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All Journal International Journal of Robotics and Control Systems
Elnaggar, Mohamed F.
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Control & Systems Engineering Electrical & Electronics Engineering

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Design and Implementation of Smell Agent Optimizer for Parameters Estimation of Single and Double Diode in PV System: A Comparative Analysis Elnaggar, Mohamed F.
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1490

Abstract

One of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits.  The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement.
Optimized Fault Detector Based Pattern Recognition Technique to Classify and Localize Electrical Faults in Modern Distribution Systems Mishra, Chandra Sekhar; Jena, Ranjan Kumar; Sinha, Pampa; Paul, Kaushik; Mahmoud, Mohamed Metwally; Elnaggar, Mohamed F.; Hussein, Mahmoud M.; Anwer, Noha Mohammed
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1474

Abstract

This research presents a method that integrates artificial neural networks (ANN) and discrete wavelet transform (DWT) to identify and classify faults in large power networks, as well as to pinpoint the zones where these faults occur. The objective is to enhance reliability and safety by accurately detecting and categorizing electrical faults. To manage the computational demands of processing the extensive and complex data from the power system, the network is divided into optimal zones, each made visible for fault detection. Niche Binary particle swarm optimization (NBPSO) is employed to place the fault detectors (FD) in each zone. This allows for precise measurement of fault voltage and current phasors without significant cost. The ANN module is tasked with identifying the fault area and locating the exact fault within that zone, as well as classifying the specific type of fault. Discrete Wavelet Transform is used for feature extraction, and a phase locked loop (PLL) is used for load angle computation. The proposed method's validity has been tested on the IEEE-33 bus distribution network.
Design and Implementation of Crowbar and STATCOM for Enhanced Stability of Grid-Tied Doubly Fed Induction Wind Generators Elnaggar, Mohamed F.
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1498

Abstract

These days, one of the most used layouts in the wind power industry is a variable-speed doubly-fed induction wind generator (DFIWG). For providing active power (P) and reactive power (Q) control during grid failures, this research examines the DFIWG. The system's transient behavior is examined under normal and abnormal circumstances. Through control of rotor side (RSC) and grid side (GSC) converters, Q assistance for the grid, and power converter stress reduction, the suggested control approach achieves system stability while enabling DFIWG to operate smoothly during grid failures. The DFIWG is exposed to three- and two-phase faults to analyze the machine's performance. The crowbar and STATCOM tools are implemented to enhance the system performance under faults and compared with the base case. The implemented tools successfully suppress rotor and stator overcurrent, over voltage at the DC link (DCL), and power oscillations, as well as supporting the grid voltage understudied cases. The obtained results prove that both STATCOM and crowbar not only enhance the system's effectiveness and performance but also enable the system to achieve the fault ride-through capacity (FRTC). MATLAB/SIMULINK 2017b is used for time-domain computer simulations.
Sensorless Speed Estimation Basing on MRAS Model for a PMSM Machine Application Elnaggar, Mohamed F.; Aymen, Flah; Mourad, Dina
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1585

Abstract

Wind energy systems utilizing synchronous machines can encounter challenges with speed detection at high rotational speeds due to increasing motor temperatures affecting parameters like stator resistance. This paper addresses these challenges by proposing a novel high-speed estimator algorithm based on the Model Reference Adaptive System (MRAS) approach. The primary contribution of this research is the development of an MRAS-based speed estimator that leverages a reactive power model to maintain robustness against variations in stator resistance, even at elevated speeds. To optimize the estimator’s performance, we employed a particle optimization algorithm for tuning, which overcomes issues related to regulator parameter identification. We implemented the proposed algorithm in Matlab and validated it on a real machine prototype capable of high-speed operation. After a comparison wth 5 different methods, the results indicate that the estimator performs effectively up to 42,000 RPM (600 Hz), demonstrating a maximum speed estimation error of 50 Hz. Stability analyses across various speed regions and practical lab tests confirm the robustness and accuracy of the proposed control scheme. The findings highlight the estimator’s improved performance in high-speed scenarios, showcasing its potential for enhancing speed detection in wind energy systems.
Optimal Controller Design of Crowbar System Using Class Topper Optimization: Towards Alleviating Wind-Driven DFIGs Under Nonstandard Voltages Elnaggar, Mohamed F.
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1694

Abstract

Increased integration of doubly fed induction wind generators (DFIWG), power sector deregulation, rising energy demands, and technological breakthroughs are all contributing to the rapid advancement of modern energy infrastructure. These advancements, nevertheless, pose serious challenges to maintaining fault ride-through capability (FRTC) in DFIWG. Thus, this work proposes a novel FRTC enhancement method that uses a crowbar system with a class topper optimization (CTO) based control technique. The crowbar system and DFIWG are integrated with the investigated system to achieve FRTC, reduce injected harmonic distortion, and maintain the DC link voltage (DCLV) below the permitted level. Additionally, the system has a DCLV control system that uses a CTO-PI controller to maintain an enclosure DCLV, which enhances crowbar performance. The findings demonstrated that when a CTO-based controller is employed, the DFIWG system reacts slightly better to angular speed, active and reactive power, DCLV, and generator speed. The MATLAB/Simulink scenarios used to test the suggested system show that it can achieve FRTC and allow for a high penetration potential of DFIWG.
Dynamic Assessment and Control of a Dual Star Induction Machine State Dedicated to an Electric Vehicle Under Short-Circuit Defect Benbouya, Basma; Cheghib, Hocine; Behim, Meriem; Mahmoud, Mohamed Metwally; Elnaggar, Mohamed F.; Ibrahim, Nagwa F.; Anwer, Noha
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1557

Abstract

The widespread use of electric vehicles (EVs) in several industries gives rise to many significant safety and reliability-related issues. Thus, there is a need for methods for identifying flaws in EV components. In this paper, a state assessment of a dual star induction machine (DSIM) under short-circuit faults is investigated. The DSIM is selected due to its widespread use in high-power applications and its numerous advantages over other conventional machine types. Our focus is particularly on its application in the automotive industry, where its dual stator windings ensure reliable and robust parallel operation, thereby enhancing its robustness and efficiency. To improve this technology and ensure its proper functioning following potential failures and during maintenance, appropriate diagnostic and monitoring methods are essential. Our methodology combines two techniques: the current space vector (CSV), utilized to prevent information loss, and the wavelet packet decomposition energy, calculated from the resulting CSV signals. This approach enables the detection of various stator short-circuit faults, presenting different severities and occurring at different locations. The outcomes of this study, which were verified through the use of a Simulink model of a DSIM devoted to an EV, showcase the efficacy of the suggested approach. Furthermore, this work underscores the significance of this approach in maintaining the performance and reliability of DSIM, particularly in demanding environments such as the automotive industry.
Optimizing Single-Inverter Electric Differential System for Electric Vehicle Propulsion Applications Moumni, Rachad; Laroussi, Kouider; Benlaloui, Idriss; Mahmoud, Mohamed Metwally; Elnaggar, Mohamed F.
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1542

Abstract

The increasing demand for electric vehicles (EVs) is driven by the urgent need for environmentally friendly transportation. This paper addresses the challenge of optimizing EV drivetrain efficiency by proposing a novel single-inverter electronic differential system for distributed EV drivetrains. The research focuses on reducing system cost and complexity while maintaining high performance. The methodology involves a detailed simulation using MATLAB/Simulink to validate the theoretical soundness of the proposed connection method. The results demonstrate that the proposed system achieves a minimum accuracy rate of 97.5%, marking a significant improvement over traditional dual-inverter systems. This approach not only enhances drivetrain efficiency but also contributes to more compact and cost-effective vehicle designs. Additionally, the findings underscore the potential for further refinement and exploration, suggesting that continued advancements in ED systems could lead to even greater performance gains in the future. This research lays the groundwork for future innovations in EV technology, particularly in the areas of cost reduction and system efficiency.
A Combination of HHO and BEI Techniques for Frequency Control in Renewable-Dominated Microgrids: Towards Advancing Sustainable Development Elnaggar, Mohamed F.
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.1953

Abstract

To address the rising need for resilient and eco-friendly power systems, this research presents an intelligent load frequency control (LFC) framework specifically designed for hybrid microgrids with significant renewable energy integration and variable operational dynamics. The proposed control scheme leverages the Harris Hawks Optimization (HHO) algorithm in conjunction with a Balloon Effect (BE) adaptation mechanism, enabling real-time tuning of controller parameters in response to system fluctuations and disturbances. The simulation model encompasses a diverse hybrid microgrid configuration, comprising PV arrays, a diesel generator, and time-varying load profiles. Performance assessments were conducted across three operating modes: diesel-alone supply, coordinated diesel-PV operation, and a high-renewable scenario incorporating uncertainties in system inertia, damping, and droop. In all tested cases, the HHO + BE controller demonstrated superior behavior compared to standard optimization techniques like GTO, SCA, and WOA, exhibiting quicker stabilization, smaller frequency deviations (down to ±0.18 Hz), and minimized control actions. Overall, this study underscores the adaptability and reliability of the HHO + BE control approach for maintaining frequency stability in modern, low-inertia microgrids. The results offer compelling evidence of its effectiveness in real-time applications, particularly in environments increasingly dominated by fluctuating renewable energy sources and uncertain operating conditions.
Co-Authors Anwer, Noha Anwer, Noha Mohammed Aymen, Flah Behim, Meriem Benbouya, Basma Benlaloui, Idriss Cheghib, Hocine Hussein, Mahmoud M. Ibrahim, Nagwa F. Jena, Ranjan Kumar Laroussi, Kouider Mahmoud, Mohamed Metwally Mishra, Chandra Sekhar Moumni, Rachad Mourad, Dina Paul, Kaushik Sinha, Pampa