Rev. Roum. Sci. Techn.– Électrotechn. et Énerg. Vol. 65, 1-2, pp. 21–26, Bucarest, 2020

Van Yüzüncü Yıl University, Institute of Science, Department of Electrical and Electronics Engineering, Van, Turkey, E-mail: 1dogancelik@yyu.edu.tr, 2emeral@yyu.edu.tr

PERFORMANCE COMPARISON OF SEQUENCE EXTRACTORS FOR REFERENCE CURRENT GENERATION AND SAG/SWELL

DETECTION IN POWER SYSTEMS DOĞAN ÇELİK1, MEHMET EMİN MERAL2

Keywords: Average filter, Positive and negative sequence extractor, Distributed generation, Power quality, Harmonic distortions.

The electric power generation systems are relatively affected by unbalanced, fault voltages and harmonic distortions in single-phase or three-phase systems. These abnormal conditions cause power quality problems and have severe influences on control of power conversion systems. This paper presents a comparative benchmarking of positive-negative sequence (PNS) extractor methods for reference current generation, sag/swell detection without time delay and eliminating oscillations on control signals. The performance comparisons of the sequence extractor are examined in terms of harmonics, unbalanced networks and start-up. The selected PNS extractors are also applicable for control of single and three phase applications. The effectiveness and validation of the PNS extractors are examined in a power conditioner controller under various cases.

1. INTRODUCTION Along with increasing penetration of power converters

and renewable energy sources based distributed generation (DG) systems, flexible alternating current transmission system (FACTs) devices, uninterruptable power supplies (UPS), custom power devices (CPD) and distribution static compensator (DSTATCOM) applications force the power system to operate under unbalanced grid conditions. In particular, sudden disconnection of these applications from the electric grid during voltage sag/swell may cause severe problems such as power outage and voltage flicker [1–5]. Hence, the control of these devices has gained more and more attention under unbalanced grid conditions. The extracted fast and accurate positive-negative sequences (PNS) components are of vital importance to generate reference current and to detect voltage sag/swell and increases the dynamic response of the controllers [6–9].

Separation of fast and accurate PNS voltage and current components are of vital importance to generate reference current, to detect voltage sag/swell and to increase the dynamic response of the control strategies. Synchronous reference-frame phase locked loop (SRF-PLL) is well known that exhibits fast and accurate performance under balanced conditions. However, the SRF-PLL suffers from some limitations in the presence of the grid voltage disturbances [10, 11]. In recent studies, many researchers have focused on improving the accuracy and response of PLLs based PNS extractors under non-ideal conditions [12] such as delayed signal cancellation (DSC) [13–15], moving average filter (MAF) [16–19] and dual adaptive filter [20]. Although the DSC and MAF based PNS extractors have an easy digital implementation and simple structure, but unfortunately, they lead to some small inaccuracies and slow dynamic response under heavily distorted voltage. In [21], another modified SRF-PLL based on reverse polarity and another signal, which has a ripple, is added to obtain pure sine signal and fast voltage sag/swell detection.

Other approaches are double second-order generalized integrator (DSOGI) [22] and decoupled double synchronous reference (DDSRF) [23]. The main drawback of the DSOGI is affected by heavily distorted voltage and

the DDSRF consists of many sub-modules and has longer computation time. Recently, other approaches have emerged such as third order sinusoidal signal integrator (TOSSI) [8] and multi complex coefficient filter (MCCF) [24] to separate fast and accurate sequence components. These techniques are affected by harmonics as well as having longer settling times and many sub modules.

This paper presents comprehensive benchmarking of the PNS extractors to generate reference current and to detect voltage sag/swell for control of the DG power systems, FACTs devices and CPD under heavily distorted voltages. The dual average filter (DAPLL) based PNS extractor achieves fast tracking the reference input signal and eliminate the low/high order harmonic components and oscillations, accurately compared to TOSSI and fast Fourier transform (FFT). A noteworthy contribution of this paper is to discuss applications of the sequence extractors for single-phase system and three-phase system.

2. THE PROPOSED TEST SYSTEM Ripple errors or oscillations caused by adverse grid

conditions can affect the control of power conversion systems such as DG power systems, FACTs devices, CPD including dynamic voltage restorer (DVR), series shunt filter, static transfer switch (STS), UPS and energy storage devices [25–27]. The proposed test system is examined in a power conditioner controller and its configuration is described in Fig. 1a. The PNS signals obtained by the sequence extractors can be used in various applications as: • Fast and accurate PNS voltage and current components

measured by sequence extractor methods are used to generate reference current without any ripple errors.

• Generation of fast and accurate PNS signals is used to eliminate oscillations (ripple errors) on the control signals of power conditioner and detect voltage sag/swell in FACTs and CPDs such as DVR and STS (Fig. 1b).

3. SEQUENCE EXTRACTOR METHODS This section presents an overview of the existing

sequence extractors to indicate the importance of using fast

22 Performance comparison of sequence extractors 2

and accurate sequence extractors which are a significant part of the control strategies.

3.1. FFT BASED SEQUENCE EXTRACTOR The fast Fourier transform (FFT) based techniques

typically depend on frequency-domain methods. The FFT implements small discrete Fourier transform (DFT) pieces to reduce complex calculations. This feature of the DFT ensures fast response and enhances steady state accuracy. The DFT is commonly used for decomposition of the voltage sequences and harmonic monitoring and metering [28, 29],

Fig. 2 – The block-diagram of the DFT.

where the input signal is obtained by sampling time

domain signal. denotes the DFT kth frequency component. The mathematical calculation of the DFT is given based on Fig. 2 as:

, (1)

where and N is the number of

sampling points.

€

! ˆ x αβk n( ) =

! ˆ x αβk n −1( ) +

! x αβ n( ) −! x αβ n − N( )[ ]e

− j2π iN

n−1( ), (2)

where is the current window and is the previous window sequence.

3.2. TOSSI BASED SEQUENCE EXTRACTOR The third order sinusoidal signals integrator (TOSSI)

filter based sequence extractor is an effective method to separate the voltage and current sequences and harmonic

components under adverse grid conditions [8]. The TOSSI filters ensure fast dynamic response compared with the second order generalized integrator (SOGI) filter. As seen from the block diagram of the TOSSI filter in Fig. 3a, the characteristic transfer functions of the TOSSI-filter can be obtained by (3) and (4)

, (3)

, (4)

where and are tuning parameter for TOSSI filter and ω0 is fundamental frequency. determines the bandwidth of filter and the parameter decides dynamic response of the filter. The dynamics of the system depends on the dynamics of the sequence extractor. Therefore, it is required to select appropriate gain parameters of the TOSSI. To provide a filtering performance, must be set to 3.5 in the TOSSI-filter. Therefore, in this paper, is set to 3.5 to ensure desired level filtering intensity. The value is tuned to give the desired dynamic response after the value of is set. Figures 3a and 3b depict using both in single phase and in three phase systems.

The relationship of positive orthogonal d and q signals and negative orthogonal d and q signals for voltage and current are , and similarly

, .

3.3. DAPLL BASED SEQUENCE EXTRACTOR The dual average filter based phase locked loop (PLL)

(DAPLL) is improved by the integration of the two average filters into the structure of the adaptive notch filter algorithm [30]. The single phase average PLL (APLL) has similar properties with FFT. However, the APLL provides simple implementation and faster transient response than FFT to extracted high-order harmonics and PNS

Fig. 1– a) The proposed system configuration, b) sequence extractor methods for generation of reference current and sag/swell detection.

.

Fig. 3 – Structure of the TOSSI based sequence components extraction;

a) TOSSI filter block diagram and b) separation of the sequence components.

3 Doğan Çelik, Mehmet Emin Meral 23 components [31, 32]. As shown in Fig. 4a, the response time of the APLL has been enhanced with removing one cycle delay through a negative feedback branch compared to APLL proposed in [31]. The response time of the APLL is also affected by using the number of samples. The DAPLL based PNS extractor has some advantage to existing methods, FFT and TOSSI such as no gain parameters, mitigates low and high harmonic components, no proportional integral (PI) controller’s gain tuning process and achieving fast and robust response. The feedback signal is also eliminated by adding negative feedback. Although using feedback gives some advantages such as reducing the steady-state error of the system, rejection of disturbances and noise signals and changing the performance of the system with parameter variations, it has some drawbacks [33, 34]: • The increasing number of components such as, such as

sensors and error detectors, • Reducing the overall gain of the system, • Requiring an error detector to compare two states, • Stability and sensitivity problems.

As given in Fig. 4b, the output signals of the DAPLL are termed as αqV and βqV which are lagging αV and βV

signals by 90 , respectively. ( )tV hp+ is the input signal

that comprises of grid phase voltage ( )tV p and harmonic

voltage ( )tVh . The input signal can be written based on phase angle hφ , grid phase voltage and harmonic voltage in the following [30]

( ) ( )hn

hpphp thVtVtV φ+ω+φ+ω= ∑∞

=+ sin)sin(

2. (5)

The magnitudes of the positive and negative input signals are calculated in the following [35]

VApl+ =1T

C t( )F t( )d t =0

T

∫

=1T

cos hϕ t( )( )F t( )d t0

T

∫ = 0.5Vp sin ωt +φh( ),,

(6)

VApl− =1T

S t( )F t( )d t =0

T

∫

=1T

sin hϕ t( )( )F t( )d t0

T

∫ = 0.5Vp cos ωt +φh( )..

(7)

The magnitude of the output voltage, AplV can be derived as [35]

( ) ( ) 222

pAplAplApl VVVV =+= −+ , (8)

where 2pV is the magnitude of the output voltage. The

phase angle of the input signal is hφ :

=φ

−

+−

Apl

Aplh

V

V1tan . (9)

The amplitudes of the positive and negative input signal are written in the following:

( ) ( ) ( )pAplAplp tVtCVV φω== +++ sincos , (10)

( ) ( ) ( )pAplAplp tVtSVV φω== −−− cossin , (11)

where ( )tS and ( )tC are related to sine and cosine functions. The output voltage ( )tVo of APLL comprises of positive sequences ( )tV p+ and negative sequences

( )tV p− of voltage. The output voltage of the APLL is

( ) ( ) ( )tVtVtV ppo −+ += . The feedback signal ( )tF is eliminated by adding negative feedback as given in the following

( ) ( ) ( ) ( ) ( )tVtVtVtVtF hpoohp ++ =−+= . (12)

Fig. 4 – Structure of the DAPLL based sequence components extraction; a) DAPLL filter block diagram and b) separation of the sequence

components.

The amplitudes of the sequence voltage components are computed in the following.

v+ = vα+( )2 + vβ

+( )2

v− = vα−( )2 + vβ

−( )2.

(13)

4. PERFORMANCE EVALUATION OF THE PNS EXTRACTORS

In this section, performance comparisons of the sequence extractors are examined in a sample power conditioner controller. The gain parameters for the PNS extractors are selected as their optimal values to ensure minimizing settling time and eliminating ripple errors. As shown in Table 1, gain parameters for the proposed test system are given. The PNS voltage components selected in per unit system (1 p.u). The performance comparison of the DAPLL has been conducted with FFT and TOSSI based PNS extractors by simulation studies using the PSCAD/EMTDC

24 Performance comparison of sequence extractors 4 software. To show the advantages and drawbacks of the PNS extractors, various cases have been carried out in the following: • Case I. Testing impact of the line to line to ground

(LLG) grid faults on the PNS extractors. • Case II. Testing impact of the start-up of the PNS

extractors. • Case III. Testing the impact of voltage swells conditions

on the PNS extractors. • Case IV. Testing impact of harmonic distortion and

LLG fault conditions on the PNS extractors.

Table 1 Gain parameters of the proposed test system

Parameters Values kT1 3.5 TOSSI-PLL kT2 3.18 Voltage 0.31 kV (1 pu) Grid Frequency 50 Hz

Load power 0.1 MW Duration of run 1 s Solution time 0.01 ms

PSCAD/EMTDC

Channel plot step 0.02 ms

4.1. CASE I At 0.2 and during eight cycles (80 ms), the impact of the

LLG (the decreasing voltage values of phase B and phase C are 55 % of their nominal value) on the sequence extractors presented in Fig. 5. To show the dynamic response of the DAPLL, a cutaway-view is taken and zoomed. The results show that the DAPLL provides the best performance in terms of fast tracking phase, the shorter settling time of voltage sequences and reducing voltages oscillations in the voltage sequences almost at zero levels. In particular, the frequency of FFT is considerably influenced by grid faults as shown at the bottom of Fig. 5. The DAPLL significantly exhibits less settling time than FFT and TOSSI-PLL (less than one cycle – 20 ms). The dynamic response time (settling time) of the TOSSI-PLL is longer than FFT.

4.2. CASE II Same observations between input and output signals of

PNS extractors are obtained and given as graphically in Fig. 6. It can observe that the DAPLL is fast tracking the

input signals as shown in Fig. 6 and the settling time of the DAPLL is smaller than the settling time of the FFT and TOSSI-PLL. In particular, the FFT is not settling. The start-up of the DAPLL and TOSSI-PLL is 14 ms and 30 ms, respectively.

Fig. 5 – The impact of the LLG on the PNS voltage components,

frequency and output signals of the FFT, TOSSI-PLL and DAPLL.

Fig. 6 – Results for start-up: a) output signals and b) extraction of the error signals for FFT, TOSSI-PLL and DAPLL.

5 Doğan Çelik, Mehmet Emin Meral 25

Fig. 7–The impact of voltage swells on the PNS voltage components and

output signals of the FFT, TOSSI-PLL and DAPLL.

4.3. CASE III As shown in Fig. 7, it can observe that the DAPLL is

fast detecting PNS voltage signals and the response time of the DAPLL is less than the response time of the FFT and TOSSI-PLL under voltage swell conditions. The transient response time of the PNS extractors is depicted using different colours (as seen in Fig. 7). However, the settling time of the FFT is less than TOSSI-PLL.

4.4. CASE IV The impact of the LLG and 5th and 7th harmonics on the

PNS signals are discussed in this case. At 0.2 s and during 80 ms, the LLG fault as considered in Case I is applied to the utility grid. The result depicts that the DAPLL has considerably minimized harmonic oscillations on PNS signals nearly at zero levels, exhibit the fast dynamic response and less phase error estimations (between input and output signals). To demonstrate the performance of the DAPLL, a cutaway-view is taken and using zoomed in Fig. 8. The TOSSI-PLL is hard to effectively filtering low/high order harmonics compared with the DAPLL and FFT. However, it has less phase error estimations than FFT. The DAPLL ensures considerably good harmonics filtering capability. The unit total harmonic distortions (THD) vector for the DAPLL is highly low and less than 0.1 % compared with TOSSI-PLL (2 %.) and FFT (2.5 %.)

4.5. NUMERICAL RESULTS FOR COMPARISONS As shown in Table 2, a brief transient performance

comparison for some PNS extractors presents to exhibit the performance of the PNS extractors. As given in Table 2, the DSOGI has a longer response time. The response time of MCCF is close to the TOSSI. The results show that the DAPLL based PNS extractor exhibits better removing

harmonic errors on the PNS components, provides the fastest transient response and lower settling time compared to previous sequence extractors.

Table 2 Settling time of the PNS extractors

Sequence extractors Settling time sources

DSOGI > 40 ms [22] MCCF 40 ms [24] TOSSI 40 ms

FFT 20 ms DAPLL 14 ms

5. CONCLUSION In this paper, a comparative benchmarking of the PNS

extractors is presented for fast phase tracking and successfully removing ripple errors as a result of unbalanced grid faults and harmonics. The effectiveness and correctness of the PNS extractor are examined and evaluated under various case studies. The case study results show that the DAPLL based PNS extractor exhibits better performance than FFT, TOSSI and various advanced PNS extractors in literature. In particular, the DAPLL based PNS extractor has slightly better performance for eliminating ripple errors under harmonic distortions. It also achieves fast phase detection and reduces settling time compared with FFT and TOSSI. The FFT is considerably influenced by frequency deviations. The DAPLL based PNS extractor

Fig. 8 –The impact of the LLG and harmonic distortions on the PNS voltage components and output signals of the FFT, TOSSI-PLL and

DAPLL.

26 Performance comparison of sequence extractors 6 is almost unaffected by low- high order harmonic components and frequency deviations. Moreover, it has a simple structure and less computational burden, which provide an easy implementation.

Fast and accurate PNS signals obtained by the DAPLL based PNS extractor has no ripple errors and can be used for the control and sag/swell detection of various applications. As a significant benefit to researchers and academician concerned with the sequence extractor methods, a deep comparison of the sequence extractors is presented under unbalanced and distorted networks.

ACKNOWLEDGMENTS This study is a part of Ph.D. thesis of first author in

Institute of Science of Van Yuzuncu Yıl University (Van, Turkey).

Received on November 4, 2018

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