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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknik ITS IPTEK Journal of Proceedings Series JURNAL NASIONAL TEKNIK ELEKTRO JAVA Journal of Electrical and Electronics Engineering Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Marine Engineering Innovation and Research JAREE (Journal on Advanced Research in Electrical Engineering) SinarFe7 Sewagati Jurnal Rekayasa elektrika Mein: Journal of Mechanical, Electrical & Industrial Technology
Feby Agung Pamuji
Institut Teknologi Sepuluh Nopember
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : International Journal of Electrical and Computer Engineering

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Novel hybrid of marine predator algorithm-Aquila optimizer for droop control in DC microgrid Aribowo, Widi; Suryoatmojo, Heri; Pamuji, Feby Agung
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp3703-3715

Abstract

This study presents a hybrid method, namely the marine predator algorithm (MPA) and Aquila optimizer (AO). The proposed algorithm is named MAO. AO duplicated the existence of the Aquila bird in nature while hunting for prey while MPA was inspired by predators in marine animal life. Although AO is widely accepted, it has several disadvantages. This causes various weaknesses such as a weak exploitation phase and slow growth of the convergence curve. Thus, certain exploitation and exploration in conventional AO can be studied to achieve the best balance. The MPA demonstrates the capacity to deliver optimal design and statistically efficient outcomes. The proposed method used AO as the main algorithm. To measure the performance of the proposed method, this study depicted a comparison using the AO, MPA, and whale optimization algorithm (WOA) methods. This paper was evaluated the performance of MAO on twenty-one CEC2017 benchmark functions test and droop control performance on direct current (DC) microgrid. From the simulation, MAO shows superior convergence ability. The proposed method and its application to droop control was successfully implemented and implied a promising performance.
Co-Authors Adi Kurniawan Adityanugraha, Dimas Febry Alfani, Denny Aprilia Rahmayanti Ardyono Priyadi Arumsari, Nurvita Arumsari, Nurvita Aryani, Ni Ketut Daniar Fahmi, Daniar Dedet Candra Riawan Dibyo, Soe Hadwim Septiawan Herbert Innah Heri Suryoatmojo Hery Suryoatmojo I Made Yulistya Negara IGP Suta Wijaya Ksatria, Arief Budi Lystianingrum, Vita Mochamad Ashari Nadilah Laksmi Marahaini Nursalim ST MT Nurvita Arumsari Ontoseno Penangsang Pius Aditya Kurnia Ray Prasetiyono Hari Mukti Rahmawan, Hanif Adi Rayhan, Muhammad Faris Rezi Delfianti Rizqulloh, Mochamad Shofwan Ronny Mardiyanto, Ronny Rony Seto Wibowo Sjamsjul Anam Soe Dibyo Soedibyo Soedibyo Soedibyo Soedibyo Soedibyo Talitha Puspita Sari Vita Lystaningrum Budiharto Putri Vita Lystianingrum Wahyu Ardi Santosa Widi Aribowo Yurisqi, Muhammad Athariq Zamratul Fuadi