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

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.

Resistive Load.

Figure 13. Pwm SignalVersus The Motor Input Voltage From The Pv

Module.

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 outstan.

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