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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Buletin Ilmiah Sarjana Teknik Elektro International Journal of Robotics and Control Systems
Abualigah, Laith
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Chaotic red-tailed hawk algorithm to optimize parameter power system stabilizer Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Aljohani, Abeer; Sabo, Aliyu
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp3536-3545

Abstract

This article introduces a recently created adaptation of the red-tailed hawk (RTH) algorithm. The proposed approach is a modified version of the original RTH algorithm, incorporating chaotic elements to enhance its integrity and performance. The RTH algorithm emulates the hunting behavior of the red-tailed hawk. This article demonstrates the adjustment of the power system stabilizer using the suggested technique in a case study involving a single-machine system. The suggested method was validated by benchmarking against known functions and evaluating its performance on a single-machine system in terms of transient responsiveness. The essay employs the original RTH algorithm as a means of comparison. The simulation results demonstrate that the proposed technique exhibits promising performance.
Power System Stabilizer Optimization Based on Modified Black‑Winged Kite Algorithm Aribowo, Widi; Abualigah, Laith; Oliva, Diego; B, Nur Vidia Laksmi; Amaliah, Fithrotul Irda; Aziz, As’ad Shidqy; Zangana, Hewa Majeed
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.14669

Abstract

This article presents a Modified Method for tuning the parameters of a power system stabilizer (PSS). This article suggests a different approach that modifies the Black Kite Algorithm (BKA). The Black Kite (BKA) method is inspired by the migratory and predatory habits of the black kite. BKA combines the Leader and Cauchy mutation strategies to improve the algorithm's capacity for global search and convergence rate. This article includes comparative simulations of the PSS objective function and transient response to verify the effectiveness of the suggested strategy. The study validates the proposed method through comparison with both conventional techniques and the original BKA. Simulation results demonstrate that, when benchmarked against competing algorithms, the proposed method consistently yields optimal performance and exhibits faster convergence in certain scenarios. Notably, it reduces undershoot and overshoot by an average of 65% and 90.22%, respectively, compared to the PSS-Lead Lag method. Furthermore, the proposed approach not only minimizes overshoot and undershoot but also achieves a significantly faster settling time.
Power sharing based on starfish optimization algorithm in DC microgrid Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Umar, Abubakar; Sabo, Aliyu; A. Shehadeh, Hisham
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.9784

Abstract

This paper presents a starfish optimization algorithm (SFOA) method for optimizing control parameters in DC microgrids. SFOA is a new metaheuristic inspired by biology to solve optimization problems, which simulates the behavior of starfish, including exploration, preying, and regeneration. SFOA consists of two main phases of exploration and exploitation. This paper evaluates the performance of SFAO on droop control of DC microgrids by comparing with walrus optimizer (WO) and grasshopper optimization algorithm (GOA). From the simulation, SFOA shows superior capability. Validation on DC microgrid control using integral of time-weighted absolute error (ITAE) and integral of time-weighted squared error (ITSE). Simulation results demonstrate that the proposed technique exhibits a superior ITAE relative to WO and GOA, which are 6.88% and 8%, respectively. The performance validation results demonstrate that the SFOA approach exhibits potential and effective performance. The proposed method on DC microgrid control has been successfully applied and shows promising performance. The proposed methodology is particularly suitable for renewable energy integration in isolated or resource-constrained regions.
Co-Authors A. Shehadeh, Hisham Abatal, Ahmed Aditya Prapanca Al-Widyan, Mohamad I. Aljohani, Abeer Almomani, Mohammad H. Alomari, Saleh Ali Alsmadi, Mutasem Khalil Amaliah, Fithrotul Irda As’ad Shidqy Aziz Ayusta Lukita Wardani B, Nur Vidia Laksmi Benlalia, Zakaria Billah, Mohammed El Kaim Eker, Erdal Ekinci, Serdar Elsayed Abd Elaziz, Mohamed Hussein, Ahmad MohdAziz Izci, Davut Jaradat, Ghaith M. Khallouki, Hajar Mahendra Widyartono Migdady, Hazem Mzili, Mourad Mzili, Toufik Oliva, Diego Rahmadian, Reza Sabo, Aliyu Smerat, Aseel Snasel, Vaclav Soleimanian Gharehchopogh, Farhad Umar, Abubakar Widi Aribowo Zangana, Hewa Majeed Zitar, Raed Abu