Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
Abdulkhaleq, Nadhir Ibrahim
Unknown Affiliation
Aerospace Engineering Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Design and Simulation of Optimized Load Frequency Control in Multi-Area Electrical Interconnection Systems Hasan, Ihsan Jabbar; Abed, Saif Ahmed; Salih, Nahla Abdul Jalil; Abdulkhaleq, Nadhir Ibrahim
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 3 (2025): November (Special Issue)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i3.3082

Abstract

Maintaining frequency stability in modern interconnected power systems is critical for operational reliability, especially under varying load demands. Load Frequency Control (LFC) plays a pivotal role in balancing power exchanges and preserving nominal frequency across multi-area grids. This paper presents the design, modeling, and optimization of a two-area Load Frequency Control (LFC) system in interconnected power networks using MATLAB/Simulink. Each area comprises a governor, turbine, generator-load system, and a PID controller to regulate frequency deviations and maintain system stability following load disturbances. The study investigates the effects of key system parameters—including governor and turbine time constants, generator inertia, and tie-line coupling—on dynamic performance. To address mismatched responses between areas, Particle Swarm Optimization (PSO) is employed to tune system parameters and improve coordination. The optimization aims to minimize frequency deviations and tie-line power fluctuations while enhancing system response. Simulation results show that the proposed optimization approach significantly improves dynamic performance. Specifically, frequency deviations in both areas are reduced by over 55%, tie-line power fluctuation is minimized by 62.5%, and settling times for frequency responses are shortened by over 44%. These improvements demonstrate the effectiveness of the optimization strategy in enhancing inter-area coordination and system resilience. The framework also serves as a practical simulation-based educational tool for power engineering students and researchers to exploreLFC design and control strategies in multi-area systems.
Smart Airport Radar: Multimodal AI Classification of Aerial Threats with Communication Link Performance Evaluation Abdulkhaleq, Nadhir Ibrahim; Hussein, Ahmed Saad
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3295

Abstract

The proliferation of small unmanned aerial vehicles (UAVs) near airports poses increasing risks to airspace safety and infrastructure security. This paper presents Smart Airport Radar, a simulation-based framework for classifying aerial threats — including drones, decoys, and birds — using multimodal AI features. The system emulates dynamic swarming behaviors and extracts five key descriptors — mean speed, heading variability, jerk, thermal signature, and radar cross-section (RCS) — to train a multiclass Support Vector Machine (SVM) classifier. Comparative analysis with a traditional RCS-based rule method shows the SVM achieving a classification accuracy of 93.33%, far outperforming the baseline at 20.00%. Radar-style trajectory visualizations and class-specific precision, recall, and F1-scores confirm the model’s robustness and interpretability. Beyond sensing and classification, the framework incorporates a communication link performance evaluation, analyzing classification accuracy under varying Signal-to-Noise Ratio (SNR) levels. Results reveal that maintaining link quality above 15 dB SNR preserves near-optimal detection performance, bridging radar sensing with wireless communication reliability. With minimal computational overhead, high adaptability, and strong cross-domain relevance, the proposed system offers a robust, explainable, and deployable solution for real-time perimeter defense in modern airport security infrastructures.
Co-Authors Abed, Saif Ahmed Hasan, Ihsan Jabbar Hussein, Ahmed Saad Salih, Nahla Abdul Jalil