Power
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Item 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.Item Evaluation of global MPPT for stand-alone PV system(2018) Soufi, Ali; Mohammadi, Abdelhaq; Kheldoun, Aissa (Supervisor)Under partial shading conditions (e.g., due to buildings, trees, and clouds), multiple peaks may exist on the power-voltage (P-V) characteristic curve of photovoltaic (PV) array, leading to the conventional maximum power point tracking methods fail to extract the global maximum power point (GMPP). To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (LMPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This work describes a new fast and efficient technique based on Particle Swarm Optimization (PSO), compared with the conventional technique Perturb and Observe (P&O) which is inadequate to track the GMPP subject to these conditions resulting in a dramatic reduction in the efficiency of the PV system. Simulations are performed in MATLAB/SIMULINK software. A system includes a DC-DC buck-boost converter to step up or down the voltage to required magnitude. P&O and PSO maximum power point tracking (MPPT) algorithms have been used to extract the possible maximum power point from the PV system. A DSP microcontroller is also used to control the duty cycle of the IGBT accompanied with this system. The results verify the accuracy of the proposed scheme. Also the results show that the proposed method has better characteristic and performance in compare with P&O methods.Item Application of golden section search MPPT control to grid-connected wind turbine driven PMSG(2018) Khelifa, Ayoub; Ben Haoua, Seif Eddine; Kheldoun, Aissa (Supervisor)This project is intended to design a PMSG based wind energy conversion system. Classical controllers, such as P&O MPPT algorithms are employed to ensure maximum power extraction from wind turbine. Speed of the generator is adjusted to match the wind turbine power- speed characteristics. In this project, a new MPPT algorithm is investigated to maximize the power coefficient Cp. The algorithm is based on Golden Section search principle and expected to be faster than the aforementioned algorithms.Item Evaluation of global MPPT for stand-alone PV system(2018) Soufi, Ali; Mohammadi, Abdelhaq; Kheldoun, Aissa (Supervisor)Under partial shading conditions (e.g., due to buildings, trees, and clouds), multiple peaks may exist on the power-voltage (P-V) characteristic curve of photovoltaic (PV) array, leading to the conventional maximum power point tracking methods fail to extract the global maximum power point (GMPP). To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (LMPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This work describes a new fast and efficient