# PERFORMANCE ANALYSIS OF SVPWM AND FUZZY CONTROLLED HYBRID ACTIVE POWER FILTER

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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

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.

10 318 Jarupula Somlal, M. Venu Gopala Rao & M Anusha Priya REFERENCES 1. SomlalJarupula, Dr.VenuGopalaRaoMannam, Ramesh Matta, Power Quality Improvement in Distribution Systems Using Fuzzy Based Hybrid Active Power Filter, International Journal of Advanced Scientific Research And Technology, Vol. 3, Issue 2,pp , June, JarupulaSomlal, VenuGopalaRaoMannam, Analysis Of Discrete & Space Vector Pwm Controlled Hybrid Active Filters For Power Quality Enhancement, International Journal of Advances in Engineering & Technology, Vol. 2,Issue 1, pp , Jan, EI-Habrouk. M, Darwish. M. K, Mehta. P, "Active Power Filters-A Review," Proc.IEE-Elec. Power Applicat., Vol. 147, No. 5, pp , Sept Akagi, H., "New Trends in Active Filters for Power Conditioning," IEEE Trans. on Industry applications, Vol. 32, No. 6, pp Nov-Dec, Singh, B, Al-Haddad.K, Chandra.A, "Review of Active Filters for Power Quality Improvement," IEEE Trans. Ind. Electron., Vol. 46, No. 5, pp , Oct An Luo, ZhikangShuai, Wenji Zhu, Ruixiang Fan, and ChunmingTu, Development of Hybrid Active Power Filter Based on the Adaptive Fuzzy Dividing Frequency- Control Method, IEEE Transactions on Power Delivery, Vol. 24, No. 1, January Rathnakumar, D., LakshmanaPerumal, Srinivasan, T., "A New Software Implementation of Space Vector PWM," IEEE Trans. Power Electron., Vol.14,No.8-10 pp , April,2005.

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