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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.
Adaptive Frequency Control of an Isolated Microgrids Implementing Different Recent Optimization Techniques Hamid, Mohamed Nasr Abdel; Banakhr, Fahd A.; Mohamed, Tarek Hassan; Ali, Shimaa Mohamed; Mahmoud, Mohamed Metwally; Mosaad, Mohamed I.; Albla, Alauddin Adel Hamoodi; Hussein, Mahmoud M.
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.v4i3.1432

Abstract

In recent years, significant improvements have been made in the load frequency control (LFC) of interconnected microgrid (MG) systems, driven by the growing demand for enhanced power supply quality. However, challenges such as low inertia, parameter uncertainties, and dynamic complexity persist, posing significant hurdles for controller design in MGs. Addressing these challenges is crucial as any mismatch between demand load and power generation inevitably leads to frequency deviation and tie-line power interchange within the MG. This work introduces sophisticated optimization techniques (grey wolf optimization (GWO), whale optimization algorithm (WOA), and balloon effect (BE)) for LFC, focusing on the optimal online tuning of integral controller gain (Ki) for controlled loads. The WOA regulates the frequency of the system so variable loads can be accommodated and 6 MW of PV is added to the MG. A PV and a diesel generator-powered isolated single area MGs with electrical random loads are managed by the adaptive controller by regulating the frequency and power of the PV. Online tuning of integral controllers is possible using the WOA. A comparison is carried out between the WOA+BE and three other optimizers, namely the GWO, GWO+BE method, and the WOA. This paper shows the effect of add BE identifier to standard WOA and GWO. MATLAB simulation results prove that the BE identifier offers a significant advantage to the investigated optimizers in the issue of adaptive frequency stability even when disturbances and uncertainties are concurrent.
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.
Design, Modeling, and Simulation of A New Adaptive Backstepping Controller for Permanent Magnet Linear Synchronous Motor: A Comparative Analysis Maamar, Yahiaoui; Elzein, I. M.; Alnami, Hashim; Brahim, Brahimi; Benameur, Afif; Mohamed, Horch; Mahmoud, Mohamed Metwally
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.v5i1.1425

Abstract

In this paper, a nonlinear adaptive position controller for a permanent magnet linear synchronous motor based on a newly developed adaptive backstepping control approach is discussed and analyzed. The backstepping approach is a systematic method; it is used for non-linear systems such as the linear synchronous motor. This controller combines the notion of the Lyapunov function, which is based on the definition of a positive energy function; to ensure stability in the sense of Lyapunov, it is necessary to ensure the negativity of this function by a judicious choice of a control variable called virtual control. But this method is mainly based on the mathematical model of the permanent magnet linear synchronous machine (PMLSM) which makes this control sensitive to the variation of the parameters of the machine, to overcome this problem an adaptive control was proposed, the adaptive backstepping control approach is utilized to obtain the robustness for mismatched parameter uncertainties and disturbance load force. The overall stability of the system controller and adaptive low is shown using the Lyapunov theorem. The validity of the proposed controller is supported by computer simulation results.
Adaptive Load Frequency Control in Microgrids Considering PV Sources and EVs Impacts: Applications of Hybrid Sine Cosine Optimizer and Balloon Effect Identifier Algorithms Hassan, Ahmed Tawfik; Banakhr, Fahd A.; Mahmoud, Mohamed Metwally; Mosaad, Mohamed I.; Rashwan, Asmaa Fawzy; Mosa, Mohamed Roshdi; Hussein, Mahmoud M.; Mohamed, Tarek Hassan
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1448

Abstract

The negative impacts of microgrids (µGs) on the load frequency highlight the importance of implementing a robust, efficient, and adaptable controller to ensure stability. This work introduces an adaptive load frequency control (LFC) for an isolated µG that includes a PV system and electric vehicles (EVs), which have a significant impact on frequency. This control utilizes a combination of sine cosine optimization (SCO) and balloon effect identifier (BEI) algorithms. The controller presented in this work transforms the LFC process into an optimization problem that is highly compatible with various random situations encountered in the control process. The suggested control method is a novel approach by utilizing SCO+BEI for adaptive LFC application, resulting in a highly efficient response. The effectiveness of the proposed adaptive controller is assessed under the conditions of 17 MW variable load, system parameters uncertainties, and installed PV systems of 6 MW.  MATLAB / Simulink package is rummage-sale as a digital test environment. According to simulation results, the proposed adaptive controller succeeds in regulating the frequency and power of an islanded µG. To measure the efficiency of the proposed control scheme, a comparison between other control techniques (such as adaptive controller using Jaya+BEI and classical integral controller) is done. The findings of the studied scenarios assured that the not compulsory control method using (SCO+BEI) has an obvious superiority over other control methods in terms of frequency solidity in case of random load instabilities and parameter uncertainties. Finally, it can be said that the proposed controller can better ensure the safe operation of the µGs.
Hybrid Adaptive Backstepping Sliding Mode Controller of Permanent Magnet Linear Synchronous Motors Maamar, Yahiaoui; Alnami, Hashim; Elzein, I. M.; Benameur, Afif; Brahim, Brahimi; Mohamed, Horch; Mahmoud, Mohamed Metwally
Control Systems and Optimization Letters Vol 2, No 3 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i3.165

Abstract

This paper tackles the tracking position control dilemma of permanent magnet linear synchronous motors with parameter uncertainties and load force disturbance. Adaptive nonlinear backstepping control augmented with sliding mode control (SMC) is proposed to solve the problem of load force distribution. The backstepping is a recursive control technique where its stability is ensured at each step. However, its sensitivity to uncertainties, disturbances, and electromagnetic noise leads to unwanted performances. SMC is a well-known nonlinear robust approach for uncertain dynamical systems and reduces its parametric adaptive laws.  However, implementing this technique in real-time applications is stopped by its main shortcoming, the undesirable chattering phenomenon.  The saturation function is used to reduce the chattering phenomenon.  The incorporation of these approaches is a promising solution to provide a suitable position tracking of PMLSM in the presence of parameter uncertainties and load force disturbance. The simulation tests have been performed on the PMLSM system to prove the effectiveness and robustness of the proposed controller law.  The results highlighted satisfactory position tracking performance in transient conditions and steady-state and under different load force disturbances.
Investigations on Grid-Connected DFIWGs Development and Performance Analysis with the Support of Crowbar and STATCOM Mahmoud, Mohamed Metwally; Benlaloui, Idriss; Benbouya, Basma; Ibrahim, Nagwa F.
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.109

Abstract

These days, one of the most used layouts in the wind power industry is a variable-speed doubly-fed induction wind generator (DFIWG). To provide real and reactive power (PQ) control during grid failures, this research examines the DFIWG. The system's transient behavior is examined under normal and abnormal conditions. Through rotor side converter (RSC) and grid side converter (GSC) control, 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. By suppressing rotor and stator overcurrent, DC link voltage (VDC) overshoot, and PQ oscillations, as well as supporting the grid voltage (GV) under both balanced and unbalanced grid fault scenarios with distinct voltage dips, the suggested technique preserves the system characteristics during grid faults. MATLAB/SIMULINK 2017b is used for time-domain computer simulations. STATCOM and crowbar, two suggested systems, are contrasted. This work proves the effectiveness of the suggested approaches in augmenting the system's fault ride-through (FRT) capacity.
Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier Raj, Abhishek; Mishra, Chandra Sekhar; Joga, S Ramana Kumar; Elzein, I. M.; Mohanty, Asit; lika, Sneha; Mahmoud, Mohamed Metwally; Ewais, Ahmed Mostafa
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.v5i1.1543

Abstract

This article presents a wavelet analysis-singular value decomposition (WA-SVD) based method for precise fault localization in recent power distribution networks using k-NN Classifier. The WA-SVD leverages the slime mould algorithm (SMA) and graph theory (GT) in enhancing the overall accuracy of fault localization. To validate the proposed methodology, extensive tests are conducted on various benchmark systems, including the IEEE 33-bus radial distribution system, the IEEE 33-bus meshed loop unbalanced distribution system, the IEEE 33-bus system with integrated renewable energy sources, and the IEEE 13-bus feeder test system. The results demonstrate a high fault classification accuracy of 99.08%, with an average localization error of just 1.2% of the total line length. The k-NN classifier exhibited a precision of 98.2% and a recall of 99.2%, underscoring the reliability and sensitivity of the proposed method. Additionally, the computational efficiency of the algorithm is evidenced by an average processing time of 0.0764 seconds per fault event, making it well-suited for real-time applications.
An Investigation of the Output Characteristics of Photovoltaic Cells Using Iterative Techniques and MATLAB® 2024a Software Hysa, Azem; Mahmoud, Mohamed Metwally; Ewais, Ahmed
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.174

Abstract

This study investigates the characteristics of photovoltaic (PV) cells using iterative methods and MATLAB® 2024a software. Its main objective is to analyze the power-voltage (P-V) and current-voltage (I-V) characteristics for various series resistances and solar irradiation levels. The precision and dependability of this study are improved by the software utilized for numerical simulations and analysis. Since the PV cells are nonlinear, numerical techniques are favored in this situation to solve their nonlinear equations. In order to investigate different curves and their characteristics, the study makes use of numerical simulations, the single diode model, and the Newton-Raphson method (NRM), which is iterative and converges to an optimal solution of the problem to be solved. The behavior of PV cells under the variation of solar irradiance and different values of series resistance is described by the I-V and P-V characteristics. From the data, we notice that the influence of sun irradiance on PV cells, demonstrates that higher solar irradiance gives more current and power, and higher series resistance decrease the output power. The highest efficiency of a solar cell measured is roughly 47.1%. Future technical advancements in these crucial areas for humankind will result in further increases in the maximum efficiency of solar cells.
Design of a Small Wind Turbine Emulator for Testing Power Converters Using dSPACE 1104 Boutabba, T.; Benlaloui, Idriss; Mechnane, F.; Elzein, I. M.; Ma'arif, Alfian; Hassan, Ammar M.; Mahmoud, Mohamed Metwally
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1685

Abstract

Interest in wind turbine emulators (WTE) has increased due to the growing need for wind power generation as a low-maintenance, more effective substitute for conventional models. This paper presents the design of a small WTE utilizing a dSPACE 1104 system. The setup includes a DC motor, driven by a buck converter, coupled to a permanent magnet synchronous generator, all managed through a hardware-in-the-loop configuration using the dSPACE 1104 board. The DC motor simulates the rotational motion generated by wind energy, accurately replicating the characteristics of an actual WT. This control system enables the simulation of various wind speeds and torque values in MATLAB/Simulink software, providing a valuable tool for analyzing and developing power converters. The results obtained confirmed the effectiveness of the proposed emulator, as the experimental outcomes closely matched the theoretical calculations.