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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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Journal : Vokasi UNESA Bulletin of Engineering, Technology and Applied Science

 1 
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.
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.
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
A Optimal Placement of Phasor Measurement Units on Shiroro 330kv Grid Network using Binary Grey Wolf Optimization Algorithm Kabiru Abubakar Tureta; SABO, ALIYU; Abdulrazak, Yakubu
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (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.v2i3.38936

Abstract

Phasor Measurement Units (PMUs) are essential for enhancing the control, monitoring, and observability of modern power systems. This research presents an optimal PMU placement approach for the Shiroro 330 kV grid network using the Binary Grey Wolf Optimization (BGWO) algorithm. The objective is to minimize the number of PMUs while ensuring full system observability under both normal and contingency conditions. The BGWO algorithm, inspired by the hunting behavior of grey wolves, is a powerful metaheuristic technique for solving binary optimization problems. By applying this method to the Shiroro grid, the study demonstrates how optimal PMU placement enhances grid observability and reliability. Compared to alternative optimization techniques, BGWO provides improved accuracy and reduced computational time. The simulation results validate the effectiveness of the proposed approach in achieving a cost-effective and reliable PMU deployment strategy for the 330 kV network.
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