Grid Connected Wind- Photovoltaic hybrid System

ABSTRACT

 This paper presents a modeling and control strategies of a grid connected Wind-Photovoltaic hybrid system. This proposed system consists of two renewable energy sources in order to increase the system efficiency. The Maximum Power Point Tracking (MPPT) algorithm is applied to the PV system and the wind system to obtain the maximum power for any given external weather conditions. The generator side converter is controlled by the Field Oriented Control (FOC). This approach is used to control independently the flux and the torque by applying the d- and q-components of the current motor. The utility grid side converter is controlled by the Voltage Oriented Control (VOC) strategy which is adopted to adjust the DC-link at the desired voltage. The simulation results using PSIM software environment prove the good performance of these used techniques to generate sinusoidal current waveforms. This current is synchronized with the grid voltage. Moreover, the DC bus voltage is perfectly constant because only the active power is injected into the grid. Simulations are carried out to validate the effectiveness of the proposed system methods.

KEYWORDS

  1. Converter
  2. FOC
  3. Grid
  4. hybrid system
  5. MPPT control
  6. photovoltaic system
  7. SCIG
  8. VOC
  9. Wind turbine

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM

 

Fig. l.The proposed PV -wind hybrid system

 EXPECTED SIMULATION RESULTS

Fig. 2 Solar irradiance changes

Fig. 3 The variation of PY arrays current

Fig. 4 The PY arrays voltage

Fig. 5 The PY arrays power and reference

Fig. 6 Duty cycle

Fig. 7 Wind speed profile

Fig. 8 Electrical angular speed of the SCIG and its reference

Fig. 9 The active power injected into the grid

Fig. 10 The Reactive power injected into the grid

Fig. 11 The waveforms of the current

Fig. 12 The three phase current and voltage waveforms

Fig. 13. DC link voltage.

CONCLUSION

In this paper, Wind-Photo voltaic hybrid system control has been investigated. An MPPT method has been studied. It has been simulated with different solar irradiation and wind speed environments in order to maximize the output power of the proposed system . Two control techniques have been employed to improve the hybrid system usefulness . The controlled rectifier connected to the squirrel-cage induction generator (SCIG) has been controlled by the Field Oriented Control (FOC) to reach the optimal rotational speed, The grid-side inverter has been controlled by the Voltage Oriented Control (VOC) method to keep the dc-link voltage at the desired value. The hybrid system simulation has been implemented in PSIM software and its performances were proved when the solar irradiance change or the wind speed occurs.

REFERENCES

 [1] Liyuan Chen, Yun Liu “Scheduling Strategy of Hybrid Wind Photovoltaic- Hydro Power Generation System” International Conference on Sustainable Power Generation and Supply (SUPERGEN 2012), Sept. 2012.

[2] Akhilesh P. Pati!, Rambabu A. Vatti and Anuja S. Morankar,” Simulation of Wind Solar Hybrid Systems Using PSIM ” International Journal of Emerging Trends in Electrical and Electronics (lJETEE), Vol. 10, Issue. 3, April-2014.

[3] Rabeh Abbassi, Manel Hammami, Souad Chebbi. “Improvement of the integration of a grid connected wind-photovoltaic hybrid system” Electrical Engineering and Software Applications (lCEESA), International Conference , 2013

[4] Harini M., Ramaprabha R. and Mathur B. L. “Modeling of grid connected hybrid windlPV generation system using matlab, Vol. 7,no. 9, September 2012.

[5] Nabil A. Ahmed “On-Grid Hybrid Wind/Photovoltaic/Fuel Cell Energy System” Conference on Power & Energy ( IPEC), December 2012.

 

 

AsokaTech9347**

Control and Performance Analysis of a Single-Stage Utility-Scale Grid-Connected PV System

IEEE SYSTEMS JOURNAL, VOL. 11, NO. 3, SEPTEMBER 2015

ABSTRACT:

For utility-scale photovoltaic (PV) systems, the control objectives, such as maximum power point tracking, synchronization with grid, current control, and harmonic reduction in output current, are realized in single stage for high efficiency and simple power converter topology. This paper considers a highpower three-phase single-stage PV system, which is connected to a distribution network, with a modified control strategy, which includes compensation for grid voltage dip and reactive power injection capability. To regulate the dc-link voltage, a modified voltage controller using feedback linearization scheme with feedforward PV current signal is presented. The real and reactive powers are controlled by using dq components of the grid current. A small-signal stability/eigenvalue analysis of a grid-connected PV system with the complete linearized model is performed to assess the robustness of the controller and the decoupling character of the grid-connected PV system. The dynamic performance is evaluated on a real-time digital simulator.

 

KEYWORDS:

  1. DC-link voltage control
  2. Feedback linearization (FBL)
  3. Photovoltaic (PV) systems
  4. Reactive power control
  5. Small signal stability analysis
  6. Voltage dip.

SOFTWARE: MATLAB/SIMULINK

 

BLOCK DIAGRAM:

One of the four 375-kW subsystems.

Fig. 1. One of the four 375-kW subsystems.

  

EXPECTED SIMULATION RESULTS:

(a) PV array voltage for MPPT. (b) PV array (PPV) and grid injected real power (Pg). (c) Grid injected reactive power (Qg).

Fig. 2. (a) PV array voltage for MPPT. (b) PV array (PPV) and grid injected real power (Pg). (c) Grid injected reactive power (Qg).

Grid injected currents and THD.

Fig. 3. Grid injected currents and THD.

PV system response to voltage dip in grid.

Fig. 4 PV system response to voltage dip in grid.

PV system response to a three-phase fault at bus 3.

Fig. 5. PV system response to a three-phase fault at bus 3.

PV system response to an LG fault.

Fig. 6. PV system response to an LG fault.

Pg  response of the whole 1.5-MW PV system.

Fig. 7. Pg  response of the whole 1.5-MW PV system.

 

CONCLUSION:

The proposed modified dc-link voltage controller with FBL technique, using INC MPPT, and real and reactive power controls with enhanced filter for compensation for grid voltage dips has been tested at different insolation levels on a real-time digital simulator (RTDS). Small-signal analysis of a PV system connected to an IEEE 33-bus distributed system is performed. The results from simulation and eigenvalue analysis demonstrate the effectiveness of the FBL controller compared with the controller without FBL. It is found that the FBL controller  outperforms the controllerwithout FBL, as the FBL controller’s  performance is linear at different operating conditions. With grid voltage dip compensator filter, the dynamic performance is much improved in terms of less oscillations and distortion in waveforms. In addition, the eigenvalue analysis shows that the effect of the disturbance in distribution system is negligible on PV system stability as the eigenmodes of the PV system are almost independent of the distribution system. This has been also confirmed by three-phase fault analysis of distribution system in RTDS model. The controller performance is also validated on 4×375 kW PV units connected to the distribution system.

 

REFERENCES:

  • Oprisan and S. Pneumaticos, “Potential for electricity generation from emerging renewable sources in Canada,” in Proc. IEEE EIC Climate Change Technol. Conf., May 2006, pp. 1–10.
  • Petrone, G. Spagnuolo, R. Teodorescu, M. Veerachary, and M. Vitelli, “Reliability issues in photovoltaic power processing systems,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2569–2580, Jul. 2008.
  • Jain and V. Agarwal, “A single-stage grid connected inverter topology for solar PV systems with maximum power point tracking,” IEEE Trans. Power Electron., vol. 22, no. 5, pp. 1928–1940, Jul. 2007.
  • Katiraei and J. Aguero, “Solar PV integration challenges,” IEEE Power Energy Mag., vol. 9, no. 3, pp. 62–71, May-Jun. 2011.
  • H. Ko, S. Lee, H. Dehbonei, and C. Nayar, “Application of voltageand current-controlled voltage source inverters for distributed generation systems,” IEEE Trans. Energy Convers., vol. 21, no. 3, pp. 782–792, Sep. 2006.

MPPT Schemes for PV System under Normal and Partial Shading Condition: A Review

ABSTRACT:

The photovoltaic system is one of the renewable energy device, which directly converts solar radiation into electricity. The I-V characteristics of PV system are nonlinear in nature and under variable Irradiance and temperature, PV system has a single operating point where the power output is maximum, known as Maximum Power Point (MPP) and the point varies on changes in atmospheric conditions and electrical load. Maximum Power Point Tracker (MPPT) is used to track MPP of solar PV system for maximum efficiency operation. The various MPPT techniques together with implementation are reported in literature. In order to choose the best technique based upon the requirements, comprehensive and comparative study should be available. The aim of this paper is to present a comprehensive review of various MPPT techniques for uniform insolation and partial shading conditions. Furthermore, the comparison of practically accepted and widely used techniques has been made based on features, such as control strategy, type of circuitry, number of control variables and cost. This review work provides a quick analysis and design help for PV systems.

KEYWORDS:

1.      Renewable Energy System

2.       Solar Photovoltaic

3.       Solar Power Conversion

4.       Maximum Power Point Tracking

5.       Partial Shading

6.      Global MPPT

 SOFTWARE:MATLAB/SIMULINK

 

BLOCK DIAGRAM:

 

 Fig. 1 Current feedback methodology for MPPT tracking

 EXPECTED SIMULATION RESULTS:

 

 Fig. 2 Irradiance pattern for the testing of MPPT controller

Fig. 3 Power output response for Voltage Fraction MPPT

 

Fig. 4 Power output response for the P&O and INC controller

Fig. 5 Power output response for Fuzzy Logic MPPT controller

Fig. 6 The P-V curve for the demonstration of Power slope technique algorithm

Fig. 7 The output power of PV array for the Power Curve Scanning technique

Fig. 8 The output power of PV array for the modified Power Slope Detection GMPPT technique

CONCLUSION:

The prominent techniques of MPPT are discussed in this paper. It may be used as tutorial material on solar MPPT. Also, an attempt has been made to describe the important GMPPT techniques with sufficient details. A comprehensive comparative analysis has been contributed in this paper considering performance, cost, complexity of circuit and other parameters of MPPT. The results of this analysis will be helpful for proper selection of MPPT method. The generated power performance through few MPPT controllers has been illustrated with the help of simulation excercise. This also provides better understanding through numerical comparison. This review work has also presented a brief analysis and comparison of MPPT techniques for partial shading conditions. This paper may be useful for solar PV system manufacturer and solar inverter designer.

 REFERENCES:

Abdourraziq, S., & El. Bachtiri Rachid (2014) A perturb and observe method using fuzzy logic control for PV pumping system. International Conference on Multimedia Computation and Systems, Marrakech, 1608-1612.

Adly, M., El-Sherif, H., & Ibrahim, M. (2011) Maximum Power Point Tracker for a PV cell using a fuzzy agent adapted by the Fractional open circuit voltage technique. IEEE International Conference on Fuzzy System, Taipei, 1918-1922.

Ahmad, J. (2010) A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays. International Conference on Soft Technology and Engineering, San Juan, 247-250.

Ahmed, N.A., and Miyatake, M. (2008) A novel maximum power point tracking for photovoltaic applications under partially shaded insolation conditions. Electric Power System Research, 78, 777-784.

Altas, I.H., & Sharaf, A.M. (1996) A novel on-line MPP search algorithm for PV arrays. IEEE Transactions on Energy Conversions, 11 (4), 748-754.

Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

Scientific Research Publishing, Smart Grid and Renewable Energy, 2015.

Maximum Power Point  ABSTRACT: This study proposes a fuzzy system for tracking the maximum power point of a PV system for solar panel. The solar panel and maximum power point tracker have been modeled using MATLAB/Simulink. A simulation model consists of PV panel, boost converter, and maximum power point tack MPPT algorithm is developed. Three different conditions are simulated: 1) Uniform irradiation; 2) Sudden changing; 3) Partial shading. Results showed that fuzzy controller successfully find MPP for all different weather conditions studied. FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected to sudden changes and partial shading in irradiation.

KEYWORDS:

  • Fuzzy Logic Controller
  • Maximum Power Point
  • Photovoltaic System
  • Partial Shading

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

Figure 1. Schematic diagram of PV system with MPPT.

EXPECTED SIMULATION RESULTS:

 

Figure 2. P-V characteristics at different irradiations.

Figure 3. P-V characteristics when partial shading from 1000 to 600 Watt/m2.

Figure 4. Output of fuzzy at1000 Watt/m2.

Figure 5. Output of fuzzy controller. (a) Full shading from 600 to 300 Watt/m2; (b) Full shading from 700 to 400 Watt/m2; (c) Full shading from 900 to 400 Watt/m2; (d) Increasing shading from 300 to 800 Watt/m2.

Figure 6. Comparison between fuzzy and P & O partial shading (partial shading 1000 to 800 Watt/m2).

CONCLUSION:

 In this study, FLC has been developed to track the maximum power point of PV system. PV panel, boost converter with FLC connected to a resistive load has been simulated using Matlab/Simulink. Simulation results have been compared to nominal power values. The proposed system showed its ability to reach MMP under uniform irradiation, sudden changes of irradiation, and partial shading. Simulation results have shown that using FLC has great advantages over conventional methods. It is found that Fuzzy controller always finds the global MPP. It is found that fuzzy logic systems are easily implemented with minimal oscillations with fast convergence around the desired MP

 REFERENCES:

 [1] Devabhaktuni, V., Alam, M., Reddy Depuru, S.S.S., Green II, R.C., Nims, D. and Near, C. (2013) Solar Energy: Trends and Enabling Technologies. Renewable and Sustainable Energy Reviews, 19, 555-556. http://dx.doi.org/10.1016/j.rser.2012.11.024

[2] Bataineh, K.M. and Dalalah, D. (2012) Optimal Configuration for Design of Stand-Alone PV System. Smart Grid and Renewable Energy, 3, 139-147. http://dx.doi.org/10.4236/sgre.2012.32020

[3] Bataineh, K. and Dalalah, D. (2013) Assessment of Wind Energy Potential for Selected Areas in Jordan. Journal of Renewable Energy, 59, 75-81.

[4] Bataineh, K.M. and Hamzeh, A. (2014) Efficient Maximum Power Point Tracking Algorithm for PV Application under Rapid Changing Weather Condition. ISRN Renewable Energy, 2014, Article ID: 673840. http://dx.doi.org/10.1155/2014/673840

[5] International Energy Agency (2010) Trends in Photovoltaic Applications. Survey Report of Selected IEA Countries between 1992 and 2009. http://www.ieapvps.org/products/download/Trends-in Photovoltaic_2010.pdf

Maximum Power Point

An Efficient Modified CUK Converter with Fuzzy based Maximum Power Point Tracking Controller for PV System

ABSTRACT:

To improve the performance of photovoltaic system a modified cuk converter with Maximum Power Point Tracker (MPPT) that uses a fuzzy logic control algorithm is presented in this research work. In the proposed cuk converter, the conduction losses and switching losses are reduced by means of replacing the passive elements with switched capacitors. These switched capacitors are used to provide smooth transition of voltage and current. So, the conversion efficiency of the converter is improved and the efficiency of the PV system is increased. The PV systems use a MPPT to continuously extract the highest possible power and deliver it to the load. MPPT consists of a dc-dc converter used to find and maintain operation at the maximum power point using a tracking algorithm. The simulated results indicate that a considerable amount of additional power can be extracted from photovoltaic module using a proposed converter with fuzzy logic controller based MPPT

KEYWORDS:

 modified Cuk Converter

Photovoltaic System

Maximum Power Point Tracker

Fuzzy Logic Controller

 SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:

 image001

Figure 1: Simulation diagram for the proposed converter

EXPECTED SIMULATION RESULTS:

 image002

(a)

image003

(b)

image004

(c)

Figure 2: Output of Solar Irradiation at 500 watts / m2 (a)

Current, (b) Voltage, (c) Power

image005

(a)

image006

(b)

image007

(c)

Figure 3: Output of Solar Irradiation at 1000 watts / m2 (a)

Current, (b) Voltage, (c) Power

CONCLUSION:

The proposed modified cuk converter was simulated in MATLAB simulation platform and the output performance was evaluated. Then, the mode of operation of proposed converter was analyzed by the different solar irradiation level. From that, output current, voltage and power were considered. For evaluating the output performance, the proposed modified cuk converter output was tested with PV system. From the testing results, the output power of the modified converter efficiency and the efficiency deviation were analyzed. The analyses showed that the proposed modified cuk converter was better when compared to conventional cuk converter and boost converter. Experimental setup has been done to prove the effectiveness of the proposed system.

REFERENCES:

  1. Singh R & Sood Y R, Transmission tariff for restructured Indian power sector with special consideration to promotion of renewable energy sources, IEEE Region 10 Conference, TENCON, (2009), 1 – 7.
  2. Xia Xintao & Xia Junzi, Evaluation of Potential for Developing Renewable Sources of Energy to Facilitate Development in Developing Countries, Asia-Pacific Power and Energy Engineering Conference (APPEEC), (2010), 1 – 3.
  3. Hosseini R & Hosseini N & Khorasanizadeh H, An experimental study of combining a photovoltaic system with a heating system, World Renewable Energy Congress, 8 (2011), 2993-3000.
  4. Shakil Ahamed Khan & Md. Ismail Hossain, Design and Implementation of Microcontroller Based Fuzzy Logic Control for Maximum Power Point Tracking of a Photovoltaic System, IEEE International Conference on Electrical and Computer Engineering, Dhaka, (2010), 322-325.
  5. Pradeep Kumar Yadav A, Thirumaliah S & Haritha G, Comparison of MPPT Algorithms for DC-DC Converters Based PV Systems, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 1 (2012), 18-23.

Grid-Connected PV Array with Supercapacitor Energy Storage System for Fault Ride Through

ABSTRACT:

A fault ride through, power management and control strategy for grid integrated photovoltaic (PV) system with supercapacitor energy storage system (SCESS) is presented in this paper. During normal operation the SCESS will be used to minimize the short term fluctuation as it has high power density and during fault at the grid side it will be used to store the generated power from the PV array for later use and for fault ride through. To capture the maximum available solar power, Incremental Conductance (IC) method is used for maximum power point tracking (MPPT). An independent P-Q control is implemented to transfer the generated power to the grid using a Voltage source inverter (VSI). The SCESS is connected to the system using a bi-directional buck boost converter. The system model has been developed that consists of PV module, buck converter for MPPT, buck-boost converter to connect the SCESS to the DC link. Three independent controllers are implemented for each power electronics block. The effectiveness of the proposed controller is examined on Real Time Digital Simulator (RTDS) and the results verify the superiority of the proposed approach.

KEYWORDS:

  1. Active and reactive power control
  2. Fault ride through
  3. MPPT
  4. Photovoltaic system
  5. RTDS Supercapacitor
  6. Energy storage

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

image001

Fig.1. Grid connected PV system with energy storage

 EXPECTED SIMULATION RESULTS:

 image002

Fig.2. Grid voltage after three phase fault is applied

image003

Fig.3. PV array power PPV with SCESS and with no energy storage

image004

Fig.4. Grid active power Pg for a three phase fault with and without energy storage

image005

Fig.5.SCESS power PSC for the applied fault on the grid side

image006

Fig.6. Grid reactive power Qg during three phase fault

image007

Fig.7. DC link voltage for the applied fault

image008

Fig.8. PV array voltage VPV during three phase fault

image009

Fig.9. MPPT output voltage Vref for the applied fault

CONCLUSION:

This paper presents grid connected PV system with supercapacitor energy storage system (SCESS) for fault ride through and to minimize the power fluctuation. Incremental conductance based MPPT is implemented to track the maximum power from the PV array. The generated DC power is connected to the grid using a buck converter, VSI, buck-boost converter with SCESS. The SCESS which is connected to the DC link controls the DC link voltage by charging and discharging process. A P-Q controller is implemented to transfer the DC link power to the grid. During normal operation the SCESS minimizes the fluctuation caused by change in irradiation and temperature. During a grid fault the power generated from the PV array will be stored in the SCESS. The SCESS supplies both active and reactive power to ride through the fault. RTDS based results have shown the validity of the proposed controller.

REFERENCES:

[1] T. Esram, P.L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,” IEEE Transaction on Energy Conversion, vol.22, no.2, pp.439-449, June 2007

[2] J. M. Enrique, E. Durán, M. Sidrach-de-Cardona, and J. M. Andújar,“Theoretical assessment of the maximum power point tracking efficiency of photovoltaic facilities with different converter topologies,” Sol. Energy, vol. 81, no. 1, pp. 31–38, Jan. 2007.

[3] W. Xiao, N. Ozog, and W. G. Dunford, “Topology study of photovoltaic interface for maximum power point tracking,” IEEE Trans. Ind. Electron., vol. 54, no. 3, pp. 1696–1704, Jun. 2007.

[4] J. L. Agorreta, L. Reinaldos, R. González, M. Borrega, J. Balda, and L. Marroyo, “Fuzzy switching technique applied to PWM boost converter operating in mixed conduction mode for PV systems,” IEEE Trans. Ind. Electron., vol. 56, no. 11, pp. 4363– 4373, Nov. 2009.

[5] A.Schneuwly, “Charge ahead [ultracapacitor technology and applications]”, IET Power Engineering Journal, vol.19, 34-37, 2005.

 

Modeling and Simulation of a Stand-alone Photovoltaic System

 

 ABSTRACT:

In the future solar energy will be very important energy source. More than 45% of necessary energy in the world will be generated by photovoltaic module. Therefore it is necessary to concentrate our forces in order to reduce the application costs and to increment their performances. In order to reach this last aspect, it is important to note that the output characteristic of a photovoltaic module is nonlinear and changes with solar radiation and temperature. Therefore a maximum power point tracking (MPPT) technique is needed to track the peak power in order to make full utilization of PV array output power under varying conditions. This paper presents two widely-adopted MPPT algorithms, perturbation & observation (P&O) and incremental conductance (IC). These algorithms are widely used in PV systems as a result of their easy implementation as well as their low cost. These techniques were analyzed and their performance was evaluated by using the Matlab tool Simulink.

 

KEYWORDS:

  1. Photovoltaic system
  2. MPPT
  3. Perturbation and Observation
  4. Incremental conductance

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image002

Fig. 1. Block diagram of the stand-alone PV system.

CIRCUIT DIAGRAM

image004

Fig. 2. Model of the photovoltaic module

image006

Fig. 3. Schematic diagram of a DC Buck-Boost converter.

 EXPECTED SIMULATION RESULTS:

 image008

Fig. 4. Output current of PV module

image010

Fig. 5. Output voltage of PV module

image012

Fig. 6 Output power of PV module

image014

Fig. 7. Output current of MPPT+DC-DC converter

image016

Fig. 8. Output voltage of MPPT+DC-DC converter

image018

Fig. 9. Output power of MPPT+DC-DC converter

image020

Fig 10 : PV-Output power with and without MPPT+DC-DC converter

image022

Fig. 11. Output current of MPPT+DC-DC converter

image024

Fig. 12. Output voltage of MPPT+DC-DC converter

image026

Fig. 13. Output power of MPPT+DC-DC converter

image028

Fig. 14. PV-Output power with and without MPPT+DC-DC converter

CONCLUSION:

In this work, we presented a modeling and simulation of a stand-alone PV system. One-diode model for simulation of PV module was selected; Buck-Boost converter is studied and applied to test the system efficiency. Two Maximum Power Point Tracking techniques, P&O and IC, are presented and analyzed. The proposed system was simulated using the mathematical equations of each component in Matlab/Simulink. The simulation analysis shows that P&O method is simple, but has considerable power loss because PV module can only run in oscillation way around the maximum power point. IC method has more precise control and faster response, but has correspondingly higher hardware requirement. In practice, in order to achieve maximum efficiency of photovoltaic power generation, a reasonable and economical control method should be chosen. The following of this work is based on optimizing the performance of PV modules and stand-alone systems using more efficient algorithms to minimize the influence of the meteorological parameters on the PV energy production.

 REFERENCES:

[1] A.KH. Mozaffari Niapour, S. Danyali, M.B.B. Sharifian, M.R. Feyzi, “Brushless DC motor drives supplied by PV power system based on Zsource inverter and FL-IC MPPT controller”, Energy Conversion and Management 52, pp. 3043–3059, 2011.

[2] Reza Noroozian, Gevorg B. Gharehpetian, “An investigation on combined operation of active power filter with photovoltaic arrays”, International Journal of Electrical Power & Energy Systems, Vol. 46, Pages 392-399, March 2013.

[3] N. Femia, D. Granozio, G. Petrone, G. Spaguuolo, and M. Vitelli, “Optimized one-cycle control in photovoltaic grid connected applications”, IEEE Trans. Aerosp. Electron. Syst., Vol. 42, pp. 954- 972, 2006.

[4] T. L. Kottas, Y. S. Boutalis, and A. D. Karlis, “New maximum power point tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive net-work”, IEEE Trans. Energy Conv., Vol. 21, pp. 793–803, 2006.

[5] Mohamed A. Eltawil, Zhengming Zhao, “MPPT techniques for photovoltaic applications”, Renewable and Sustainable Energy Reviews, Vol. 25, P. 793-813, 2013.