E-ISSN 2414-6013 | ISSN 2411-9636
 

Technical Note
Online Published: 30 Mar 2024
 


A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions

Aiman Nouh, Alhasan Almalih, Moneer Faraj, Alhusayn Almalih, Faisal Mohamed.


Abstract
Solar energy has a significant role in meeting rising energy demand while reducing environmental impact. Solar radiation and temperature are important factors on which PV energy production depends, but its optimal operation point is influenced by variations in the aforementioned environmental factors. The nonlinear behavior of the solar system and the variable nature of environmental conditions make determining the optimal operation point difficult. To overcome these difficulties, maximum power point tracking (MPPT) finding techniques are used to extract the optimal power from the photovoltaic energy system. The behavior of MPPT varies for different weather conditions, such as partial shading conditions (PSC), and uniform irradiance conditions. Conventional techniques are simple, quick, and efficient for tracing the MPP quickly, but they are limited to uniform weather conditions. In addition, these techniques don't achieve the Global Maxima (GM) and mostly stay stuck at the Local Maxima (LM). The Meta-Heuristic techniques aid in finding the GM, but their primary disadvantage is that they take a longer time to trace the Global Maxima. This study addresses the problem by combining Cuckoo Search (CS) and Particle Swarm Optimization (PSO) algorithms, leading to a hybrid (CSPSO) technique to extract the global maximum (GM). To verify the effectiveness of the suggested technique, its performance is examined under three different irradiance patterns for different PV array configurations (such as 3S and 4S3P) through MATLAB simulation. The outcomes of CSPSO are compared with the prior well-known Meta-Heuristic techniques such as Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Crow Search Algorithm (CSA). The results show the suggested technique excels over other techniques in terms of accuracy, tracking efficiency, and tracking speed. The suggested technique is capable of tracking GMPP with an average efficiency of 99.925% and an average tracking time of 0.13 s in all shading patterns studied.

Key words: Cuckoo search (CS), particle swarm optimization (PSO), partial shading conditions (PSC).


 
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How to Cite this Article
Pubmed Style

Nouh A, Almalih A, Faraj M, Almalih A, Mohamed F. A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Sol. Energy Sustain. Dev.. 2024; 13(1): 114-132.

doi:10.51646/jsesd.v13i1.178



Web Style

Nouh A, Almalih A, Faraj M, Almalih A, Mohamed F. A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. https://www.jsesd.org/?mno=302658293 [Access: November 12, 2026].

doi:10.51646/jsesd.v13i1.178



AMA (American Medical Association) Style

Nouh A, Almalih A, Faraj M, Almalih A, Mohamed F. A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Sol. Energy Sustain. Dev.. 2024; 13(1): 114-132.


doi:10.51646/jsesd.v13i1.178



Vancouver/ICMJE Style

Nouh A, Almalih A, Faraj M, Almalih A, Mohamed F. A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Sol. Energy Sustain. Dev.. (2024), [cited November 12, 2026]; 13(1): 114-132.


doi:10.51646/jsesd.v13i1.178



Harvard Style

Nouh, A., Almalih, . A., Faraj, . M., Almalih, . A. & Mohamed, . F. (2024) A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Sol. Energy Sustain. Dev., 13 (1), 114-132.


doi:10.51646/jsesd.v13i1.178



Turabian Style

Nouh, Aiman, Alhasan Almalih, Moneer Faraj, Alhusayn Almalih, and Faisal Mohamed. 2024. A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Solar Energy and Sustainable Development, 13 (1), 114-132.


doi:10.51646/jsesd.v13i1.178



Chicago Style

Nouh, Aiman, Alhasan Almalih, Moneer Faraj, Alhusayn Almalih, and Faisal Mohamed. "A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions." Solar Energy and Sustainable Development 13 (2024), 114-132.


doi:10.51646/jsesd.v13i1.178



MLA (The Modern Language Association) Style

Nouh, Aiman, Alhasan Almalih, Moneer Faraj, Alhusayn Almalih, and Faisal Mohamed. "A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions." Solar Energy and Sustainable Development 13.1 (2024), 114-132. Print.


doi:10.51646/jsesd.v13i1.178



APA (American Psychological Association) Style

Nouh, A., Almalih, . A., Faraj, . M., Almalih, . A. & Mohamed, . F. (2024) A Hybrid of Meta-Heuristic Techniques Based on Cuckoo Search and Particle Swarm Optimizations for Solar PV Systems Subjected to Partially Shaded Conditions. Solar Energy and Sustainable Development, 13 (1), 114-132.


doi:10.51646/jsesd.v13i1.178