ar

jing

(HPS)

ctric me astuATPdr

studies have been carried out in a distribution network to investigate the dynamic behavior of the micro-

the engeneraG). Inlar pownd put

source is unavailable or insufcient in meeting the load demands,the others can compensate for the difference. Several hybrid powersystems have been developed [3e6]. A dynamic simulation modelof the Hybrid Power System (HPS) has been developed [4], afterdetermining the most appropriate combination of components

turbines and hydro turbines has been created in EMPT/ATP. Nor-mally these sources are directly coupled to the grid through powerelectronic converters and thus have a direct effect on grid voltageand frequency [7]. Therefore, basic models of their equivalentpower electronic interfaces, control strategies and batteries havebeen developed as well. Case studies have been carried out toinvestigate the dynamic behavior of micro-sources in steady andfaulty states. Feasibility of the proposed models has been veriedby simulation results.

* Corresponding author. Tel.: 86 10 62737842, 86 10 62736746.

Contents lists availab

Renewable

els

Renewable Energy 39 (2012) 96e106E-mail address: yelin@cau.edu.cn (L. Ye).voltage (LV) power networks, especially in vast rural areas. Nor-mally DG based micro-sources deliver power to the load throughhybrid power system (HPS) which can basically solve theproblem of energy demand in remote areas. HPS mircrogridscan be connected to the main power network or be operatedautonomously [1,2].

Hybrid Power System (HPS) microgrid may use three-phasescircuits and be loaded with three-phases loads. These factorsgenerate balanced and unbalanced conditions that can be accen-tuated with line fault, short-circuit, wire-break, etc. When one

hybrid system [6]. A grid connected hybrid scheme for residentialpower supply based on an integrated PV array and a wind-driveninduction generator were discussed [7]. However, all the hybridpower systems didnt mention hydro source. Moreover, steady stateof hybrid microgrids was mainly discussed, whereas neglecting thetransient fault analysis.

In this paper, Alternative Transient Program (ATP) version ofElectromagnetic Transient Program (EMTP) and ATPDraw arechosen as a platform to do modeling and simulations. A dynamicmodel of hybrid power systems including photovoltaic cell, windDynamic modelDistributed generation (DG)

1. Introduction

The increasing consumption andcaused by the conventional powertion to the distributed generation (Drenewables such as wind power, sobiomass etc., have been installed a0960-1481/$ e see front matter 2011 Elsevier Ltd.doi:10.1016/j.renene.2011.07.018vironmental problemstion is drawing atten-China, more and moreer, small hydropower,into operation in low

according to the variations in loads. It has been pointed out thata transformer-less small-scale centralized DC-bus grid connectedhybrid (wind/PV) power system supplying electric power to a threephase low voltage distribution grid [5]. An isolated network forvery low voltage decentralized energy production and storagebased on photovoltaic andwindwas developed, mainly consideringthe energy management and control of the photovoltaic and windElectroMagnetic Transient Program/Alternative Transient Program (EMTP/ATP)models. 2011 Elsevier Ltd. All rights reserved.Microgrid sources in both steady state and fault scenarios. Simulation results verify the feasibility of the proposedDynamic modeling of a hybrid wind/sol

Lin Ye a,*, Hai Bo Sun b, Xu Ri Song c, Li Cheng Li a

aDepartment of Electric Power Systems, China Agricultural University, P.O. Box 210, Beib Sui Hua Electric Power Company, Helongjiang Province, Suihua 152061, PR ChinacChina Electric Power Research Institute (CEPRI), Beijing 100192, PR China

a r t i c l e i n f o

Article history:Received 23 December 2010Accepted 14 July 2011Available online 24 August 2011

Keywords:Wind/solar/hydro hybrid power system

a b s t r a c t

Microgrids are LV or MV eleloads. In this paper, dynamwind turbine, hydro turbinexcitation system of hydroTransient Program (EMTP/and reactive power/voltage

journal homepage: www.All rights reserved./hydro microgrid in EMTP/ATP

100083, PR China

ic networks which utilize various distributed generators (DG) to serve localodels of the main distributed generators including photovoltaic (PV) cell,well as the equivalent power electronic interfaces, battery unit of PV and

rbine have been made in ElectroMagnetic Transient Program/Alternative) software package. Control strategies based on active power/frequencyoops for the power control of the inverters have been also developed. Case

le at ScienceDirect

Energy

evier .com/locate/renene

Pe usqisq usdisd (6)From Equations (3) and (6) we get the rotational speed u under

the condition of non-rotational speed.

2.2. Modelling of PV arrays

The electric power generated by a photovoltaic array is uctu-ating according to the illumination and the temperature. Thebuilding block of PV arrays is the PV cell, which is basically a P-Njunction semiconductor that products current via the photovoltaiceffect. PV arrays are constructed by placing numerous PV cellsconnected in series and in parallel [2]. The most commonly usedmodel of a PV cell is the one-diode equivalent circuit as shown in

Energy 39 (2012) 96e106 972. Modeling of the hybrid power system (HPS)

2.1. Modeling of wind turbines (WTs)

The direct-driven Permanent Magnet Synchronous Generator(PMSG) has been widely used in modern wind energy conversionsystem (WECS), since it does not need external excitation anda gearbox. It consists of wind model, turbine model, generatormodel, converter model and MPPT controller model for maximumwind energy capture. These features make PMSG a competitivemachine type of low cost, weight, size, noise emissions, mainte-nance requirements, and high efciency. The available aero-dynamic power on the turbine rotor is given by the followingexpression:

pm 0:5rAv3Cpl (1)where r is air density (kg/m3); A is swept area (m3). The powercoefcient Cp of thewind turbine in Equation (1) is a function of tip-speed ratio l, which is given by:

l uRv

(2)

where R is the radius of blades and u is the rotational speed of thewind turbine shaft. In order to keep maximum efciency in windgeneration, the rotational speed u is adjusted along with windspeed v to maintain l in a constant value which makes Cp have itsmaximum value Cpmax. It can keep wind turbine in maximumwindpower capturing by changing the output active power of generatoraccording to the wind velocity, theoretically. The rotational speed uis determined by the difference between themechanical power andthe output active power of generator without consideration of thelosses [8], which is represented by:

12Ju2

ZPm Pedt (3)

where J is the equal inertia of wind generation system (includingthe inertia of wind turbine, drive train and the rotor of generator)and Pe is the output active power of generator.

The generator model carries out the calculation of terminalvoltage of PMSG as a function of rotational speed u and statorcurrent in d-q synchronous reference frame. The machine modelthat has been used is based on the following equations:

8>:

usd Rsisd Lddisddt

usLqisqusq Rsisq Lqdisqdt usLdisd usjf

(4)

where usd and usq are the terminal voltages; isd, isq are the statorcurrents; Rs is the stator winding resistance, Ld and Lq are the statordirect and quadrature inductances and Jf is the excitation uxlinkage. To minimize generator losses, which are mainly caused bythe losses in the stator winding resistance, the current should bekept as small as possible [9].

The electrical torque Te of the PMSG can be calculated as follow:

Te 32piqhidLd Lq

jfi (5)where p is the number of pole-pairs. For a non-salient-polemachine the stator inductances Ld and Lq are approximatelyequal. This means that the direct-axis current id does not contributeto the electrical torque. So id is kept near to zero in order to obtainthe maximal torque with a minimum current. Then, the output

L. Ye et al. / Renewableactive power of generator Pe is:Fig. 1.The currentevoltage characteristic of a PV cell is derived as

follow:

I Iph ID (7)

I Iph I0exp

qU RsI

AkBT 1

U RsI

Rsh

(8)

where: Iph photo current (A), ID diode current (A),I0 saturation current (A), A the diode quality constant (whenT 28 C, A 28), q electronic charge (1.6 109 C),kB Boltzmanns gas constant (1.38 1023), T cell temperature(C), Rs series resistance (U), Rsh shunt resistance (U), I cellcurrent (A), U cell voltage (V).

There are several parameters (Iph, I0, Rs, Rsh, T, etc) which need tobe determined before the IeU relationship can be obtained. In thispaper a mathematical model of relation between the power, outputcurrent and output voltage is given based on technical parameters,such as short-circuit current (Isc), open-circuit voltage (Uoc),maximum power current (Im) and maximum power voltage (Um),which could reect the output characteristic of the PV cells [10].The novel models are presented as follow.

At Standard Test Conditions (STC) (T 25 C, S 1000 W/m2),the currentevoltage characteristic of a PV cell can be modeledmathematically using Equation (9).

I Isc1 C1

exp

Uo

C2Uoc

1

(9)

C1 1 Im

Isc

exp

UmC2Uoc

(10)Fig. 1. One-diode equivalent circuit model of a PV cell.

C2 UmUoc

1

ln1 Im

Isc

1(11)

where: Isc short-circuit current (A),Uoc open-circuit voltage (V),Im maximum power current (A), Um maximum power voltage(V), Uo cell voltage (V), I cell current (A).

According to the Isc, Uoc, Im, Um on reference condition, the new0 0 0 0

>>>>>>>>DS S

Sref 1

2.3.1. Small hydro turbineIn general, ordinary turbines and waterwheels use the energy

that can be evaluated as the sum of the three forms of energy givenby Bernoullis theorem [11]. This expression remains constant fora given cross section and position in a channel:

v2

2g h p

rg P

rgQ(13)

where v is water ow speed (m/s), g is gravity constant (9.8 m/s2), his height of the water (m), p is pressure of the water (N/m2), r isdensity of the water (kg/m3), P is power (kg m/s) (1 HP 75 kg m/s 746 W), Q is ow of the watercourse (m3/s).

For ordinary modern turbines, the effective power at their inputmay be obtained from Equation (13) neglecting the terms v and pfor the potential energy in the watercourse as:

Pt htrgQHm (14)where ht is the turbine simplied efciency (for standard

Fig. 2. Battery equivalent circuit.

L. Ye et al. / Renewable Energy 39 (2012) 96e10698>>>>>>>>>>>>>>:

I0sc IscS

Sref1 aDT

U0oc Uoc1 cDTln1 bDSI0m Im

SSref

1 aDTU0m Um1 cDTln1 bDS

(12)

where: Sref reference illumination intensity (1000 W/m2),Tref reference cell temperature (25 C), DT difference betweenactual temperature and reference one (C), DS differencebetween actual illumination intensity and reference one (C),a 0.0025/C, b 0.5/C, c 0.00288/C.

2.3. Modeling of hydro turbines

The EMTP/ATPmodels of the small hydropower system, includinghydro turbine, synchronous machine and excitation control system.parameters (Isc , Uoc , Im , Um ) can be developed, thus getting thenew IeU relationship considering the illumination intensity andtemperature on the output characteristic of PV cell.

8>>>DT T TrefFig. 3. Control bloturbines it is taken as 0.80) and Hm is the water head. The availableow of a watercourse (m3/s) is expressed by:

Q Av (15)where A is the area of the cross section (m2) and v is water owspeed (m/s).

2.3.2. Synchronous machineFirst assume: (1) ignoring the motor iron core saturation; (2)

excluding the eddy current and hysteresis motor loss; (3) perma-nent magnets in the stator windings create a sinusoidal uxdistribution. Based on above assumptions, a mathematical model ofsynchronous motor has been built in the EMTP/ATP softwareplatform. Hydroelectric power unit adopts an equivalent models ofwinding synchronous generators [12e16].

Usually, in the d-q coordinate system, winding synchronousgenerator has the following ux equation in the view of thegenerator stator coils point:

8>>>>>>>>>:

vds Rsids umjqs djdsdt

vqs Rsiqs umjds djqsdt

vfd Rfdifd djfddt

(16)ck of PMSG.

3.1. Control of wind turbines (WTs)

The Wind Energy Conversion System includes wind turbines,PMSG and the converter. The converter makes it possible to controlthe PMSG ux and consequently the speed of the generator, facil-itating the integration of WTs. The converter model together withthe MPPT controller model is expressed in the following diagram(Fig. 3).

ontrol block diagram.

Energy 39 (2012) 96e106 99where jds and jqs are total uxes of stator d-axis and stator q-axis,jfd is excitation winding ux, ids and iqs are stator d-axis and statorq-axis currents, ifd is excitationwinding current and um is electricalangular frequency of generator, vds and vqs are stator d-axis andstator q-axis voltages, Rfd is the excitation resistance, Rs is the statorresistance.

Active power, reactive power and electromagnetic torque areexpressed by the following equations:8>>>>:

id vdP vqQv2d v2q

iq vqP vdQv2d v2q

(19)

where id and iq are stator d-axis and stator q-axis currents, vdand vq are stator d-axis and stator q-axis voltages, P and Q are activepower and reactive power.

Searching the optimal operation point of photovoltaic systems iscalled maximum point tracking (MPPT). Based on the characteristicof wind turbine rotor output power P against angular velocity ucorresponding to wind speed v, there is one maximum for eachcurve, and the optimal rotor angular velocity u increases with thewind speed v. This relation is helpful in nding out the point ofFig. 7. Equivalent control diagIt can get the optimal output active power command easily if windvelocity and rotor angular speed are known.

3.2. PV array control strategy

PV array delivers power to loads through a converter and controlsystem (Fig. 4).

As for control of PV arrays, the Droop control Algorithm waschosen to control the converter. Principally, the control strategy ofPV arrays is developed for frequency and voltage based on instan-taneous current and voltage. Thus, the calculated active and reac-tive powers are used to adjust the output frequency and the outputvoltage via droops.

The method of implementing droop control is to use the activepower P as a function of the angular frequency u and use thereactive power Q as a function of the voltage amplitude E. Whenregulating the output power, each source has a constant negativeslope droop on the P, u plane, P is the amount of power injected byeach source when connected to the grid, at system frequency andu* is the system frequency (50 Hz), reactive power regulationcorresponding similarity, thus we can regulate P/Q separately asfollow:(u u* RfPE E* RvQ (20)ram of excitation system.

where u* is the system frequency (50 Hz) and E* is the voltageamplitude.

3.3. Maximum Power Point Tracking (MPPT) algorithm of PV arrays

The characteristics at Standard Test Conditions (STC) providedby the manufacturers show that the power generated by the PV

array depends on the illumination intensity, cell temperatureand cell voltage. Therefore it is necessary for MPPT device toextract the maximum power from the PV arrays. Several MPPTmethods have been reported in to search MPPT [10]. Theextremum method of algorithm is developed in this case. Theoutput power from the PV array in any conditions can beexpressed as:

Fig. 8. Block diagram of transfer function.

L. Ye et al. / Renewable Energy 39 (2012) 96e106 101Fig. 9. Conguration of the Hybrid Power System.

the generator. From the power system point of view, the excitation

25

50

75-75

-50

-25

0

25

50

75-75

-50

-25

0

25

50

75

)

HTsfault occurs

fault occurs

I_W

a(A)

WTs

fault clears

I_Pa

(A)

PVsfault occurs

fault clears

Energy 39 (2012) 96e106P U I U Isc

2641 C1

0B@e

UC2Uoc

1

1CA375 (21)

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5-400

-200

0

200

400-

-200

0

200

400-400

-200

0

200

400

U_Ha

(V)

time (s)

HTs

U_W

a(V)

WTs

fault clears

fault clears

fault occurs

fault occurs

U_Pa

(V)

PVs

fault occurs

fault clears

Fig. 10. Terminal voltages of each micro-source unit.

L. Ye et al. / Renewable102The algorithm searches the voltage operating point where dP/dU 0. To demonstrate the algorithm, the Equation (21) is differ-entiated to get Equation (22).

Isc

2641 C1

0B@e

UC2Uoc

1

1CA375 UIscC1e

U

C2Uoc

C2Uoc

0 (22)

The maximum power voltage is derived by using Newton iter-ation method.8>>>>>>>>>>>>>>>>>>>>>>>>>>>:

Uk1 Uk f 0Ukf 00Uk

Uk1 Uk

I Uk

0B@ IscC1

C2Uoce

UkC2Uoc

1CA

2 Uk

C2Uoc

0B@ IscC1C2Uoc

eUk

C2Uoc

1CA

(23)

where jUk1 Ukj< , is an error. Umax Uk1, Uk is the voltageof the rst K iterations, f0(Uk) is the rst derivative of Uk and f00(Uk) isthe second derivative of Uk. The owchart algorithm is describedby Fig. 5.

3.4. Excitation control strategy of hydro turbines

The excitation control system supplies and automaticallyadjusts the eld current of the synchronous generator to maintainthe terminal voltage as the output varies within the capability of

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5-75

-50

-25

0

I_H

a (A

time (s)

fault clears

Fig. 11. Currents of each micro-sources unit.system should contribute effective control of voltage to enhance ofsystem stability [19]. The excitation control system of synchronousgenerator regulates the excitation voltage across the eld windings,thus affecting electromotive force of generator, ultimately aiming tostabilize the terminal voltage.

Fig. 6 shows the block diagram of an equivalent model based ontransfer function system which can be used to simulate the inputand output characteristics of the excitation system [20].

Fig. 7 shows the equivalent block diagram of excitation controlsystem. Here, we adopt equivalent transfer function model instead

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5-30000

-20000

-10000

0

10000

20000 main grid microgrid

Faul

t cur

rent

(A)

time (s)

fault occursfault clears

Fig. 12. Fault currents of main grid and microgrid.

Circuit breaker is modeled as an ideal time-controlled switch.Simulations are carried out with the fault occurred at t 0.8 s(t 0 s, the beginning of the simulation) cleared at t 1.2 s and thetotal simulation time is 2 s.

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0-4000-2000

02000400060008000

10000reactive power of WTs

react

ive

powe

r of W

Ts(va

r)time(s)

fault occurs

fault clears

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0-8000-4000

0

40008000

120001600020000

active power of WTs

act

ive

powe

r of W

Ts(W

)

time(s)

fault occursfault clears

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

-2000-1000

010002000300040005000

reactive power of PVs

react

ive

powe

r of P

Vs(va

r)

time(s)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0-1000-500

0500

1000150020002500

active power of PVs

act

ive

powe

r of P

Vs(W

)

time(s)

fault occurs

fault clears

fault occurs

fault clears

0500

1000150020002500

reactive power of HTs

pow

er o

f HTs

(var)

fault occurs fault clears

-2000-1000

010002000300040005000

active power of HTs

act

ive

powe

r of H

Ts(W

)

time(s)

fault occurs fault clears

Energy 39 (2012) 96e106 103of real system of excitation system, including four critical parts,such as detection-comparison, series-correction, parallel-correction and modulation-amplication. Corresponding blockdiagram of transfer function is showed in Fig. 8.

where Kma is amplication factor of voltage increment betweenbase voltage of BG1 transistor and its collector voltage, Kse is staticamplication factor of detection-comparison part, ssp is timeconstant of detection comparison. DUF is voltage variation of theexcitation system which is used as an input for the detection-comparison circuit. Wjj is an output parameter of the controlsystem. K stands for proportionality constant.

4. Case studies

4.1. EMTP/ATP modeling issues

The Alternative Transients Program (ATP) is considered to beone of the most widely used ElectroMagnetic Transient Program(EMTP) system for digital simulation of transient phenomena ofelectromagnetic as well as electromechanical nature in electricpower systems. With this digital program, complex networks andcontrol systems of arbitrary structure can be simulated. ATP hasextensive modeling capabilities and additional important featuresbesides the computation of transients. EMTP/ATP has many modelsincluding rotating machines, transformers, surge arresters, trans-mission lines and cables. Interfacing capability to the programmodules TACS (Transient Analysis of Control Systems) andMODELS(a simulation language) enables modeling of control systems andcomponents with nonlinear characteristics. Dynamic systemswithout any electrical network can also be simulated using TACSand MODELS control system modeling [21].

In this case, we chose EMTP/ATP to study the integrationbehavior ofmicro-sources into power networks in steady and faultystates. A dynamic model of hybrid power systems includingphotovoltaic cell, wind turbines and hydro turbines has beencreated in EMPT/ATP. Models of the equivalent power electronicinterfaces, control strategies and batteries have been developed aswell. System studies have been carried out to investigate thedynamic behavior of micro-sources in steady and faulty states.Feasibility of the proposed models has been veried by simulationresults.

4.2. System conguration

In this paper, the hybrid power system consisted of windturbines, PV arrays, hydro turbine, converter, a transformer, batteryand load. Conguration of the studied hybrid power system is rep-resented by Fig. 9. The Permanent Magnet Synchronous Generator(PMSG) is rectied and controlled by an AC/DC/AC converter whichregulates the voltage of the PMSG. The PV system constituted ofseveral panels is connected to the AC bus via a DC/AC converter,which controls the operating point of the PV arrays and the outputpower. The hydro turbine is directly coupled to the AC bus system.The battery is used as energy storage unit, capable of meeting thereal and reactive power demands under fault condition.

The most prevalent distribution voltage class in rural areas is10 kV in China. The bus is supplied by a step-down transformer(10 kV/400 V) from a 10 kV radial network. Feeders are composed ofcables (overhead lines, connection cables) and circuit breakerbetween load and source. Cable can be modeled as an equivalentcircuit with inductance and resistance per-unit length, we choosethe typical value for a distributed level cable: Lc 0.264 mH/km,Rc 0.28 U/km. Loads are modeled as a lumped series R, L branchwith a power factor of 0.8 (cos4 0.8). A fault simulation switch at

L. Ye et al. / Renewablethe main grid side is closed to create a three-phases short-circuit.0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0-1000-500

react

ive

time(s)Fig. 13. Active power and reactive power curves for each micro-sources.

-400-300-200-100

0100200300400

with

bat

tery

(V)

ti

fault occurs

battery acts fault clears

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

-400-300-200-100

0100200300400

with

out b

atte

ry (V

)

time (s)

terminal voltage of PVs

fault occurs

fault clears

A

B

PV

L. Ye et al. / Renewable Energy 39 (2012) 96e1061045. Simulation results and analysis

Fig. 14. Terminal voltages ofSimulation has been performed to verify the performances ofthe proposedmodels and control strategies, both in the steady state

-1000

0

1000

2000

3000

4000

act

ive

powe

r of b

atte

ry(W

)

t

fault occurs

0.5 0.6 0.7 0.8 0.9

0.5 0.6 0.7 0.8 0.9

-1000

0

1000

2000

3000

4000

react

ive

powe

r of b

atte

ry(va

r)

t

fault occurs

Fig. 15. Active power/reacand fault conditions. The simulations covered two scenarios of

me (s)arrays with/without battery.regimes, one is dedicated to the analysis of performances at steadystate (from 0 to 0.8 s) and the other is reserved for the faultconditions (three-phases short-circuit, from 0.8 s to 1.2 s) and the

active power of battery

ime (s)

fault clears

1.0 1.1 1.2 1.3 1.4 1.5

1.0 1.1 1.2 1.3 1.4 1.5

reactive power of battery

ime (s)

fault clears

tive power of battery.

-400-300-200-100

0100200300400 without automatic excitation

U_Ha

(V)

time (s)

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

-400-300-200-100

0100200300400

fault clearsfault occurs

with automatic excitation

U_Ha

(V)

time (s)

fault occurs

atuomatic excitation acts

fault clears

Fig. 16. Compared output voltage of hydro turbine with/without automatic excitationcontrol system.

L. Ye et al. / Renewable Enecontrol of the renewable energy sources interconnected to themain grid.

5.1. Case A. Simulation without battery and excitation system

Fig. 10 presented the terminal voltages of each micro-source. Itcan be seen that the HPS worked in the steady state from initial to0.8 s. The Root Mean Square (RMS) of the terminal voltage is 220 Vat each micro-source. However, when a three-phase short-circuitfault occurs on the main distribution network at 0.8 s, the terminalvoltages droop heavily, especially the wind turbines, which droopsdown to 10% of rated value. The short-circuit fault lasts for 0.4 s(from 0.8 s to 1.2 s) and is cut off at 1.2 s, then the voltages starts torise to normal value. The voltage level during the short circuit isdetermined by the location where fault occurs and the per-unitimpedance of the distribution network. The nearer the fault loca-tion is, the more serious the voltage sags.012345678

auto

mat

ic e

xcita

tion(A

)

time (s)

automatic excitation acts

automatic excitation clears

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

0.00.51.01.52.02.53.03.54.0

const

ant e

xcita

tion(A

)

time (s)

constant excitation

A

B

Fig. 17. Compared excitation currents of hydro turbine with/without automatic exci-tation control system.From Fig. 11 we can see a short transient course at the beginningof simulation, which corresponds to the beginning time of micro-source. Then, a steady state achieved at 0.1 s. When short-circuitoccurs, the fault current is nearly ve times greater than previousvalues of steady state operation. A small direct current appears atthe beginning of fault leading to an increasing fault current.Currents go back to normal values after fault is cut off at 1.2 s.

When a fault occurs in the network, the fault currents are shownin Fig. 12.

It can be seen that most fault currents are supplied by the maindistribution network while the micro-sources provide only a smallfraction of the total fault current.

Fig. 13 shows active power and reactive power of each micro-sources in steady state and fault condition. For wind turbines, theactive power and reactive power could reach 8.412 kW and1.903 kVar in steady state, meanwhile decreasing to 1.668 kWand 0.131 kVar respectively when fault condition occurred. Theactive power and reactive power of hydro turbine rise from2.342 kW to 0.16 kVar in steady state to 2.927 kW and 1.712 kVarunder fault condition. For PVs, active power decreased from2.004 kW to 0.967 kW in fault condition, however, reactive powerincreased from 0.503 kVar to 1.274 kVar when fault conditionoccurred. Overall, the active effort of micro-source reduces,whereas the reactive effort increases. That means micro-sourceswill reallocate the active and reactive powers during fault conditionto maintain the voltage and frequency stability of the microgrid.

5.2. Case B. Simulation with battery and automatic excitationsystem

Simulation has been carried out in the conditionswith battery atPV node and automatic excitation control system at Hydro turbinenode. During fault condition, the battery injects active power andreactive power to the microgrid immediately, which can maintainvoltage and frequency stable of the microgrid. While the automaticexcitation control system of hydro turbine is activated to improvethe terminal voltage of hydro turbine. Simulation results are shownin Figs. 14e16.

It is noted that a three-phase short-circuit fault occurs at 0.8 sand the terminal voltage of PVs decreases dramatically to 8% of itsnominal value. However, the battery is active after 5 cycles,providing active power 2.948 kW and reactive power 0.128 kvar toincrease the terminal voltage. Compared with the situationwithoutbattery, the voltage improves nearly 40%.

During fault condition, the automatic excitation control systemof hydro turbines is also in action. Simulations have been done intwo scenarios of regimes. Firstly, automatic excitation controlsystem is not activated, a constant module of excitation voltage isconnected instead of the automatic excitation control system.Secondly, the automatic excitation control system is connected.

Voltage decreases greatly under fault condition and recoversafter 1.2 s when the fault is cleared (Fig. 16).

Fig. 17 shows compared excitation currents in two scenarios ofregimes. In normal operation, excitation current is kept a constantvalue of 3 A as depicted in Fig. 17. During fault condition, excitationcontrol system is activated automatically at 0.1 s to adjust the eldcurrent to maintain the terminal voltage of the generator. Terminalvoltage increases gradually with the activation of the automaticexcitation control system. It can be seen that the automatic excitationcontrol systemcontributeseffective improvementof terminalvoltage.

6. Conclusions

A dynamic model of a hybrid power system including wind

rgy 39 (2012) 96e106 105turbines, photovoltaic system, hydropower unit has been created in

EMTP/ATP software plateform. The equivalent power electronicinterfaces, control strategies and batteries have been developed aswell. Case studies have been carried out to investigate the dynamicbehavior of micro-sources in steady and faulty states. Feasibility ofthe proposed models has been veried by simulation results.

Acknowledgments

This work is in part supported by the Scientic and TechnicalSupporting Programs of China During the 11th Five-year PlanPeriod (Grant No. 2006BAJ04B03), Program for New CenturyExcellent Talents in China University (Grant No. NCET-08-0543),the Key Project of Chinese Ministry of Education (GrantNo.109017), the National Natural Science Foundation of China

tion (Grant No. 3113029).

Appendix

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The parameters of the hybrid microgrid depicted in Fig. 9 are given as follows:

Wind turbineR 13.26 m, ur 19 rpm, Pr 15 kWPMSGPole pairs: 48 Rs 3.8 U, Ld 13.32 mH, Lq 13.32 mHPower: 15 kW Voltage: 220 V Connection:starPhotovoltaicNs 200, Np 180Sref 1000 W/m2, Tref 25 CIsc 4.9 A, Voc 43.2 V, Im 4.51 A, Vm 34.4 VHydro turbineWater ow speed, v 5 m/sGravity acceleration, g 9.8 m/s2

Hight of the water, h 90 mCross section of dam, A 765 m2

Induction generatorStator resistance, Rs 2.875 UStator inductance, Ls 8.5 mHPole pairs, n 2Automatic excitation control systemKj 2.16, sj 0.21 s, Kz 0.895, Kse 0.495, Km 70.2,Ksp 0.124, DU1 0.28 V, ssp 0.0011 s, s1 1.72 103 s, s2 3.47 103 s,a1 2.82 103, a2 4.82 103, b1 1.63 103, Kma 30.7692Transformer10/0.4 kV, 50 Hz, 1 MVARk 0.0004 U, Lk 0.006 mH, Uk 4%, Dyn11Converter control system/droop parametersFrequency controller F 50 Hz, Rf 1 106

5

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Dynamic modeling of a hybrid wind/solar/hydro microgrid in EMTP/ATP1 Introduction2 Modeling of the hybrid power system (HPS)2.1 Modeling of wind turbines (WTs)2.2 Modelling of PV arrays2.3 Modeling of hydro turbines2.3.1 Small hydro turbine2.3.2 Synchronous machine

2.4 Modeling of battery

3 Control strategy of the hybrid power systems (HPS)3.1 Control of wind turbines (WTs)3.2 PV array control strategy3.3 Maximum Power Point Tracking (MPPT) algorithm of PV arrays3.4 Excitation control strategy of hydro turbines

4 Case studies4.1 EMTP/ATP modeling issues4.2 System configuration

5 Simulation results and analysis5.1 Case A. Simulation without battery and excitation system5.2 Case B. Simulation with battery and automatic excitation system

6 Conclusions Acknowledgments Appendix References