Power

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Author: search.filters.author.Kheldoun, Aissa (Supervisor)Subject: search.filters.subject.Induction motor

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    Sizing of PV Pumping System with Optimizing MPPT Algorithm
    (Université M’Hamed Bougara de Boumerdes : Institut de génie electrique et electronique (IGEE), 2024) Benmbarek, Malik; Daif, Mouhaned; Kheldoun, Aissa (Supervisor)
    This report covers a comprehensive study of the sizing, modeling and simulation of a stand-alone solar water pumping system in El Oued, Algeria. The initial part involves selecting a farm located in Hassi Khalifa, El Oued, Algeria, which has an average water consumption of 43m/h. The irrigated site covers 1 hectare (10,000 square meters) of land. Sizing such a system has been carried out using differen ttool ssuc ha sCropwat ,Climwat ,an dPVgis. Sizing has led to the selection of a 2.2 kW submersible pump, 3.19 kW PV array, 3 kW inverter, and a 74m2 Tank of height 3 m. System dynamic modeling is done using MATLAB/Simulink which contains several models of sub-systems such as solar arrays, DC-DC boost converter, two-level inverter, Squirrel cage IM, and centrifugal pump, This dynamic modeling has been developed based on the sizing of the system. To improve further the overall system’s efficienc y,an enhanced P&O MPPT algorithm has been developed. Moreover, a DTC algorithm is used to regulate both the motor’s speed and torque. Various numerical simulations were conducted to illustrate and validate the effectivenes so fthi ssystem .MATLAB/Simulin ksimulation shows that this system can deliver the required energy needed for the farm to satisfy all the requirements.
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    Identification and control of asynchronous motor using meta-heuristic algorithms
    (2023) Ghernaout, Rayane; Kheldoun, Aissa (Supervisor); Belmadani, Hamza
    The present study is centered on the examination, regulation, and enhancement of induction motors (IMs) through the application of meta-heuristic algorithms. The aim of this study is to optimize the performance and efficiency of induction motors (IMs) in various applications. The study begins with the formulation of a mathe- matical model for induction motors (IMs). Subsequently, meta-heuristic algorithms, namely EO, RSBA, and JAYA, are employed to determine the parameters of the IM.The estimation of parameters is conducted by utilizing the inputs of measured stator voltages, currents, and rotor speed. This study focuses on the modeling of indirect rotor flux-oriented control(IRFOC )and the utilization of the resulting IM param- eters to identify the motor. Control gains are then optimized through the imple- mentation of RSBA and JAYA algorithms. The findings of the simulation indicate that the system’s performance has been enhanced in comparison to conventional manual tuning techniques. The project acknowledges the difficulties involved in the optimization process and emphasizes the significance of meticulous parameterse- lection. In summary, this study serves as a valuable contribution to the progression of IM technology, highlighting its potential to enhance performance and efficiency in industrial settings.