DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI

Hakan Işıker; Kadir Abacı

doi:10.17780/ksujes.1770702

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DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI

Abstract

Bu çalışmada, optimal yük (güç) akışı (OYA) probleminin doğrusal olmayan ve dışbükey olmayan yapısını etkin biçimde çözmek için ilk kez Hipopotam Optimizasyon (HO) algoritması OYA’ya uyarlanmış ve çoklu değişkenlere özgü sınırlar için modifiye edilmiştir. Orijinal HO’nun tekil sınır yaklaşımı, geliştirilen sınır_kontrolü fonksiyonu ile her kontrol değişkenine özgü alt–üst limitleri gözetebilecek şekilde genişletilmiştir. Keşif, savunma ve sömürü fazlarının dengeli etkileşimi hızlı yakınsama ve yerel minimumlardan kaçış sağlamaktadır. Önerilen yöntem yakıt maliyeti ve aktif güç kaybını eşitlik ve eşitsizlik kısıtları altında optimize etmektedir. IEEE 14 baralı sistemde başlangıç yakıt maliyeti 842,34 $/h’den 828,1560 $/h’ye düşürülmüş; SKH, PSOGSA, MSG-HS, MPSO ve PSO-ANN algoritmalarına karşı 1,184–6,204 $/h aralığında ek iyileşme elde edilmiştir. Türkiye 22 baralı sisteminde de Gradient ve ABC tabanlı yöntemlere kıyasla hem maliyet hem aktif kayıp hedeflerinde üstün sonuçlar elde edilmiştir. HO'nun diğer modern algoritmalara kıyasla daha hızlı yakınsadığını ve daha kararlı sonuçlar ürettiğini ortaya koymaktadır. Bulgular, modifiye HO’nun OYA için etkin, sağlam ve ölçeklenebilir bir alternatif sunduğunu göstermektedir.

Keywords

OPTIMAL POWER FLOW USING A NEW HIPPOPOTAMUS OPTIMIZATION ALGORITHM INSPIRED BY NATURE

Abstract

This study presents the first adaptation of the Hippopotamus Optimization (HO) algorithm to the optimal power flow (OPF) problem in order to effectively address its nonlinear and non-convex structure, and modifies it to handle variable-specific heterogeneous bounds. The original single-bound approach of HO is extended through a customized boundary_control function so that each control variable can respect its own lower and upper limits. The balanced interaction of the exploration, defense, and exploitation phases enables fast convergence and avoidance of local minima. The proposed method optimizes fuel cost and active power loss under equality and inequality constraints. On the IEEE 14-bus system, the initial fuel cost is reduced from 842,34 $/h to 828,1560 $/h, achieving an additional improvement of 1,184–6,204 $/h over SKH, PSOGSA, MSG-HS, MPSO, and PSO-ANN. On the Turkish 22-bus system, it also attains superior results for both cost and active loss targets compared with Gradient-based and ABC-based methods. This demonstrates that HO converges more rapidly and produces more stable results in comparison to other contemporary algorithms. The findings demonstrate that the modified HO is an effective, robust, and scalable alternative for OPF.

Keywords

References

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Details

Primary Language

Turkish

Subjects

Electrical Energy Transmission, Networks and Systems, Power Plants

Journal Section

Research Article

Authors

Hakan Işıker ^*
0000-0002-6465-8480
Türkiye

Kadir Abacı
0000-0001-5627-0032
Türkiye

Publication Date

December 3, 2025

Submission Date

August 22, 2025

Acceptance Date

October 27, 2025

Published in Issue

Year 2025 Volume: 28 Number: 4

DOI

https://doi.org/10.17780/ksujes.1770702

IZ

https://izlik.org/JA93WY48CM

Cite

RIS / Bibtex

APA

Işıker, H., & Abacı, K. (2025). DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(4), 2000-2013. https://doi.org/10.17780/ksujes.1770702

AMA

1.Işıker H, Abacı K. DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI. KSU J. Eng. Sci. 2025;28(4):2000-2013. doi:10.17780/ksujes.1770702

Chicago

Işıker, Hakan, and Kadir Abacı. 2025. “DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 28 (4): 2000-2013. https://doi.org/10.17780/ksujes.1770702.

EndNote

Işıker H, Abacı K (December 1, 2025) DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 28 4 2000–2013.

IEEE

[1]H. Işıker and K. Abacı, “DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI”, KSU J. Eng. Sci., vol. 28, no. 4, pp. 2000–2013, Dec. 2025, doi: 10.17780/ksujes.1770702.

ISNAD

Işıker, Hakan - Abacı, Kadir. “DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 28/4 (December 1, 2025): 2000-2013. https://doi.org/10.17780/ksujes.1770702.

JAMA

1.Işıker H, Abacı K. DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI. KSU J. Eng. Sci. 2025;28:2000–2013.

MLA

Işıker, Hakan, and Kadir Abacı. “DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, vol. 28, no. 4, Dec. 2025, pp. 2000-13, doi:10.17780/ksujes.1770702.

Vancouver

1.Hakan Işıker, Kadir Abacı. DOĞADAN ESİNLENEN YENİ BİR HİPOPOTAM OPTİMİZASYON ALGORİTMASI İLE OPTİMAL YÜK AKIŞI. KSU J. Eng. Sci. 2025 Dec. 1;28(4):2000-13. doi:10.17780/ksujes.1770702

Cited By

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Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

https://doi.org/10.17780/ksujes.1883002