https://doi.org/10.6113/JPE.2019.19.2.519
ISSN(Print): 1598-2092 / ISSN(Online): 2093-4718
Precise Modeling and Adaptive Feed-Forward Decoupling of Unified Power Quality Conditioners
Yingpin Wang†, Rubangakene Thomas Obwoya*, Zhibo Li*, Gongjie Li*, Yi Qu**, Zeyu Shi***, Feng Zhang***, and Yunxiang Xie***
†,*College of Physics and Electronic Engineering, Hainan Normal University, Hainan, China
**Hainan Province Key Laboratory of Laser Technology and photoelectric Functional Materials, Haikou, China
***School of Electric Power, South China University of Technology, Guangzhou, China
Abstract
The unified power quality conditioner (UPQC) is an effective custom power device that is used at the point of common coupling to protect loads from voltage and current-related PQ issues. Currently, most researchers have studied series unit and parallel unit models and an idealized transformer model. However, the interactions of the series and parallel converters in AC-link are difficult to analyze. This study utilizes an equivalent transformer model to accomplish an electric connection of series and parallel converters in the AC-link and to establishes a precise unified mathematical model of the UPQC. The strong coupling interactions of series and parallel units are analyzed, and they show a remarkable dependence on the excitation impedance of transformers. Afterward, a feed-forward decoupling method based on a unified model that contains the uncertainty components of the load impedance is applied. Thus, this study presents an adaptive method to estimate load impedance. Furthermore, simulation and experimental results verify the accuracy of the proposed modeling and decoupling algorithm.
Key words: Adaptive feed-forward decoupling, Interaction analysis, Power quality, Precise unified modeling, UPQC
Manuscript received Apr. 12, 2017; accepted Nov. 17, 2018
Recommended for publication by Associate Editor Jinjun Liu.
†Corresponding Author: wangyingppp@126.com Tel: +8615217630408, Hainan Normal University
*College of Physics & Electronic Eng., Hainan Normal Univ., China
**School of Electric Power, South China Univ. of Technol., China
Ⅰ. INTRODUCTION
Recently, power quality (PQ) issues have attracted a lot of attention. PQ issues can be broadly classified into voltage problems and current problems [1]. These problems include voltage sags that decrease the efficiency of power system networks, and current harmonics that increases energy losses and reduce the life span of connected equipment. Common solutions to these problems include dynamic voltage restorers [2], active power filters [3] and unified PQ conditioners (UPQCs) [4].
Studies define UPQC as an effective custom power device that is used at the point of common coupling to protect a load from PQ issues. UPQCs can solve voltage sags, harmonics, a low power factor and three-phase unbalance. Moreover, the UPQC is a combined series and parallel converter (also called a shunt converter) used to enhance the voltage and current qualities [5].
Most researchers have focused on the control algorithms of UPQCs [6], [7] and rarely investigated their modeling. A number of studies have been conducted on the modeling of the parallel and series converters and idealized transformer models [8], [9]. Raphael J. Millnitz dos Santos considered the leakage inductance of transformers and modeled each of the converters separately [10]. A. Senthilkumarand proposed a unified equivalent circuit for UPQCs and used a series converter as the voltage source and a parallel converter as the current source [11]. Kian Hoong Kwan [12], [13] applied an L filter and an idealized transformer model to establish a unified equivalent circuit of UPQCs. However, they did not reveal the natural characteristics of UPQCs. None of the above-mentioned studies considered the effects of excitation impedance and they did not extensively analyze the interactions of the series and parallel units in the AC-link. Thus, a precise model should be established to analyze the natural characteristics of UPQCs.
Most of the decoupling studies have investigated the interaction of the d-axis and the q-axis in one converter [14], [16]. R. Modesto stated that UPQCs have strong coupling and decoupling from the dq coordinate to the αβ coordinate in single converters [14]. Najafi M. proposed a decoupled system consisting of separate UPQCs and wind turbines in a DC-link [15]. Ryszard S. presented a diagram with a combination of series and parallel converters decoupled in a single converter and analyzed the interactions in the DC-link [16]. Li Peng revealed that the interactions of the series and parallel units occur in the AC and DC-links. He also analyzed the interactions in the steady state and idealized conditions, and superficially eliminated the interactions. However, the natural characteristics of the coupling were not explored [17].
The coupling of the series and parallel units in the AC-link severely affects the compensation performance. Thus, the interference of the series and parallel units should be accurately decoupled to improve the compensation performance.
This study utilized an equivalent transformer model to accomplish the electric connection of the series and parallel converters in the AC-link and established a precise unified mathematical model of UPQCs. The interactions of the series and parallel units were then analyzed. Afterward, an adaptive feed-forward decoupling method based on a unified model was applied to eliminate the interference of the series and parallel units. An adaptive method was used to estimate the load impedance. Furthermore, simulations and experiments were conducted to verify the accuracy of the proposed modeling and decoupling algorithm.
Ⅱ. UNIFIED MATHEMATICAL MODELING OF UPQC
At present, the most common topologies of UPQCs are grid side series and load-side parallel. Their schematics are shown in Fig. 1.
Fig. 1. Schematic of a grid side series and load side parallel UPQC.
The series converter is mainly used to compensate for the voltage offset, and the parallel converter is applied to inhibit the harmonics and reactive compensation. Series and parallel converters share a DC capacitor, and this is called coupling. However, the interaction is small [15], and the interaction in the DC-link is not observed in this study.
A circuit diagram is shown in Fig. 2. The parallel converter applies an LCL filter and the series converter applies an LC filter since the transformer is equivalent to the inductance, and the filter is equivalent to the LCL filter. One phase is considered, where the transformation ratio is 1:1 and the three phases are symmetrical.
Fig. 2. Circuit diagram of a UPQC in one phase.
As shown in Fig. 2, the transformer output voltage is:
The transformer input voltage is:
The transformer input current is:
The parallel injecting current is:
where ,
,
,
,
,
,
,
, and
.
In an idealized transformer model, the transformer output voltage u2 is equal the input voltage u1, and the output current i2 is equal to the input current i1. In other words, the leakage inductances z1 and z2 are equal to zero, and the excitation impedance zm is infinite. Consequently, the impact of the transformer leakage inductance and excitation impedance are negligible. In fact, an equivalent transformer model can precisely indicate the transformer, as shown in Fig. 2. In the MATLAB simulation, the excitation impedance zm was calculated by the transformer capacitor PN and rating voltage VN, as shown in Equ. (5), and the leakage inductances z1 and z2 were set to 1% of excitation impedance. In the experiment, the transformer parameters were obtained from no-load and short-circuit tests. The following modeling and simulation indicate that the transformer leakage inductance and excitation are important in terms of device performance. Thus, these factors should be modeled in an equivalent transformer model.
where ω is the angular frequency (commonly equal to 100π).
Ⅲ. INTERACTION ANALYSIS OF SERIES AND PARALLEL UNITS
As shown in Fig. 2, the state equations were difficult to establish considering that the unified circuit of a UPQC was an improper network. Thus, a transfer relationship was established based on equations (1)-(4), as shown in Fig. 3.
Fig. 3. Transfer relationship of a UPQC.
where:
A. Series Converter Output Voltage to Transformer Output Voltage
As shown in Fig. 3, the influences of the source voltage Us and the parallel converter output voltage Up were negligible, and the transfer function between the series converter output voltage Ui and the transformer output voltage U2 was obtained by Equ. (16).
B. Series Converter Output Voltage to Parallel Injecting Current
As shown in Fig. 3, the influences of the source voltage Us and the parallel converter output voltage Up were negligible, and the transfer function between the series converter output voltage Ui and the parallel injecting current Ip was obtained by Equ. (17).
C. Parallel Converter Output Voltage to Parallel Injecting Current
As shown in Fig. 3, the influences of the source voltage Us and the series converter output voltage Ui were negligible, and the transfer function between the parallel converter output voltage Up and the parallel injecting current Ip was obtained by Equ. (18).
D. Parallel Converter Output Voltage to Transformer Output Voltage
As shown in Fig. 3, the influences of the source voltage Us and the series converter output voltage Ui were negligible, and the transfer function between the parallel converter output voltage Up and the transformer output voltage U2 was obtained by Equ. (19).
E. Relative Gain Calculation
A UPQC control system can be considered to be a two-input and two-output system. The control system is expressed in the following transfer function matrix as:
A relative gain array (RGA) method is applied, where the relative gain λij for the input uj and the output yi is defined by the ratio of the uncontrolled and controlled gains [18]. The RGA matrix is defined as:
where G(s) = |gij(s)| is the transfer function matrix in Equ. (20).
For a 2×2 system:
where:
The main relative gains are the elements of the RGA matrix in the input–output pairing. Generally, an RGA matrix is applied to analyze the degree of coupling in multi-input multi-output systems [19]. For the UPQC control system, the input signal Ui is designed to control U2, and Up is designed to control Ip. Thus, the main relative gains are λ11 and λ22.
(16), (17), (18) and (19) are substituted into (24) to obtain (25).
F. Interaction Analysis in a Bode Diagram
The system parameters are listed in Table I. As shown above, Eqns. (6)-(15) are substituted into Eqns. (16)-(19) and (25) to obtain the transfer functions, and Bode diagrams are shown in Fig. 4. The main relative gains of 20 kVA and 2000 kVA of λ11 in the transformer capacitor PN are depicted as the lines “r11-P20” and “r11-P2000,” respectively.
Parameters |
Value |
RMS source voltage (Us) |
380 V |
Fundamental frequency (f ) |
50 Hz |
Series L filter (Lf/Rf) |
1 mH/0.01 Ω |
Series C filter (Cf/Rc) |
30 μF/2 Ω |
Parallel L filters (Lp1/Rp1) and (Lp2/Rp2) |
0.2 mH/0.02 Ω |
Parallel C filter (Cp/Rpc) |
10 μF/2 Ω |
Transformer capacity (PN) |
20 kVA |
Transformer rated voltage (VN) |
110 V |
DC-link desired voltage (Vdc) |
700 V |
DC-link capacitor (Cdc) |
5000 μF |
Fig. 4. Bode diagram of the UPQC interaction relationship.
As shown in Fig. 4, the parallel output voltage Up and the series converter output voltage Ui affect the transformer output voltage U2 and the parallel injecting current Ip. In the UPQC control system, the series converter output voltage Ui is designed to control the transformer output voltage U2 in a compensating voltage problem (G(Ui2U2)). However, the series converter output voltage Ui affects the parallel injecting current Ip(G(Ui2Ip)≠0) and disturbs the compensation of the parallel converter. Similarly, the parallel converter output voltage Up is designed to control the parallel injecting current Ip when compensating for the current problem (G(Up2Ip)). Thisaffects the transformer output voltage U2(G(Up2U2) ≠0).
The line “r11-P20” indicates that the main relative gain is low, especially at medium frequencies (10–300 Hz), which indicates that the system is strongly coupled [19]. However, in the line “r11-P2000,” the main relative gain is close to 1, which indicates that the system is weakly coupled and decoupling is not required. However, the capacitor in a 2000 kVA transformer is large and expensive. The above analysis shows that the coupling relationship of the series and parallel units is highly dependent on the transformer capacitor (excitation impedance). Thus, a precise model should be established for the equivalent transformer model.
Ⅳ. DECOUPLING CONTROL ALGORITHM
On the basis of the above analysis, the series and parallel converters are strongly coupled, and they affect the transformer output voltage and the parallel injecting current. Thus, the mutual interference should be mitigated.
Fig. 5. Feed-forward decoupling control method of a UPQC.
A. Feed-Forward Decoupling Method
The feed-forward decoupling method is a simple and effective method. Thus, a feed-forward decoupling method based on a mathematical model can be used to mitigate the interaction of series and parallel converters. A diagram of the feed-forward decoupling method is shown in Fig. 5, where:
Substituting Eqns. (6), (8), (9) and (11)-(15) into (26) and (27) yields:
The control system without decoupling is expressed as:
The close loop of U2 without decoupling is expressed as:
The control system of series and parallel converters after decoupling are separated is expressed as:
The close loop of U2 after decoupling is expressed as:
Bode diagrams of close loops without decoupling and after decoupling are shown in Fig. 8.
Fig. 6. Control system of voltage without decoupling.
(a) |
(b) |
Fig. 8. Bode diagrams of decoupled and coupled controls.
As shown in Fig. 8, the control system after decoupling is stable, whereas the control system without decoupling is unstable, and the resonance is approximately 1.5 kHz.
B. Adaptive Feed-Forward Decoupling Algorithm
As shown in Eqns. (28) and (29), the feed-forward transfer function G(DUp2Ui) is only related to the parameters of a UPQC. However, the transfer function G(DUi2Up) contains load impedance zL. In fact, the load impedance is uncertain, and a feed-forward method cannot completely or accurately decouple the load impedance. This study presents an adaptive feed-forward decoupling algorithm to estimate the load impedance. A nonlinear load is equivalent to a linear load and a harmonics current source. The harmonics current source is used as a disturbance, and the equivalent linear load is only considered in modeling. The equivalent linear load impedance is expressed as:
where ZL is the amplitude of the load impedance, and φ is the angle of the impedance, which can be expressed as:
For the abc reference frame, the voltage and current are periodic variations, and are transformed into the dq reference frame to calculate the value of the impedance [20]. Afterward, the amplitudes of the voltage UL and the current IL are applied to calculate the amplitude of the impedance ZL, and impedance angle φ is calculated from id and iq. Considering that the current contains harmonics, a moving average filter method is applied to obtain the DC component and to eliminate harmonics [21], as depicted in Equ. (36).
where = 0.01 s presents the window width, and x(t) can be UL, IL, id and iq.
On the basis of the moving average filter, the calculation can converge to an accurate value of the impedance ZL and the impedance angle φ within 0.01 s when the load impedance changes. The adaptive decoupling algorithm is shown in Fig. 9.
Fig. 9. Adaptive feed-forward decoupling control method of a UPQC.
Ⅴ. SIMULATION ANALYSIS
Simulations were conducted in MATLAB/Simulink and the simulation parameters are listed in Table I. The applied system PI control method and the parameters are PI1 (Kp1 = 1, Ki1 = 500) and PI2 (Kp1 = 4, Ki1 = 200). The load consisted of linear and nonlinear types, and the rated voltage was 380 V (L-L). The system was analyzed under different operating conditions as follows.
A. Case 1: Source Voltage Distortion
The compensation performance without decoupling control was compared with adaptive feed-forward decoupling control. The working condition was a source voltage with 20% of the 5th harmonic, and the load was a resistance parallel to a diode rectifier. The results of series and parallel converters without decoupling control are shown in Fig. 10. The results of series and parallel converters with adaptive feed-forward decoupling control are shown in Fig. 11.
(a) |
(b) |
(a) |
(b) |
As shown in Fig. 10, the total harmonic distortions (THDs) of the source current and load voltage are 14.44% and 26.50% when the source current and load voltage contain a lot of harmonics for approximately 30 s. This condition is due to the mutual interference of the series and parallel units, as shown in Fig. 8. As shown in Fig. 11, the THD of the source current is 2.20%, and the THD of the load voltage is 2.69% with adaptive feed-forward decoupling control, which meet the IEEE 519 standard. The above comparisons show that the adaptive feed-forward decoupling method is excellent and that the mathematical model is accurate.
B. Case 2: Load Change
The compensation performance without decoupling control is compared with adaptive feed-forward decoupling control under a load change of 0.1 s. The simulation results in the load change condition without decoupling control are shown in Fig. 12. The results of the load change condition with adaptive feed-forward decoupling control are shown in Fig. 13.
(a) |
(b) |
(a) |
(b) |
As shown in Fig. 12, the source current and load voltage without decoupling control contain large harmonics for approximately 30 s. The THD of the source current and load voltage are 19.06% and 25.03%. As shown in Fig. 13, the current compensation response is fast, and the load voltage is stable when adaptive feed-forward decoupling control is applied. The THD of load current is 18.11%. After compensation, the THD of the source current and load voltage are 1.71% and 2.33%. These results verify that the proposed algorithm performs under load changes.
C. Case 3: Source Voltage Unbalance
Simulation results of the source voltage unbalance condition using the proposed method are shown in Fig. 14.
(a) |
(b) |
As shown in Fig. 14, the load current has a serious distortion, the THD is 18.32%, and the source voltage peak values are 363.8, 322.5 and 256.1 V. After compensation, the THD of the source current and load voltages are 2.77% and 2.48%, and the load voltages are 311.1, 310.8 and 310.7 V. These results demonstrate that the proposed algorithm performs well in source voltage unbalance conditions.
Ⅵ. EXPERIMENTAL ANALYSIS
Experiments were implemented in a three-phase four wire UPQC prototype to validate the simulation results of the proposed algorithm. The parameters and control methods used in the experiment are the same as those used in the simulation.
Experimental waveforms are obtained by using a Tektronix oscilloscope, and the DSP is a TMS320F28335. The system is unstable without decoupling control. Thus, experiments are only conducted with the decoupling control, and are expressed under the following conditions.
A. Case 1: Load Change
Experimental results of the adaptive feed-forward decoupling algorithm under the load change condition are shown in Fig. 15.
(a) |
(b) |
As can be seen in Fig. 15, the UPQC achieves good current compensation and a rapid responses, and the load voltage is stable under a load change. The THD of the source current is 3.87%. Thus, the proposed algorithm performs well under load changes.
B. Case 2: Source Voltage Unbalance
Experimental results of the source voltage unbalance condition using the proposed method are shown in Fig. 16.
(a) |
(b) |
(c) |
(d) |
As shown in Fig. 16, the THD of the load current is 17.73%, and the source voltages are unbalanced. After compensation, the THD of source current is 4.57%, and load voltages are balanced.
The above simulation and experimental results verify that the mathematical model is accurate, and that the proposed algorithm is effective in compensating both voltage and current problems.
Ⅶ. CONCLUSION
This study presented a precise unified mathematical model that is valuable in terms of parameter optimization, interaction analysis and control algorithm design. On the basis of the interaction analysis, the series converter and parallel converters are strongly coupled, and are mainly dependent on the excitation impedance of the transformer. The application of an adaptive feed-forward decoupling control algorithm based on the established model completely eliminated the interactions and improved the voltage and current compensation performance. Simulation and experimental results verified that the precise model is accurate and that the proposed adaptive feed-forward decoupling control algorithm remarkably improves the compensation performance.
ACKNOWLEDGMENT
This work is supported by the project of ‘Natural Science Foundation of Hainan Province (No.2018CXTD336)’ and ‘National Natural Science Foundation of China (61864002)’.
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Yingpin Wang was born in Hainan, China, in 1985. He received his B.S. degree in Mechanical Engineering and Automation from Jilin University, Changchun, China, in 2008. He received his M.S. degree in Mechanical Manufacturing and Automation and his Ph.D. degree in Power Electronics from the South China University of Technology, Guangzhou, China, in 2011 and 2017, respectively. From 2011 to 2012, he worked as a Mechanical Engineering at Sany Heavy Industry, Changsha, China. From 2012 to 2014, he worked as an Assistant Research Fellow at the Guangzhou Institute of Advanced Technology, Chinese Academy of Sciences, Guangzhou, China. He is presently working at Hainan Normal University, Haikou, China. His current research interests include active power filters, rectifiers and switching power supplies.
Rubagaknene Thomas Obwoya was born in Masindi, Uganda, in 1997. He is presently working towards his B.S. degree in Mechanical and Electrical Integrated Engineering, Hainan Normal University, Haikou, China. His current research interests include electrical systems and control technologies.
Zhibo Li was born in Chongqing, China, in 1982. He received his B.S. degree in Mechanical Engineering and Automation from the Nanjing Agricultural University, Nanjing, China; and his M.S. degree in Vehicle Engineering from Shandong University, Jinan, China. He is presently working as a Lecturer at Hainan Normal University, Haikou, China. His current research interests include automation, electric machine drives, and vibration and noise control.
Gongjie Li was born in Hainan, China, in 1986. He received his B.S. and M.S. degrees in Control Science and Engineering from the Harbin Institute of Technology, Harbin, China, in 2010 and 2013, respectively. He is presently working as an Assistant at Hainan Normal University, Haikou, China. His current research interests include industrial automation, motors and control.
Yi Qu was born in 1969. He received his B.S. and M.S. degrees from the Changchun Institute of Optics and Fine Mechanics, Changchun, China, in 1991 and 1999, respectively. He received his Ph.D. degree from Jilin University, Changchun, China, in 2002. From 2003 to 2005, he was a Postdoctoral Research Fellow in the School of Materials Engineering, Nanyang Technological University, Singapore. From January 2006 to October 2006, he was a Singapore Millennium Scholarships Postdoctoral Research Fellow. From February 2012 to August 2012, he was a Senior Visiting Fellow in the Department of Electrical Engineering, Yale University, New Haven, CT, USA. From 2003 to 2017, he was with the National Key Laboratory on High Power Semiconductor Lasers, Changchun University of Science and Technology, Changchun, China. Since April 2017, he has been a Professor and a Vice Director Professor of the College of Physics and Electronics Engineering, Hainan Normal University, Haikou, China. He has published over 150 papers in journals and conference proceedings. His current research interests include the fabrication and application of optoelectronics devices.
Zeyu Shi was born in Ganzhou, China, in 1991. He received his B.S. degree in Electrical Engineering from the Hefei University of Technology, Hefei, China, in 2013. He is presently working towards his Ph.D. degree in Electrical Engineering at the South China University of Technology, Guangzhou, China. His current research interests include high-power density rectifiers and control strategies.
Feng Zhang was born in Shanxi, China, 1986. He received his B.S. degree in Electrical Engineering from Lushan College, Guangxi University of Technology, Liuzhou, China, in 2010; and his M.S. degree in Control Engineering from Guangxi University, Nanning, China, in 2014. Since 2016, he has been working towards his Ph.D. degree in Power Electronics at the South China University of Technology, Guangzhou, China. His current research interests include micro-inverters and multi-level inverters for photovoltaic applications.
Yunxiang Xie received his Ph.D. degree in Electrical Engineering from Xi'an Jiaotong University, Xi’an, China, in 1991. Since 1991, he has been a Professor in the School of Electric Power, South China University of Technology, Guangzhou, China. He was a Professor at the University of Queensland, Brisbane, Australia. From 1996 to 1997, he was a Visiting Professor at the University of Western Ontario, London, ON, Canada. He is the author or coauthor of about 50 scientific papers published in international journals and conference proceeding. His research interests include power inverters, power quality, active filters, switched-mode power supplies, electric drives and digital control systems. His current research interests include power electronic converters, matrix converters, active and hybrid filters, the application of power electronics in renewable energy systems and electrified railway systems, reactive power control, harmonics, and power quality compensation systems such as SVC, UPQC and FACTS devices. Dr. Xie is a senior member of China Electro-Technical Society, and China Power Electronics Society.