A New Stability Enhanced Power System Based on Adaptive ... · drives, power quality conditioners and HVDC transmission for offshore wind generation. Unlike the line commutated converter

International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190

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A New Stability Enhanced Power System Based on Adaptive Controller and

Space Vector Technique

Abeena A*, Faris K K**

* (PG Scholar, EEE Department, Al-Ameen Engineering College, Shornur

** (Assistant Professor, EEE Department, Al-Ameen Engineering College, Shornur

Abstract

Most of the wind energy conversion systems are deployed or

integrated into the grid using Double Fed Induction

Generators. This paper proposes a wind energy conversion

system using permanent magnet synchronous generator

along with pulse width modulated current source inverter. It

forms a good alternative because of its high reliability and

efficiency. The proposed system can be made adaptive to

varying wind speed providing an adaptive control strategy

with an aid of PI controller which is self-tuned based on

linear approximations and also by a maximum power point

tracking system. The pulse width modulation can be

achieved by the algorithm of space vector modulation

technique that may control the power output of the inverter.

Keywords: Adaptive PI control, permanent magnet synchronous

generator, Maximum power point tracking, pulse width

modulated current source inverter, space vector modulation

I. INTRODUCTION

Most of the wind turbines for on-land

emplacements use double fed induction generators due to

their economic advantages (i.e., high efficiency, improved

controllability and reduced rating of the converter). The

challenges of making the wind energy conversion system

adaptive to varying wind speed can be met by a combination

of non-conventional energy conversion systems and

improved adaptive control strategies. One of the most

promising of them is the permanent magnet synchronous

generator (PMSG) which has clear advantages in terms of

efficiency and power density. Integration into the grid of this

type of generators requires a full rated AC/AC converter.

The possible type of converter is the pulse-width modulated

current source converter (PWM-CSC) which has potentially

more advantages for medium size wind turbines. It is

capable of controlling the DC current according to the wind

velocity independently of the DC voltage. This characteristic

is exploited to create an adaptive control which does not

require measure of the rotational speed. In addition, it

permits the use of a full bridge diode rectifier in the side of

the machine and hence, efficiency and reliability are

improved.

The adaptive control techniques that perform

identification and control of dynamic systems can be

adapted to highly-complex dynamic systems in order to

auto-adjust the controller parameters. However, these

methods require an adequate initialization of the controller

parameters and detailed system data. Adaptive control

allows the integration of wind resources as plug-and- play

devices in electric power systems. As a result, this type of

control is a key technology in smart-grids and electric

energy systems with non-dispatchable generating sources.

The PI controls has been widely used for control of

power systems, but the tuning of these controllers is a highly

demanding task when the parameters of the controlled

process either are poorly known or vary during normal

operation. An adaptive PI control can be designed in order to

achieve high-performance control systems. However, during

normal operation where the controlled process are almost

time invariant, a fixed PI control may have similar

performance in terms of reference tracking. Additionally,

since the process is nonlinear, by using linear estimators it is

possible to obtain a time varying linear approximation which

can be used to self-tune the controller.

Thus proposed a new adaptive control strategy for a

wind energy conversion system based on a permanent

magnet synchronous generator and a pulse-width modulated

current source converter. The proposed conversion system is

a good alternative due to its high efficiency and reliability.

The control strategy uses an adaptive PI which is self-tuned

based on a linear approximation of the power system and a

desired closed loop response.

F

II. WIND ENERGY CONVERSION SYSTEM

The increasing number of renewable energy sources

and distributed generators requires new strategies for the

operation and management of the electricity grid in order to

maintain or even to improve the power-supply reliability and

quality. In addition, liberalization of the grids leads to new

management structures, in which trading of energy and

power is becoming increasingly important. The power-

electronic technology plays an important role in distributed

generation and in integration of renewable energy sources

into the electrical grid, and it is widely used and rapidly

expanding as these applications become more integrated with

the grid-based systems. The proposed energy conversion system is based on

PMSG. This type of machine has three main features which

are relevant for wind power applications: there are no

significant losses generated in the rotor; magnetization

provided by the permanent magnets allows soft start; and

there is no consumption of reactive power. The first

characteristic implies an improvement in efficiency while the

second and third effect the power electronic converter which

does not require bidirectional power capability. Hence, a full

bridge diode rectifier is enough for the AC/DC conversion. In

addition, PMSGs allow smaller, flexible and lighter designs

as well as lower maintenance and operating costs. A gear box

is not required if it is designed appropriately with a high

number of poles.

A PMSG requires a full rated converter which is

usually a back-to-back configuration with voltage source

converters as shown in Fig. 1(a). This type of converter is

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efficient for integrating induction generators since it controls

reactive power in the rectifier as well as in the inverter.

However, a PMSG does not require reactive power and hence

the rectifier can be replaced by a diode rectifier [11].

Nevertheless, the DC voltage in a VSC must remain within

certain limits in order to maintain stability. As a consequence

of this, a DC/DC boost converter is required for controlling

the power in the electric machine as depicted in Fig. 1(b).

The use of a three-phase diode rectifier improves the

efficiency and reliability of the energy conversion system but

the boost converter could have an opposite effect.

Three main possible configurations of PMSG are:

Fig 1(a): back to back converter with VSC’s

Fig 1(b): diode bridge rectifier and diode converter

Fig 1(c): proposed conversion system

Variation on the DC voltage is not a limitation on

the PWMCSC; hence the power can be controlled directly

by the inverter. In addition, a PWM-CSC does not require an

electrolytic capacitor as the VSC. This impacts the

reliability of the systems since 30% of failures on AC

converters are related to the electrolytic capacitor.

PWM-CSC technology has been applied

successfully in a wide range of applications such as motor

drives, power quality conditioners and HVDC transmission

for offshore wind generation. Unlike the line commutated

converter a PWM-CSC is based on forced commutation and

consequently it is able to control active and reactive power.

In addition, it has an inherent short-circuit protection

capability.

A PWM-CSC requires semiconductor devices with

reverse voltage blocking capability. This can be added to a

standard insulated-gate bipolar transistor (IGBT) using a

diode connected in series as shown in Fig. 2

Fig 2: pulse width modulated CSC

Another alternative is the new type of

semiconductor devices such as reverse blocking IGBTs

(RB-IGBT) or integrated gate commutated thyristors

(IGCTs). The latter alternative is promising for PWM-CSCs.

The DC current is directly controlled by the

converter. This feature is especially important for low wind

velocities when voltage in the machine is greatly reduced.

While a voltage source converter requires a constant voltage

on the DC side, a PWM-CSC is able to adapt its voltage

according to the wind velocity. Efficiency is improved due

to this capability. The unity power factor is achieved by the

modulation itself. This can be done by using space vector

modulation. In addition, output voltage presents low

harmonic distortion and the performance for weak grids is

guaranteed.

Nevertheless, PWM-CSC has some challenges related to the

control of the converter. The filter placed in the AC side can

create resonances with the grid so that active damping

techniques are required. However, these techniques reduce

the band width of the control. In addition, the voltage on the

DC side must be controlled according to the wind velocity in

order to improve efficiency and guarantee stability.

III. PROPOSED CONVERSION SYSTEM

Fig 3: proposed hierarchical strategy with adaptive control and SVM

technique



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1. Maximum Power Point Tracking (MPPT)

The power generated by a wind turbine is

proportional to the cube of the wind velocity.

Maximum power transference is achieved by an optimal

value of

Consequently the rotational speed must be proportional

to the wind velocity and hence, power must be proportional

to the cube of the rotational speed.

On the other hand, the PMSG is modelled on the

rotor reference frame (dq) as follows:

The voltage UDC on the diode rectifier is proportional to the

voltage in the terminals of the machine which in turn is

given where a proportional constant.

UDC(pu) = s

A speed sensor is not required when using this

expression since the voltage UDC is measured. The generated

power is given by UDC . IDC (PMSG losses are ignored). As a

result, the optimal IDC to achieve maximum tracking

IDC(t) = G . (UDC(t))2

This equation establishes a set point for current IDC as given

in Fig. 4

Fig.4: Reference for using a maximum tracking point algorithm

A low pass digital filter (LPF) is required to

smooth voltage. The cut-off frequency is set below

commutation frequency. On the other hand, the dynamics of

IDC depends on the inductance LDC as follows:

The modulation of the converter depends on the

current IDC which varies according to the wind velocity but

cannot be zero.

Where Px is the power delivered by the converter which in

turn depends on the modulation index m as follows:

where is the angle of the output current. This angle must

be equal to the angle of the grid voltage in order to achieve a

unity power factor. A phase locked loop is required as

illustrated in Fig. 7.1. Therefore, the only control variable is

m

The output power beyond the capacitive filter is

approximately equal to Px. Usually, the control in current

source converters is made in two stages, one controlling the

active power and the other controlling the voltage in the AC

side. This approach directly controls the active power and

the reactive power is maintained by the modulation itself.

Therefore, the possible resonances on the controls are

reduced.

2. Adaptive PI Controller

By adaptive control any control strategy which uses

parameter estimation of the plant in real time by using

recursive identification. The adaptive controller to be

designed is based on the certainty equivalence principle:

design the controller as long as the plant parameters are

known. However, since these are unknown at time tk, they

are replaced by an estimate given by an online identifier.

This adaptive controller is easy to implement, since

for the controlled plant, only the output signal is needed for

feedback. An adaptive PI control is designed where the plant

parameters are estimated by an online identifier, as shown in

Fig. 5

Fig. 5: Adaptive control and identifier

In continuous time, a PI controller can be defined as



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being u(t) the control signal, and e(t) the error signal

(represented by the difference between the reference and the

output signals). In this case, these variables are given as

follows:

-

In discrete time, the PI controller can be defined as

Being the sample time h=tk-tk-1, e(tk)and ei(tk) the error and

the integral error at time tk respectively, and ei(tk-1) the

integral error at time tk-1. By defining a delay operator q-

1such as y(tk-1)=q

-1y(tk) . Equation can be rewritten as

follows:

Therefore, the control signal at time tk can be expressed as

Obtaining the following expression for the PI controller in

discrete time

where the parameters and of the PI controller in continuous

time can be related to the controller in discrete time, as

follows:

Since the process to be identified is nonlinear, the identified

model is a linear approximation of the nonlinear model at

time instant tk. A simplified first order model is selected,

described by a discrete transfer function, as

Equations by using the transformation as follows:

and

By using equations it is possible to formulate the block

diagram of Fig. 5

Fig. 6: Diagram block using transformation

From this figure it is possible to obtain the closed loop

transfer function, as follows:

If defining desired closed loop poles, given by

Pd (z) = (1- 1z-1

) (1- 2-2

)

where 1 and 2 are the discrete time roots of (34), which

can be related to the continuous time roots 1 and 2 by

using

1=es1h

2=es2h

It is possible to obtain the controller parameters by

comparing the closed loop poles with the desired closed

loop poles as follows:

Therefore, the controller parameters can be obtained as

where it is evident that c1 and c2 are related to the linear

approximation model of the nonlinear process, represented

by the discrete transfer function. When the projection



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algorithm is applied in for the estimation the following

actualization rule is obtained:

where a1’(tk) and b0’(tk) are the estimated parameters at time

tk, and a1’(tk-1) and b0’(tk-1) are the estimated parameters

at time tk-1. Since the controller parameters are dependent on

and according a1’ to b0’, a time varying parameters for each

can be obtained as follows:

where c1(tk) and c2(tk) are automatically tuned according to

the desired closed loop poles.

Finally, the controller parameters KP and KI can be

calculated by

Therefore, the resultant controller is an adaptive PI

controller calculated for each tk. The behaviour of the

controller can be determined by the selection of the desired

closed loop poles and the sample time h.

3. Model Reference Adaptive Control

Reference current Iref is modified during a short

circuit in order to improve the short circuit behaviour of the

converter. A slightly different current Iref in which the

desired output is generated by a linear reference model is

proposed. The reference model can be selected with an order

less than or equal to the order of the process. In this work, a

zero order model is used in pre-fault (I’ref=Iref), no control

during the fault and a first order model after the fault as

follows:

where 0 must be selected as a stable root ( | 0 | < 1 ) ,

where it is clear that the reference model must be selected as

a stable model with unitary gain. However, the selection of

the reference model and the pole placement technique are

separate problems, so it is evident that by using a reference

model the flexibility of the control system in the assignment

of the closed loop poles is increased. The fault condition is

detected using the voltage Ux.

IV. RESULTS

Wind velocity for 15-s simulation is performed. Base wind

velocity is 12 m/s. A gust is simulated in order to

demonstrate the maximum tracking point capability of the

proposed control. Wind velocity profile was created using a

detailed model which considers stochastic behaviour.

Rotational speed and voltage are plotted. The linear

approximation given in (5) is more accurate for low wind

velocities. At high wind velocities, the generated power

increases the current and hence, the voltage drop on the

inductance influences the generated voltage.

The linear approximation is accurate enough from

a practical point of view and maximum tracking is achieved.

High inertia of the set turbine-generator produces a delay in

the rotational-speed tracking capability but also a smoothing

effect. This is expected in almost all type of controls for

wind energy. Generated power. Wind velocity is again

shown in this figure. An almost perfect tracking

characteristic is achieved. The control strategy changes

dynamically according to the wind conditions. If a time

invariant PI control is used the performance could be similar

at least at nominal wind velocity. In that case, the proposed

algorithm can be used as a tuning technique. Three-phase

voltages and currents in the PWM-CSC. Small harmonic

distortions are present in three-phase voltages due to the

commutation process. They are attenuated by the

transformer and hence, the voltage in the point of common

coupling is completely sinusoidal. A smoother waveform

can be achieved by increasing the switching frequency at the

expense of higher switching losses.

Transient behaviour of the proposed control was

also tested in the same distribution feeder. Wind velocity

was maintained constant in 12 m/s. A three-phase short

circuit at Node 3 was simulated. The voltage on the grid

dropped to almost zero. Current increased due to the drop on

the grid voltage in Node 3. The converter still worked in this

condition maintaining the unity power factor. The reference

model enter into operation by maintaining. This allows for

energy storage in three-phase voltages due to the

commutation process. They are attenuated by the

transformer and hence, the voltage in the point of common

coupling is completely sinusoidal. A smoother waveform

can be achieved by increasing the switching frequency at the

expense of higher switching losses.

Transient behaviour of the proposed control was

also tested in the same distribution feeder. The reference for

changes smoothly since it depends on the wind velocity. The

modulation index increases up to the point of over-

modulation. Consequently, the parameters of the control

decreases. These parameters return to their normal values

after the fault is cleared. Notice that the voltages and



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currents after the fault are within the maximum limits due to

the introduction of the reference model.

Fig.7: Wind velocity provided to the system having 300 varying wind

speeds for 0-15 sec

Fig 8: Output of Stator voltage and Stator Current (with fault time from

0.6-0.7 sec)

Fig. 9: Output of DC Voltage and Current (with fault time between 0.6-0.7

sec)

Fig.10: Output of Modulation Index(m), DC Current(Idc), Reference

Current(Iref), Total Power(P)(with fault time 0.6-0.7 sec)

Fig. 11: Output of PWM-CSC (with fault) showing the decrease in Voltage

and increase in Current at 0.6-0.7 sec

Fig. 12: Output of Grid showing the Voltage zero and high Current with

fault time 0.6-0.7 sec



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Fig 13: FFT Analysis with fault

V. CONCLUSION

Thus a new stability enhanced power system was

implemented based on adaptive controlling technique and

space vector modulation. Both the control and the type of

converter increase the flexibility of the wind turbine. They

are able to operate in critical conditions such as short circuit

and fast changes in wind velocity. Measurements of wind

velocity or rotational speed are not required. A reference

model is used to improve the transient behaviour of the

control after critical faults. For systems with time invariant

behaviour, the adaptive controller also behaves as a fixed

controller. Therefore, it can be seen that he adaptive

controller method can be used as a technique for self-tuning

the controller based on the desired response.

The extension of this project can be performed

moving form generation side towards transmission side.

Transmission of power is a high demanding task. It require a

thorough analysis and procedure to reduce the losses

involved. The best option on extending the project is

focusing on to transmission side using HVDC links that

shows high priority in reduced power loss transmission.

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A New Stability Enhanced Power System Based on Adaptive ... · drives, power quality conditioners and HVDC transmission for offshore wind generation. Unlike the line commutated converter