# A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

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## Abstract

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## 1. Introduction

## 2. MPPT Algorithms for WECS

#### 2.1. Conventional IPC Based MPPT Algorithms for WECS

#### 2.1.1. TSR MPPT Algorithm

#### 2.1.2. OT MPPT Algorithm

#### 2.1.3. PSF MPPT Algorithm

#### 2.2. Conventional DPC Based MPPT Algorithms for WECS

#### 2.2.1. Conventional P&O MPPT Algorithm

#### 2.2.2. Conventional INC MPPT Algorithm

#### 2.2.3. Conventional ORB MPPT Algorithm

#### 2.3. Modified Conventional MPPT Algorithms for WECS

#### 2.3.1. Modified Optimum Torque (OT) MPPT Algorithm

#### 2.3.2. Modified PSF MPPT Algorithm

#### 2.3.3. Modified INC MPPT Algorithm

#### 2.3.4. Modified P&O MPPT Algorithms

- Fixed step sizes: A fixed amplitude of the step size is employed to perturb the control variable while carrying out the tracking procedure.
- Variable step sizes: Step sizes of varying amplitudes are employed, with a unique step size for each region.
- Adaptive step sizes: The step size employed for perturbation is finalized depending on the variation in the general objective function at each operating point.
- Hybrid step sizes: A combination of two different generated step sizes while MPP tracking is employed. Figure 16a–d portrays the P&O algorithm-based categories of step sizes that are generated while carrying out the tracking process. Table 5 summarizes the P&O method-based generated step sizes, and Table 6 summarizes the references for modified MPPT algorithms. Finally, Figure 17 shows the classification of P&O algorithms for WECS.

#### 2.4. Smart MPPT Algorithms

#### 2.4.1. Fuzzy Logic Controller Based MPPT Algorithm

#### 2.4.2. Neural Network Based MPPT Algorithm

#### 2.4.3. Smart Sensorless MPPT Algorithms

#### 2.4.4. Multi-Variable Perturb and Observe MPPT Algorithms

#### 2.5. Hybrid MPPT Algorithms

#### 2.5.1. P&O Based Hybrid MPPT Algorithms

#### 2.5.2. Optimization Algorithms Based Hybrid MPPT Algorithms

## 3. Discussion

## 4. Trends and Future Scope

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Abbreviations

WT | Wind Turbine |

WECS | Wind energy conversion system |

MPP | Maximum power point |

MPPT | Maximum power point tracking |

P&O | Perturb and observe |

VAWT | Vertical axis wind turbine |

HAWT | Horizontal axis wind turbine |

VSWT | Variable speed wind turbine |

FSWT | Fixed speed wind turbine |

SCIG | Squirrel cage induction generator |

DFIG | Doubly fed induction generator |

PMSG | Permanent magnet synchronous generator |

FRT | Fault ride through |

IPC | Indirect power control |

DPC | Direct power control |

TSR | Tip speed ratio |

PSF | Power signal flow |

OT | Optimal torque |

INC | Incremental conductance |

ORB | Optimal relation based |

NN | Neural network |

ANN | Artificial neural network |

FLC | Fuzzy logic control |

PID | Proportional integral derivative |

MVPO | Multi variable perturb and observe |

CPO | Conventional perturb and observe |

MPO | Modified perturb and observe |

CS | Cuckoo search |

PSO | Particle swarm optimization |

ACO | Ant colony optimization |

TLBO | Teaching learning based optimization |

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**Figure 1.**Globally installed wind power capacity. Reused with permission from ref. [3]. Copyright 2021 Elesevier.

**Figure 2.**Grid tied WECS general configuration. Reused with permission from ref. [3]. Copyright 2021 Elsevier.

**Figure 3.**Relation between ${C}_{p}$ and TSR. Reused with permission from ref. [23]. Copyright 2019 Elesevier.

**Figure 4.**WECS operating regions. Reused with permission from ref. [24]. Copyright 2019 Elesevier.

**Figure 5.**Characteristics of Wind Turbine Power under optimal values of $\lambda $ opt and ${C}_{popt}$. Reused with permission from ref. [23]. Copyright 2019 Elsevier.

**Figure 11.**Concept of working of CPO MPPT algorithm. Reused with permission from ref. [3]. Copyright 2021 Elsevier.

**Figure 12.**Problem of tracking MPP under varying speeds of the wind. Reused with permission from ref. [3]. Copyright Elsevier 2021.

**Figure 16.**P&O algorithm-based types of step sizes generated. Reused with permission from ref. [3]. Copyright 2021 Elsevier.

**Figure 17.**Classification of P&O algorithm. Reused with permission from ref. [3]. Copyright 2021 Elsevier.

Features of the MPPT Algorithm | TSR | PSF | OT |
---|---|---|---|

Efficiency | High efficiency | Moderate efficiency | High efficiency |

Complexity | Less | Less | Less |

Convergence speed | Higher | Higher | Higher |

Oscillations at MPP | No | No | No |

Prior knowledge | Not needed | Needed | Needed |

Memory requirement | No | Yes | No |

Sensors for wind speed measurement | Yes | Yes | No |

Parameter sensitivity | Yes | Yes | Yes |

Cost | Very high | Moderate | Moderate |

Online updating | No | No | No |

Performance under fluctuating wind speed | Moderately fair | Moderately fair | Moderately fair |

Type of Algorithm | Reference | Remarks |
---|---|---|

TSR | [52] | TSR algorithm is compared with the OT algorithm and TSR is found to provide a faster response to higher fluctuations in the wind speeds but suffers from the issue of greater fluctuations in the output. |

TSR | [55] | A technique is proposed for improvement in the efficiency of the TSR and OT methods. |

TSR | [34] | A review of different MPPT methods is presented. TSR algorithm requires speed sensors and hence suffers from the issue of higher cost. |

OT | [55] | A technique is proposed for improvement in the efficiency of the TSR and OT methods. |

OT | [66] | Some of the drawbacks of OT algorithm are discussed. |

OT | [52] | A comparison of the OT algorithm is conducted with the TSR algorithm and it reveals that OT provides an improved response in terms of power smoothing and power extraction. |

PSF | [32] | A review of several algorithms is presented. The PSF algorithm provides higher efficiency and faster response but has greater complexity. |

PSF | [34] | A review of different MPPT methods is presented. PSF algorithm requires speed sensors and knowledge of the parameters of the turbine and hence suffers from the issue of higher complexity. |

Features of the MPPT Algorithm | CPO | INC | ORB |
---|---|---|---|

Efficiency | Low | Low | Moderate |

Complexity | Simple | Simple | Simple |

Convergence speed | Slow | Slow | Medium |

Oscillations at MPP | Yes | Yes | No |

Prior knowledge | Not needed | Not needed | Not needed |

Memory requirement | No | No | Yes |

Need of sensors for measuring wind speed | Not needed | Not needed | Not needed |

Parameter sensitivity | No | No | Yes |

Cost | Moderate | Moderate | High |

Online updating | Yes | Yes | No |

Performance under fluctuating wind speed | Moderately fair | Moderately fair | Moderately fair |

Type of Algorithm | Reference | Remarks |
---|---|---|

CPO | [36] | A review of several MPPT algorithms is presented and the basic working concepts of these algorithms are described. The advantages of the CPO algorithm such as ease of implementation and no requirement of the sensors are listed. |

CPO | [72] | Several MPPT algorithms are reviewed and the advantages and disadvantages of each of them are described. CPO being sensor less, is cheaper but suffers from the issue of lower efficiency for fluctuating wind speeds. |

CPO | [40] | The problems in the CPO algorithm are addressed by the proposed novel peakdetection technique. It eliminates the trade-off between the efficiency and speed. |

ORB | [75] | A sensorless technique to extract maximum power from WECS is presented. |

ORB | [68] | Several MPPT algorithms are discussed and reviewed.The drawbacks and advantages of ORB algorithm are also discussed. |

ORB | [84] | The features, advantages and disadvantages of the CPO and the ORB algorithms are discussed and a new algorithm which is a combination of the two is presented. |

INC | [68] | Several MPPT algorithms are discussed and reviewed. The drawbacks and advantages of INC algorithm are also discussed. |

INC | [74] | Two different boost converter topologies are used and compared by implementing the INC algorithm. |

Generated Step Size Type | Reference | Remarks |
---|---|---|

Fixed step size | [42,109,110,111] | Challenging to decide the step size used for perturbation, and significant oscillation of the MPP is observed near the MPP. |

Variable step size | [23,24,89,112,113] | The oscillations around the MPP and higher tracking time are well addressed, although the step size procurement strategy results in higher complexity. |

Adaptive step size | [48,69,76,114] | Depending on the definite objective function, accurate clarification of the relation among the control variables, and wind speed, the step sizes are varied. The objective function can be dependent on multiple constants. Accurate tuning of these constants needs to be conducted by the process of complex competition analysis. |

Hybrid step size | [115,116] | Step sizes of different types are generated. Their operation order and their activation need accurate designing and add to the complexity. |

Type of Algorithm | Reference | Remarks |
---|---|---|

Modified OT | [81] | A sensor less modification in the OT algorithm is presented. |

Modified OT | [33] | A review of different MPPT algorithms is presented and the modification in the OT algorithm is also mentioned. |

Modified PSF | [33] | A review of different MPPT algorithms is presented and the modification in the PSF algorithm is also mentioned. |

Modified PSF | [89] | An Intelligent algorithm for extracting maximum power from WECS is presented. |

Modified INC | [92] | An ANN based modified INC algorithm for photovoltaic systems is presented. |

Modified PO | [93] | A modified version of INC algorithm is presented for a PMSG micro-WT. |

Modified PO | [3] | A review of C PO and MPO MPPT algorithms is presented. |

Modified PO | [23] | A modular sector MPO algorithm that eliminates the drawbacks of the CPO algorithm is presented. |

Modified PO | [24] | A MPO algorithm for a variable speed WECS is investigated for a five-phase large scale system. |

Modified PO | [38] | An MPO algorithm that employs variable step sizes and makes use of model reference adaptive control, which helps eliminate the issues of CPO, is presented. |

Features of the MPPT Algorithm | FLC | NN | Sensor Less | MVPO | Other |
---|---|---|---|---|---|

Efficiency | Higher | Higher | Moderate | Moderate | Depends |

Complexity | Higher | Higher | Higher | Higher | Moderately complex |

Speed of convergence | Medium | Medium | Medium | Slow | Medium |

Oscillations at MPP | Do not occur | Do not occur | Depends | Occur | Depends |

Prior knowledge | Needed | Needed | Not needed | Not needed | Depends |

Memory | Required | Required | Required | Not Required | Depends |

Need of sensors for wind speed measurement | Depends | Depends | Not needed | Not needed | Depends |

Parameter sensitivity | Depends | Depends | Not found | Not found | Depends |

Cost | Higher | Higher | Lower | Lower | Medium |

Online updating | Required | Required | Depends | Required | Depends |

Performance under fluctuating wind speed | Higher | Higher | Higher | Moderate | Moderate |

Type of Algorithm | Reference | Remarks |
---|---|---|

Smart | [132] | MPPT algorithm based on FLC that makes use of the master-slave FLC training mode is presented. |

Smart | [130] | An intelligent MPPT algorithm based on ANN is presented. |

Smart | [37] | A review of MPPT algorithms is presented and the MVPO algorithm is discussed. |

PO based Hybrid | [149] | A combination of FLC with CPO is employed that provides improved tracking of the MPP. |

PO based Hybrid | [150] | The self-tuning P&O is combined with the ORB algorithm and this combination provides better MPP tracking. |

PO based Hybrid | [151] | The combination of MPO and PSF is employed to improve the efficiency. |

PO based Hybrid | [152] | A combination of ANN and PSF is employed which results in better accuracy. |

Optimization based Hybrid | [153] | The combination of ORB and (PSO) is employed to form the hybrid MPPT algorithm. PSO is used in the first phase to search the optimum coefficient and in the second phase, ORB is used. This method yields higher efficiency. |

Features of the MPPT Algorithm | Hybrid |

Efficiency | Very high |

Complexity | Medium |

Convergence speed | Fast |

Oscillations at MPP | Depends |

Prior knowledge | Not needed |

Memory requirement | No |

Wind speed sensor | Depends |

Parameter sensitivity | No |

Cost | Moderate |

Online updating | Depends |

Performance under fluctuating wind speed | Good |

$\beta $ | Pitch angle |

${C}_{p}$ | Power coefficient |

${P}_{m}$ | Mechanical power (watts) |

$\lambda $ | Tip speed ratio |

${\lambda}_{opt}$ | Optimum tip speed ratio |

${V}_{cutin}$ | Cut-in wind speed (m/s) |

${V}_{cutout}$ | Cut-out wind speed (m/s) |

${V}_{rated}$ | Rated wind speed (m/s) |

${C}_{popt}$ | Optimal power coefficient |

${P}_{opt}$ | Optimal power (watts) |

${\omega}_{m}$ | Mechanical angular speed of the turbine (rad/s) |

${V}_{dc}$ | DC voltage (volts) |

${P}_{m}^{opt}$ | Optimal mechanical power (watts) |

$\omega $ | Rotor angular speed (rad/s) |

${\omega}_{ref}$, ${\omega}_{opt}$ | Reference rotor speed (rad/s) |

${T}_{m}$ | Mechanical torque ( N.m.) |

${T}_{em}$ | Electromagnetic torque ( N.m.) |

${T}_{m}^{opt}$ | Optimum mechanical torque (N.m.) |

${V}_{wind}$ | Wind speed (m/s) |

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**MDPI and ACS Style**

Pande, J.; Nasikkar, P.; Kotecha, K.; Varadarajan, V.
A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems. *J. Mar. Sci. Eng.* **2021**, *9*, 1187.
https://doi.org/10.3390/jmse9111187

**AMA Style**

Pande J, Nasikkar P, Kotecha K, Varadarajan V.
A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems. *Journal of Marine Science and Engineering*. 2021; 9(11):1187.
https://doi.org/10.3390/jmse9111187

**Chicago/Turabian Style**

Pande, Jayshree, Paresh Nasikkar, Ketan Kotecha, and Vijayakumar Varadarajan.
2021. "A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems" *Journal of Marine Science and Engineering* 9, no. 11: 1187.
https://doi.org/10.3390/jmse9111187