REACTIVE POWER COMPENSATION AND HARMONIC ELIMINATION BY FUZZY LOGIC CONTROLLED SHUNT ACTIVE POWER FILTER

International Journal of Recent Advances in Engineering & Technology (IJRAET). REACTIVE POWER COMPENSATION AND HARMONIC ELIMINATION BY FUZZY LOGIC CONTROLLED SHUNT ACTIVE POWER FILTER 1. S. Sarada, 2K. Azmathulla. 1. Assistant Professor, EEE Department M. Tech (Electrical power systems), EEE Department Annamacharya Institute of Technology &Sciences, Rajampet, Kadapa, Andhra Pradesh Email - 1saradasasi@gmail.com, 2azmu.me@gmail.com 2. used. Passive compensation though simple approach for achieving above goals but they are associated with several drawbacks such as, resonance problems, bulky, tuned for particular frequency component, component ageing, etc. [7], [8]. For overcoming the drawbacks of passive filters and reducing power quality problems, a number of attempts have been made on the design, analysis and optimal control development of active power filter (APF). APF allows compensation of voltage harmonics (series APF), compensation of current harmonics (shunt APF) with reactive power compensation required by nonlinear load. This paper emphasis on elimination of current harmonics and reactive power compensation, hence shunt APF between the conventional PI and proposed FLC are presented. It is shown by the simulation results that proposed controller based on fuzzy logic is robust that conventional PI controller for steady-state and transient conditions of load. topology has been considered. Shunt APF harmonic current is equal but opposite in-phase with the required harmonic component of load current. Computation of reference current signal and switching pulse generation for voltage source inverter (VSI) is main task. Various control approaches such as instantaneous reactive power theory [2] , synchronous reference frame theory, closed loop PI control [9], etc. are used for generation of reference current signal by sensing combinations of source voltage, load current, filter current and source current. More number of sensor increase complexity and not cost effective solutions. Hence, control algorithm should be such that which give it‟s best performance under steady-state as well as transient load conditions with less sensor count. Duke et all [10] have proposed simple synthetic sinusoidal generation technique by sensing load current which further modified by sensing source current only [10] .. Abstract— Active filters are widely used in electrical distribution system for reactive power compensation and voltage / current harmonic elimination. In this paper, a fuzzy logic controlled, three-phase shunt active filter to improve power quality by compensating reactive power and current harmonics required by a nonlinear load is presented. PI regulator is replaced by fuzzy logic controller to improve the dynamic performance of shunt active filter under varying load conditions. The advantage of fuzzy control is that it is based on defined linguistic rules and does not require any mathematical model of the system unlike the other traditional controller. The compensation process is based on source current sensing only, an approach different from conventional methods. The performance of fuzzy logic controller is compared with PI controller under dynamic load conditions. Simulated studies show that fuzzy controller is found suitable for steady state and transient conditions of load. Keywords- Power electronics, power quality, shunt active filter, fuzzy logic controller, current controller.. I .INTRODUCTION The rapid use of power electronic controlled equipment in electrical distribution system offers highly nonlinear characteristics and produces voltage and current waveforms distortions called as „harmonics‟[1] . Some major problems in electrical distribution system due to harmonics are well enumerated in[2-6] . Distorted current and voltage waveform further affects other consumers connected to the same point of common coupling (PCC) by propagating these distortions in their premises. In order to overcome these power quality problems, passive and active compensation (filters) approaches is. ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 71. International Journal of Recent Advances in Engineering & Technology (IJRAET) The conventional methods use PI controller to regulate the DC bus voltage of VSI. Nemours methods have been proposed to replace PI control scheme such as optimal regulator control [12], sliding mode control [13], and model reference adaptive control. However, the design of these mentioned controllers depends on derived accurate mathematical models which are difficult to obtain. Also, these models do not give satisfactory operation under varying load condition with increased nonlinearity [8], [14], [15]. Artificial intelligence is one of the key area to solve such system complexity and make control more robust for transient conditions. Neural network, fuzzy logic, expert system, various other optimization methods are used for the improvement of power quality [15]. Fuzzy logic control (FLC) is one of the significant tool in control design originated by Zadeh [16]. The advantages of FLC over conventional controllers are high robustness, insensitivity to parameters variations, handling of non-linearity and independent on mathematical models [8], [15], [17]-[19] .. (a). This paper presents a fuzzy logic controlled shunt APF for the elimination of current harmonics and reactive power compensation of nonlinear load. The control scheme is based on indirect current control scheme in which only source current is sensed for avoiding switching spikes[20].. (b) Figure 1. (a) Basic scheme of APF compensation (b) Different waveforms of phase „a‟ load, source and compensating current. Three phase voltage and current signal is sensed using two voltage and current sensors. The effectiveness and validity of the proposed FLC is verified through MATLAB simulation. The total harmonic distortion (THD) results between the conventional PI and proposed FLC are presented. It is shown by the simulation results that proposed controller based on fuzzy logic is robust that conventional PI controller for steady-state and transient conditions of load.. A. Estimation of Reference current Supplied by source The peak value of the reference source current component is calculated by regulating DC link voltage of VSI. Source only supplies active component of current and rest of the component will be supplied by shunt APF for power quality improvement. In addition to the active current component source will also supplies loss component of current. A PI regulator is normally used to maintain DC bus voltage constant and the output of this PI controller is considered as required value of active current component. An experimental study of shunt APF has shown that load current having fundamental and other harmonic components which can be separated by Fourier series. Let the source voltage and instantaneous source current and load current can be written as[21]:. II. BASIC COMPENSATION PRINCIPLE Fig. 1 (a) shows the basic APF compensation scheme including nonlinear loads with a three-phase supply system. A current controlled VSI converter is used as an APF. APF is controlled to supply extract compensating current to from the utility (PCC). Fig. 1 (b) shows the different waveform of load current, source current and compensating current of one of the phase „a‟.. vs (t )  vm sin t is (t )  iL (t )  ic (t ). 1. ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 72. International Journal of Recent Advances in Engineering & Technology (IJRAET). iL (t ) . Finally, peak value of this source current when multiplied with unit templates generated from supply voltage will give three reference source currents.. .  If sin( nt  n) n 1. .  I 1 sin(t  f )   In sin( nt  n ) ( 2). III. THE PROPOSED FUZZY CONTROLLER. n2.  iLf (t )  iLh (t ). Fuzzy logic becomes more popular due to dealing with problems that have uncertainty, vagueness, parameter variation and especially where system model is complex or not accurately defined in mathematical terms for the designed control action. The concept of the fuzzy logic introduced by Zadeh, is a combination of fuzzy set theory and fuzzy inference system (FIS). Elements of a fuzzy set belong to it with a certain degree, called degree of membership. The degree of membership is a result of mapping the input to certain rules using a membership function (MF). The progression which maps the specified input data to the output using fuzzy logic is known as fuzzy inference. A fuzzy inference system can be classified as: (a) fuzzification: which is the process of converting any crisp value to analogous linguistic variable based on certain MF, (b) inference engine: simulates human decision, (c) knowledge base: consists MF definitions and necessary rules like IF-THEN or it is combination of condition part with their associated rules (d) defuzzification: is the progression of transforming the fuzzy output into a crisp numerical value. In this paper main control input variable is the DC-link voltage error and output of FLC is the peak value of the reference source current. The range of operating current, normalization and de-normalization is one of the important design factors of fuzzy controller. The block diagram representation of fuzzy logic controller with inference system is shown in Fig. 2. The scaling factor Ge, Gce, and Gu are used to scaling the input and outputs as per the designing of FLC.. where iLf and iLh are the fundamental and harmonic component of load current. I1 and In are the peak values of fundamental and harmonic component of load currents, respectively. Hence for given supply voltage the. PL(t )  vs (t )  iL (t ) . VmI 1 sin 2 t  cos f  VmI 1 sin t  cos t  sin f. 3. .  Vm sin t   In sin(nt  n) n2.  pact(t )  qreact.(t )  ph(t ) instantaneous power can be written as:. pact (t )  VmI 1 sin 2 wt  cos f. 4.  (Vm sin t ).( I 1 cos f ) sin t  vs (t )  is (t ). where pact, qreact. and ph are active, reactive and harmonic power of load. Out of these powers only first component will be supplied by source. From (3), peak value of fundamental component can be calculated as:. Ism  Ism  IsLoss. 5. Where Ism=I1cosØf is the peak value of the supply side current. In order to incorporate switching losses and converter losses, additional loss component of current will be supplied by source in addition to the real power of the load. Hence, the total peak current supplied by supply source can be written as:. isa  Ism  usaf. Figure 2. Detailed structure of fuzzy logic controller. 6. isb  Ism  usbf. A.. isc  Ism  uscf. Designing of control rules. Computational methods determine the computational efficiency, processor memory requirement and processing time. The fuzzy control rules based on membership function defining or relate input variables to output variables. The number and type of MF determines the computational efficiency of fuzzy control technique. The determination of MFs depends on the designer‟s experience and knowledge. The shape decision of MFs affects how well a fuzzy system rules. Conventionally, the actual capacitor voltage (Vdc) is compared with a calculated reference value (Vdc,ref). The error signal is then fed to a PI controller. The output of PI controller is considered as peak value of supply current (I sm). The DC side capacitor mainly serve two purpose, (a) it maintain DC bus voltage to set value with some steady- state error, and (b) in transient period it serves as energy storage element to supply real power difference between source and load.. ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 73. ). International Journal of Recent Advances in Engineering & Technology (IJRAET) approximate a function.. unequal; it is set here for cover a band of load current with good accuracy. After this rules formation as knowledge base, different inference mechanisms have been developed for defuzzify fuzzy rules.. Triangles or triangular membership function (TMF) have been frequently used in several applications of FLC [22], [23]. TMF are preferred due to simplicity, easy implementation, symmetrical along the axis. Fig. 3 shows the MFs relating input and output linguistic variables. The number of linguistic variables is directly related to the accuracy of approximating function and plays an important role for input-output mapping [24]. However, some limits variables in view of accuracy and complexity of FLC. The above can be summarized as for implementing FLC: . First, scaling factors consist of normalization gain for input and normalization gain is selected properly.. the de-. . Rules decision complexity.. and. . Fuzzification, implication using mamdani‟s operator and finally defuzzification to get desired output.. based. on. accuracy. Fig. 4 shows the block diagram of the proposed FLC scheme with shunt active filter. The designed rules for knowledge base are shown in Table 1. The top row and left column of the matrix indicate the fuzzy sets of the variables e and ce. (a) error „e‟ and change in error „ce‟. (b) Change in reference output current. Figure 4. Proposed fuzzy logic scheme based shunt active filter. Figure 3. Triangular shaped membership function used in fuzzification. TABLE I. FUZZY CONTROL RULE BASE e ce NB NM NS Z PS PM PB. The error e and change of error ce at nth sampling instant are used as input of FLC and can be written as:. e  Vdc, ref  Vdc ce(n)  e(n)  e(n  1). 7. The output of FLC with limiter is considered as amplitude of derived reference current ( Ism ). In this paper seven triangular membership functions have been chosen for representing numerical variables into linguistic variables [15], viz., NL (negative large), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium), PL (positive large). The spacing between MFs may be equal or. NB. NM. NS. Z. PS. PM. PB. NVB NVB NVB NB NM NS Z. NVB NVB NB NM NS Z PS. NVB NB NM NS Z PS PM. NB NM NS Z PS PM PB. NM NS Z PS PM PB PVB. NS Z PS PM PB PVB PVB. Z PS PM PB PVB PVB PVB. IV. DESIGNING OF APF PARAMETERS Mainly, selection of active power filter inductor (LC), DC link capacitor (Cdc) and it‟s reference value (Vdc,ref) are the main parameters while designing the power ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 74. International Journal of Recent Advances in Engineering & Technology (IJRAET) circuit. The output of the bridge is a PWM voltage that has to be filtered by an inductance or a high order filter to limit the level of ripple current. The APF filtering inductor is used to reduce the ripple of VSI fed converter caused by the switching of the power devices [9]. Hence, the design of filtering inductor is based on principle of harmonic current reduction technique [25] .On the dc side of the Shunt APF, capacitor supplies the dc voltage Vdc.. VI. SIMULATION RESULTS To simulate the proposed FLC based control scheme with reduced sensors, a model in MATLAB\ SIMULINK and Sim Power System Block set is developed. The complete 3-phase active filter system is composed using a supply source, a voltage source inverter, coupling and smoothing inductors with highly non-linear characteristic based load. Various simulations are carried out to verify the performance of the active power filter using proposed FLC and conventional PI controller with during steady-sate and transient conditions. The system parameters selected for simulation studies are given in Table 2.. The quality of distortion compensation is affected by the-choice of the energy storage element parameters, a high dc voltage Vdc, ameliorate the dynamics of the filter and minimize the voltage ripple in the capacitor. As per the specification of peak of dc ripple voltage and rated filter current Ic,rated , the following relation can obtain for (Cdc):.  .Ic , rated Cdc  3..Vdcr, p  p. TABLE II.. 8. The value of Cdc depends on the maximum possible variation in load and not on the steady state value of load current. Hence, proper forecasting in the load variation reduces the value of Cdc. Further, filter inductor can be Calculated as Lc, min . maVdc, ref 2 2 .Isw, p  p.KL. fsw, max. . . SYSTEM PARAMETERS. System parameters. Values. Supply voltage and frequency. 230 V.50Hz. Source impedence (Rs,Ls). 0.05Ω,0.5mH. Filter impedance (Rc,Lc). 0.25Ω,4mH. Smoothing inductor (Rsm,Lsm). 0.5Ω,1.5mH. Load impedance (RL1,RL2,LL1,LL2). 25Ω,75Ω,10mH, 15mH. 9 Reference DC link voltage (Vdc,ref). 680 volts. V. HYSTERESIS CURRENT CONTROLLER. DC link capacitance (Cdc). 1650µF. Among different pulse width modulation (PWM) techniques, hysteresis-band current control technique has proven to be most suitable for generating switching pulses for the switching device of VSI based active filter. It is broadly used because of its ease and inherentpeak current limiting capability without much information about system parameters. The actual source currents are monitored instantaneously, and then compared to the reference source currents generated by the proposed fuzzy logic based control algorithm. The positive group device and the negative group device in one phase leg of VSI are switched in complementary manner for avoiding a dead short circuit.. Switching frequency (fsm). 10-12 KHz. Fig. 7 shows the performance results using fuzzy controller of source voltage (VS), source, load and filter current (IS, IL and IC) and DC side capacitor voltage (Vdc). For the clarity purpose, only one phase filter current is shown. The filter is switched on at 0.06 s. Initially the three-phase load is 11-12 kW. The instant the filter is switched on the source current becomes sinusoidal having THD as per specified by IEEE standard from the stepped wave shape. The THD in the load current is 27%. THD of source current is reduced from 27 % to 2.36 %, which proves the effectiveness of proposed FLC.. The switching logic for „phase-a‟ is formulated as follows for hysteresis-band width (HB): if isa <(isa - HB ) , then upper switch is OFF and lower switch is ON in the phase “a” leg then Sa =1 ; if isa >(isa +HB ) , then upper switch is ON and lower switch is OFF in the phase “a” leg then Sa=0. Similarly, the switching pattern of rest of phase‟s devices can be derived using HB as the width of hysteresis band.. ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 75. International Journal of Recent Advances in Engineering & Technology (IJRAET). Figure 9. Transient response of PI controlled shunt APF. Figure 7. Switch-on response of system parameters based on FLC. Fig. 9 depicts that DC-link voltage rise at load change instant is much slower using PI controller. Also, settling time for transient case is also more as compared to FLC controller. It is clear from simulation results that the transient performance of supply current and DC-link voltage is good for FLC as compared to PI controller. However, THD performance for both FLC and PI are well with-in the are well with-in the limits specified by IEEE 519 standards as shown in Table 3.. To show the performance during transient condition load is increased to 11 kW to 15 kW at t=0.12 s. Fig. 8 shows the various system parameters waveform of the fuzzy logic controlled shunt APF during load change. Fig. 8 shows that there is smooth change in source current during this transient due to accurate control of FLC block. The variation of the dc capacitor voltage during the change in load current can be observed from this figure. When the load current is reduced or increased, capacitor voltage increase or decrease to compensate for the real power supplied by source. This change will be taken into account by the FLC controller to adjust the peak value of reference current.. TABLE III. HARMONIC SPECTRUM OF LOAD AND SOURCE CURRENT FOR PI AND FUZZY LOGIC CONTROLLER Order of. Under varying load the desired response of the FLC and APF system is reasonably fast and steady-state condition is reached within few cycles of AC mains. THD of source current is reduced from 26 % to 2.05 %, which shows a significant reduction in THD. Supply currents are sinusoidal, balanced and slightly leading with respect to supply voltage which is necessary to compensate line impedance drop.. Load current. harmonics. Source current THD with PI controller. Source current THD with Fuzzy controller. THD 1. 100. 100. 100. 5. 21.89. 1.1. .84. 7. 10.64. .75. 1.25. 11. 7.63. .64. .85. 13. 5.27. .50. .58. 17. 3.76. .39. .27. 19. 2.89. .1. .20. THD. 26.66%. 3.15%. 2.59%. Figure 8. Transient response of fuzzy logic controlled shunt APF. VII. CONCLUSION. The same MATLAB model of three phase shunt APF is tested for conventional PI controller by replacing fuzzy logic controller by PI controller. The value of proportional and integral gains (Kp and Ki) are selected as 0.59 and 2.35, respectively. Fig. 9 shows the performance results using conventional PI controller of source voltage (VS), source, load and filter current (I S, IL and IC) and DC side capacitor voltage (Vdc).. A simple fuzzy logic based three-phase shunt active power filter for current harmonic elimination and reactive power compensation is presented in this paper. The performance of fuzzy logic controlled shunt APF has been studied and compared with the conventional PI controller. The steady state performance is comparable ISSN (Online): 2347 - 2812, Volume-1, Issue - 2, 2013. 76. International Journal of Recent Advances in Engineering & Technology (IJRAET) to the PI controller whereas transient response is found better than the PI controller. The system has fast dynamic response for varying load condition and harmonic spectrum is found well below 5%, harmonic limit imposed by the IEEE-519 standard. The compensation process is simple with less sensor count and is based on sensing source current only. Experimentation of the proposed scheme using TMS320F28335 floating point digital signal processor is in process and will be reported in near future.. shunt active power filter for harmonics and reactive power compensation,” Elect. Power Comp. and Sys., vol. 31, pp. 671-692, 2003. [10]. R. M. Duke and S. D. Round, “The steady state performance of a controlled current active filter,” IEEE Trans. Power Electron., vol. 8, pp. 140146, 1993.. [11]. B. Singh, K. Al-Hadded and A. Chandra, “Computer aided modeling and simulation of active power filters,” Electr. Mach. 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