A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions

Wasim, Muhammad Shahid; Amjad, Muhammad; Habib, Salman; Abbasi, Muhammad Abbas; Bhatti, Abdul Rauf; Muyeen, S. M.

doi:10.1016/j.egyr.2022.03.175

Cited by 57 publications

(37 citation statements)

References 99 publications

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“…The researcher employs several MPPT approaches in the PV system. For detecting the Global Maximum Power Point (GMPP), P-V and I-V characteristics will be used [6,7].…”

Section: Introductionmentioning

confidence: 99%

Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions

et al. 2022

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Photovoltaic (PV) solar energy is a very promising renewable energy technology, as solar PV systems are less efficient because of climate conditions, temperature, and irradiance change. So, to resolve this problem, two PV topologies are used, i.e., centralized and distributed PV systems. The centralized technique is quicker than the distributed technique in terms of convergence speed and a faster power tracking approach. In the event of uniform irradiance, the centralized system also has the benefit of supplying superior energy, but in PS scenarios, a huge amount of energy is lost. However, the distributed approach requires current and voltage measurements at each panel, resulting in a massive data set. Nevertheless, in the event of shading circumstances, the distributed technique is highly effective because a modular level power electronics (MLPE) converter is used. While in a centralized PV system, there is only a single DC-DC converter for the whole PV system. In this research work, a DFO-based DC-DC converter is designed for modular level, with an ability to perform a rapid shutdown of the module under fire hazard conditions, troubleshooting, and monitoring of a module in a very efficient way. The robustness of the proposed MPPT DFO algorithm is tested with different techniques such as Cuckoo Search (CS), Fruit Fly Optimization (FFO), Particle swarm optimization (PSO), Incremental conductance (InC), and Perturb and observe(P&O) techniques. The proposed technique shows better results in terms of MPPT efficiency, dynamic responsiveness, and harmonics. Furthermore, the result of MLPE and the centralized system is verified by using the Helioscope with different inverter companies like SMA, Tigo, Enphase, Solar edge, and Huawei. The results prove that MLPE is a better option in the case of shading region for attaining the maximum power point.

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“…The researcher employs several MPPT approaches in the PV system. For detecting the Global Maximum Power Point (GMPP), P-V and I-V characteristics will be used [6,7].…”

Section: Introductionmentioning

confidence: 99%

Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions

et al. 2022

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“…The particle swarm optimization (PSO) algorithm was implemented for tracking the global MPP (GMPP) considering the PSCs (Charin et al, 2021). The applicatins of the evoluationary algorithms in improving the performance of MPPT had been significantly increasing (Ahmed et al, 2022;Fan and Ma, 2022;Lousuwankun and Jantharamin, 2022;Rajesh et al, 2022;Wasim et al, 2022). In (Kulaksız and Akkaya, 2012), a genetic algorithm was proposed for determining the number of neurons in a multilayer artificial neural network for MPPT in a PV system.…”

Section: Introductionmentioning

confidence: 99%

Hill Climbing Artificial Electric Field Algorithm for Maximum Power Point Tracking of Photovoltaics

Alanazi

Memon

et al. 2022

Front. Energy Res.

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In this paper, maximum power point tracking (MPPT) of a photovoltaic (PV) system is performed under partial shading conditions (PSCs) using a hill climbing (HC)–artificial electric field algorithm (AEFA) considering a DC/DC buck converter. The AEFA is inspired by Coulomb’s law of electrostatic force and has a high speed and optimization accuracy. Because the traditional HC method cannot perform global search tracking and instead performs local search tracking, the AEFA is used for a global search in the proposed HC-AEFA. The critical advantage of the HC-AEFA is that it is desirable performing local and global searches. The proposed hybrid method is implemented to derive an MPP by tuning the converter duty cycle, considering the objective function for maximizing the PV system extracted power. Its capability is evaluated and compared with well-known particle swarm optimization (PSO), considering standards, PSCs, and radiation changes conditions. The tracking efficiency for the most challenging shading pattern (third pattern) using the HC-AEFA, HC, AEFA and PSO is obtained at 99.93, 90.35, 98.85, 99.80%, respectively. The analysis of the population-based optimization process for different algorithms proved the HC-AEFA faster convergence at lower iterations than the other methods. So, the superiority of the proposed HC-AEFA subjected to different patterns is confirmed with higher tracking efficiency and global power peak, fewer fluctuations, higher convergence speed, and higher dynamic and Static-efficiency compared to the other methods.

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“…It is obtained a maximum load power despite variations in solar irradiation and wind speeds [2]- [7]. A great diversity of optimization methods has been adopted to track the photovoltaic panels and wind turbines powers [8]- [10]. The proposed strategy optimization is the fuzzy logic control (FLC) method and it is compared to perturb and observ (P&O) method.…”

Section: Introductionmentioning

confidence: 99%

Optimization, design and control of a photovoltaic/wind turbine/battery system in Mediterranean climate conditions

et al. 2022

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The goal of this study is to design and optimize a photovoltaic/wind turbine/batteries system. The application is made in the area of Bejaia (Algeria), a Mediterranean region where the solar and wind energy are extremely exploitable in this area due to its geographical location. The total incident energy approach was used to develop the device under consideration. To optimize power, the fuzzy logic control (FLC) is applied and to highlight the benefits of this maximum power point tracking (MPPT) strategy, it was compared to perturb and observe (P and O) method. A power management control has been applied. The findings from the three different days are displayed and analyzed to demonstrate the applicability of the suggested system. The examined system is assessed using the Homer software to demonstrate the best feasible integration of the several sources at the Bejaia location. There has been an increase in renewable power, which is one of the study's key novelty and objectives, so less stress on batteries in a PV/wind system. This is owing to the suggested accurate sizing procedure and to the FLC algorithm. The findings of the suggested study under various solar irradiation and wind speed velocity profiles are presented to demonstrate its applicability.

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A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions

Cited by 57 publications

References 99 publications

Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions

Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions

Hill Climbing Artificial Electric Field Algorithm for Maximum Power Point Tracking of Photovoltaics

Optimization, design and control of a photovoltaic/wind turbine/battery system in Mediterranean climate conditions

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