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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Mechatronics, Electrical Power, and Vehicular Technology Jurnal Teknik Elektro Proceeding of the Electrical Engineering Computer Science and Informatics Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Multitek Indonesia : Jurnal Ilmiah Community Development Journal: Jurnal Pengabdian Masyarakat JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Jurnal Nasional Teknik Elektro dan Teknologi Informasi POLIGRID SinarFe7 Energy: Jurnal Ilmiah Ilmu-ilmu Teknik
Khusnul Hidayat
Universitas Muhammadiyah Malang
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health

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An Epistemological Analysis of Metaheuristic MPPT Performance for Photovoltaic Systems under Partial Shading Conditions Hidayat, Khusnul; Afandi, Arif Nur; Patmanthara, Syaad
ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK 2025: ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK (Special Issue on Engineering Paradigm 2025 Edition)
Publisher : Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/energy.si2025.258

Abstract

Metaheuristic-based maximum power point tracking algorithms are widely used in photovoltaic systems to address nonlinear and multi-peak characteristics under partial shading conditions. However, many reported performance claims rely mainly on numerical simulation and therefore require cautious interpretation. This study presents a simulation-based comparative and epistemological analysis of Particle Swarm Optimization and Differential Evolution for photovoltaic maximum power point tracking. Both algorithms are implemented in an identical buck converter-based photovoltaic framework to ensure fair comparison. Performance is evaluated under uniform irradiance and partial shading conditions using convergence time and tracked power as evaluation metrics. The results show that under uniform irradiance, both algorithms reliably converge to the maximum power point with similar steady-state accuracy, while Particle Swarm Optimization converges faster. Under partial shading conditions, Particle Swarm Optimization consistently tracks the global maximum power point, whereas Differential Evolution shows occasional convergence failure or suboptimal tracking. From an epistemological standpoint, these findings constitute coherent and pragmatically useful model-based knowledge, while remaining provisional due to the absence of experimental validation.
Co-Authors A.N. Afandi Adji, Bima Septian Amrul Faruq Aqmal, Muhammad Bayanaka, Dzaky Darrell Cahyadi, Basri Nor Effendy, ME, Machmud Elmunsyah, Hakku Hasanah, Rini Nur Isnani Dzuhrina Izzan Silmi Aziz Laksono, Pranadi Sigit Dwi Lukman Hakim M. Irfan Machmud Effendy Machmud Effendy Machmud Effendy Machmud Effendy, ME Mardiayah, Nur Alif Mardiyah, Nur Alif Mardiyah, Nuralif Merinda Lestandy Mohammad Chasrun Hasani Muhamad Adam Alkhaidir Muhamad Adam Alkhaidir Noor Cahyadi, Basri Novendra Setyawan Nur Alif Mardiyah Nur Alif Mardiyah Nur Alif Mardiyah, Nur Alif Nuralif Mardiyah Nuralif Mardiyah Nuralif Mardiyah Nuralif, Nuralif Nurhadi Nurhadi Nurhadi, Nurhadi Prasojo, Fadillah Shanty Kusuma Dewi Siti Sendari Suyono, Hadi Syaad Patmanthara Syafaah, Lailis Syahputra, Rosyadi Nur Wahyu Dianto Pramana Zulfatman Zulfatman