Maximum Power Point Tracking Technique Using Combined Perturb &amp; Observe and Owl Search Algorithms

Farhan, Alaa; Feilat, Eyad A.; Al‐Salaymeh, Ahmed

doi:10.1109/icecta48151.2019.8959738

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Hence, they can easily detect quarries' location in the search arena. Furthermore, time and intensity differences in sound wave arrival play a crucial role in estimating their distance to their prey, as illustrated in Figure 27 [81]. The owl search algorithm (OSA) simulates the owl's hunting method, i.e., relying on the hearing ability in the dark rather than sight to locate the prey.…”

Section: Usv Symbol Macro(s) Descmentioning

confidence: 99%

Meta-Heuristic Optimization Techniques Used for Maximum Power Point Tracking in Solar PV System

et al. 2021

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A critical advancement in solar photovoltaic (PV) establishment has led to robust acceleration towards the evolution of new MPPT techniques. The sun-oriented PV framework has a non-linear characteristic in varying climatic conditions, which considerably impact the PV framework yield. Furthermore, the partial shading condition (PSC) causes major problems, such as a drop in the output power yield and multiple peaks in the P–V attribute. Hence, following the global maximum power point (GMPP) under PSC is a demanding problem. Subsequently, different maximum power point tracking (MPPT) strategies have been utilized to improve the yield of a PV framework. However, the disarray lies in choosing the best MPPT technique from the wide algorithms for a particular purpose. Each algorithm has its benefits and drawbacks. Hence, there is a fundamental need for an appropriate audit of the MPPT strategies from time to time. This article presents new works done in the global power point tracking (GMPPT) algorithm field under the PSCs. It sums up different MPPT strategies alongside their working principle, mathematical representation, and flow charts. Moreover, tables depicted in this study briefly organize the significant attributes of algorithms. This work will serve as a reference for sorting an MPPT technique while designing PV systems.

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Section: Usv Symbol Macro(s) Descmentioning

confidence: 99%

Meta-Heuristic Optimization Techniques Used for Maximum Power Point Tracking in Solar PV System

et al. 2021

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“…Bio-inspired MPPT algorithms like the cuckoo search algorithm (CSA) [20], Flying Squirrel Search Optimization Strategy (FSSO) [21], and owl search algorithm (OSA) [22]. Overall, the recent Bio-Inspired Algorithm for MPPT brings significant advantages in terms of global optimization, adaptability, robustness, and parallel processing.…”

Section: Introductionmentioning

confidence: 99%

Energy Valley Optimizer (EVO) for Tracking the Global Maximum Power Point in a Solar PV System under Shading

Azad,

Sajid,

et al. 2023

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Incorporating bypass diodes within photovoltaic arrays serves to mitigate the negative effects of partial shading scenarios. These situations can lead to the appearance of multiple peaks in the performance of solar panels. Nevertheless, there are cases where conventional maximum power point tracking (MPPT) techniques could encounter inaccuracies, causing them to identify the highest power point within a specific area (the local maximum power point; LMPP) instead of the overall highest power point across the entire array (the global maximum power point; GMPP). Numerous methods based on artificial intelligence (AI) were proposed to address this issue; however, they frequently used cumbersome and unreliable methodologies. This research presents the energy-valley-optimizer-based optimization (EVO) technique, which is designed to efficiently and dependably tackle the issue of partial shading (PS) in detecting the maximum power point (MPP) for photovoltaic (PV) systems. The EVO algorithm enhances the speed of tracking and minimizes power output fluctuations during the tracking phase. Through the utilization of the Typhoon hardware-in-the-loop (HIL) 402 emulator, extensive validation of the proposed technique is conducted. The effectiveness of the suggested method is compared with the established cuckoo search algorithm for achieving maximum power point tracking (MPPT) within a photovoltaic (PV) system. This comparison takes place under equivalent conditions to ensure a fair performance evaluation.

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An Enhanced MPPT with Incremental Conductance and Owl Search Algorithm under Partial Shading

Altamimi

Jamleh

Feilat

et al. 2022

2022 International Conference on Smart Systems and Power Management (IC2SPM)

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Maximum Power Point Tracking Technique Using Combined Perturb & Observe and Owl Search Algorithms

Cited by 4 publications

References 18 publications

Meta-Heuristic Optimization Techniques Used for Maximum Power Point Tracking in Solar PV System

Meta-Heuristic Optimization Techniques Used for Maximum Power Point Tracking in Solar PV System

Energy Valley Optimizer (EVO) for Tracking the Global Maximum Power Point in a Solar PV System under Shading

An Enhanced MPPT with Incremental Conductance and Owl Search Algorithm under Partial Shading

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