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SIMULATION AND EXPERIMENTAL VALIDATION OF SHUNT ACTIVE POWER FILTER FOR HARMONIC MITIGATION Hamisu Usman, Ramatu Aliyu Abarshi, Aminu Hamisu Kura Department of Electrical and Electronic Engineering, College of Engineering, Kaduna Polytechnic ABSTRACT The proliferation of power electronics devices used in industrial, commercial and residential applications, have lead to the deterioration of supply current and voltage wave forms, and this caused power quality problems within the supply system. These power electronics devices are nonlinear in nature, which draws reactive power and harmonic distortions from the alternating current source in the fundamental current. Traditional passive filter was the earliest solution for mitigating harmonics and reactive power produced by nonlinear loads, but passive filter have the disadvantages of series and parallel resonances with the supply source impedance and it’s heavy in size. Due to these problems in passive filter, it applications becomes very limited. With the introduction of shunt active power filter, harmonics mitigations of current and voltage distortion wave forms can therefore be suppressed. In this paper, the modeling and simulation of DSP based single phase shunt active power filter controlled with fuzzy logic controller for power quality improvement in MATLAB/ SIMULINK fuzzy inference system (FIS), is proposed. Synchronous reference frame for the extraction of harmonics is introduced in this paper. The simulated results are validated with experimented results of the proto type hardware implementation via TMS320F28335 digital signal processor (DSP) in order to show the effectiveness and good performance of the proposed control algorithm. The simulated results of the THD are in conformity with IEEE 519-1992 harmonics standard limit, while the results of the hardware THD do not obey the IEEE standard because of the hardware deficiency in sampling rate in real time development. Keywords: Shunt active power filter, harmonics, fuzzy logic, current extraction and THD Introduction Nowadays with the increase demand of power electronics equipment and devices for the use of industrial, commercial and residential consumers, have lead to the serious power quality problems within the supply System network. These equipment and devices are nonlinear in nature that draws harmonic currents which deteriorates the quality of currents and voltage waveforms. Nonlinear loads like arc furnaces, adjustable speed drives, rectifiers, Fluorescent lamps, personal computers are the major responsible for harmonics in power system. These nonlinear loads have adverse effects on the quality of power and system performances of the supply system, which resulted in overheating of the supply cables, equipment ageing, interference with nearby communication facilities, frequent tripping of sensitive devices like circuit breakers and can even result in total blackout of the entire power supply system. As a result of these power quality problems, classical passive filters are the earliest solution to mitigate harmonics drawn by the nonlinear loads. But passive filters have some drawbacks such as heavier in size, tendency of series and parallel resonances with the supply impedance (Dehini, Bassou &Ferdi, 2010) , fixed harmonic compensation and may cause detuning. With the problems of passive filters, active power filters have been tested and proven to be a viable and dynamic solution to overcome the difficulties of passive power filters in suppressing current harmonics drawn by nonlinear loads within the power system network. Active power filters are therefore controlled with various control techniques in controlling the gating signal of the semiconductor switching devices for proper compensation of harmonics drawn by nonlinear loads. Among the control algorithms for shunt active power filters are hysteresis current control, dead beat control, sliding mode control, pulse width modulation control, neural network, genetic algorithm and fuzzy logic controllers etc. However, with the emergence of digital controllers, like digital signal processors (DSPs), field programmable gate array (FPGAs) and electronics micro-controllers, all in the application of shunt active power filter control algorithms gives rooms for hardware implementation for validation of the shunt active power filter simulation results. In this paper, modeling and simulation of single phase shunt active power filter with harmonic extraction in synchronous reference frame (SRF) for the reference current generation of the filter together with the fuzzy logic controller for the switching of the gating signal of the semiconductor switching devices for harmonic mitigation drawn by the nonlinear load is presented. An experimental validation of the proposed simulation results are also presented via digital signal processor DSP TMS320F28335 in order to show the feasibility and good performance of the proposed control algorithm. Single Phase Shunt Active Power Filter Configuration The Fig. 1 depicts the general configuration of single phase shunt active power filter topology. This type of active filter topology is the most popular and frequent type in active filtering for harmonic mitigations drawn by nonlinear loads (El-Habrouk, Darwish & Mehta 2000) . Shunt active power filter work on the principle of current harmonic injection, its main principle is to control to draw/supply current compensation from/to the supply authority main at the point of common coupling (Sahu, Gadanayak, 2012), in such a way as to cancel harmonic currents and reactive power drawn my nonlinear loads, with the aim at compensating current harmonics which is to be in phase with the source voltage. Shunt active power filter configuration could be either voltage source inverter (VSI) or current source inverter (CSI) types, depending on the applications to be used. But (VSI) type is the most widely employed in active filtering due to its simplicity and popular in recognition topology (Salam, Chenga &Jusoh, 2006) . Basically, shunt active power filter consists of two parts, the power circuit and control circuit. The power circuit consists of IGBT or MOSFET semiconductors switching devices with an interfacing inductor for taking care of the harmonics ripples after compensation by the active filter, DC capacitor for maintaining DC voltage by the inverter. While the control circuit is the main brain of the filter, which control the semiconductor switching gating signal for proper compensating of the current harmonics. Fig.1 Basic Principle topology of Single Phase Shunt Active Power Filter Harmonic Current Extraction Technique In this section, shunt active power filter requires harmonic current extraction of the reference current to be compensated by the filter. Different current harmonic extraction techniques are available, in either frequency domain or time domain approaches. In this paper, a time domain approach with balanced three phase synchronous reference frame (SRF) was modified to work as single phase. In a normal three phase synchronous reference frame, the load currents of the three phases, and the three phases source voltages with the DC link voltage of the shunt active power filter are sensed in order to generate the reference harmonic current which to be control by fuzzy logic controller. In synchronous reference generation, the sensed load current due to nonlinear loads of the three phases ia , ib , ic are converted in to the d-q coordinates by the use of Park transformation technique which resulted in obtaining the components of the d-q load currents as shown by equation 1. The source current from d-q coordinates 2 are further transformed by the inverse Clarks transform in to abc coordinates as seen by equation 2. In this work, phase a were selected out of the three phases (SRF) transformations under balanced phases condition to work as single phase. cos t id 2 i q 3 sin t 2 cos t 3 2 sin t 3 2 cos t ia 3 ib 2 sin t i 3 c cos t ia* 2 * 2 ib 3 cos t 3 ic* 2 cos t 3 sin t 2 sin t 3 2 sin t 3 1 * id i* q 2 Fuzzy Logic Controller Fuzzy logic controller was first introduced by Professor Zadeh Lotfi of University California Berkeley in early 1960s. He proposed a technique of how to process an imprecise data with complex input. The idea of Zadeh’s was fully utilized after the introduction and availability of modern computers and controllers applications. Fuzzy logic controllers gain interest by many researchers and system engineers in the application of control system analyst, as well as in the control algorithm for shunt active power filter applications. Fuzzy logic controller has advantages of simplicity in design procedures that does not require any accurate mathematical modeling, can work with an imprecise input of the system and it can also work with non-linearity. Fuzzy controller is very robust than classical controllers such as PI and PID controllers (Kerrouche, Karim, 2009). In our study, a Mamdani fuzzy controller was chosen and designed with linguistic term “if then” rules. The linguistic variables for the rule base was selected as, positive large (PL), positive medium (PM), positive small (PS), negative large (NL), negative medium (NM), negative small (NS) and zero (Z). However, Fig. 2 depicts the general structure of fuzzy logic controller. The design of the proposed fuzzy logic controller is characterize as follows. 1. Five memberships function for each two inputs error (e) and its derivative (Δe) are used. 2. Seven memberships function for the output. 3. Mamdani implication in the design was also used. 4. Centre of area (COA) was used for the Deffuzzification process. 5. Implication using “min-max” approach 6. twenty five rules for both error and change of error are used. Triangular membership functions are used due to its simplicity, completeness and easy to implement. 3 Fig. 2 Structure of fuzzy logic controller As it was defined for the linguistic rule variables, table 1 below shows the “if then” rules for the five membership functions selected for each of the input error (e) and the change of error (Δe). For the two inputs, only twenty five possible rules are possible based on (5*5) =25 “if then” combinations rules. Table 1. Linguistic variables rules for the Fuzzy logic Controller Simulation Model And Analysis As shown in Fig. 3, the modeling of the single phase shunt active power filter in MATLAB/SIMULINK environment. The parameters of the simulation model are as follow: VS= 25V peak amplitude, F= 50HZ, RS= 40Ω, CL= 500µF, RL= 150Ω, RF= 40Ω, LF= 1mH. In the simulation, RC parallel load were fed from the diode rectifier as a nonlinear load. In the same vein, the simulation results are also presented in this section. AS shown in Fig. 4, the result of the nonlinear load due the harmonic produced by the rectifier shows a waveform which is opposite to the source voltage (i.e out of phase to each other). Fig. 5 depicts the filter current which also distorted due to the same nonlinear load, while Figure 6 and Figure 7 are the corresponding source voltage and source current respectively and they seems to be purely sinusoidal and in phase to each other. In the same analysis, Figure 8 and Figure 9 indicate the FFT analysis of the THD which are also found to be 39.82% and 3.91% respectively. These THD have drastically reduced and is within the recommended IEEE 519-1992 harmonic limits. 4 Discrete, Ts = 1e-006 s. i i + - + - powergui + IL Rs Is A Series RLC Branch AC Source B - + v - Vs Universal Bridge Full wave Rectifier R g + Cdc Vdc i Source voltage Source current + - Load Current Rf & Lf A B Shunt Active Filter Iref Vc Iref Pulses 1 z iF, iL, iref Iinj Unit Delay1 Vs Harmonic Extraction Current Controller with Fuzzy Fig. 3 Simulation of Single Phase Shunt Active power Filter Fig. 4 Load current before applying shunt active power filter 5 v - VL1 IL1 - IL + Fig.5 Filter current Fig.6 Source Voltage Fig.7 Source Current after compensation 6 Fig. 8 FFT Spectrum of the load current before compensation Fig. 9 FFT Spectrum of the load current after compensation Experimental Validation In this section the experimental validation of the proposed simulation results is presented. A prototype single phase shunt active power filter was constructed in the laboratory, in order the show the validity of the proposed fuzzy logic controller algorithm in suppression current harmonics produced by nonlinear loads within the power system network. Fig. 10 shows the hardware of the complete reference current generated with the fuzzy logic controller setup of the shunt active power filter. In this paper, four electrical quantities are sensed for the implementation of the prototype hardware implementation via the DSP (Singh, 2008). Two current sensors LA25-NP for sensing the load current and the injected current of the active power filter which are fed to the DSP for conversion from analog to the digitized form are also shown in setup. However, two voltage sensors were also sensed, one from the source voltage while the other from the DC side capacitor of the shunt active filter. The digitized output of the TMS320F28335 was fed to the gating signal of the IGBT semi conductor switching for compensation of the harmonics produced by nonlinear load. Fig. 11 depicts the experimental load current before compensation, and Fig. 12 shows the source voltage which is purely sinusoidal in nature, while Fig. 13 is the source current. The THD for the load current before and after compensation found to be 99.98% and 16.69% respectively. This result indicates a drastic reduction in the THD, but is not in conformity with the IEEE harmonic standard limit because of the deficiency in hardware sampling rate in real time application. 7 ADC-PWM Synchronization via ADC Interrupt 10 Gain1 1.21 C280x/C28x3xA0 Constant IL A1 A2 ADC A3 91.8 Vc Gain2 Vs ADC2 Iref Iref Iinj Harmonic Extraction1 91.8 Current Controller with Fuzzy 1.21 Gain3 Constant2 10 Copyright 2007-2014 The MathWorks, Inc. Info Gain4 1.21 F28335 eZdsp Constant1 Fig. 10 Control algorithm interfaced with DSPTMS320F28335 processor Fig 11 Experimented load current before compensation 8 Fig. 12 Experimented source voltage Fig. 13 Experimented source current Conclusion This paper, discussed the simulation of single phase shunt active power filter controlled with fuzzy logic controller, the simulation results are validated with a prototype hardware constructed in the laboratory via DSPTMS320F28335 digital processor. The simulation results of the proposed controller indicates that, THD of the load current and source current obtained to be 39.82% and 3.91% respectively. While THD of the experimental results shows that, load current to be 99.98% and 16.69% for the corresponding source current without and with compensation. The simulation result obeyed the IEEE 519-1992 harmonic standard limit, while that of the hardware shows a drastic reduction in the THD, but does not meet the harmonic standard; this is because of the limitation of real time hardware implementation and losses in the system. 9 References Dehini, R., Bassou, A., Ferdi, B. (2010). The harmonics detection method based on neural network applied to harmonics compensation, International Journal of Engineering Science and Technology, vol. 2, no. 5, pp. 258–267. El-Habrouk, M., Darwish, M. K., Mehta, P. (2000). Active power filters: A review, IEE Proceedings Electric Power Applications, vol. 147, no. 5, p. 403. Sahu, I., Gadanayak, D. A. (2012). Comparison between Two types of Current Control Techniques Applied to Shunt Active Power Filters and Development of Fuzzy Logic Controller to Improve SAPF Performance, International Journal of Engineering Research and Development, Vol. 2, no.4, pp 1-4. Salam, Z., Cheng, T. P., Jusoh, A. (2006). Harmonics Mitigation Using Active Power Filter: A Technological Review, Journal of Elektrika, Vol.8, no. 2, pp. 17-26. Sing, K., Krim, F. (2009). Three -phase Active Power Filter Based on Fuzzy Logic Controller, International Journal of Science and Techniques of Automatic Control & Engineering, Vol. 3, no. pp. 942–955, Sugh, V. K. (2008). Generalised single-phase p-q theory for active power filtering : Simulation and DSPbased Experimental investigation, Journal of the Institution of Engineering and Technology, Vol. 2, no. 3, pp. 67–78, 10