MPPT Algorithm Based on Modified Human Psychology Optimization for PV System in Partial Shading Conditions

Putera, Rivaldi Dwi Syah; Efendi, Moh. Zaenal; Qudsi, Ony Asrarul

doi:10.1109/ies59143.2023.10242405

2023 International Electronics Symposium (IES) 2023

DOI: 10.1109/ies59143.2023.10242405

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MPPT Algorithm Based on Modified Human Psychology Optimization for PV System in Partial Shading Conditions

Rivaldi Dwi Syah Putera,

Moh. Zaenal Efendi,

Ony Asrarul Qudsi

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2024

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A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms

Fan,

Setianingrum,

Lian

et al. 2024

Energies

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This study presents a new approach for Maximum Power Point Tracking (MPPT) by combining the honey badger algorithm (HBA) with a Genetic Algorithm (GA). The integration aims to optimize photovoltaic (PV) system performance in partial shading conditions (PSCs). Initially, the HBA is utilized to explore extensively and identify potential solutions while avoiding local optima. If necessary, the GA is then employed to escape local optima through selection, crossover, and mutation operations. On average, this proposed method has a 40% improvement in tracking time and 0.77% in efficiency compared with the HBA. In a dynamic case, the proposed method achieves a 4.81% improvement compared to HBA.

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A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms

Fan,

Setianingrum,

Lian

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

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MPPT Algorithm Based on Modified Human Psychology Optimization for PV System in Partial Shading Conditions

Cited by 1 publication

References 20 publications

A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms

A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms

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