PERFORMANCE ANALYSIS OF SVPWM AND FUZZY CONTROLLED HYBRID ACTIVE POWER FILTER

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1 International Journal of Electrical and Electronics Engineering Research (IJEEER) ISSN X Vol. 3, Issue 2, Jun 2013, TJPRC Pvt. Ltd. PERFORMANCE ANALYSIS OF SVPWM AND FUZZY CONTROLLED HYBRID ACTIVE POWER FILTER JARUPULA SOMLAL 1, M. VENU GOPALA RAO 2 & M ANUSHA PRIYA 3 1 Associate Professor, EEE Department, KL University, Guntur, Andhra Pradesh, India 2 Professor, EEE Department, KL University, Guntur, Andhra Pradesh, India 3 M.Tech Student, EEE Department, KL University, Guntur, Andhra Pradesh, India ABSTRACT This paper investigates on performance analysis and control methods of Hybrid Active Power Filters using Space Vector PWM and Adaptive Fuzzy based controllers for mitigating the harmonics, improving power factor there by conditioning the power of a distribution system. In Space Vector PWM technique, reference voltage vector of Active Power Filter (APF) is generated rather the reference current, and the required output voltage of APF is generated by SVPWM. In Fuzzy based Hybrid filter, Proportional plus Integral (PI) control unit and fuzzy adjustor units are proposed. PI control unit is for obtaining dividing frequency control and the fuzzy adjustor unit is for adjusting elements of the PI control unit to produce better adaptive ability and dynamic response. The complete power system set model of the proposed filter techniques has been developed in MATLAB. The control algorithms developed by two schemes are very simple. Simulations are carried out for the two schemes by using MATLAB, it is noticed that the %THD has been improved from 1.61(SVPWM technique) to 0.78 by the Fuzzy based Hybrid Filter technique. KEYWORDS: Fuzzy Controller, Hybrid Active Power Filter, SVPWM Controller, Total Harmonic Distortion (THD) INTRODUCTION Harmonics are the major concerned problem in the distribution system. The growing use of electronic equipments is one of the major causes to impute the harmonics. In order to solve these problems, the passive power filter (PPF) is often used conventionally. However, it has many de-merits such as being bulk, resonance, tuning problem, fixed compensation, noise, increased losses, etc., which discourages its implementation. On the contrary, the APF can solve the above problems and is often used to compensate currentharmonics and low power factor that is caused by nonlinear loads, which has drawn much attention since the 1970s. The commonness of this method is the request for generating reference current of Active Power Filter (APF), either with the load current or the mains current. The second is that controls the VSI to inject the compensating current into AC mains. However, they are limited by high cost, low-power capacity, and are difficult to use in high-voltage grids. Another solution for the harmonic problem is to adopt a hybrid active power filter [3]-[4]. It is the combination of active and passive power filters. The main objective of design of Hybrid filters is to enhance the performance of the active power filter or passive power filter by adding passive or active components to its structure. HAPF is categorized in parallel hybrid active power filters (PHAPFs) and series hybrid active power filters (SHAPFs) based on the used active filter type. A series of PHAPFs was proposed after the 1990s [4] [5]. Cheng etal. proposed a new hybrid active power filter to achieve the power-rating reduction of the active filter. The Hybrid Active Power filter configuration investigated in this paper is based on space vector pulse-width modulated (PWM) [1] and fuzzy logic controller [2]. For harmonic current tracking controls, there are two schemes [6], [7]:One is the linear current control, such as ramp comparison control, deadbeat control, sinusoidal internal model control,

2 310 Jarupula Somlal, M. Venu Gopala Rao & M Anusha Priya generalized integrators control, etc.; the other is nonlinear current control, such as hysteresis control, predictive control, etc. Hysteresis control has the advantage of simplicity, but leads to a widely varying switching frequency. This limitation has been improved with variable hysteresis band switching strategies but it requires a complex controller to achieve satisfactory performance. Predictive current control offers the best potential for precise current control, but the implementation of a practical system can be difficult and complex. In this paper, two control schemes are proposed such as Space Vector PWM and Fuzzy based Hybrid Active Power Filter. The simulation and experimental results also show that the new control methods are not only easy to be calculated and implemented, but also very effective in reducing harmonics. CONFIGURATION OF PROPOSED HYBRID ACTIVE POWER FILTER Figure.1 shows the hybrid power filter consist of three phase LC filter tuned at the 7 th harmonic frequency and three phase voltage source inverter. It is a forced commutated VSI having stiff DC voltage source at its input terminals. This capacitor also suppresses harmonics and also feedback control to the total circuit. This system is investigated and the performances of parameters are verified under non-linear load conditions. It can be assumed that the supply voltage and current is ideal and sinusoidal and the three-phase balanced parameters are shown as below: (1) (2) (3) Where represents the supply voltage. If equations (1), (2) and (3) are the three phase voltages. [ ] in a- b-c can be expressed as two-phase representation in d-q reference frame by Clark s transformation and it is given by equation (4). (4) Above equation can be reduced as Where a=e j2/3π, is angle of supply current. (5) Figure 1: Configuration of Proposed Hybrid Active Power Filter

3 Performance Analysis of SVPWM and Fuzzy Controlled Hybrid Active Power Filter 311 PROPOSED CONTROL METHODS Using SVPWM Controller Figure 2 shows the block diagram of proposed active filter control method implemented using SVPWM in MATLAB /Simulink. Initially, the three phase supply currents are sensed and transformed into synchronous reference frame (d-q) axis. The fundamental component of the supply current is transformed into DC quantity in the (d-q) axis and the supply current amplitude is generated by the PI controller. The obtained d-q axis components generate voltage command signal. By using Fourier magnitude block, voltage magnitude and angle is calculated from the obtained signal. These values are fed to the developed code and generated switching actions are applied to the APF, thus the power balancing of the filter takes place. Figure 2: Block Diagram Proposed Controller Using SVPWM Figure 3: Configuration of Adaptive Fuzzy Dividing Frequency Controller Using Fuzzy Dividing Controller The dynamic response of the system and/or to increase the stability margin of the closed loop system, the conventional linear feedback controller (PI controller, state feedback control, etc.) can be utilized. However, these controllers may present a poor steady-state error for the harmonic reference signal. The fuzzy dividing control method is presented in Figure 3, which consists of two control units: 1) a generalized integrator control unit, which can ignore the influence of magnitude and phase, is used for dividing frequency integral control and 2) a fuzzy adjustor unit or fuzzy arithmetic is used to timely adjust the PI coefficients. Since the purpose of the control scheme is to receive a minimum steady-state error, the harmonic reference signal r is set to zero. First, supply harmonic current is detected. Then, the expectation control signal of the inverter is revealed by the fuzzy dividing frequency controller. The stability of the system is achieved by a proportional controller, and the perfect dynamic state is received by the generalized integral controller. The fuzzy adjustor is set to adjust the parameters of proportional control and generalized integral control. Therefore, the proposed harmonic current tracking controller can decrease the tracking error of the harmonic compensation current, and have better dynamic response and robustness.

4 312 Jarupula Somlal, M. Venu Gopala Rao & M Anusha Priya Fuzzy Logic Controller Figure 4: Block Diagram of Fuzzy Logic Controller A block diagram of fuzzy-logic adjustor is shown in Figure 4. Once the fuzzy controller were developed and incorporated into the simulated system, the simulation performances helped in the iteration of the controllers and best adaptive controller to the linear and non linear systems. Fuzzy controller main parts are evaluation and control rules from the rule base and data base is called fuzzifier and defuzzifier is takes highest MF component. The FLC having different membership functions (M.Fs) to analyse the performance of instantaneous real active and reactive current (id iq) control strategy for extracting reference currents of SHAF under different source voltage conditions. PWM pattern generation based on carrier less hysteresis current control is used for quick response. In addition, the i d i q method is used for obtaining reference currents in the system, because in this strategy, angle u is calculated directly from the main voltages and enables operation to be frequency independent; thereby, this technique avoids a large number of synchronization problems. The fuzzy control rule design involves defining rules that relates to the output model properties. For designing the control rule base for tuning ΔKp and ΔK i, the following important factors have been taken into account. For large values of /e/, a large Δk p is required, and for small values of /e/, a small Δk p is required. For e, e c >0, a large Δk p is required and for e, e c >0 a small Δk p is required. For large values of /e/ and /e c /, ΔK p is set to zero, which can avoid control saturation. For small values of /e/, ΔK p is effective, and Δk p is larger when /e/ is smaller, which is better to decrease the steady state error. So the tuning rule of ΔK p and ΔK i can be obtained as shown in Table.1 and Table.2. Table 1: Adjusting Parameters of ΔKp e ΔK P NB NM NS O PS PM PB NB PB PB NB PM PS PS 0 NM PB PB NM PM PS 0 0 NS PM PM NS PS 0 NS NM 0 PM PS 0 0 NS NM NM PS PS PS 0 NS NS NM NM PM 0 0 NS NM NM NM NB PB 0 NS NS NM NM NB NB e c

5 Performance Analysis of SVPWM and Fuzzy Controlled Hybrid Active Power Filter 313 Table 2: Adjusting Parameters of Δk I ΔK i NB NM NS 0 PS PM PB NB 0 0 NB NM NM 0 0 NM 0 0 NM NM NS 0 0 NS 0 0 NS NS e NS NM PS 0 0 PS PS PS 0 0 PM 0 0 PS PM PM 0 0 PB 0 0 NS PM PB 0 0 e c RESULTS AND DISCUSSIONS System Parameters Supply system Balanced linear load Unbalanced linear load Non-linear load APF (SVPWM) APF(Fuzzy) Table 3: Parameter Values Values of Parameters 230 V (rms), 50 Hz, three-phase supply Z l = 75 + j Ω Z la = 75 + j Ω, Z lb = j Ω, Z lc =85+ j Ω R=10.6 Ω, L=58.2mH C dc =1000µf, Vref = 750V,C f = 24µf, L f = 30 mh L/mH C/ F Q Output filter th turned filter th turned filter th turned filter C F :19.65,C I :690 The developed control method for three-phase shunt APF is simulated in MATLAB/Semulink. Firstly, the threephase supply currents are sensed and transformed into synchronous reference frame (d-q) axis. The fundamental component of the supply current is transformed into dc quantities in the (d-q) axis and the supply current amplitude I s generated by the PI controller. The obtained d-q axis components generate voltage command signal. By using Fourier magnitude block, voltage magnitude and angle is calculated from the obtained signal. These values are fed to the developed code and generated switching actions are applied to the APF. Thus, power balancing of the filter takes place. Further, the performance with different type of loads is presented. SVPWM Based Hybrid Active Power Filter For Balanced Linear Load (a) The Phase-A Supply Voltage and Load (b) The Phase-A Supply Voltage and Current Waveforms Supply Current Waveforms Figure 5: Simulation Results of Balanced Linear Load The Figure 5 shows the simulation results of the APF when load is three-phase balanced RL load. Figure 5(a) is the waveforms of the phase-a supply voltage and the load current before compensation. Figure 5(b) is the waveforms of

6 314 Jarupula Somlal, M. Venu Gopala Rao & M Anusha Priya the phase-a supply voltage and the supply current after compensation. For Unbalanced Linear Load The Figure 6 shows the simulation results of APF when three-phase unbalanced RL load is considered. Figure 6 (a) is the waveforms of the three-phase load current before compensation. Figure 6 (b) is the waveforms of the three-phase mains current after compensation. From the figures, it can be seen that APF controller can remedy the system unbalance. (a) Three-Phase Load Current Waveforms (b) Three-Phase Supply Current Waveforms Figure 6: Simulation Results of Unbalanced Linear Load For Non-Linear Load with Resistance Figure 7 (a) is the waveforms of the source phase voltage. Figure 7 (b) is the wave forms of the load current before compensation. Figure 7 (c) is the waveforms of the supply current after compensation. The Figure 8 shows the simulation of harmonic spectrum of APF when the non-linear is a three-phase diode bridge rectifier with resistance load. Figure 8(a) is the harmonic spectrum of the current before compensation on the load side. Figure 8 (b) is the harmonic spectrum of the current after compensation on the source side. The harmonic spectrum of the load current shows that magnitude of the 5th, 7th, 11th and 13th harmonics is very large. The harmonic spectrum of the source current shows that magnitude of the 5th, 7th, 11th and 13th harmonics are evidently reduced after compensation. The load current Total Harmonic Distortion (THD) is 21.08%, while the supply current THD is 1.61%. It should be noted that the higher frequency harmonics caused by APF in mains current can be canceled easily by a small passive filter, and there are pulses in main current at the points, where of load current is large, because fixed switching frequency restrict the tracking capability of APF. (a)

7 Performance Analysis of SVPWM and Fuzzy Controlled Hybrid Active Power Filter 315 (b ) (c) (a) The Three-Phase Source Voltage Waveforms (b) The Three-Phase Load Current Waveforms (c) The Three- Phase Source Current Waveforms Figure 7: Simulation Results of Non-Linear Load (a) The Phase-A Load Current Harmonic Spectrum (b) The Phase-A Source Current Harmonic Spectrum Figure 8: Harmonic Spectrum of Non-Linear Load FUZZY Based Hybrid Active Power Filter Figure 9 shows the simulation results of the dynamic performance with the conventional PI controller. Figure 10 shows the simulation results of the dynamic performance with the conventional generalized integral controller. Fig.11 simulation results of the dynamic performance with the proposed controller. It is observed from Figure 12 and Figure 13 that at 0.2s to 0.3 s, the THD increases from 9.40% to 21.34%. When the conventional PI controller is used, the error can be reduced to ±09A in 0.05 s, but there is an obvious steady state error at 1.0 s all the same. When the generalized integral controller is used, the error reduces to ±06 A at 0.5 s; however, it can only be reduced to ±15 A in 0.05 s. When the proposed controller is used, the error can be reduced to 1.5 A

8 316 Jarupula Somlal, M. Venu Gopala Rao & M Anusha Priya in 0.05 s. It is observed that compared to the conventional PI controller and generalized integral controller, the proposed controller has better dynamic performance. Figure 9: Dynamic Performance with Conventional PI Controller Figure 10: Dynamic Performance with Conventional Integral Controller Figure 11: Dynamic Performance with the Proposed Controller Figure 12: FFT Analysis at 0.2sec for FHAPF Figure 13: FFT Analysis at 0.3sec for FHAPF Figure 14: Steady-State Compensation with the Conventional PI Controller Figure 14 shows the Simulation results of steady-state compensation with the conventional PI controller. Figure 15 shows the simulation results of the steady-state compensation with the conventional generalized integral controller. Figure 16 shows the simulation results of the steady-state compensation with the proposed controller. When the conventional generalized integral controller is used, the current THD reduces to 3.42% from 21.34%, while after the FHAPF with the proposed PI controller runs; the current THD reduces to 0.78% from 21.34% as shown in Figure 17. So it can be observed that the proposed current controller exhibits much better performance than the conventional PI controller and the conventional generalized integral controller.

9 Performance Analysis of SVPWM and Fuzzy Controlled Hybrid Active Power Filter 317 Figure 15: Steady-State Compensation with the Conventional Integral Controller Figure 16: Steady-State Compensation with the Proposed Controller CONCLUSIONS Figure 17: FFT Analysis for the FHAPF with the Proposed Controller In this paper, the two control methodologies for the Hybrid active power filter was proposed by using SVPWM and Fuzzy controller. The performances of hybrid filter with the proposed methods are done in MATLAB/Simulink. The harmonic spectrum under non-linear load conditions shows that reduction of harmonics is better. Under unbalanced linear load, the magnitude of three-phase source currents are made equal and also with balanced linear load the voltage and current are made in phase with each other. The simulation study of two level inverter is carried out using SVPWM because of its better utilization of DC bus voltage more efficiently. Generalized PI control unit and fuzzy adjustor unit based fuzzy dividing control method was discussed clearly. The proposed method is able to increase the response of the dynamic system, robustness and also which is able to decrease the tracking error. The proposed method is very much useful and also applicable to any other type of active filters. Simulations are carried out for the two schemes by using MATLAB, it is noticed that the %THD has been improved from 1.61(SVPWM technique) to 0.78 by the Fuzzy based Hybrid Filter technique. The simulation and experimental results also show that the new control method is not only easy to be calculated and implemented, but also very effective in reducing harmonics.

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