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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Ayman Hoballah
Taif University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Adaptive filter-FLC integration for torque ripples minimization in PMSM using PSO Yasser Ahmed; Ayman Hoballah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.647 KB) | DOI: 10.11591/ijpeds.v10.i1.pp48-57

Abstract

The article presents torque and flux ripples minimization based on adaptive filter. The adaptive filter coefficients optimized and adapted on line by using particle swarm optimization (PSO) technique. The proposed methodology applied on closed loop speed control based on direct torque control (DTC) for surface mounted permanent magnet synchronous motor (PMSM). Fuzzy logic controller (FLC) used as speed controller while proportional-integral (PI) controller used as torque and flux controllers. Second order infinite impulse response (IIR) filter is used for ripple reduction generated due to FLC. The drive system modeled using Matlab/Simulink software in order to dynamically evaluate the performance of the proposed drive system at different operating conditions. The results provide evidence that the adaptive filter-FLC integration with optimal coefficients minimizes torque and flux ripples with reduction of total harmonic distortion generated in the three-phase currents.
Fractional order PID controller adaptation for PMSM drive using hybrid grey wolf optimization Yasser Ahmed; Ayman Hoballah; Essam Hendawi; Sattam Al Otaibi; Salah K. Elsayed; Nagy I. Elkalashy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 12, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v12.i2.pp745-756

Abstract

In this paper, the closed loop speed controller parameters are optimized for the permanent magnet synchronous motor (PMSM) drive on the basis of the indirect field-oriented control (IFOC) technique. In this derive system under study, the speed and current controllers are implemented using the fractional order proportional, integral, and derivative (FOPID) controlling technique. FOPID is considered as efficient techniques for ripple minimization. The hybrid grey wolf optimizer (HGWO) is applied to obtain the optimal controllers in case of implementing conventional PID as well as FOPID controllers in the derive system. The optimal controller parameters tend to enhance the drive response as ripple content in speed and current, either during steady state time or transient time. The drive system is modeled and tested under various operating condition of load torque and speed. Finally, the performance for PID and FOPID are evaluated and compared within MATLAB/Simulink environment. The results attain the efficacy of the operating performance with the FOPID controller. The result shows a fast response and reduction of ripples in the torque and the current.
Risk assessment of power system transient instability incorporating renewable energy sources Ayman Hoballah; Salah Kamal EL-Sayed; Sattam Al Otaibi; Essam Hendawi; Nagy Elkalashy; Yasser Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4649-4660

Abstract

Transient stability affected by renewable energy sources integration due to reductions of system inertia and uncertainties associated with the expected generation. The ability to manage relation between the available big data and transient stability assessment (TSA) enables fast and accurate monitoring of TSA to prepare the required actions for secure operation. This work aims to build a predictive model using Gaussian process regression for online TSA utilizing selected features. The critical fault clearing time (CCT) is used as TSA index. The selected features map the system dynamics to reduce the burden of data collection and the computation time. The required data were collected offline from power flow calculations at different operating conditions. Therefore, CCT was calculated using electromagnetic transientsimulation at each operating point by applying self-clearance three phase short circuit at prespecified locations. The features selection was implemented using the neighborhood component analysis, the Minimum Redundancy Maximum Relevance algorithm, and K-means clustering algorithm. The vulnerability of selected features tends to result great variation on the best features from the three methods. Hybrid collection of the best common features was used to enhance the TSA by refining the final selected features. The proposed model was investigated over 66-bus system.
Co-Authors Essam Hendawi Nagy Elkalashy Nagy I. Elkalashy Salah K. Elsayed Salah Kamal EL-Sayed Sattam Al Otaibi Yasser Ahmed