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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi The Asian Journal of Technology Management (AJTM) JURNAL NASIONAL TEKNIK ELEKTRO ZERO : Jurnal Sains, Matematika dan Terapan INTEGER: Journal of Information Technology JMPM: Jurnal Matematika dan Pendidikan Matematika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Pengabdian Masyarakat Asia
Vivi Aida Fitria
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Mathematics Other

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Orca Predation Algorithm as an Innovative Solution for IEEE 30 Bus Vivi Aida Fitria; Zahratul Laily Binti Edaris; Azwar Riza Habibi; Lilis Widayanti
JURNAL NASIONAL TEKNIK ELEKTRO Vol 14, No 3: November 2025
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v14n3.1296.2025

Abstract

The effective operation of the IEEE 30 Bus power system requires economic dispatch optimization to minimize production costs, align energy supply with demand, and ensure system stability. This economic dispatch problem is complex due to its non-linear characteristics, interdependence between generators, and the need to combine cost minimization with power loss reduction. Conventional optimization techniques often struggle to find global solutions, easily get stuck in local optima, and require significant computational time. This study introduces the Orca Predation Algorithm (OPA) as a new approach to address these challenges. Inspired by the hunting behavior of orcas, OPA balances exploration and exploitation through two distinct phases: pursuit and attack. Evaluated on the IEEE 30-Bus system using power loss computation with coefficient B, the algorithm ensures that generator output power allocation meets demand at the lowest cost. OPA's performance is comprehensively compared with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Bat Algorithm. The results consistently show that OPA achieves the lowest total cost of $772,754 while maintaining superior system stability and effectively minimizing power losses among the evaluated algorithms. These findings highlight the significant potential of OPA to enhance energy management and advance power system optimization.
Co-Authors A.N. Afandi Adriani Kala’lembang Afiyah, S. Nurul Afiyah, S. Nurul Aripriharta - Azwar Riza Habibi, Azwar Riza Budi Santoso Kala'lembang, Adriani Khadiki, Mohammad Rizan Lilis Widayanti Nira Rusanti Siti Nurul Afiyah Suastika Yulia Riska Sulistyo, Danang Arbian Titania Dwi Andini Yudistira Arya Sapoetra Zahratul Laily Binti Edaris