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RISS 인기검색어
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- 저자 : Amin Arslan Ahmed (검색결과 3 건)
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Arslan Ahmed Amin,Hamza Ahmad,Hassan Khalid,Neha Masroor,Huda Mahmood,Muhammad Abubakar 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.1
This paper presents the development and experimental verifi cation of the mathematical model of wind turbine and Doubly Fed Induction Generator (DFIG) using the current control and voltage estimation method between the DC link. The rotor of the induction generator (IG) is rotated with the wind turbine at a specifi c speed. The DFIG is directly coupled with a grid station and the synchronization between DFIG and the grid station is controlled by setting two converters: Machine Side Converter (MSC) implemented with the rotor side and Grid Side Converter (GSC) implemented with the grid. PI controllers have been utilized in the control loops and the parametric range is extracted to maximize the mechanical power transferred to the IG rotor. The model is tested under three conditions DFIG running at super synchronous speed, synchronous speed, and under synchronous speed using MATLAB Simulink. In the end, the same model is also tested through a series of experiments using lab modules. The results show that the proposed model is much simplifi ed and accurate as compared to previous versions available in the literature.
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Amin Arslan Ahmed,Mahmood-ul-Hasan Khalid 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.3
This paper proposes a Unifi ed Fault-Tolerant Control System (UFTCS) based on advanced analytical and hardware redundancies for Air-Fuel Ratio (AFR) control of Spark Ignition (SI) Internal Combustion (IC) engines. The advanced analytical redundancy part is termed the Hybrid Fault-Tolerant Control System (HFTCS) which consists of both active and passive types. The Lookup Tables (LTs) have been utilized in the active part and a robust proportional feedback controller of high gain with fuel throttle actuator has been implemented in the passive part. Since the failure of any two sensors at the same time or failure of a single actuator causes engine shutdown, an advanced hardware redundancy protocol Modifi ed Triple Modular Redundancy (MTMR) has been suggested for the sensors, and Dual Redundancy (DR) has been proposed for the actuators to prevent the tripping of the engine. MATLAB/Simulink simulation results indicate that the suggested UFTCS is highly robust to the sensor faults in both normal and noisy conditions. The probabilistic reliability analysis for various hardware redundancy schemes also proves the greater overall reliability of UFTCS. Finally, a comparison with the existing AFR control systems is carried out to demonstrate its superior performance
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Shahzad Kashif,Amin Arslan Ahmed 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.5
In this paper, the optimal planning of Distributed Energy Storage Systems (DESSs) in Active Distribution Networks (ADNs) has been addressed. As the proposed problem is mixed-integer, non-convex, and non-linear, this paper has used heuristic optimization techniques. In particular, fi ve optimization techniques namely Genetic algorithm, Particle swarm optimization, Tabu search, Simulated annealing, and Pattern search optimization techniques have been applied to optimal planning of DESS. The problem has been formulated to consider distributed storage units’ optimal locations and sizes to be placed in an ADN while respecting the constraints of the system. The problem has been addressed on two levels. In the fi rst level, an optimization technique is applied for DESS planning to determine the optimal solution and in the second level, the fi tness value of this solution is evaluated by solving a daily AC Optimal Power Flow (OPF) problem. Simulations have been done for the IEEE 34 and IEEE 123 nodes network to demonstrate and compare the effi ciency of diff erent optimization techniques. The comparison of these optimization techniques has shown that Particle swarm optimization and Tabu search optimization (with a particular value of tabu tenure found by hit and trial) have performed better in fi nding the lowest DESS location corresponding to minimum fi tness value as compared to other optimization techniques both for IEEE 34 nodes and IEEE 123 nodes network
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