# Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Modeling of Solar Photovoltaic Cell

_{D}= diode voltage

_{o}= reverse saturation current

_{T}= thermal voltage

## 3. Flower Pollination Algorithm

_{best}after observing the output power against each one. Afterward, the produced pollens experience local or global pollination depending on the outcome of the comparison of a random number with probability switch “P” (P = 0.8, but can be varied) for each pollen and then sent to the converter to get a second P

_{best}. Equations for the local and global pollinations are presented nn Equations (3) and (4), respectively. Where “${X}_{i}^{t}$”, “${X}_{j}^{t}$”, and “${X}_{k}^{t}$” represent different pollens in iteration “t”, and the “ε” (epsilon) denotes the local search ε ∈ [0, 1]. Whereas, “L and λ” are the levy factor and standard gamma function). Repetition of the second iteration was conducted to complete the set of 25 P

_{best.}P

_{best}with the highest power is selected as a Global Best “G

_{best}”. A flowchart of the FPA algorithm is displayed in Figure 2.

_{V}) and current (d

_{I}), use the hit and trial method as shown in Equations (5) and (6). Where, I

_{PV}and V

_{PV}represent the current and voltage of the solar PV array, and k represents the iteration number.

## 4. Problem Formulation

## 5. Proposed Data Arrangement Technique

## 6. Simulation and Results

#### 6.1. S Solar Photovoltaic System

^{2}at 25 °C. The proposed algorithm will be compared with the conventional FPA at 2S PV system under constant and changing weather conditions at MPP tracking speed and efficiency.

^{2}, and the characteristic curve will generate a single MPP as shown in Figure 6. Tracking a single MPP is not a big deal. Here MPP occurs at 19.99 V, 3.001 A, and 60 Ws.

^{2}illumination, and the other gets 1000 W/m

^{2}as depicted in Figure 5. This shading disturbs the 2S-PV system and creates multiple peaks in the characteristic curve as shown in Figure 7 and Figure 8. Detecting the real MPP also called the global MPP (GMPP) is a bit difficult compared to the zero shading. Here the GMPP occurs at 21.61 V, 1.589 A, and 34.34 Ws.

^{2}) due to partial shading. Each module experiences a different illumination level. In this case, the two modules are receiving 800 W/m

^{2}and 500 W/m

^{2}as depicted in Figure 5. Strong shading disturbs the characteristic curve as shown in Figure 8. Here the GMPP occurs at 21.4 V, 1.586 A, and 33.94 Ws.

#### 6.2. S2P Solar Photovoltaic System

## 7. Discussion

## 8. Conclusions

## 9. Future Work

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**One Diode Model of PV cell [24].

**Figure 2.**Flowchart of FPA Algorithm [24].

**Figure 9.**Simulation Results for 2S PV System for Zero Shading. (

**A**) Flower Pollination Algorithm. (

**B**) OFPA.

**Figure 11.**Simulation Results for 2S Configuration under Strong PSC. (

**A**) FPA algorithm. (

**B**) OFPA algorithm.

**Figure 17.**Simulation Results for 2S2P Configuration under Zero PSC. (

**A**) FPA algorithm for Zero Shading. (

**B**) OFPA algorithm for Zero Shading.

**Figure 18.**Simulation Results for 2S2P Configuration under Weak PSC. (

**A**) FPA algorithm. (

**B**) OFPA Algorithm.

**Figure 19.**Simulation Results for 2S2P Configuration under Strong PSC. (

**A**) FPA algorithm. (

**B**) OFPA algorithm.

Partial Shading | MPPT Algorithms | Power Output (W) | Rated Power (W) | Efficiency (%) | Tracking Speed (s) | Improvement in Tracking Speed (%) |
---|---|---|---|---|---|---|

Zero Shading | FPA | 59.85 | 60 | 99.75 | 0.7537 | 85.4 |

OFPA | 59.85 | 99.75 | 0.1103 | |||

Weak Partial Shading | FPA | 34.27 | 34.34 | 99.8 | 0.7525 | 86 |

OFPA | 34.27 | 99.8 | 0.1055 | |||

Strong Partial Shading | FPA | 33.9 | 33.94 | 99.88 | 0.7541 | 86 |

OFPA | 33.9 | 99.88 | 0.1052 |

Partial Shading | Algorithms | Power Output (W) | Rated Power (W) | Efficiency (%) | Tracking Speed (s) | Improvement in Tracking Speed (%) |
---|---|---|---|---|---|---|

Zero Shading | FPA | 119.7 | 120 | 99.75 | 0.7648 | 86 |

OFPA | 120 | 100 | 0.1071 | |||

Weak Partial Shading | FPA | 68.16 | 68.67 | 99.26 | 0.7584 | 85.10 |

OFPA | 68.16 | 99.26 | 0.113 | |||

Strong Partial Shading | FPA | 67.22 | 67.88 | 99.02 | 0.7581 | 85.02 |

OFPA | 67.22 | 99.02 | 0.1128 |

Sr. No. | Parameters | P&O [27,28] | Fuzzy [29] | PSO [30] | FPA [24] | Ordered FPA | |
---|---|---|---|---|---|---|---|

Algorithms | |||||||

1 | Steady StateOscillations | High | Low | Zero | Zero | Zero | |

2 | Tracking Speed | Low | Adequate | Adequate | Fast | FASTEST | |

3 | ProceduralComplications | Less | High | Reasonable | Reasonable | Nil | |

4 | MemorizingNecessity | Few | Large | Few | Few | FEW | |

5 | ComputationalComplications | Zero | High | Average | Average | No | |

6 | Implementation | Cheap | Costly | Costly | Costly | Costly | |

7 | Performance in PSC | N/A | Good | Good | Good | EXCELLENT | |

8 | Module Dependent | Yes | Yes | No | No | No | |

9 | Efficiency | Fail | Low under PSC | Effective | Effective | Exciting | |

10 | Structure | Simple | Complex | Complex | Complex | Simple |

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**MDPI and ACS Style**

Awan, M.M.A.; Asghar, A.B.; Javed, M.Y.; Conka, Z.
Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System. *Sustainability* **2023**, *15*, 3332.
https://doi.org/10.3390/su15043332

**AMA Style**

Awan MMA, Asghar AB, Javed MY, Conka Z.
Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System. *Sustainability*. 2023; 15(4):3332.
https://doi.org/10.3390/su15043332

**Chicago/Turabian Style**

Awan, Muhammad Mateen Afzal, Aamer Bilal Asghar, Muhammad Yaqoob Javed, and Zsolt Conka.
2023. "Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System" *Sustainability* 15, no. 4: 3332.
https://doi.org/10.3390/su15043332