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 Total Downloads : 1598
 Authors : Jogi Sindhura, Manda Sridhar
 Paper ID : IJERTV1IS7427
 Volume & Issue : Volume 01, Issue 07 (September 2012)
 Published (First Online): 26092012
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Improve the Dynamic Stability of an Integrated GridConnected Offshore Wind Farm and MarineCurrent Farm Using FACTS
Jogi Sindhura*, Manda Sridhar**
*(Department of EEE, GIET, JNTU University, Kakinada
** (Department of EEE, GIET, JNTU University, Kakinada
ABSTRACT
This paper presents a control scheme based on Flexible AC Transmission system (FACTS) controller device to achieve both voltage control and damping enhancement of a grid connected integrated 80MW offshore wind farm (OWF) and 40MW marine current farm (MCF). The performance of the studied OWF is simulated by an equivalent doublyfed induction generator (DFIG) driven by an equivalent wind turbine (WT) while an equivalent squirrelcage rotor induction generator (SCIG) driven by an equivalent marinecurrent turbine (MCT) is employed to simulate the characteristics of the MCF. A damping controller of the STATCOM is designed by using modal control theory to contribute effective damping characteristics to the studied system under different operating conditions. A frequencydomain approach based on a linearized system model using eigenvalue techniques and a timedomain scheme based on a nonlinear system model subject to various disturbances are both employed to simulate the effectiveness of the proposed control scheme. It can be concluded from the simulated results that the proposed STATCOM joined with the designed damping controller is very effective to stabilize the studied system under disturbance conditions. The voltage fluctuations of the AC bus subject to the activepower variations of the studied system can also be effectively controlled by the proposed control scheme.
Keywords Dynamic stability, marinecurrent farm, offshore wind farm, static synchronous compensator.

INTRODUCTION
Currently, both ocean energy and wind energy have been combined together in the United Kingdom [1][3]. The ocean is an untapped resource that is capable of making a major contribution to our future energy needs. There are several different forms of ocean energy that are being investigated as potential resources for power generation. Ocean energy includes thermal energy, wave energy, offshore wind energy, tidal energy, ocean current energy, etc.Marinecurrent turbine generators (MCTGs) combined with offshore wind turbine generators (WTGs) will become a new trend for energy production in the future. There has been an extensive growth and quick development in the exploitation of wind energy in recent years, which requires the development of larger and more robust wind energy conversion systems. Today, more than 28 000 WTGs are successfully operating all over the world. Since oceans are covering more than 70% surface of the earth, a hybrid power generation system with both offshore wind farm (WF) and
marinecurrent farm (MCF) can be extensively developed in the whole world in the future. One of the simple methods of running a WF or an MCF is to use many induction generators (IGs) connected directly to the power grid because IGs have the inherent advantages of cost effectiveness and robustness for variablespeed energy conversion systems. Moreover, both WTGs and MCTGs have very similar operating characteristics. However, an IG requires reactive power for magnetization. When the generated active power of an IG is varied due to wind or marinecurrent fluctuations, the absorbed reactive power and the terminal voltage of the IG can be significantly affected. The generated power and the terminal voltage of an IG are always fluctuating with time due to the inherent random characteristics of wind speed and marinecurrent speed. A power control scheme of a WF or an MCF is required under normal operation to allow proper control over active power production. In the event of increasing grid disturbances (e.g., grid faults), an energy storage system for a WF is generally required to compensate fluctuating components generated by the WF. A WF may combine with different flexible ac transmission system (FACTS) devices and energy storage systems such as static compensator (STATCOM) [4], [5], etc.
The analyzed results of stability improvement of power systems using STATCOMs and the damping controller design of STATCOMs were presented in [6]. The design of an output feedback linear quadratic controller for a STATCOM and a variableblade pitch of a wind energy conversion system to perform both voltage control and mechanical power control under gridconnection or islanding conditions were shown in [7]. System modelling and controller design for fast load voltage regulation and mitigation of voltage flicker using a STATCOM were demonstrated in [8]. A new DSTATCOM control algorithm enabling separate control of positive and negativesequence currents was proposed, and the algorithm was based on the developed mathematical model in the coordinates for a D STATCOM operating under unbalanced conditions [9]. An indepth investigation of the dynamic performance of a STATCOM and a static synchronous series compensator (SSSC) using digital simulations was performed in [10]. The results of a study on the application of the recently developed STATCOM for the damping of torsional oscillations occurred in a series compensated AC system
were studied while dynamic performance of the nonlinear system with an optimized STATCOM controller was evaluated under a threephase fault condition [11]. Discussion and comparison of different control techniques such as PSS, static VAR compensator (SVC) and STATCOM for damping undesirable interarea oscillations in power systems were carried out in [12]. The conventional method of PI control for a STATCOM was compared and contrasted with various feedback control strategies, and a linear optimal control based on LQR control was shown to be superior in terms of response profile and control effort required [13]. A STATCOM based on a currentsource inverter (CSI) was proposed, and the nonlinear model of the CSI was modified to be a linear model through a novel modelling technique [14]. The integrated STATCOM/BESS was introduced for the improvement of dynamic and transient stability and transmission capability.
The performance of the different FACTS/BESS combinations was compared and provided experimental verification of the proposed controls on a scaled STATCOM/BESS system [15]. A dynamic voltage control scheme based on a combination of SVC and STATCOM technology on a connected transmission system with IGs in a wind farm was discussed [16]. This paper is organized as below. The configuration and the employed models for the studied integrated OWF and MCF with STATCOM are introduced first. Then, the design procedure and design results for the PID damping controller of the proposed STATCOM using poleplacement technique are depicted. Both steadystate operation points under various wind speeds and marine current speeds and the comparative dynamic responses of the studied system with and without the designed PID damping controller under a noise wind speed disturbance, a marinecurrent speed disturbance, and a threephase shortcircuit fault at the grid are described later. Finally, specific important conclusions of this paper are drawn.

MODELS OF THE STUDIED INTEGRATED OWF AND MCF
Fig. 1 shows the configuration of the studied integrated DFIGbased OWF and SCIGbased MCF with the proposed STATCOM. The 80MW OWF is represented by a large equivalent aggregated DFIG driven by an equivalent aggregated variablespeed WT through an equivalent aggregated gearbox. The 40MW MCF is represented by a large equivalent aggregated SCIG driven by an equivalent aggregated variablespeed CT through an equivalent aggregated gearbox. The OWF, the MCF, the STATCOM and a local load are connected to an AC bus that is fed to the onshore power grid through an offshore stepup transformer and undersea cables. The employed mathematical models of the studied system are described as below.
A. Wind Turbine
The mechanical power (in W) produced by a WT can be expressed by
Where is the air density in kilograms per cubic meter ( = 1.225), Ar is the blade impact area in square meters, VW is the wind velocity in meters per second, Cpw is the power
Coefficient of the WT. w is the tip speed ratio of WT, w is blade pitch angle of WT in degrees. The wind speed is modelled as the algebraic sum of a base wind speed, a gust wind speed, a ramp wind speed, and a noise wind speed. The detailed equations for these four wind speed components can be referred to [17] while the power coefficient of the WT is given by [18].
The cutin, rated, and cutout wind speeds of the studied WT are 4, 15, and 24 m/s, respectively. When Vw is lower than the rated wind speed of the WT (Vwrated), w =
00. When Vw > Vwrated, the pitchangle control system of the WT shown in Fig. 2 activates and the pitch angle of the WT (w) increases. Fig. 3 shows the characteristics of the captured perunit mechanical power versus the perunit generator rotor speed of one of the forty 2MW WTs of the studied 80MW OWF from cutin wind speed to rated wind speed [19]. The optimal output points in Fig. 3 are the ideal maximum output mechanical power of the WT.
Fig.1. Configuration of the integrated OWF and MCF with STATCOM.
Fig.2.Block diagram of the pitchangle control system of the studied WT.
Fig. 3. Characteristics of turbine power versus generator rotor speed [19].
B.MassSpringDamper System and Induction Generator
Fig.4. Twoinertia reducedorder equivalent massspringdamper model of the WT coupled to the rotor shaft of the studied wind DFIG.
Fig. 4 shows the twoinertia reducedorder equivalent mass springdamper model of the WT coupled to the rotor shaft of the studied wind DFIG [20][22]. The effect of the equivalent gearbox (GBw) between the WT and the DFIG has been included in this model. The perunit – and axis voltagecurrent equations of an induction generator can be referred to [25], [26] and they can be used for the electrical parts of the wind DFIG and the marine current SCIG.

Power Converters of DFIG
Fig.5. Oneline diagram of the studied doublyfed induction generator.
Fig. 5 shows the oneline diagram of the studied wind DFIG. The stator windings of the wind DFIG are directly connected to the lowvoltage side of the 0.69/23kV stepup transformer while the rotor windings of the DFIG are connected to the same 0.69kV side through a rotorside converter (RSC), a DC link, a gridside converter (GSC), a stepup transformer, and a connection line. or normal operation of a wind DFIG, the input ACside voltages of the RSC and the GSC can be effectively controlled to achieve
the aims of simultaneous output activepower and reactive power control. Fig. 6 shows the control block diagram of the RSC of the studied DFIG. As shown in Fig. 6.
Fig. 6. Control block diagram for the RSC of the DFIG.
Fig. 7. Control block diagram for the GSC of the DFIG.
The operation of the RSC requires iqrw and idrw to follow the varying reference points that are determined by maintaining the output active power and the statorwinding voltage at the setting values, respectively. The required voltage for the RSC (vrw) is derived by controlling the per unit q and daxis currents of the RSC [27][29]. The control block diagram of the GSC of the studied wind DFIG is shown in Fig. 7. The perunit – and axis currents of the GSC, iqrw and idrw have to track the reference points that are determined by maintaining the DC link voltage vdcw at the setting value and keeping the output of the GSC at unity power factor, respectively. The required perunit voltage of the GSC (vgw) is derived by controlling the perunit q and daxis currents of the GSC [27][29].

MarineCurrent Speed and MarineCurrent Turbine
The MCT is assumed to be driven by tide velocities, and the current velocity is determined by spring and neap tides. The marinecurrent speeds are given at hourly intervals starting at 6 h before high waters and ending 6 h after. It is easy to derive a simple and practical model for marinecurrent speeds under the knowing tide coefficients as follows:
Where Cmr is the marine coefficient, 95 and 45 are the
spring and neap tide medium coefficients, respectively, and Vst and Vnt are the spring and neap marinecurrent speeds, respectively [1], [3]. The employed marinecurrent model is between France to England area [1], [3]. The mechanical power (in W) generated by the studied MCT can be expressed by


DESIGN OF A PID DAMPING CONTROLLER FOR STATCOM USING MODAL CONTROL THEORY
This section presents a unified approach based on modal control theory to design the PID damping controller of the proposed STATCOM shown in Fig. 8 for dynamic stability improvement of the studied system.
Where mr is the seawater density in kg/m (mr = 1025 kg/m3 ), Armr is the blade impact area in m2, VMR is the marine velocity in m/s as depicted in (2), and Cpmr is the power coefficient of the MCT.
The cutin, rated, and cutout speeds of the studied MCT are 1, 2.5, and 4 m/s, respectively. When VMR is higher than the rated speed, the pitchangle control system of the MCT activates to limit the output power of the MCT at the rated value. Since the employed turbine model, pitchangle control system, and massspringdamper model of the studied MCF are similar to the ones that are employed in the OWF, some mathematical models employed in the OWF can be slightly modified to be used in the MCF except the parameters.

STATCOM Fig. 8. Control block diagram of the proposed STATCOM including
The oneline diagram of the studied STATCOM was shown in Fig. 1. The perunit q and daxis output voltages of STATCOM can be expressed by, respectively, [13]
Where Vqsta and Vdsta are the perunit q and d axis voltages at the output terminals of the STATCOM, respectively, bus is the phase angle of the ACbus voltage, Vdcsta is the perunit DC voltage of the DC capacitor Cm, and km and are the modulation index and phase angle of the STATCOM, respectively. The perunit DC voltage current equation of the DC equivalent capacitance Cm can be written as
Where
is the perunit DC current flowing into the positive terminal of Vdcsta , Rm is the perunit equivalent resistance that considers the equivalent electrical losses of the STATCOM, and iqsta and idsta are the perunit q and d axis currents flowing into the terminals of the STATCOM, respectively. The control block diagram of the proposed STATCOM including a PID damping controller is shown in Fig. 8. The perunit DC voltage Vdcsta controlled by the phase angle while the voltage Vsta is varied by changing the modulation index km. The employed parameters of this paper are listed in Table I.
the designed PID damping controller.
TABLE I
EMPLOYED SYSTEM PARAMETERS
The nonlinear system equations developed in Section II are first linearized around a nominal operating point to obtain a set of linearized system equations in matrix form of [30]
Where X is the state vector, Y is the output vector, U is
the external or compensated input vector, W is the disturbance input vector while A,B,C and D are all constant matrices of appropriate dimensions. To design a damping controller for the proposed STATCOM, the disturbance input vector W in (8) and the external input vector U in (9) can be properly neglected by letting D = V
= 0. The state vector X can be partitioned into five sub state vectors as X = [ XDFIG, XSCIG, XMECH, XELEC, XSTA]T, where XDFIG, XSCIG, XMECH, XELEC, and XSTA
are reerred to the system state vectors of the wind DFIG,
the marinecurrent SCIG, the mechanical systems of both WT and MCT, the electrical system including the AC bus, three transmission lines and local load, and the STATCOM, respectively. Because VW seldom reaches the rated wind speed of 15 m/s and VMR seldom operated above the rated marinecurrent speed of 2.5 m/s, VW of 12 m/s and VMR of

m/s are properly selected as the operating points for designing the PID damping controller of the STATCOM.
The eigenvalues and the corresponding damping ratios of the studied integrated OWF and MCF without and with the STATCOM under VW = 12 m/s and VMR = 2.5 m/s are listed in the third and the fourth columns of Table II, respectively. The eigenvalues 1 4 and 5 8 listed in Table II relate to the electrical modes of the studied DFIG and SCIG, respectively. The eigenvalues 9 18 and 19 24 listed in Table II refer to the mechanical modes and the electrical modes of the studied system, respectively. The eigenvalues 25 29 refer to the modes of the STATCOM. An examination of the eigenvalues listed in Table II has the following points. 1) The DFIG modes, the SCIG modes, and the electrical modes of the studied system are almost fixed on the complex plane; 2) The damping of both 9.10 and 11,12 is slightly improved when the STATCOM is connected to the integrated OWF and MCF. The damping of both 9.10 and 11,12 can be simultaneously improved by the addition of the designed PID damping controller; 3) All system eigenvalues are located on the left half of the complex plane under a fixed wind speed and a fixed marinecurrent speed.
The control block diagram of the phase angle of the STATCOM including the PID damping controller was shown in Fig. 8. It is seen that the PID damping controller employs the activepower deviation of the transmission line (Pt) as a feedback signal to generate a damping signal Vcs in order that the damping characteristics of the poorly damped modes 9.10 and 11,12 listed in Table II can be effectively improved. Hence, the output signal in (9) is Y=(Pt) and U= Vcs is the input vector. The transfer function H(s) of the proposed PID damping controller in s domain is given by
Where Tw is the time constant of the washout term while KP, KI and KD are the proportional, integral, and derivative gains of the damping controller, respectively. Taking the Laplace transformation of (8)(9), an algebraic equation of the closedloop system containing the PID damping controller can be obtained. The input signal in domain can be expressed by
Combining (10)(11), we have
The characteristic equation of the closedloop system including the PID damping controller is given by
The four parameters of the PID damping controller can be determined by substituting two pairs of the specified complexconjugated eigenvalues corresponding to the assigned modes (9.10 and 11,12) into (13). The design results of the PID damping controller of the STATCOM are presented as below.
Prespecified Eigenvalues:
9.10 = 5.5Â±j4.8 11,12 = 15.5Â±j0.56.
Parameters of the Designed PID Damping Controller:
KP =10.5, KI =2.37, KD =0.06, Tw = 0.08s
The system eigenvalues of the studied integrated OWF and MCF with the proposed STATCOM joined with the designed PID damping controller are listed in the fifth column of Table II. It can be clearly observed that both 9.10 and 11,12 have been exactly positioned on the desired locations on the complex plane. Some major constraints for selecting the assigned eigenvalues
are simply depicted as below [30].

The obtained parameters of the PID damping controller should be reasonable. For example, the time constant of the washout term must be positive and the gains of the PID damping controller should be as small as possible.

The eigenvalues of the closedloop system including the designed PID damping controller should be completely located on the left half of the complex plane at the selected operating conditions.
According to the eigenvalue results listed in the fifth column of Table II and the four parameters of the designed PID damping controller of the STATCOM shown above, it can be concluded that both constraints 1) and 2) mentioned above can be simultaneously met.

When Pw or Pmr is larger than its rated value, the
Fig. 9. Steadystate operating conditions of the studied system under various values of wind speed and marinecurrent speed
(a) Pw, (b) Qw, (c) Pmr ,(d) Qmr, (e) w, (f) mr, (g) PL, (h) QL, (i) Pgrid, (j) Qgrid, (k) Vbus, (l) Qsta
pitch angle of the WT (w) shown in Fig. 9(e) or



STEADYSTATE ANALYSIS UNDER VARIOUS OPERATING CONDITIONS
This section presents the steadystate operating condition results of the studied system when VW is increased from 4 to 24 m/s while VMR is increased from 1 to 4 m/s. Fig. 9 shows thev3D plots for the calculated steadystate operating conditions of the studied system under the selected values for VW and VMR. The steadystate operating conditions shown in Fig. 9 are analyzed
as below.

Fig. 9(a) shows that the output active power of the OWF (Pw) increases with the increase of VW when Vw is less than the rated wind speed of 15 m/s. Fig. 9(c) shows that the output active power of the MCF (Pmr) increases with the increase of VMR when VMR is less than the rated marine current speed of 2.5 m/s.

However, the output reactive power of the DFIG based OWF (Qw) shown in Fig. 9(b) is kept nearly zero due to the unitypowerfactor operation of the GSC of the DFIG. The output reactive power of the MCF (Qmr) shown in Fig. 9(d) is kept a negative constant value due to the inherent required magnetization VAR of the SCIGbased MCF.
the pitch angle of the MCT (mr) shown in Fig. 9(f) increases to limit the output active power at the rated value.

The ACbus voltage magnitude (Vbus) shown in Fig. 9(k) can be kept at 1.0 pu by the proposed STATCOM. Hence, the absorbed active power (PL) and reactive power (QL) of the local load can also be kept at constant values as shown in Fig. 9(g) and (h).

When both VW and VMR increase from the cutin values to the rated values, Pw and Pmr increase accordingly and, hence, the active power (Pgrid) delivered to the onshore grid increases as shown in Fig. 9(i) but the reactive power (Qgrid) delivered to the onshore grid slightly increases as shown in Fig. 9(j). When both VW and VMR are higher than the rated values, Pw and Pmr both Pgrid and Qgrid exhibit flat tops as shown in Fig. 9(i) and (j).

The reactivepower variation of the STATCOM (Qsta) shown in Fig. 9(l) is similar to the one of Qgrid because Qsta is responsible to supply or absorb the required reactive power from the AC bus to maintain constant Vbus .
Fig. 10. Dynamic responses of the studied system with and without the designed PID STATCOM damping controller under a noise wind speed disturbance (a)Pw, (b) Qw, (c) Pmr ,(d) Qmr, (e) Pgrid, (f) Qgrid, (g) Vbus, (h) Vw
Fig. 11. Dynamic responses of the studied system with and without the PID STATCOM damping controller under a marine current speed disturbance (a)Pw, (b) Qw, (c) Pmr ,(d) Qmr, (e) Pgrid, (f) Qgrid, (g) Qsta, (h) VMR
Fig. 12. Transient responses of the studied system with and without the designed PID STATCOM damping controller under a threephase fault at power grid (a)Pw, (b) Qw, (c) Pmr ,(d) Qmr, (e) Pgrid, (f) Qgrid,(g) mr, (h) rmr, (i) Vw, (j) Vmr, (k) Vbus,(l) Qsta


NONLINEAR MODEL SIMULATIONS
This section uses the nonlinear system model developed in Section II to compare the damping characteristics contributed by the proposed STATCOM joined with the designed PID damping controller on dynamic stability improvement of the studied system under a noise wind speed disturbance, a marinecurrent speed disturbance, and a threephase shortcircuit faultat the grid, respectively.

Noise WindSpeed Disturbance
Fig. 10(a)(g) illustrates the studied system with and without the proposed STATCOM and the designed PID damping controller under the noise windspeed disturbance shown in Fig. 10(h). The simulation sequence is as below:

When 0 s < t < 0.5 s , the OWF operates under a base wind speed of 12 m/s and the MCF operates under a base marinecurrent speed of 2.5 m/s; 2) When 0.5 s < t < 30 s , the noisewind speed shown in Fig. 10(h) is added to the system but the marine current speed is still kept at VMR.=2.5 m/s. The dynamic simulation results shown in Fig. 10(a)(g) are analyzed as below.

It can be seen from the dynamic response of Vbus shown Fig. 10(g) that the proposed STATCOM with the designed PID damping controller can
effectively maintain the AC bus voltage at around
1.0 pu by properly adjusting to tune the quantity of the reactive power of the STATCOM delivered to the AC bus.

Because the proposed STATCOM joined with the designed PID damping controller can offer adequate damping characteristics to the studied system, the oscillations of Pmr, rmr, Vmr and Vbus due to the random noise wind speed disturbance can be fast damped, and they have the smallest amplitudes in three curves.

The amplitudes of the active power delivered to the power grid (Pgrid) shown in Fig. 10(e) and the active power generated by the SCIG of the MCF shown in Fig. 10(c) can be slightly reduced and the absorbed reactive power from the power grid (Qgrid) shown in Fig. 10(f) can be decreased when the STATCOM joined with the PID controller is included in the studied system.

The generated active power of the DFIG Pw shown in Fig. 10(a) is not affected by the addition of the STATCOM with the PID controller.



MarineCurrent Speed Disturbance
Fig. 11(a)(g) plots the studied system with and without the proposed STATCOM and the designed PID damping controller under the marinecurrent speed disturbance shown in Fig. 11(h). When t < 0 s, the OWF operates under a base wind speed of VW = 12 m/s and the MCF operates under a base marinecurrent speed of VMR = 2.5 m/s. It is seen from the dynamic simulation results shown in Fig. 11(a)(g) that all quantities are slightly deviated from the steadystate operating points at t =0 s due to the small variations on marinecurrent speed. Since marinecurrent speed is closely related to the output active power of the MCT, it is seen that the dynamic response of Pmr shown in Fig. 11(c) is similar to the one of VMR shown in Fig. 11(h) and the high frequency components existing in VMR shown in Fig. 11(h) have been filtered out. Comparing the dynamic responses of Qmr shown in Fig. 11(d) with VMR shown in Fig. 11(h), it is found that the magnitude of Qmr gets higher when VMR increases. This is due to the fact that the IGbased
MCF requires larger reactive power for magnetization when the rotational speed and the output active power of the SCIG of the MCF increase.

ThreePhase ShortCircuit Fault at Power Grid
Fig. 12 plots the transient responses of the studied system with and without the proposed STATCOM joined with the designed PID damping controller under a threephase short circuit fault at the grid. The OWF operates under a base wind speed of 12 m/s while the MCF operates under a base marine current speed of 2.5 m/s. A threephase shortcircuit fault is suddenly applied to the grid at t =1 s and is cleared at t =1.25 s. It is seen from the transient simulation results shown in Fig. 12 that most quantities suddenly drop to low values when the fault occurs. When the fault is cleared, all responses shown in Fig. 12 stably return the original steady state operating conditions within 4 s. The proposed STATCOM with the designed PID damping controller can offer better damping characteristics to the studied system under the severe threephase shortcircuit fault than without the PID controller.


CONCLUSION
This paper has presented the improvement dynamic stability of an integrated OWF and MCF using a FACTs (STATCOM). A PID damping controller has been designed for the STATCOM by using a unified approach based on poleassignment approach. Eigenvalue calculations and timedomain simulations of the studied system subject to a noise windspeed disturbance, a marine current speed disturbance, and a threephase shortcircuit fault at the grid have been systematically performed to demonstrate the effectiveness of the proposed STATCOM joined with the designed PID damping controller on suppressing voltage fluctuation of the studied system and improving system dynamic stability under different operating conditions. It can be concluded from the simulation results that the proposed STATCOM joined with the designed PID damping controller is capable of improving the performance of the
studied integrated OWF and MCF under different operating conditions.
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International Journal of Engineering Research & Technology (IJERT)
ISSN: 22780181
Vol. 1 Issue 7, September – 2012