# A State-of-Art-Review on Machine-Learning Based Methods for PV
## 6 The Latest Research on MPPT in PV
\begin{table}
\begin{tabular}{p{42.7 pt} p{34.1 pt} p{34.1 pt}} \hline \hline
**Year** & **Reference** & **Notes** \\ \hline
2020 & [85] & A detailed comparison of classification and performance between six major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results. Each technique is compared in terms of algorithm structure, cost, complexity, platform, input parameters, tracking speed, oscillation accuracy, efficiency and their applications. The AI-based MPPT techniques are generally classified into fuzzy logic control (FLC), ANN, GA, swarm intelligence (SI), ML and other emerging techniques. \\ \hline
2020 & [86] & The presented study gives an extensive review of 23 MPPT techniques present in literature along with recent publications on various hardware design methodologies. MPPT classification is done into three categories, i.e., Classical, Intelligent and Optimisation depending on the tracking algorithm utilised. During uniform insolation, classical methods are highly preferred as there is only one peak in the P-V curve. The paper furnishes the hardware information of the particular technique by different authors performed in various platforms with their tracking speeds and efficiencies. In addition, the parameters of these techniques, their flowcharts and a clear explanation of MPPT algorithm implementation are explained in brief. The fundamental objective is to give ongoing innovation advancements in MPPT techniques. \\ \hline
2020 & [87] & The main MPPT techniques for PV systems are reviewed and summarized and divided into three groups according to their control theoretic and optimization principles: Traditional MPPT methods, MPPT methods based on intelligent control and MPPT methods under PSCs. In particular, the advantages and disadvantages of the MPPT techniques for PV systems under PSCs are compared and analyzed. \\ \hline
2020 & [88] & This paper reviews (extensively) the most used MPPT algorithms. They are classified into three groups: (1) direct, such as hill climbing, Perturb and Observe (P&O) and incremental conductance (INC); (2) indirect, namely fractional short-circuit current, Fractional Open-Circuit Voltage and pilot cell and (3); soft computing methods such as a Kalman filter, FLC, ANN, PSO, ant colony optimization (ACO), artificial bee colony (ABC), bat algorithm and hybrid PSO-FLC. The purpose of the presented review is to provide a general insight into various MPPT methods describing their principles of operations and highlighting their advantages and limitations. In addition, the suitable embedded board for the hardware implementation of each method is outlined; low-cost only embedded boards have been studied. \\ \hline
2019 & [89] & This study provides an extensive review of the current status of MPPT methods for PV systems which are classified into eight categories (methods based on mathematical calculations, constant parameters-based methods, measurement and comparison-based methods, trial and error based methods, numerical methods, intelligent prediction based methods and methods based on iterative in nature). The categorization is based on the tracking characteristics of the discussed methods. The novelty of this study is that it focuses on the key characteristics and 11 selection parameters of the methods to make a comprehensive analysis, which is not considered together in any review works so far. Again, the pros and cons, classification and immense comparison among them described in this study can be used as a reference to address the gaps for further research in this field. A comparative review in tabular form is also presented at the end of the discussion of each category to evaluate the performance of these methods, which will help in selecting the appropriate technique for any specific application. \\ \hline
2018 & [90] & The paper focuses mainly on a review of advancements of MPPT techniques of PV systems subjected to partial shading conditions (PSC) to help the users to make the right choice when designing their system. The choice of MPPT depends on several parameters such as the application, hardware availability, cost, convergence speed, precision, and system reliability. \\ \hline \hline \end{tabular}
\end{table}