Control Scheme of A Comprehensive Power Quality Controller

Lei Kou College of Electrical and Information Engineering,

Hunan University Changsha, China

An Luo College of Electrical and Information Engineering,

Hunan University Changsha, China

Abstract—A control strategy of the combined system for power distribution grid is proposed, which is composed of a resonant impedance type hybrid active power filter (RITHAF) and static var compensator (SVC). Based on the topology and operating principles, electric model of combined system is established. Then, its control scheme composed of specified harmonics detection and the neural cell generalized integrator PI control for RITHAF and fuzzy PI control for SVC is designed. The harmonic components of grid are detected by specified harmonics detection while the frequency dividing compensation for specified harmonics is implemented using neural-cell generalized integrator control. The fuzzy PI control adjusts the control parameters online in accordance with control error of power grid voltage and fuzzy rules, enhancing the response speed and control precision of reactive power control. With simple structure and good robustness, the proposed controller adjusts parameters adaptively to improve tracking performance. Finally, results of simulation demonstrate the feasibility and effectiveness of new control scheme.

Keywords- harmonic suppression； reactive compensation；integrated dynamic compensation；hybrid active power filter.

I. INTRODUCTION With the power electronic devices applied widely in

industrial enterprises, reactive power and harmonic currents are also produced by inductive load and nonlinear load, increasing the losses and unwanted disturbance and voltage and/or current stress etc. With swift response and low operating cost, SVC, which is composed of TCR and FC, compensates reactive power and eliminates negative sequence component effectively by regulating each phase. However, TCR itself would produce harmonic currents especially in unbalanced load compensation. Active power filter has been an effective way to compensate harmonics dynamically, and because of its swiftness it is widely used nowadays [1]. Yet, restricted by the capacity of its switching elements, APF is not suitable for medium and high voltage systems.

This paper has adopted a comprehensive power quality system which is composed of a resonant impedance type hybrid active power filter (RITHAF) and static var compensator (SVC). It greatly reduces the rating VA of APF [2] and can be used in medium and high voltage system. Based on some researches and control methods on this system [3] - [6], a new control scheme for this system is proposed which includes SVC control and APF control. In SVC part, the

controller has applied an intelligent rule-based fuzzy-PI control method which, according to condition of system, could change PI controller parameters. As for APF part, grid harmonic components are detected through specified harmonics detection, and frequency dividing compensation for each specified harmonics can be obtained by the neural cell generalized integral PI control. To verify its feasibility and effectiveness, representative simulation for the system is presented.

II. STRUCTURE AND OPERATING PRINCIPLE OF COMBINED CONTROL SYSTEM

The configuration of combined system is shown in Fig.1. The active part of RITHAF consists of DC-side capacitor and voltage source converter. Output filter, composed of inductor

0L and capacitor 0C , aims to eliminate the high-frequency ripples caused by switching devices of the inverter. 1L , 1C are tuned at fundamental frequency so that the inverter carries litter fundamental voltage, thus reducing the rating of APF. 5 5L C ,

7 7L C are monotonic filters. HL , HR and HC are high-pass filter in second order. To prevent third harmonic and multiples of third harmonic, TCR adopts delta connection. Passive filter could provide fixed capacitive reactive power while TCR provides a consecutive reactive power, so both of them satisfy reactive power of grid or load. APF could improve the performance of passive filter and keep resonance between passive filter and grid equivalent impedance from happening.

Load

5C

5L7C

7LHC

HLHRGrid

VSIoutputfilter

passivefilter

TCR

FSRC

susz si

Fi

TCRi

Fig.1 the structure of combined system

978-1-4577-1600-3/12/$26.00 © 2012 IEEE

Harmonic-impedance-type equivalent circuit of combined system is shown in Fig.2. shZ is grid equivalent harmonic reactance; shI is harmonic current in grid; LhI is load harmonic current (including TCR); active part of HAPF is considered as an ideal controlled current source cI ; cU is output voltage of inverter; RhI and PFhI denote fundamental resonance branch current and passive filter branch current;

RhZ and PFhZ represent equivalent harmonic impedance of fundamental resonance branch and passive filter branch.

shZshI 0U

PFhZ

cURhZ

LhIRhI

PFhI

Fig.2 Equivalent circuit of Harmonic-impedance

So the equation of the system proposed in the paper can be derived

0

0

sh PFh Lh

PFh Rh c

PFh PFh C

sh sh

C Rh Rh

c Lh

I I II I IU Z I UU Z IU Z II I

= +⎧⎪ = +⎪⎪ = +⎪⎨ = −⎪⎪ =⎪

= −⎪⎩

(1)

From (1), we can get

PFhsh Lh

PFh Rh sh

ZI IZ Z Z

=+ +

(2)

0sh PFh

LhPFh Rh sh

Z ZU IZ Z Z

= −+ +

(3)

Thus, from equation (2), we could get the equivalent circuit adopting the control strategy c LhI I= − , as is shown in Fig.3. We can see that equivalent impedance RhZ is bigger than harmonic impedance of passive filter. As a result, most of harmonic currents would be diverted into the passive filter circuit and the harmonic currents injected into the power grid will be close to zero. Therefore, the combined system can not only control harmonics but reduce the influence on voltage fluctuation on common connection point.

shZPFhZ

RbZ

shI

FhILhI

Fig.3 Simplified circuit

III. CONTROL SCHEME OF COMBINED SYSTEM In order to achieve a fast responding speed and good

control accuracy, this paper has adopted fuzzy PI control method for SVC and specified harmonic detection and neural cell generalized integral PI control method for HAPF. The methods will be discussed in details.

A. APF control 1) Method of specified harmonics detection

Reference [9] adopted specific harmonics detection method based on the instantaneous power theory. The process is: First, detect the currents of three-phase load branches (including the part of TCR) Lai , Lbi and Lci ; convert them into Li α , Li β using

abcC αβ− transformation; by jpqC + and j

pqC − transformation, Li α

and Li β are converted into thj harmonic components under

rotating coordinate system Lpji+ , Lqji+ and Lpji− , Lqji− ; then DC

components Lpji+ , Lqji+ and Lpji− , Lqji− are obtained through low-pass filter, and through reversal inverse transformation these DC components are transformed into thj harmonic components.

However, in the system described by the paper, the process that inverter output harmonic voltage compensates harmonic current would cause deviation of phase angle and cast an influence on compensation performance of the system. Therefore, the paper puts forward a method for compensating the reversal inverse transforming matrix of Lpj Lqj Lpj Lqji i i i+ + − − .

According to the delay caused by harmonic of different frequency, the fixed matrixes j

pqC + and jpqC − are

( )

sin( ) cos( )

cos( ) sin( )j

s j s jjpq

s j s j

j t j tC

j t j tθ

ω θ ω θω θ ω θ

++ − +

=− + − +

(4)

( )

sin( ) cos( )

cos( )sin( )j

s j s jjpq

s j s j

j t j tC

j t j tθ

ω θ ω θω θ ω θ

−− + − +

=− + +

(5)

Where jθ is thj harmonic delay angle caused by system

hardware, sω is angular frequency of grid fundamental

frequency. Adding components of Lpj Lqj Lpj Lqji i i i+ + − − which are converted through inverse transformation of modified matrixes

( )j

jpqC θ

+ and ( )j

jpqC θ

− to harmonic components of each time,

we obtain three phase harmonics Lhai , Lhbi and Lhci , delay of which has been eliminated.

2) Neural cell generalized integral PI control

Fig.4 shows the block diagram of PI control with neural cell generalized integrator. J-state transition is included. Input of the controller is the difference between grid harmonic current Lhi and inverter output current ci while output is u .

2,5....

j

∑ IK▲

PK▲/d dtK inverter

Lhi

ci

Fig.4 neural-cell generalized integral PI control

Now, let’s define the difference between grid harmonic current and inverter output current as ( ) Lh ce t i i= − . Because generalized integrator could perform integral of amplitude of periodic quantity and has no influence on its frequency and angle, generalized integral signal of each harmonic can be obtained.

Similar to general PI control method, the discrete expression of the output of PI control with neural-cell generalized integrator is

( ) [ ( ) ( 1)] ( )

/ (| | | |)

/ (| | | |)

P I jj N

P P P I

I I P I

u k K e k e k K e k

K K K K

K K K K

∈

⎧ = − − +⎪⎪ = +⎨⎪ = +⎪⎩

∑▲ ▲

▲

▲

（6）

PK , IK are control coefficient and integral coefficient of controller respectively; N is times of harmonics RITHAF needs to filter. Considering target of combined system is main harmonics in power distribution system, so

{ }2,5,7,11,13,17N ∈ （7）

Inverter output signal is

( ) ( ) ( 1)u k K u k u k= + − （8）

Where u is inverter input, and K is neural scale factor which varies according to variation of error e (k).

0.08 0 | ( ) | 0.10.15 0.1 | ( ) | 0.30.05 0.3 | ( ) |

when e kK when e k

when e k

≤ ≤⎧⎪= < <⎨⎪ ≤⎩

（9）

B. SVC control: In closed-loop control algorithm of SVC, satisfying steady-

state accuracy could be achieved by conventional PI control algorithm but issue of contradiction between swiftness and stability is not easy to solve. Additionally, because of the nonlinear characteristic of SVC, plus load and variation of environment during system operation, coefficient of control system would fluctuate. Obviously, to control SVC system using fixed PI parameters would affect control performance.

To achieve a quick response rate and nice control precision, this paper combines conventional PI control and fuzzy control, and adjusts PI parameters PK and IK online through fuzzy reasoning strategy to optimize dynamic property. Control system of fuzzy PI control is shown in Fig.5. In the fig, error e and rate of error variation ce are input of fuzzy controller while output is two parameters of PI controller. System based on fuzzy controller of single-input is designed.

ddt

Mux FuzzyController

PIcontroller argT etIK PKe

ce

refu

Fig.5 Fuzzy PI control for SVC

Where E and cE are input language variables, their fuzzy set is { }, , , ,NB NS Z PS PB and domain of discourse is [-0.06, 0.06]. Similarly, the corresponding output language variables are PK and IK ; there fuzzy set is { }, , , ,Z PS PM PB PVB and domain of discourse is [0, 0.04]. Since characteristic of triangle shape grade of membership function is swiftness, each fuzzy data is calculated using it.

Fuzzy rules are the most important part of fuzzy controller, and from several simulation results they can be concluded as follows

• When difference between procedure value and desired value is large, a large PK and a small IK are required so as to improve responding speed and avoid long period fluctuation.

• When difference is small and within the range of control requirement, we need a small PK and a large

IK to reduce the static error and increase control accuracy.

IV. SIMULATION AND APPLICATION RESULTS To verify suitability and feasibility of the proposed control

scheme for combined system, the paper executes the simulations based on the software MATLAB. Simulation parameters are shown in Table.1. To make a comparison, both conventional system control and proposed control are used in simulations. Parameters of neural cell PI control method are:

0 0.31c = 0.51Iη = 0.36Pη = . Fig.6 (b) shows the dynamic effect of convention control (hysteresis control for RITHAF

and conventional PI control for SVC), while (c) shows the dynamic effect of the proposed control method.

TABLE I. SIMULATION PARAMETERS

/L mH /C Fμ /R Ω

Impedance of grid 0.5 0.02

TCR 20 0.2

Output filter 0.25 48 0.07

High-pass filter 0.28 201 1..02

5th tuned filter 1.6 286.5 0.05

7th tuned filter 0.69 301.2 0.03

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1-500

0

500

IL(A

)

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1-300

-200

-100

0

100

200

300

Is(A

)

Time(s)

(a)

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1-500

0

500

IL(A

)

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1-300

-200

-100

0

100

200

300

Is(A

)

Time(s)

(b)

Fig.6 Comparison of current compensation effect (a) source current and spectrum compensated by conventional control method (b) source current and spectrum compensated by proposed control method

From the Fig.6, it is obvious that sinusoidal feature of the supply current with the proposed detection and control is more obvious and the compensation accuracy is much higher than conventional control method.

V. CONCLUSIONS Based on topology of a combined system with the roles of

unbalanced load compensation, power factor compensation and harmonic current filtering, this paper has proposed a new control scheme. The performance of system is enhanced by above-mentioned control methods. Simulation has shown the proposed system under new methods is effective in power correction and harmonic suppression.

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