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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Sabo, Aliyu
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Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering Transportation

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Enhanced hippopotamus optimization algorithm for power system stabilizers Aribowo, Widi; Mzili, Toufik; Sabo, Aliyu
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp22-31

Abstract

This article presents techniques for modifying the power system stabilizer's (PSS) parameters. An enhanced version of the hippocampal optimization algorithm (HO) is presented here. HO represents a novel approach in metaheuristic methodology, having been inspired by the observed clinging behavior in hippos. The notion of the HO is defined using a trinary-phase model that includes their position updates in rivers or ponds, defensive techniques against predators, and mathematically described evasive methods. To confirm the efficacy of the recommended approach, this article provides comparison simulations of the PSS objective function and transient response. This study employs validation through a comparison between Original HO and conventional methods. Simulation results demonstrate that, when compared to competing algorithms, the suggested approach yields optimal results and, in some cases, exhibits fast convergence. It is known that, in comparison to the original HO approach, the recommended way can lower the average undershoot of the rotor angel and speed by 12.049% and 26.97%, respectively.
Hybrid horned lizard optimization algorithm-aquila optimizer for DC motor Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Mzili, Toufik; Sabo, Aliyu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp1673-1682

Abstract

This research presents a modification of the horned lizard optimization (HLO) algorithm to optimize proportional integral derivative (PID) parameters in direct current (DC) motor control. This hybrid method is called horned lizard optimization algorithm-aquila optimizer (HLAO). The HLO algorithm models various escape tactics, including blood spraying, skin lightening or darkening, crypsis, and cellular defense systems, using mathematical techniques. HLO enhancement by modifying additional functions of aquila optimizer improves HLO performance. This research validates the performance of HLAO using performance tests on the CEC2017 benchmark function and DC motors. From the CEC2017 benchmark function simulation, it is known that HLAO's performance has promising capabilities. By simulating using 3 types of benchmark functions, HLOA has the best value. Tests on DC motors showed that the HLAO-PID method had the best integrated of time-weighted squared error (ITSE) value. The ITSE value of HLOA is 89.25 and 5.7143% better than PID and HLO-PID.
A Review on Techniques Used for Solving the Economic Load Dispatch Problems: Categorization, Advantages, and Limitations Sabo, Aliyu; Buba, Sadiq; Muhammed, Kabir; Kalau, Samuel ephraim; Olaniyi, Daramola paul; Veerapandiyan Veerasamy; Abdulmajid Muhammed Na'inna
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 1 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i1.35591

Abstract

The increasing global demand for electric power presents significant challenges for power utilities, as they must balance the need for reliable and sustainable power generation with the goal to minimize generation costs. This challenge has led to studying Economic Load Dispatch (ELD), which aims to optimize power generation at minimal fuel costs.  This paper presents a comprehensive review of several primary techniques used in solving ELD problems, including traditional methods such as the Lambda Iteration, Gradient, and Newton-Raphson techniques, as well as modern optimization methods like Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Sine Cosine Algorithm (SCA), and Gravitational Search Algorithm (GSA). The paper also provides a comparative analysis using tables and chart in section three outlining the advantages, disadvantages, and limitations of each technique discussed in section two. Additionally, this review examines the applications of these techniques on IEEE test systems in various studies, highlighting their effectiveness on practical utility making it easier for researchers to make a choice in selecting a technique for their ELD problem.
A Modelling and Simulation of Damping Controller In DFIG AND PMSG Integrated With A Convectional Grid: A Review Sabo, Aliyu; Dahiru, Dauda; Noor Izzri, Abdul Wahab
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.34749

Abstract

One of nature's most plentiful energy sources is a wind energy conversion system, which also has higher sustainability and no pollution. Damping controllers are designed to enhance hybrid robustness and adaptability when using permanent magnet and double-fed induction synchronous generators. The generators are integrated with convectional sources, which requires careful consideration of grid stability (rotor angle stability), which helps prevent mechanical oscillation and grid disruptions due to the instability. Power system stabilizers with excitation are designed and optimized to assure power system stabilizer settings for ideal damping performance and ignore energy losses; damping controllers are essential.
Enhancing photovoltaic parameters based on modified puma optimizer Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Elsayed Abd Elaziz, Mohamed; Soleimanian Gharehchopogh, Farhad; A. Shehadeh, Hisham; Sabo, Aliyu; Prapanca, Aditya
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8977

Abstract

This article presents a photovoltaic (PV) optimization approach using the puma optimizer (PO) approach, which has been enhanced by utilizing Lévy flight optimization. The name of this approach is modified puma optimizer (MPO). PV generation systems are essential for sustainable solar energy utilization. It is an innovation and clean energy. There is an urgent demand for suitable and reliable simulation and optimization techniques for PV systems. This will result in increased efficiency. Algorithms with a high degree of reliability are needed to ensure optimal PV parameters. This study was conducted with MATLAB software. This article introduces the original PO method as a means to evaluate the performance of the MPO approach. The root mean square error (RMSE) function serves as a benchmark. Based on the simulation findings, the MPO approach shows superior RMSE compared to the PO method, specifically at a value of 0.0026%.
Microgrid Control Techniques: A Review Abdulmalik; Sabo, Aliyu; Ogunleye , Olutosin; Noor Izzri, Abdul Wahab; Shahinzadeh , Hossein; Na’inna , Abdulmajid Muhammad
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.36477

Abstract

Microgrids (MGs) are localized energy systems that integrate distributed energy resources (DERs) such as renewable energy, energy storage systems (ESS), and conventional generation sources. A critical challenge in the operation of microgrids is maintaining frequency stability, particularly during transient disturbances or load imbalances. This review provides a comprehensive analysis of various frequency control strategies employed in microgrids to ensure stable and reliable operation. The paper categorizes existing approaches into primary, secondary, and tertiary frequency control methods, evaluating their mechanisms, advantages, and limitations. Primary control focuses on immediate frequency regulation through local droop control, while secondary control ensures the restoration of frequency to its nominal value through centralized or decentralized coordination. Tertiary control manages economic dispatch and energy optimization for long-term stability. Additionally, the review addresses the impact of DER characteristics, such as variability and intermittency, on frequency regulation, and discusses advanced techniques, including model predictive control, fuzzy logic control, and Neural network control. The paper concludes with a discussion on future trends in microgrid frequency control, emphasizing the need for robust encryption and intrusion detection systems that protect microgrid control networks from cyber threats, ensuring reliable frequency regulation even in the event of a cyber-attack.
PID controller tuning for an AVR system using Particle Swarm Optimisation Techniques and Genetic Algorithm Techniques; A comparison based approach Sabo, Aliyu; Bawa, Mahmud; Yakubu, Yunusa; Ngyarmunta , Alan Audu; Aliyu, Yunusa; Musa, Alama; Katun, Mohamed
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.36821

Abstract

This paper presents the tuning of a Proportional-Integral-Derivative (PID) controller for an Automatic Voltage Regulator (AVR) system using a metaheuristic optimization technique. The aim is to enhance the system's dynamic response by minimizing overshoot, settling time, and steady-state error. Particle Swarm Optimization (PSO), a robust and widely applied metaheuristic technique, was selected due to its simplicity and efficiency in exploring the search space for optimal solutions. The AVR system was modelled and simulated using MATLAB and the performance of the optimized PID controller was analyzed and compared with a traditional manually tuned PID controller. The results show a significant improvement in system performance with the PSO-tuned PID controller, validating the potential of metaheuristic optimization for PID tuning in control systems.
The Use of Genetic Algorithm Optimization Approach In Comparison With Lambda Iteration Technique to Solve Economic Load Dispatch Problem. Sabo, Aliyu; Buba, Sadiq; Ogunleye, Olutosin; Mohammed , Kabir; Ephraim Kalau, Samuel; P. Olaniyi, Daramdla
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.38275

Abstract

The increasing demand for efficient and reliable power generation systems has amplified the importance of solving Economic Load Dispatch (ELD) problems. This study compares the performance of two optimization techniques—Genetic Algorithm (GA), a robust metaheuristic approach, and Lambda Iteration, a traditional iterative method—on the IEEE 39-bus 10-generator test system. The analysis focuses on fuel cost minimization and computational efficiency. GA achieves a significant reduction in total fuel cost to $1390.29, outperforming Lambda Iteration's $2324.22. However, Lambda Iteration demonstrates faster convergence at 0.2 seconds compared to GA's 1.2 seconds. The results underscore the trade-offs between cost efficiency and computational speed, providing valuable insights into the suitability of advanced optimization methods like GA for complex ELD problems and the practicality of Lambda Iteration for simpler systems.
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.
Frilled Lizard Optimization to optimize parameters Proportional Integral Derivative of DC Motor aribowo, widi; Abualigah, Laith; Oliva, Diego; Mzili, Toufik; Sabo, Aliyu; A. Shehadeh, Hisham
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 1 (2024)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v1i1.33973

Abstract

This paper presents a Proportional-Integral-Derivative (PID) parameter optimization method for direct current (dc) motors. The method utilizes a metaheuristic technique known as Frilled Lizard Optimization (FLO), which is inspired by natural processes. FLO draws inspiration from the lizard's hunting method of employing a sit-and-wait approach with great patience. The method is divided into two distinct phases: the exploration phase, which simulates a swift predator attack by a lizard, and the exploitation phase, which imitates the lizard's return to the treetop after feeding. This study confirms the effectiveness of FLO by conducting performance tests on the CEC2017 benchmark function and a DC motor. Through the simulations conducted on the CEC2017 benchmark function, it has been determined that FLO has superior exploration and exploitation capabilities. When testing a DC motor, it was discovered that the PID-FLO approach is effective in reducing overshoot and achieving optimal performance
Co-Authors A. Shehadeh, Hisham Abdulmajid Muhammed Na'inna Abdulmalik Abdulrazak, Yakubu Abualigah, Laith Aditya Prapanca Aliyu, Yunusa Aljohani, Abeer Bawa, Mahmud Buba, Sadiq Dahiru, Dauda Elsayed Abd Elaziz, Mohamed Ephraim Kalau, Samuel Kabiru Abubakar Tureta Kalau, Samuel ephraim Katun, Mohamed Mohammed , Kabir Muhammed, Kabir Musa, Alama Mzili, Toufik Na’inna , Abdulmajid Muhammad Ngyarmunta , Alan Audu Noor Izzri, Abdul Wahab Ogunleye, Olutosin Ogunleye , Olutosin Olaniyi, Daramola paul Oliva, Diego P. Olaniyi, Daramdla Shahinzadeh , Hossein Soleimanian Gharehchopogh, Farhad Veerapandiyan Veerasamy Widi Aribowo Yakubu, Yunusa