Tech-nology, Kanpur, India, and the Ph.D. degree from the Uni-versity of Technology, Sydney, Australia. From 1985 to 1991,she was with the Central Power Research Institute, Bangalore,India. Subsequently, she joined the Department of Electricaland Electronics Engineering, National Institute of Technology(then known as Regional Engineering College), Tiruchirap-palli, India, as a lecturer, where she is currently a professor.Her areas of interest include power electronics and drives, re-newable energy systems, and FACTS controllers.

Maddikara Jaya Bharata Reddy received the B.E. degree inElectrical and Electronics Engineering from Nagarjuna Uni-versity, Guntur, Andhra Pradesh, India, in 2002. He receivedthe M.E. degree in electrical engineering and the Ph.D. de-gree from Birla Institute of Technology (BIT), Ranchi, India,in 2004 and 2008, respectively. He is currently an associateprofessor in the Department of Electrical and Electronics En-gineering, National Institute of Technology (NIT), Tiruchirap-palli. He has 10 years of experience in teaching and research.In 2010, he received the prestigious national level IEI YoungEngineers Award in the field of Electrical Engineering. Heis a senior member of the IEEE. He is an editor of ElectricalPower Components and Systems. His current research interestsinclude smart grid, substation automation, wide-area protec-tion, digital relaying, soft computing applications in powersystem, power quality analysis, and power system protection.

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