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Optimum control and design of a small hydro power plant for agriculture investment in Iraqi desert Hameed, Jamal Ahmed; Atyia, Thamir Hassan; Jaf, Saba Fadhil Ahmed; Abdulkareem, Zubaidah Ghaze; Hasan, Ghanim Thiab
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i3.pp560-568

Abstract

The aim of this paper is to conduct a mathematical and physical analysis to get a systematic treatment of design parameters and thus optimize water wheels. By today's standards, one finds empirical formulas instead, which take into account the practical experience of previous constructions, estimates of particular wheelbase shapes and sizes. So, based on the basic design and optimization standards for water wheels implementation, this paper attempts to design a water wheel power source in desert areas. Since the water wheels mainly use the gravitational force of water, there is only a slight hydrodynamic power losses. In addition to the high torque due to the large inertia of the water wheel. The obtained results indicate that the optimum operating range of the trailing water wheels is at a diameter of (2-7 m) and the Q water flow of about (0.1 m3/s). So, it can conclude that the implementing design has good efficiency and offer an economic benefit when use for the agriculture investment in desert areas.
Torque sharing function optimization for switched reluctance motor control using ant colony optimization algorithm Ismael, Dhiyaa Mohammed; Atyia, Thamir Hassan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1537-1551

Abstract

Switched reluctance motors (SRMs) are gaining popularity in industrial and automotive applications due to their robust design, fault tolerance, and high torque density, particularly in wide-speed-range operations. However, SRM performance is often limited by torque ripple, speed oscillations, and inefficiencies, which can lead to mechanical stress, vibration, and acoustic noise. Addressing these challenges requires the effective optimization of control strategies. This study aims to enhance the performance of SRM drives by employing an ant colony optimization (ACO) algorithm to optimize the torque sharing function (TSF). The proposed method iteratively tunes TSF parameters to minimize torque ripple and improve speed stability under varying operating conditions. Simulation results demonstrate significant improvements: torque ripple is reduced from a range of –20 Nm to 10 Nm without optimization to below 10 Nm with ACO-based optimization. Similarly, current peaks decrease from 60 A to 5.5 A, ensuring smoother motor operation and enhanced efficiency. Comparative analysis confirms that the ACO-based TSF provides superior tracking of speed set points, reduced mechanical stress, and improved reliability, making it well-suited for high performance applications in both industrial and automotive sectors.