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A new MPPT design using ISFLA algorithm and FLC to tune the member functions under different environmental conditions

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Abstract

Fluctuations in the output power of photovoltaic (PV) under climate changes such as variations in temperature and radiation is an important challenge for these resources. Therefore, it is very important to keep the output power of solar systems constant without any fluctuation at their maximum power point in the event of climate change. The aim of this paper is to suggest a maximum power point tracking (MPPT) method to cancel the output power oscillation of PV systems in severEe weather conditions, especially under radiation and temperature changes. In order to find the optimal parameters of the MPPT controller, the improved shuffled frog-leaping algorithm (ISFLA) and fuzzy controller are used. In addition, to fine-tune the member functions (MFs) of FLC, the combination of the fuzzy logic controller (FLC) and the ISFLA algorithm are employed. The ISFLA is an effective solution to cope with the stochastic behavior of the PV system under changing the radiation and ambient temperature. A storage system is also used to provide more stability and reliability for the system. Simulation results show that the recommended scheme provides excellent tracking efficiency from 98.1 to 99.6%. The case study under partial shading conditions also confirms the 16% improvement in the efficiency of the proposed method and more stability compared to the conventional P&O MPPT controller.

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Enquiries about data availability should be directed to the authors.

Abbreviations

R s :

Series resistance (Ω)

R sh :

Shunt resistance (Ω)

I ph :

Photocurrent of the cell (A)

n :

P–n junction ideality factor

I PVO :

Reverse saturation current (A)

K :

Boltzmann constant (1.38 × 10–23 J/K)

q :

Electronic charge (1.602 × 10–19C)

T :

Cell temperature (Kelvin)

I MP :

Maximum current

VMP :

Maximum voltage

P Max :

Maximum power

V OC :

Open-circuit voltage

I SC :

Short-circuit current

N P :

Number of parallel cells

N S :

Number of series cells

U m :

Maximum voltage magnitude of u

ω :

Angular frequency

u d and u q :

Grid voltage in the dq frame

i d and i q :

Inverter current in the dq frame

L:

Filter inductance

v d and v q :

Control voltages in the dq frame

E :

Error at sample time k (input of FLC)

CE:

Change in error at sample time k (input of FLC)

D :

Duty cycle (output of FLC)

Dj:

Center of max–min method composition at the output MF

V PV :

Voltage of boost converter

I PV :

Input current of boost converter

P PV (k):

Power of the PV system

\(X_{w}^{\mathrm{new}}\) :

Location of the weakest member in current position

D :

Vector of members’ mutation

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Funding

This study was not funded any institution and organization.

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Authors and Affiliations

  1. Jiangsu Vocational College of Electronics and Information, Huai′an, 223033, Jiangsu, China

    Guo Aihua & Xu Yihan

  2. Solar Energy and Power Electronic Co.,Ltd, Tokyo, Japan

    Kengo Suzuki

Authors
  1. Guo Aihua
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  2. Xu Yihan
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  3. Kengo Suzuki
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Corresponding author

Correspondence to Xu Yihan.

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Appendix A

Appendix A

PV Model

$$ {\text{P}}_{{{\text{Max }} = }} {9}0{\text{ W}} {\text{V}}_{{{\text{OC}}}} = {22}.{\text{32 V}} {\text{I}}_{{{\text{SC}}}} = {5}.{\text{24 A}} {\text{I}}_{{{\text{MP}} = }} {4}.{\text{94 A}} $$

PQ Model

$$ {\text{K}}_{{{\text{pVdc}}}} = { 3}.{9} {\text{K}}_{{{\text{iVdc}}}} = { 6}.{3} {\text{K}}_{{{\text{pId}}}} = { 5}.{1} {\text{K}}_{{{\text{iId}}}} = {323} {\text{K}}_{{{\text{pIq}}}} = { 5}.{1} {\text{K}}_{{{\text{iIq}}}} = { 321} $$

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Aihua, G., Yihan, X. & Suzuki, K. A new MPPT design using ISFLA algorithm and FLC to tune the member functions under different environmental conditions. Soft Comput 27, 1511–1531 (2023). https://doi.org/10.1007/s00500-022-07452-7

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