International Electrical Engineering Journal (IEEJ) Vol. 4 (2013) No. 3, pp ISSN

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1 Power Quality Improvement of Constant Frequency Aircraft Electric Power System Using Fuzzy Logic, Genetic Algorithm and Neural Network Control Based Control Scheme Saifullah Khalid 1, Bharti Dwivedi 2 1 Member, IEEE 1 saifullahkhalid@outlook.com, 2 I.E.T., Lucknow, India 2 bhartii_dwivedi@yahoo.com Abstract- A novel improved ANN control based aircraft shunt filter has been proposed in this paper. The shunt active power filter model has been improved using Genetic Algorithm and fuzzy logic. Genetic Algorithm has been used to find the optimum value of filter inductor; whereas fuzzy logic controller has been used in voltage control loop of the filter. The improvement in the control scheme using ANN control makes APF versatile for compensation of reactive power, harmonic currents, and unbalance in source currents. Proposed aircraft shunt filter also provide proper solution to the neural current in the system. The simulated results using MATLAB model are presented and they clearly prove the effectiveness of the proposed control method of aircraft shunt APF. Keywords: Active power filter, Artificial Neural Network, Fuzzy Logic controller, Genetic algorithm. I. INTRODUCTION More advanced aircraft power systems [1]-[3] has been required due to increased application of electrical power in place of other alternate power sources. The subsystems like flight control, flight surface actuators, passenger entertainment, etc. are driven using electric power, which in turn increased the demand for creating aircraft power system more intelligent and advanced. These subsystems has significantly increased electrical loads i.e. power electronic devices, increased consumption of electrical energy, more demand for power, and over to all of that; much more stability and power quality problems. In contrast to normal supply system source frequency of 50 Hz, aircraft ac power system is using source frequency of 400 Hz [1]-[3]. Aircraft power utility is having source voltage of 115/200V. The loads associated with the aircraft ac system are different from the normal loads used in 50 Hz supply system [1]. When we consider the generation portion; aircraft system will remain AC driven from the engine for aircraft primary power. Fuel cell technology can be used to produce a DC output for ground power where its silence operation would match up to satisfactorily with the Auxiliary Power Unit (APU). However when considering the distribution of primary power, whether AC or DC; each approach has its merits. In DC distribution, HVDC power distribution systems allow the more resourceful employ of generated power by antithetical loss from skin effect. This allows paralleling and load sharing between the generators. In AC distribution, Switching of AC is very clear-cut even at high levels as it naturally has a zero crossing point. Due 1098

2 to its high reliability over HVDC system, wide range of Contactors, Relays can be utilized. While discussing Aircraft Power Systems we also need to consider increased power electronics application in aircraft which creates harmonics, large neutral currents, waveform distortion of both supply voltage and current, poor power factor and excessive current demand. Furthermore if a number of non linear loads are impressed upon a supply their effects are additive. Due to these problems, there may be nuisance tripping of circuit breakers or increased loss and thermal heating effects which may incite early component failure. This is very big problem to any motor loads on the system. Therefore good power quality of the generation system is of particular interest to the Aircraft manufacturer. We know that aircraft systems work on high frequency so even on the higher frequencies in the range of 360 to 900Hz; these components would still remain very important Now days, advance soft computing techniques are used widely in automatic control system or for optimization of the system applied. Some of them are such as fuzzy logic [4]-[8], optimization of active power filter using GA[9]- [12], power loss minimization using particle swarm optimization[13], neural network control [14]-[18] applied in both machinery and filter devices. In this paper, three different AI techniques i.e. GA, Fuzzy and ANN have been used to make a complete optimized active filter for reduction of harmonics and others problem created into the aircraft electrical system due to the non linear loads [1]. The simulation results clearly show their effectiveness. The simulation results obtained with new model are much better than those of traditional methods. The paper has been organized in the following manner. The APF configuration and the load under consideration are discussed in Section II. The control algorithm for APF is discussed in Section III. MATLAB/ Simulink based simulation results are discussed in Section IV and finally Section V concludes the paper. The aircraft electrical system is a three-phase power system with source frequency of 400 Hz. As shown in Fig. 1, shunt Active Power filter improves the power quality and compensates the harmonic currents in the system [22],[24]- [25],[27]-[28],[30]. The shunt APF is realized by using one voltage source inverters (VSIs) connected at point of common coupling (PCC) with a common DC link voltage [20]-23]. The loads used in this paper are a combination of unbalanced and balanced non-linear loads. The load used is a three-phase rectifier connects a pure resistance directly The values of the circuit parameters and load under consideration are given in Appendix. Fig. 1. Aircraft system using Shunt Active Power filter III. CONTROL THEORY The proposed control of APF depends on Constant instantaneous power control strategy applied with artificial intelligent techniques such as Genetic algorithm, fuzzy logic and ANN [4]-[18]. The following section deals with basic application of Genetic algorithm, fuzzy logic and overall control scheme using ANN based on constant source current control strategy [19],[20],[29]. II. SYSTEM DESCRIPTION 1099

3 A. Design Using Genetic Algorithm Gas work on principles of natural evolution and genetic laws and used as new search techniques. GA can be used online or offline in the system for the selection of the parameters used in controller, the evaluation process includes a test, which gives the result in a format of a number representative of the performance of each individual. With any mean either use online or offline, there will be advantages and disadvantages both. The major advantage comes out of the on-line approach is the steadiness of the ultimate solution, because it is selected on the basis of its real performances. We know that GAs typically involve lots of tests to reach a perfect result. This means that this optimization process will take much more time for experiments to run on the real system. The off-line optimization can be based on a much more precise model of the system including all components, all non-linearties and limits of the controllers. It should however be understood that a compromise required to be meet in terms of simulation accuracy and optimization time. In this paper, GA is applied to the system simulated using MATLAB Simulink and has been used to search the optimum value inductor filter (L f ). The boundary and limits of parameters in the filter has been defined and a program using genetic algorithm has been written to give the best value of the filter inductor. B. Fuzzy logic control The fuzzy logic control has been used in the dc voltage control loop of the active power filter. In fuzzy, the design uses centrifugal defuzzification method. There are two inputs; error and its derivative and one output, which is the command signal. The two inputs uses Gaussian membership functions while the output uses triangle membership function. Table 1 presents the fuzzy control rule and Fig. 2 shows the membership functions used. Fig. 2. Membership functions TABLE 1 FUZZY CONTROL RULE C. Artificial Neural Network Control In this paper, the Constant source current control strategy based current controller has been modeled, by an artificial neural network (ANN) using two hidden layers with 12 neurons each, and one output layer with 3 neurons. As seen in the Constant instantaneous power control strategy theory, the current controller has seven inputs and three outputs. The network type used is feed forward back prop. TRAINLM has been used as a training function and LEARNGDM has been used as adaptive linear function. In this model each neurons of the hidden layers has n inputs and it varies based on the function of chosen hidden layer. The adaptation of the weights (W) and bias (b) in the ANN, is based, initially, on the calculation of the mean square error (MSE) between the outputs of the Constant instantaneous power control technique and those of the ANN, and secondly, on TRAINLM algorithm. D. Control Scheme 1100

4 In this paper Constant instantaneous power control strategy [19],[20],[23] has been used for active power filer with the application of artificial intelligent techniques as shown in the Fig. 3. The intelligent techniques like Fuzzy logic; genetic algorithm and ANN technique have been used to optimize the system so that the system will give the best performance under all conditions. We know that, the hysteresis controllers produce high switching frequency, which is very harmful for aircraft power utility of 400 Hz. So, we have applied the space vector modulation technique to this HB controller so that the disadvantages of the hysteresis controller can be reduced. SVM technique treats the inverter as a whole unit, which is different when compared to normal PWM technique. This technique is based on the decomposition of a reference voltage vector into voltage vector. However, when using this concept eight possible outputs are available out of them; two of the outputs are the null voltage vectors while the remaining six vectors are 60 apart of each other. The inverter will be driven to one of the eight unique switching states, where each state corresponds to a space vector. The eight space voltage vectors of the inverter are shown in Fig. 4. Each state corresponds to a space vector. V0 is the null voltage vector, and it generally has two switching patterns V0 (000) and V0 (111). The others six voltage vectors are labeled from V1 to V6 and are divided into six regions. This configuration can produce a better current shape by using a significant bandwidth of the hysteresis control [8],[31]. Fig. 3. Block diagram of the optimized active filter using GA, Fuzzy Logic and ANN Techniques The whole system based on Constant instantaneous power control strategy [24],[29] utilizing SVM based HB [31] has been implemented using MATLAB/Simulink to give the filter currents which will compensate the harmonics and make the system clean and well within standard limit [26]. IV. Fig. 4. Voltage output in space vector Simulation Results & Discussions The proposed scheme of APF is simulated in MATLAB environment to estimate its performance. The load consists of a three-phase rectifier connected to a pure resistance directly. The proposed control scheme has been simulated to compute the performance of APF and analysis through THD of source and load current. To realize compensation by APF, a small inductance is connected at the terminals of the load. The simulation results clearly demonstrate that 1101

5 the scheme is able to successfully reduce the significant amount of THD in source current and voltage within limits. Simulation results have been analyzed on the basis of THD and response time obtained. Simulation has been done for 15 cycles. A. Uncompensated system with three-phase rectifier connected a pure resistance directly After doing simulation in MATLAB/Simulink without using any filter (Figure 5) i.e. for Uncompensated System, it has been observed that the THD of source current found when load connected with the system is 2.07 % and THD of source Voltage were 28.96%. By observing these data, we can easily understand supply has been polluted when load has been connected. During the analysis of simulation results based on THD, this has been observed (Figure 6) that while doing simulation of Shunt Active power based on Conventional constant source instantaneous power strategy that the THD of source current found was 2.3% and THD of source Voltage were 1.45%; whereas when model has been optimized using Genetic Algorithm, Fuzzy Logic and current controller developed using ANN control techniques has been used, it has been observed that the THD of source current reduces to an amazing 0.99%, and THD of source voltage reduces to 1.4% which is absolutely the improvement from conventional one. During the analysis of simulation results based on response time for compensation, this has been observed that after the comparison of both model i.e. conventional constant source instantaneous power strategy model and improved model using Genetic Algorithm, Fuzzy Logic and current controller developed using ANN control techniques, the response time of new improved model was only sec; as comparison from old simple conventional model takes approx double time of sec, we found that new model is better than old conventional model. Figure 5 Source Voltage and source current waveforms of uncompensated system B. Performance of APF under three-phase rectifier connected to a pure resistance directly Figure 6 Source Voltage, source current, compensation current (phase b), load current and DC link Voltage waveforms of Active power filter using GA-FL with neural network controller 1102

6 The simulation waveforms shown and the result tabulated in table 2 confirms that the new improved GA-FL-ANN control based Shunt APF is able to compensate the system efficiently. TABLE 2 THDs & Response Time of Compensated System V. CONCLUSION A novel GA-FL-ANN control aircraft shunt active filter has been reported which clearly demonstrate its fast compensation ability. This also has been observed that Genetic Algorithm, Fuzzy Logic and ANN have well optimized the model and increased the ability of conventional model. From the simulation results, this can be easily seen that the proposed novel active filter can be effectively applied in higher frequency system. APPENDIX The system parameters used are as follows [1]: Three-phase source voltage: 115V/400 Hz Fig. 7. Graphical representation of THD-I and THD-V for uncompensated system, conventional and GA-FL-ANN control strategy From figure 7, we can clearly observe that THD for current and voltage are the least for AI(GA-FL-ANN) technique and figure 8 shows that AI technique applied is fast as compared to conventional technique. Techniques THD-I (%) THD-V (%) Compensation Time(sec) Conventional Technique GA-FL-ANN Technique Filter inductor=0.25m H Filter capacitor: 5 uf, Dc voltage reference: 400 V Dc capacitor: 4700uF REFERENCES Fig. 8. Graphical representation of Compensation Time for uncompensated system, conventional and GA-FL-ANN control strategy [1] Chen Donghua, Tao Guo, Shaojun Xie, Bo Zhou, Shunt Active Power Filters Applied in the Aircraft Power Utility, 36th Power Electronics Specialists Conference, PESC '05, IEEE, (2005), pp [2] Zixin Li,Yaohua Li, Ping Wang, Haibin Zhu, Congwei Liu, and Fanqiang Gao, Single-Loop Digital Control of High-Power 400-Hz Ground Power Unit for Airplanes, IEEE Transactions on Industrial Electronics, Vol. 57, No. 2, pp , February (2010). [3] E.Lavopa, P.Zanchetta, Real-time estimation of Fundamental Frequency and harmonics for active shunt power filters in aircraft Electrical Systems, IEEE Trans. on Industrial Electronics, Vol. 56, No. 8, Aug (2009). [4] Maurício Aredes, Luís. F. C. Monteiro, Jaime M. Miguel, Control Strategies for Series and Shunt Active Filters, IEEE Bologna Power 1103

7 Tech Conference, June 23th-26th, Bologna, Italy, (2003), pp [5] Mauricio Aredes, Jurgen Hafner, Klemens Heumann, Three-Phase Four-Wire Shunt Active Filter Control Strategies, IEEE Transactions on Power Electronics, Vol. 12, No. 2, pp , March (1997). [6] S.Khalid, B.Dwivedi, N.Kumar, N.Agrawal, A Review of State of Art Techniques in Active Power Filters and Reactive Power Compensation, National Journal of Technology, No 1, Vol. 3, pp.10-18, Mar. (2007). [7] F. Z.Peng,, H.Akagi,, and A.Nabae, A New Approach to Harmonic Compensation in Power Systems a Combined System of Shunt Passive and Series Active Filters, IEEE Trans. on Industry Applications, Vol. 6, No. 26,pp , (1990). [8] B.K.Bose, Recent Advances in Power Electronics, IEEE Trans. on Power Electronics, Vol. 7, No.1, pp. 2-15, Jan.(1992). [9] R. C. Dugan, M. F. McGranaghan, and H. W. Beaty, Electrical Power Systems Quality. New York: McGraw-Hill, (1996). [10] C. Sankaran, Power Quality. Boca Raton, FL: CRC Press, (2002). [11] IEEE Recommended Practices and Requirements for Harmonic Control in Electrical Power Systems, IEEE Standard , (1992). [12] S.Khalid, N.Vyas, Application of Power Electronics to Power System. University Science Press, New Delhi (2009). [13] N.Mohan, T. Undeland, and Robbins, W. Power Electronics Converters, Applications, and Design, 2nd. ed. Canada: John Wiley & Sons, (1995). [14] H. Akagi, E.H. Watanabe and M. Aredes, Instantaneous Power Theory and Applications to Power Conditioning, John Wiley & Sons, Inc., New Jersey, (2007). [15] Ali Emadi, A. Nasiri and S.B. Bekiarov, Uninterruptible Power Supplies and Active Power Filters, CRC Press, New York, (2005). [16] Saifullah Khalid, Bharti Dwivedi, Bhim Singh, New Optimum Three-Phase Shunt Active Power Filter based on Adaptive Tabu Search and Genetic Algorithm using ANN control in unbalanced and distorted supply conditions, Elektrika : Journal of Electrical Engineering, Vol. 14, Issue 2, pp , (2012). [17] S.Khalid, B.Dwivedi, Power Quality Improvement of Constant Frequency Aircraft Electric Power System using Genetic Algorithm and Fuzzy Logic Control Based Control Scheme, International Electrical Engineering Journal (IEEJ),Vol. 4, No. 1, pp , [21] Bhim Singh, Kamal Al-Haddad and Ambrish Chandra, A review of active filters for power quality improvement, IEEE Trans. on Industrial Electronics, Vol. 46, No. 5, pp , October (1999). [22] F. Z.Peng,, H.Akagi,, and A.Nabae, A New Approach to Harmonic Compensation in Power Systems a Combined System of Shunt Passive and Series Active Filters, IEEE Trans. on Industry Applications, Vol. 6, No. 26,pp , (1990). [23] B.K.Bose, Recent Advances in Power Electronics, IEEE Trans. on Power Electronics, Vol. 7, No.1, pp. 2-15, Jan.(1992). [24] R. C. Dugan, M. F. McGranaghan, and H. W. Beaty, Electrical Power Systems Quality. New York: McGraw-Hill, (1996). [25] C. Sankaran, Power Quality. Boca Raton, FL: CRC Press, (2002). [26] IEEE Recommended Practices and Requirements for Harmonic Control in Electrical Power Systems, IEEE Standard , (1992). [27] A. Ghosh and G. Ledwich, Power Quality Enhancement Using Custom Power Devices. Boston, MA: Kluwer, (2002). [28] N.Mohan, T. Undeland, and Robbins, W. Power Electronics Converters, Applications, and Design, 2nd. ed. Canada: John Wiley & Sons, (1995). [29] H. Akagi, E.H. Watanabe and M. Aredes, Instantaneous Power Theory and Applications to Power Conditioning, John Wiley & Sons, Inc., New Jersey, (2007). [30] Ali Emadi, A. Nasiri and S.B. Bekiarov, Uninterruptible Power Supplies and Active Power Filters, CRC Press, New York, (2005). [31] Leow Pei Ling, SVM Based Hysteresis Current Controller for a Three Phase Active Power Filter, M.E. Thesis, Department of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, (2004). [18] R. Dehini, A. Bassou, B. Ferdi, Artificial Neural Networks Application to Improve Shunt Active Power Filter, International Journal of Computer and Information Engineering, Vol. 3, No. 4, pp , (2009). [19] Maurício Aredes, Luís. F. C. Monteiro, Jaime M. Miguel, Control Strategies for Series and Shunt Active Filters, IEEE Bologna Power Tech Conference, June 23th-26th, Bologna, Italy, (2003), pp [20] Mauricio Aredes, Jurgen Hafner, Klemens Heumann, Three-Phase Four-Wire Shunt Active Filter Control Strategies, IEEE Transactions on Power Electronics, Vol. 12, No. 2, pp , March (1997). 1104