Fast and improved PSO (FIPSO)‐based deterministic and adaptive MPPT technique under partial shading conditions

Imtiaz, Tabish; Khan, B.H.; Khanam, Nida

doi:10.1049/iet-rpg.2020.0039

Cited by 10 publications

(14 citation statements)

References 23 publications

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“…All of these MOAs have several problems, including extended convergence times, premature convergence, and particle stagnation at one of the LPs. The majority of recent studies on this subject have been proposed to overcome these challenges [13][14][15][16][17][18]. Still, additional efforts are needed in this sector to lower convergence time while maintaining GP tracking accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…Various strategies have been used in the literature to overcome the long convergence time problem. The majority of these studies are centered on making changes to current MOAs to capture the GP quicker [13][14][15][16][17][18]. To overcome the random aspect of the PSO in tracking the MPP of PV systems, a deterministic approach was used to modify it [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…The majority of these studies are centered on making changes to current MOAs to capture the GP quicker [13][14][15][16][17][18]. To overcome the random aspect of the PSO in tracking the MPP of PV systems, a deterministic approach was used to modify it [13,14]. The fundamental concept behind this approach is to replace the random values that should be multiplied by the acceleration factors to estimate particle velocity.…”

Section: Introductionmentioning

confidence: 99%

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Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems

Eltamaly¹

2023

Preprint

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Because of the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relationship between output power and array voltage has only one peak under uniform irradiance, whereas it has multiple peaks under partial shade circumstances (PSC). There is only one global peak (GP) and many local peaks (LPs), where the typical maximum power point trackers (MPPT) may become locked in one of the LPs, significantly reducing the PV system's generated power and efficiency. The metaheuristic optimization algorithms (MOAs) solved this problem, albeit at the expense of the convergence time, which is one of these algorithms' key shortcomings. Most MOAs attempt to lower the convergence time at the cost of the failure rate and the accuracy of the findings because these two factors are interdependent. To address these issues, this work introduces the dandelion optimization algorithm (DOA), a novel optimization algorithm. The DOA's convergence time and failure rate are compared to other modern MOAs in critical scenarios of partial shade PV systems to demonstrate the DOA's superiority. The results obtained from this study showed substantial performance improvement compared to other MOAs, where the convergence time is reduced to 0.4 s with zero failure rate compared to 0.9 s, 1.25 s, and 0.43 s for other MOAs under study. The optimal number of search agents in the swarm, optimal initialization of search agents, and optimal design of the dc-dc converter is introduced for optimal MPPT performance.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems

Eltamaly¹

2023

Preprint

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“…An ant‐colony‐based search in the initial stages of tracking followed by P&O method has been proposed in [23]. In such a hybrid approach, the global search ability of ant‐colony optimization (ACO) and local search capability of P&O method are integrated to yield faster and efficient convergence.…”

Section: Introductionmentioning

confidence: 99%

“…A large variety of these algorithms can be feasibly used to locate the GMPP. Some popular ones are particle swarm optimization (PSO) [10,22,23], ant colony [24], firefly algorithm (FA) [25], cuckoo search (CS) [26], artificial bee colony (ABC) [27], pattern search (PS) [28] and grey wolf optimization (GWO) [29,30].…”

Section: Introductionmentioning

confidence: 99%

Maximum power point tracking in partially shaded photovoltaic systems using grasshopper optimization algorithm

Tabar

Shahnazari

Heshmati

2022

IET Renewable Power Gen

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The P-V curve of photovoltaic (PV) arrays has several peaks under partial shading conditions (PSCs). Therefore, to extract maximum power, it is necessary to detect its global maximum power point (GMPP). The conventional maximum power point tracking (MPPT) algorithms are trapped in local maximum power point (LMPP) under PSCs. In this paper, a MPPT method based on grasshopper optimization algorithm (GOA) has been presented. A PV system has been implemented in Matlab/Simulink and different operating conditions have been investigated to compare the performance of the proposed method with two well-known grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms. Furthermore, an experimental setup has been developed to verify the efficiency of the proposed MPPT method. The simulation and experimental results confirmed the speed and accuracy of convergence compared to GWO and PSO algorithms.

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Design and Implementation of Type-3 Intuitionistic Fuzzy Logic MPPT Controller for PV Solar System: Comparative Study

Hamdy,

Ibrahim,

Abozalam

et al. 2024

ISA Transactions

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Fast and improved PSO (FIPSO)‐based deterministic and adaptive MPPT technique under partial shading conditions

Cited by 10 publications

References 23 publications

Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems

Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems

Maximum power point tracking in partially shaded photovoltaic systems using grasshopper optimization algorithm

Design and Implementation of Type-3 Intuitionistic Fuzzy Logic MPPT Controller for PV Solar System: Comparative Study

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