Fajer M. Alelaj
Kuwait Institute for Scientific Research

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Crocodile Optimizer-Based DC Chopper Control for Voltage Dip and Swell Mitigation in PMSG-Based WT Basiony Shehata Atia; Fajer M. Alelaj; M. Metwally Mahmoud; Alfian Ma’arif; Abdel-Magid M Ali
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.15464

Abstract

The increasing penetration of wind energy systems requires advanced control strategies capable of maintaining stable operation during grid disturbances while complying with modern GC requirements. This paper proposes a COA-based control scheme for a DC chopper integrated into a PMSWG system to enhance its FRTC under severe voltage disturbances. The COA is employed to optimally tune the controller parameters, ensuring effective regulation of the DC-link voltage and improved transient performance. The proposed approach is evaluated under four critical grid conditions, including three voltage dip scenarios corresponding to 100%, 80%, and 40% retained voltage levels, as well as a 20% voltage swell condition. Simulation results demonstrate that the proposed controller maintains the DC-link voltage close to its reference value of 1150 V, preventing excessive overvoltage during fault events and reducing stress on power electronic converters. Moreover, the control strategy satisfies GC requirements by providing appropriate reactive power support during VDs while ensuring controlled active power transfer. The optimized controller effectively suppresses electromagnetic torque oscillations, limits transient current peaks in the GSC, and enables rapid recovery of generator speed following fault clearance. Comprehensive MATLAB/Simulink studies confirm that the proposed COA-based DC chopper control significantly improves system transient stability, enhances grid-support capability, and ensures reliable operation under both voltage dip and swell conditions. In addition, the improved DC-link voltage regulation contributes to increased converter lifetime and reduced operational downtime, demonstrating the practicality and effectiveness of the proposed solution for modern wind energy conversion systems.
Adaptive Smart Energy Management for Wind-Battery Systems Considering Grid Fault Scenarios Habib Chaib; Housseyn Chaib; Belkacem Belabbas; Fajer M. Alelaj; Alfian Ma’arif; Mohamed Metwally Mahmoud; Vojtech Blazek; Shady M. Sadek
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16033

Abstract

This work introduces a novel energy management system based on radial basis function neural network (RBFNN) adapted for both grid-connected and segmented modes. The system components are electrical distribution grid, wind generator, power electronic converters and batteries. The study uses intelligent control and prevents the spread of potential problems or disturbances. This system incorporates various controllers responsible of specific functions like MPP monitoring, of battery charging and discharging, and of an inverter for effectively managing the transition between energy sources based on load requirements and available sources operating at their MPP. The objectives are to facilitate coordinated operation among distributed energy resources, ensuring the provision of necessary active power and additional services as necessary. The simulation uses MATLAB/Simulink environment. Simulation results demonstrate the effectiveness and feasibility of the proposed strategy. Overall, the obtained results affirm the practicality and advantages of employing neural networks in energy management systems.