An Enhanced EPP-MPPT Algorithm With Modified Control Technique in Solar-Based Inverter Applications: Analysis and Experimentation

ABSTRACT:

In this paper, an optimized adaptive perturb-perturb (PP) based algorithm is presented. The modified algorithm has a predictive variable step size calculated through the Newton-Raphson procedure, making its programming effort simple. This combination merits fewer calculations, faster response time and can simply be applied effectively in both bright and shady conditions. The algorithm is developed as a C language code linked to the PSIM simulation representing a typical photovoltaic module system. The proposed algorithm's simulation results proved faster tracking time response with a reduced error than the standard system. The tracking time is ten times faster than the MPPT method and reduced by 10 seconds in a 100 kHz converter. The measured error is less than 0.03% at steady state. A modified control modulation scheme is blended with the algorithm as well. Experimental results are provided using a 10Wprototype for

telecom applications and another 300W practical micro inverter as a proof of concept, and in agreement with both modelling and simulation results. In addition, the results validate the viability of the proposed algorithm in the cases of linear (resistor) and non-linear (brushless motor) loads. The PSIM and experimental setups are provided to prove the concept of the proposed methodology, which is critical for universal solar-inverter applications.

KEYWORDS:

1.      DC-DC converters

2.      MPPT improved algorithms

3.      Rural water pump applications

4.      Solar energy

5.      Standalone rural inverters

6.      Telecom distribution

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

 Figure 1. Block Diagram For The Complete System.

EXPECTED SIMULATION RESULTS:

Figure 2. The Output Power With The Conventional P&O Method.

 

Figure 3. (A) Power Tracking For A Resistive Data Chip Load. (B) The Optimum Power Versus The Output Tracking Power For Load And Light Intensity Of 1000 W/M2 And Varying The Temperature From 20 _C To 30 _C.

Figure 4. The Optimum Power Versus The Output Tracking Power At Resistive Inductive (Motor) Load And Varying Light Intensity From 800 W/M2 To 1000 W/M2 And Temperature Of 25 _C.

Figure 5. (A) The Traditional Mppt Algorithm Has A Slow Tracking Time. (B) The Epp-Mppt Tracking Time For The Proposed Algorithm. (C) Curve Translating The Voltage Across The Dc-Link In A Pv-Ev-Grid System For A Variable Irradiation.

 CONCLUSION:

 This paper provided a (i) novel adaptive numerical EEP-MPPT algorithm with a new EPP modified algorithm and a predictive variable step size calculated using Newton-Raphson method, (ii) This combination gives outstanding results; the steady-state error has been reduced from 8% in MPPT and 1.2% in incremental conductance to 0.063 % with a tracking time of 1 _s instead of 10 _s, (iii) The system proves to have the ability to adjust itself in a very short period of time to track the new operating point for maximum power, within acceptable error, (iv) The new control proves excellent results under normal and shaded conditions as well. This will optimize the overall output power and add to the reliability, which is paramount for this industry, (v) PSIM simulation and experimental measurements are presented using different linear/non-linear loads; pure resistive load, and a brushless DC motor, (vi) Experimental results have verified the proof of concept, ensuring that the proposed numerical and control algorithms are working efficiently and precisely under motor loading conditions, (vii) In addition, the controller's ability to recover the output voltage waveform under faulty conditions, proves compliant to the IEEE 519 standard. These advantages prove a reliable solution for this research problem.

 REFERENCES:

[1] M. A. A. M. Zainuri, M. A. M. Radzi, A. C. Soh, and N. A. Rahim, ``Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost DC_DC converter,'' IET Renew. Power Gener., vol. 8, no. 2, pp. 183_194, Mar. 2014.

[2] C. R. Sullivan and M. J. Powers, ``A high-ef_ciency maximum power point tracker for photovoltaic arrays in a solar-powered race vehicle,'' in Proc. IEEE Power Electron. Spec. Conf., Jun. 1993, pp. 574_580.

[3] K. Hussein, I. Muta, T. Hoshino, and M. Osakada, ``Maximum photovoltaic power tracking: An algorithm for rapidly changing atmospheric conditions,'' IEE Proc. Gener., Transmiss. Distrib., vol. 142, no. 1, pp. 59_64, 1995.

[4] S. H. Hosseini, A. Farakhor, and S. K. Haghighian, ``Novel algorithm of MPPT for PV array based on variable step Newton-Raphson method through model predictive control,'' in Proc. 13th Int. Conf. Control, Autom. Syst. (ICCAS). Gwangju, South Korea: Kimdaejung Convention Center, Oct. 2013, pp. 1577_1582.

[5] Y. Chen, Y. Kang, S. Nie, and X. Pei, ``The multiple-output DC_DC converter with shared ZCS lagging leg,'' IEEE Trans. Power Electron., vol. 26, no. 8, pp. 2278_2294, Aug. 2011.

An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems

 ABSTRACT:

Recently, solar energy has been intensively employed in power systems, especially using the photovoltaic (PV) generation units. In this regard, this paper proposes a novel design of a fuzzy logic based algorithm for varying the step size of the incremental conductance (INC) maximum power point tracking (MPPT) method for PV. In the proposed method, a variable voltage step size is estimated according to the degree of ascent or descent of the power-voltage relation. For this purpose, a novel unique treatment is proposed based on introducing five effective regions around the point of maximum PV power. To vary the step size of the duty cycle, a fuzzy logic system is developed according to the locations of the fuzzy inputs regarding the five regions. The developed fuzzy inputs are inspired from the slope of the power-voltage relation, namely the current-voltage ratio and its derivatives whereas appropriate membership functions and fuzzy rules are designed. The benefit of the proposed method is that the MPPT efficiency is improved for varying the step size of the incremental conductance method, thanks to the effective coordination between the proposed fuzzy logic based algorithm and the INC method. The output DC power of the PV array and the tracking speed are presented as indices for illustrating the improvement achieved in MPPT. The proposed method is verified and tested through the simulation of a grid-connected PV system model. The simulation results reveal a valuable improvement in static and dynamic responses over that of the traditional INC method with the variation of the environmental conditions. Further, it enhances the output dc power and reduce the convergence time to reach the steady state condition with intermittent environmental conditions.

KEYWORDS:

1.      Maximum power point tracking

2.      Fuzzy logic

3.       Incremental conductance

4.      PV system

5.      Dynamic responses

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Figure 1. An Overview Of The Grid-Connected Pv Array With The

Proposed Flc Based Variable Step Inc Mppt Method.

EXPECTED SIMULATION RESULTS:

Figure 2. Testing The Flc Based Algorithm Through The Step Variations

Of (A) The Solar Irradiance (G) (B) The Cell Temperature (Tc ).

Figure 3. Comparisons Of Flc Based And Fixed Duty Cycle Of The Inc

Mppt Method (Fixed Step=0.0003 S) For Step Variations Of G And Tc :

(a)     For The Step Change At 0.8 S; (B) For The Step Change At 1 S.

Figure 4. The Output Dc Power Comparison When Applying The

Conventional Fixed Step Inc Method, The Fixed Step P&O Method And The

(a)     Flc Based Variable Step Inc Method For Mppt.

 

Figure 5. The Difference Between The Output Dc Power When Applying

The Flc Based Algorithm And These Of The Conventional Fixed Step Inc And

(a)     P&O Methods For Mppt.

 

Figure 6. Proximate Views Of The Output Dc Power Comparison When

Applying The Flc Based Algorithm And These Of The Conventional Fixed

Step Inc And P&O Methods For Mppt: (A) From 0.2 To 0.5 S; (B) From

(a)     0.7 To 0.95 S; (C) From 1.2 To 1.4 S; (D) From 1.4 To 1.5 S.

 

Figure 7. Testing The Flc Based Algorithm Through The Ramp Variations

(a)    Of: (A) The Solar Irradiance (G); (B) The Cell Temperature (Tc ).

 

CONCLUSION:

The PV system efficiency is a crucial index to evaluate the performance of grid-connected PV systems where the MPPT performance is a keynote. The conventional fixed step INC method for MPPT is widely used but it lacks some accuracy and speed of convergence. To tackle this issue, the proposed improvement of the INC method is introduced to employ a fuzzy logic algorithm to generate a variable step voltage increment or decrement, which is executed through decrement or increment of the duty cycle of the dc-dc boost converter. The voltage (duty cycle) step has five different sizes according to proposed five regions of the fuzzy inputs. The simulation results demonstrate that the proposed FLC based variable step INC method for MPPT enhances the output dc power and reduce the time of convergence to reach the steady state when switching of the environmental conditions. To illustrate the efficacy of the proposed MPPT method, it is compared to two conventional methods. The first one is the INC method with fixed step sizes of 0.0003 s and 0.001 s. The second method is the conventional P&O method with fixed step of 0.0003 s. In future work, the experimental application of the proposed FLC variable step method will be studied in a grid-connected PV systems.

REFERENCES:

[1] N. Priyadarshi, F. Azam, A. K. Bhoi, and A. K. Sharma, ``Dynamic operation of grid-connected photovoltaic power system,'' in Advances in Greener Energy Technologies. Singapore: Springer, 2020, pp. 211_218.

[2] H. Rezk, M. Aly, M. Al-Dhaifallah, and M. Shoyama, ``Design and hardware implementation of new adaptive fuzzy logic-based MPPT control method for photovoltaic applications,'' IEEE Access, vol. 7, pp. 106427_106438, 2019.

[3] A. S. Bayoumi, R. A. El-Sehiemy, K. Mahmoud, M. Lehtonen, and M. M. F. Darwish, ``Assessment of an improved three-diode against modified two-diode patterns of MCS solar cells associated with soft parameter estimation paradigms,'' Appl. Sci., vol. 11, no. 3, p. 1055, Jan. 2021, doi: 10.3390/app11031055.

[4] B. Subudhi and R. Pradhan, ``A comparative study on maximum power point tracking techniques for photovoltaic power systems,'' IEEE Trans. Sustain. Energy, vol. 4, no. 1, pp. 89_98, Jan. 2013.

[5] D. Sera, L. Mathe, T. Kerekes, S. V. Spataru, and R. Teodorescu, ``On the Perturb-and-Observe and incremental conductance MPPT methods for PV systems,'' IEEE J. Photovolt., vol. 3, no. 3, pp. 1070_1078, Jul. 2013.

Adaptive Hybrid Generalized Integrator Based SMO for Solar PV Array fed Encoderless PMSM Driven Water Pump

 ABSTRACT:

The encoder influences reliability and cost of permanent magnet synchronous motor (PMSM) operated solar water pump (WP). It is even sensitive to electromagnetic noise and temperature, which thereby reduces its accuracy. To overcome these problems, an encoderless PMSM control by using adaptive hybrid generalized integrator (AHGI) based sliding mode observer (SMO) for the solar WP system is presented in this paper. The widely used low pass filter based SMO produces phase-shift, attenuation and dominant lower order harmonics (DLOH). This decreases the position estimation accuracy. Besides, the need for tracking dynamic system frequency further exacerbates its performance. The developed AHGI structure eliminates these drawbacks and provides an accurate estimate of position over a wide speed range. A harmonic decoupling network, a hybrid generalized integrator and an adaptive frequency tracker constitute AHGI, which respectively performs dominant harmonic signal generation, DLOH elimination and frequency tracking. The improvement in behavior of AHGI over the existing methods is analyzed by transfer functions, Bode plots and back electromotive force helices. Meanwhile an incremental conductance algorithm for PV array maximum power control is used. The developed structure is experimentally validated on a laboratory prototype and a comparison with the existing methods is also made.

 KEYWORDS:

1.      Solar water pump

2.      Solar photovoltaic (PV) array

3.      Encoderless control

4.      PMSM

5.      Adaptive hybrid generalized integrator (AHGI)

6.      Adaptive frequency tracker (AFT)

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

Fig. 1 Encoderless PMSM driven solar WP system with developed AHGI based SMO for rotor position estimation

 EXPECTED SIMULATION RESULTS:

Fig. 2 Experimental performance of the solar WP system with the developed AHGI based SMO (a) Starting at 1000 W/m2, (b) Starting at 500 W/m2, (c),(d) continuous running at 1000 W/m2, (e),(f) continuous running at 500 W/m2

 

Fig. 3 Experimental dynamic performance of solar WP system with the developed AHGI based SMO for irradiation variation from (a),(b),(c) 500 W/m2 to 1000 W/m2; (d),(e),(f) 1000 W/m2 to 500 W/m2

CONCLUSION:

An adaptive hybrid generalized integrator (AHGI) based SMO for encoderless operation of PMSM driving a solar WP has been presented here. It has been found that the developed AHGI structure has produced a satisfactory estimate of both the speed and rotor position through selective elimination of DLOH along with the removal of phase-shift and fundamental attenuation. The improved performance of AHGI structure over the LPF, SOGI and FOGI has been demonstrated by the transfer function and the frequency response. Besides, the superiority of AHGI has also been shown through both the simulated and experimental performances of back EMF and rotor position. Even the detailed experimental performance of system with the AHGI at continuous running and starting under dynamics of solar irradiation have been obtained. It has been found that the developed AHGI structure has produced a satisfactory estimate of αβ-components of back-EMF even under dynamics. It has also been shown experimentally that the developed AHGI successfully tracks the variations in the speed. A stable and reasonably satisfying performance of the system has been observed under all operating conditions. The developed AHGI structure can be used with any PMSM system for rotor position and speed estimation.

REFERENCES:

[1] M. Rezkallah, A. Chandra, M. Tremblay and H. Ibrahim, “Experimental Implementation of an APC With Enhanced MPPT for Standalone Solar Photovoltaic Based Water Pumping Station,” IEEE Trans. Sustain. Energy, vol. 10, no. 1, pp. 181-191, Jan. 2019.

[2] M. E. Haque, Y. C. Saw and M. M. Chowdhury, “Advanced Control Scheme for an IPM Synchronous Generator-Based Gearless Variable Speed Wind Turbine,” IEEE Trans. Sustain. Energy, vol. 5, no. 2, pp. 354- 362, April 2014.

[3] C. Lascu and G. Andreescu, “PLL Position and Speed Observer With Integrated Current Observer for Sensorless PMSM Drives,” IEEE Trans. Ind. Electron., vol. 67, no. 7, pp. 5990-5999, July 2020.

[4] S. Shukla and B. Singh, “Reduced Current Sensor Based Solar PV Fed Motion Sensorless Induction Motor Drive for Water Pumping,” IEEE Trans. Ind. Informat., vol. 15, no. 7, pp. 3973-3986, July 2019.

[5] A. Andersson and T. Thiringer, “Motion Sensorless IPMSM Control Using Linear Moving Horizon Estimation With Luenberger Observer State Feedback,” IEEE Trans. Transport. Electrific., vol. 4, no. 2, pp. 464- 473, June 2018.

Active Fault Current Limitation for Low-Voltage Ride-Through of Networked Microgrids

ABSTRACT:

With the continuously increasing penetration of networked microgrids (MGs) on the local utility grid (UG), MGs face the challenge to avoid increasing system fault currents during low-voltage ride-through (LVRT). To solve this challenge, an active fault current limitation (AFCL) method is proposed with three parts: 1) a novel phase angle adjustment (PAA) strategy is conducted to relieve the impact of MGs output fault current on system fault current; 2) the current injection (CI) strategy for LVRT is formulated to fit the function of PAA; 3) a novel converter current generation (CCG) strategy is developed to achieve a better voltage support ability by considering network impedance characteristics. The proposed AFCL method is applied to the back-to-back converter, as a connection interface between MGs and UG. Extensive tests and pertinent results have verified the improvements of proposed AFCL method with better LVRT performance, while the networked MGs output fault current does not increase the amplitude of system fault current.

KEYWORDS:

1.      Networked microgrids

2.      Back-to-back converter

3.      Low-voltage ride-through

4.      Fault current limitation

SOFTWARE: MATLAB/SIMULINK

 SCHEMATIC DIAGRAM:

Fig. 1. Structure of networked MGs and the corresponding fault current flow.

EXPECTED SIMULATION RESULTS:

Fig. 2. The PCC voltage of MG#1 and MG#2 with existing FCL method in [23]-[25].

Fig. 3. The PCC voltage of MG#1 and MG#2 with proposed AFCL method.

Fig. 4. The MG#1 and MG#2 fault current with existing FCL method in [23]-[25].

Fig. 5. The MG#1 and MG#2 fault current with proposed AFCL method.

Fig. 6. The MG#1 and MG#2 power injected by existing method in [23]-[25].

 

Fig. 7. The MG#1 and MG#2 power injected by proposed AFCL method.

Fig. 8. DC voltage of BTB converter with proposed/existing FCL in [23]-[25].

Fig. 9. The UG fault current with proposed/existing FCL in [23]-[25].

 

Fig. 10. The system fault current with existing FCL method in [23]-[25].

Fig. 11. The system fault current with proposed AFCL method.

 

CONCLUSION:

Under the UG fault condition, in view of the high-level system fault current during the LVRT of networked MGs, an AFCL method is proposed to avoid monotonically increasing system fault currents during the LVRT of networked MGs. In this method, in order to improve the voltage control ability of LVRT, the CCG strategy is proposed by embedding the network impedance characteristics. Then, in order to achieve a better fault current limitation by relieving the impact of MGs fault current, the PAA strategy is proposed with considering voltage’s phase angle difference from UG and MGs to fault branch. Meanwhile, the CI strategy is conducted to fit the feature of PAA. Numerous simulation results have validated the improvements of the proposed AFCL method with a successful LVRT, meanwhile, the networked MGs fault current does not increase the system fault current amplitude. Considering the fields with a high proportion of sensitive load, the BTB converter is widely used for the PCC connection point of DGs and MGs to provide high power quality. To reduce the fault current level, the AFCL method can be applied to the BTB converter, and can be also used to the other inverter products, such as wind and photovoltaic inverter, AC/DC microgrids, and HVDC transmission system.

REFERENCES:

[1] Q. Zhou, M. Shahidehpour, et al, “ Distributed Control and Communication Strategies in Networked Microgrids,” IEEE Communications Surveys & Tutorials, vol. 22, no. 4, pp. 2586-2633, Fourth quarter 2020.

[2] X. Zhao, J. M. Guerrero, et al, “Low-Voltage Ride-Through Operation of Power Converters in Grid-Interactive Microgrids by Using Negative-Sequence Droop Control,” IEEE Trans. Power Electron., vol. 32, no. 4, pp. 3128–3142, April 2017.

[3] I. Sadeghkhani, M. E. H. Golshan, A. Mehrizi-Sani, J. M. Guerrero, “Low-voltage ride-through of a droop-based three-phase four-wire grid-connected microgrid,” IET Gener. Transm. Distrib., vol. 12, no. 8, pp. 1906–1914, 2018.

[4] Y. He, M. Wang and Z. Xu, “Coordinative Low-Voltage-Ride-Through Control for the Wind-Photovoltaic Hybrid Generation System,” IEEE Journal of Emerging & Selected Topics in Power Electronics, vol. 8, no. 2, pp. 1503–1514, Jun. 2020.

[5] Y. Yang, F. Blaabjerg, and Z. Zou, “Benchmarking of grid fault modes in single-phase grid-connected photovoltaic systems,” IEEE Trans. Ind. Appl., vol. 49, no. 5, pp. 2167–2176, Sep./Oct. 2013.