Grid Interactive PV System with Harmonic and Reactive Power Compensation Features using a Novel Fuzzy Logic Based MPPT

ABSTRACT:

Photovoltaic (PV) cell characteristics are highly nonlinear that gives single Maximum Power Point (MPP) on P-V curve under uniform insolation condition. The characteristics and hence MPP point changes with the variation in insolation and temperature. In order to extract a maximum power from PV array, a fuzzy based MPP tracking algorithm is proposed. The algorithm accepts single input that is slope of P-V curve and generates the duty ratio as an output that operates the boost converter to track MPP. The algorithm gives faster convergence by applying variable step in duty ratio and gives accurate MPP. The two stage grid interactive PV system described in this paper supplies active power as well as provides harmonic and reactive power compensation. This additional feature increases the effective utilization of PV inverter and increases the overall efficiency of the system. The simulation results validate the performance and stability of the grid interactive PV system using the proposed algorithm for active current injection as well as harmonics and reactive power compensation.

KEYWORDS:

1.     Photovoltaic system

2.     Maximum power point tracking

3.     Fuzzy logic controller

4.     Harmonic elimination

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

 CONCLUSION:

In this paper, multi functional grid interactive PV system is presented using a novel fuzzy logic based MPPT. The proposed MPPT controller is able to track the MPP accurately under uniformly varying as well as rapidly changing insolation and gives faster convergence as a variable step size in duty ratio is applied inherently by the algorithm. The proposed fuzzy controller maintains the dc link voltage within the limit for injecting the power into the grid. Apart from injecting active power during day time, the PV inverter also compensates the harmonics and reactive power during day time as well as at night. The current drawn from the grid is sinusoidal and the total harmonic distortion is well below the specified limit in the IEEE-519 standard. The simulation results validate the performance of grid interactive PV system for both active power injection as well as shunt active power filter functionality to mitigate the power quality issues thus increases the utilization factor of the system.

REFERENCES:

 [1] T. Esram and P. Chapman, “Comparision of photovoltaic array maximum power point tracking techniques”, IEEE Trans. on Energy Conversion, vol. 22, No. 2, June 2007.

[2] S. Jain and V. Agarwal , “Comparison of the performance of maximum power point tracking schemes applied to single-stage grid-connected photovoltaic systems”, IET Electr. Power Appl., vol. 1, no. 756(5), pp. 753-762, September 2007.

[3] P. Takun, S. Kaitwanidvilai and C. Jettanasen, “Maximum Power Point Tracking using Fuzzy Logic Control for Photovoltaic Systems”, International conference of engineers and computer scientists (IMECS), Vol.-II, pp. 986-990, March-2011.

Neural Network Based Dynamic Simulation of Induction Motor Drive

ABSTRACT:

With the improvement in the technology of Microprocessor and Power Electronics, Induction motor drives with digital control have become more popular. Artificial intelligent controller (AIC) could be the best candidate for Induction Motor control. Over the last two decades researchers have been working to apply AIC for induction motor drives. This is because that AIC possesses advantages as compared to the conventional PI, PID and their adaptive versions. The main advantages are that the designs of these controllers do not depend on accurate system mathematical model and their performances are robust. In recent years, scientists and researchers have acquired significant development on various sorts of control theories and methods. Among these control technologies, intelligent control methods, which are generally regarded as the aggregation of Fuzzy Logic Control, Neural Network Control , Genetic Algorithm, and Expert System, have exhibited particular superiorities. The artificial neural network controller introduced to the system for keeping the motor speed to be constant when the load varies. The speed control scheme of vector controlled induction motor drive involves decoupling of the speed and ref speed into torque and flux producing components. The performance of artificial neural network based controller's is compared with that of the conventional proportional integral controller. The dynamic modeling of Induction motor is done and the performance of the Induction motor drive has been analyzed for constant and variable loads. By using neuro controller the transient response of induction machine has been improved greatly and the dynamic response of the same has been made faster.

KEYWORDS:

1.      Vector Control (VC)

2.      Direct, Dynamic Simulation

3.      Artificial Intelligence (AI)

4.       PI Controller

5.      Artificial Neural Network (ANN)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

 

CONCLUSION:

An Artificial intelligent based vector controlled induction motor has been presented in this paper. The vector control strategy is developed with Neural network controller. The conventional vector control of induction motor is compared with the proposed neural network based controllers, and from the results it is observed that the performance with neural network controller is better than PI controller. In steady state condition, the rise time and speed regulation with conventional controller is more than that of the ANN controller. During transient condition, the settling time before changing the load and after changing the load is less in case of ANN controller as compared to PI controller. It is observed that there is no overshoot in case of ANN controller. Thus, by using neuro controller the transient response of induction machine has been improved greatly and the dynamic response of the same has been made faster.

 REFERENCES:

 [1] K. L . Shi, T . F. Chan, Y. K. Wong and S. L . HO, "Modeling and simulation of the three phase induction motor Using SIMULINK," Int.J. Elect. Enging. Educ., Vol. 36, 1999, pp. 163–172.

[2] Tze Fun Chan and Keli Shi, "Applied intelligent control of induction motor drives," IEEE Willey Press, First edition, 2011.

[3] P.C. Krause, "Analysis of Electrical Machinery and Drives System, "IEEE Willey Press, 200).

[4] Ned Mohan, "Advanced Electric Drives: Analysis, Control Modeling using Simulink,"MNPERE Publication ,2001.

[5] M. Nasir Uddin and Muhammad Hafeez, "FLC-Based DTC Scheme to Improve the Dynamic Performance of an IM Drive," IEEE Trans.on Industry Applications , Vol -48 , No 2, Mar/Apr 2012, pp 823-831.

SPEED CONTROL OF SWITCHED RELUCTANCE MOTOR USING SLIDING MODE CONTROL STRATEGY

ABSTRACT:

A robust speed drive system for a switched reluctance motor (SRM) using sliding mode control strategy (SLMC) is presented. After reviewing the operation of an SRM drive, a SLMC based scheme is formulated to control the drive speed. The scheme is implemented using a micro controller and a high resolution position sensor. The parameter insensitive characteristics are demonstrated through computer simulations and experimental verification.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

 CONCLUSION:

This paper has described the application of sliding mode control to SRM drive. Tests were carried out a 5 hp SRM to validate the speed control responses predicted by simulation and to validate the analytical approach. It has been shown that sliding mode control is insensitive to plant parameter variations and that it provides rejection of inherent drive non linearities. The problem of torque chattering is overcome by adopting a cascaded integral operation in the torque control path between the sliding mode controller and the feed forward controller.

 REFERENCES:

 1. P.J.Lawrenson, J.M. Stephenson, P.T. Blenkisop, J. Corda and N.N. Fulton, "Variable-speed switched reluctance motors", IEE Proc., pt. B, vol. 127, no. 4, pp. 253-265, July 1980.

2. T.J.E. Miller, "Converter volt-ampere requirements of the switched reluctance motor drive", IEEE IAS Annual Meeting Conf. Record, Chicago, pp. 813-819, Oct. 1984

3.B.K. Bose, T.J.E. Miller, P.M. Szczesny and W.H. Bicknell, "Microcomputer control of switched reluctance motor", IEEE US Annual Meeting Conf. Record, Toronto, pp. 542-547, Oct. 1985.

4.A.R Oza, R. Krishnan and S . Adkar, "A microprocessor control scheme for switched reluctance motor drives", Conf. Record, IEEE Industrial Electronics Conference, pp.

5.V.I. Utkin,"Variable structure control systems with sliding mode", IEEE Trans. on Auto. Control, Vol. AC-22, No. 2, pp. 210-222, April 1977.

Analysis of the Operation of a D-STATCOM in Unbalanced Distribution Systems Under Voltage Disturbances

ABSTRACT:

In this paper, a study on the operation of a static synchronous compensator for distribution systems, DSTATCOM, in relation to its performance in the presence of events that can affect system´s power quality, is presented. Performance under short-circuit and load variation is assessed. The IEEE 13 node test feeder, which is a highly loaded unbalanced system, is used in the study. The D-STATCOM consists mainly of a three-level inverter with IGBTs and PWM control. Modeling and simulations are implemented in Matlab/Simulink.

KEYWORDS:

1.      D-STATCOM

2.      Power Quality

3.      Unbalanced Distribution Systems.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

This work presented simulation results for a D-STATCOM operating in a typical unbalanced distribution test system. Simulations were conducted in order to assess the DSTATCOM performance under balanced and unbalanced disturbances. A commercially available D STATCOM topology was chosen. In addition, a standard control system was used, in order to illustrate that, in general, good solutions for power quality related problems can be obtained without resorting to more complex and specific problem-oriented control systems. The DC voltage, although not shown, was in all cases, stable with low ripple. Controller parameters did not have to be modified for different situations in order to perform satisfactorily. Finally, it can be concluded that the D-STATCOM used in this study can contribute significantly to the improvement of power quality in unbalanced distribution systems.

REFERENCES:

[1] N. G. Hingorani, and L. Gyugyi, Understanding Facts: Concepts and Technology of Flexible AC Transmission Systems. Wiley-IEEE Press, December 1999.

[2] P. Giroux, G. Sybille, and H. Le-Huy, “Modeling and Simulation of a Distribution STATCOM using Simulink´s Power System Blockset,” in IECONOl: The 27th Annual Conference of the IEEE Industrial Electronics Society, pp. 990-994.

[3] C. Hochgraf, and R. H. Lasseter, “Statcom Controls for Operation with Unbalanced Voltages,” IEEE Transactions on Power Delivery, vol. 13, No. 2, April 1998.

[4] M. T. Bina, and M. D. Eskandari, “Consequence of Unbalance Supplying Condition on a Distribution Static Compensator,” in 35^th Annual IEEE Power electronics Specialists Conference, pp. 3900-3904.

[5] B. Blažič, and I. Papič, “Improved D-StatCom Control for Operation With Unbalanced Currents and Voltages,” IEEE Transactions on Power Delivery, vol. 21, No. 1, January 2006.

Control of the Dynamic Voltage Restorer to Improve Voltage Quality

ABSTRACT:

In this study a method is proposed in order to improve the voltage compensation performance of Dynamic Voltage Restorer by using Self Tuning Filter. The proposed control method gives an adequate voltage compensating even for 50% voltage sag and distorted voltage conditions. The proposed DVR control method is modeled using MATLAB/SIMULINK and tested both in off-line and real-time environment. Results are then presented as a verification of the proposed method.

KEYWORDS:

1.      DVR; voltage sag

2.      Voltage harmonics

3.      STF

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

This paper shows the effectiveness of implementing STF in the traditional control method of DVR to compensate the distorted and unbalanced grid voltage condition as well as sudden drop or increase in grid voltage. Performance of the improved method is tested both in off-line and real-time mode. Results show that the proposed method can significantly improve the performance of the DVR and thus the load does not sense any kind of grid voltage disturbances.

Moreover, the grid voltage harmonics are effectively suppressed on the load terminal.

REFERENCES:

[1] M. Ramasamy, S. Thangavel, Experimental verification of PV based Dynamic Voltage Restorer With Significant Energy Conservation, Electrical Power and Energy Systems 49 (2013) 296-307.

[2] O. S. Senturk, A. M Hava, "High-Performance Harmonic Isolation and Load Voltage Regulation of the Three-Phase Series Active Filter Utilizing the Waveform Reconstruction Method," IEEE Transactions on Industry Applications, vol.45, no.6, pp.2030,2038, Nov.-dec. 2009.

[3] M. Abdusalam, P. Poure, S. Karimia, S. Saadate, "New Digital Reference Current Generation for Shunt Active Power Filter under Distorted Voltage Conditions", Electric Power Systems Research, vol. 79, pp 759-76, 2009.

[4] A. Ghamri , M. T. Benchouia & A. Golea "Sliding-Mode Control Based Three-Phase Shunt Active Power Filter", Simulation and Experimentation, Electric Power Components and Systems, 40:4, 383- 398, Jan. 2012.

Incremental Fuzzy PI Control of a HVDC Plant

Incremental Fuzzy PI Control of a HVDC Plant

ABSTRACT:

This paper investigates a Fuzzy Logic (FL) based current controller for a High Voltage Direct Current (HVDC) plant connected to a weak AC system under the EMTP RV simulation environment. A typical HVDC system is modeled with a detailed representation of the converter, converter controls and AC system. An Incremental Fuzzy Gain Scheduling Proportional and Integral Controller (IFGSPIC) is used for the rectifier current control. The current error and its derivative are taken as two parameters necessary to adapt the proportional (P) and integral (I) gains of the controller based on fuzzy reasoning. Two different fuzzy rule bases are designed to tune the PI gains independently. The fuzzy control rules and analysis of IFGSPIC are presented. To improve performance, the IFGSPIC is designed like a hybrid controller that combines the advantages of a FL and conventional PI controllers. During transient states, the PI gains are adapted by the IFGSPIC to damp out undesirable oscillations around the set point and reduce settling time. During the steady state, the controller is automatically switched to the conventional PI controller to maintain the control stability and accuracy. Performance evaluation under AC fault and set-point step change is studied. A performance comparison between the conventional PI controller and hybrid IFGSPIC is made. Results from the various tests show that the proposed controller outperforms its conventional counterpart in each case.

KEYWORDS:

1.     FL Controller

2.     Gain scheduling

3.     EMTP RV

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 EXPECTED SIMULATION RESULTS:

CONCLUSION:

In this paper, a method combining FL with a conventional PI controller is proposed and applied to the current controller of a HVDC plant. A performance comparison between the two types of controllers showed that the robustness and adaptation of the proposed FL controller is better. For a strong AC system at the HVDC converter, both controllers have an acceptable performance. But when the AC system is weak (an increasingly important requirement for such plants), the HVDC system is prone to collapse with the conventional controller while the FL controller has a satisfactory performance.

REFERENCES:

1. V. K. Sood, “HVDC and FACTs Controllers,” Kluwer Academic Publishers, 2004, ISBN 1-4020-7890-0.

[2]. P.K.Dash, A.C.Liew, and A. Routray, “High-performance controllers for HVDC transmission links.” IEE, Proc.-Gener. Transm. Distrib., Vol. 141, No. 5, September 1994.

[3]. S. Haykin, “Neural Networks: A Comprehensive Foundation.” 2^nd ed. New York: Prentice Hall, 1995.

[4]. Li-Xin Wang, “A Course in Fuzzy Systems and Control,” Prentice Hall PTR, 1997.

[5]. V.K. Sood, N. Kandil, R.V. Patel, and K. Khorasani, “Comparative evaluation of neural network-based and PI current controllers for HVDC transmission.”, IEEE Transactions on Power Electronics, Vol. 9, No. 3, pp. 288-296, May 1994.

Application of Artificial Neural Networks for Shunt APF Control

Application of Artificial Neural Networks for

Shunt APF Control

ABSTRACT:

Artificial Neural Network (ANN) is becoming an attractive estimation and regression technique in many control applications due to its parallel computing nature and high learning capability. There has been a lot of effort in employing the ANN in shunt active power filter (APF) control applications. Adaptive Linear Neuron (ADALINE) and feed-forward Multilayer Neural Network (MNN) are the most commonly used ANN techniques to extract fundamental and/or harmonic components present in the non-linear currents. This paper aims to provide an in-depth understanding on realizing ADALINE and feed-forward MNN based control algorithms for shunt APF. A step-by-step procedure to implement these ANN based techniques, in Matlab/ Simulink environment, is provided. Furthermore, a detailed analysis on the performance, limitation and advantages of both methods is presented in the paper. The study is supported by conducting both simulation and experimental validations.

KEYWORDS:

1.     Shunt APF

2.     ANN

3.     ADALINE

4.     Feed-forward MNN.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 CONTROL BLOCK DIAGRAM:

 EXPECTED SIMULATION RESULTS:

CONCLUSION:

In this paper, two widely used ANN based shunt APF control strategies, namely the ADALINE and feed-forward MNN, are investigated. A simple step by step procedure is provided to implement each method in Matlab/Simulink environment. The ADALINE is trained online by the LMS algorithm, while the MNN is trained offline using the SCG back propagation algorithm to extract the fundamental load active current magnitude. The performance of these ANN based shunt APF controllers is evaluated through detailed simulation and experimental studies. Based on the study conducted in this paper, it is observed that the ADALINE based control technique performs better than the feed-forward MNN. For untrained load scenario, the feed-forward MNN

fails to extract the fundamental component, resulting in overcompensation from the dc link PI regulator. On contrary, the online adaptiveness of ADALINE makes it applicable to any load condition.

REFERENCES:

[1] P. Kanjiya, V. Khadkikar, and H. H. Zeineldin, “A Noniterative Optimized Algorithm for Shunt Active Power Filter Under Distorted and Unbalanced Supply Voltages,” IEEE Trans. Ind. Electron., vol.60, no.12, pp.5376,5390, Dec. 2013.

[2] B. Singh, K. Al-Haddad, and A. Chandra, “A review of active filters for power quality improvement,” IEEE Trans. Ind. Electron., vol.46, no.5, pp.960-971, Oct 1999.

[3] M. Popescu, A. Bitoleanu, and V. Suru, “A DSP-Based Implementation of the p-q Theory in Active Power Filtering Under Nonideal Voltage Conditions,” IEEE Trans. Ind. Informat., vol.9, no.2, pp.880,889, May 2013.

[4] V. Silva, J. G. Pinto, J. Cabral, J. L. Afonso, and A. Tavares, “Real time digital control system for a single-phase shunt active power filter,” in Conf. Rec. INDIN, 2012, pp.869,874.

[5] A. Hamadi, S. Rahmani, K. Al-Haddad, “Digital Control of a Shunt Hybrid Power Filter Adopting a Nonlinear Control Approach,” IEEE Trans. Ind. Informat., vol.9, no.4, pp.2092,2104, Nov. 2013.