# An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method For Grid-Connected PV Systems BTech/Mtech Final Year Electrical Projects

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

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 :

• 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

• 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

• 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

• 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

• 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.