000			05477nam a22002657a 4500
008			201210b2024 a|||f bm|| 00| 0 eng d
024	7		_a0000-0002-5903-6409 _2ORCID
040			_aEG-CaNU _cEG-CaNU
041	0		_aeng _beng _bara
082			_a621
100	0		_aAhmed Tarek Mohamed Ibrahim _93283
245	1		_aPV Modeling with MPPT Using Different Optimization Techniques _c/Ahmed Tarek Mohamed Ibrahim
260			_c2024
300			_a84 p. _bill. _c21 cm.
500			_3Supervisor: Ahmed G. Radwan
502			_aThesis (M.A.)—Nile University, Egypt, 2024 .
504			_a"Includes bibliographical references"
505	0		_aContents: Contents Page Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Chapters: 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.1 Thesis scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.2 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2. Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2 Photovoltaic (PV) modelling . . . . . . . . . . . . . . . . . . . . . 18 2.2.1 Empirical models . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.2 Numerical models . . . . . . . . . . . . . . . . . . . . . . . 20 2.2.3 Analytical models . . . . . . . . . . . . . . . . . . . . . . . 21 2.3 Meta-Heuristic Techniques . . . . . . . . . . . . . . . . . . . . . . . 25 2.3.1 Single solution-based techniques . . . . . . . . . . . . . . . . 27 2.3.2 Population based techniques . . . . . . . . . . . . . . . . . . 28 2.3.3 Recent advancements and hybrid approaches . . . . . . . . 32 2.4 Maximum Power Point Tracking (MPPT) . . . . . . . . . . . . . . 34 2.4.1 Conventional MPPT Techniques . . . . . . . . . . . . . . . 35 5 2.4.2 Global MPPT Techniques . . . . . . . . . . . . . . . . . . . 40 2.4.3 Hybrid MPPT Techniques . . . . . . . . . . . . . . . . . . . 44 3. PV Modeling using different optimization techniques . . . . . . . . . . . 46 3.1 Meta-Heuristic Optimization Techniques for PV Parameters Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.1.1 Water Cycle Algorithm (WCA) . . . . . . . . . . . . . . . . 47 3.1.2 The Arithmetic Optimization Algorithm (AOA) . . . . . . . 49 3.2 The PV mathematical model . . . . . . . . . . . . . . . . . . . . . 55 3.3 Problem Formulation, Results and Discussion . . . . . . . . . . . . 57 3.4 PI and FOPI Controller . . . . . . . . . . . . . . . . . . . . . . . . 61 3.5 DC-DC converter control method . . . . . . . . . . . . . . . . . . . 65 3.6 DC-DC converter results with different controller types . . . . . . . 68 4. Improved MPPT for Partially Shaded PV Systems through Accelerated Particle Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . 74 4.1 The Mathematical Model of the used PV Model . . . . . . . . . . . 76 4.2 DC–DC Converter Design . . . . . . . . . . . . . . . . . . . . . . . 77 4.3 Proposed MPPT algorithm . . . . . . . . . . . . . . . . . . . . . . 79 4.3.1 Particle Swarm Optimization Algorithm(PSO) . . . . . . . 79 4.3.2 Accelerated PSO Algorithm(APSO) . . . . . . . . . . . . . 81 4.4 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5. Conclusions and Future Work . . . . . . . . . . . . . . . . . . . . . . . . 86 6. List of Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
520	3		_aAbstract: The usage of PV systems as an effective source of renewable energy has increased significantly in recent years. However, PV systems are inherently nonlinear and affected by varying weather conditions, which makes it challenging to get the maximum power from the system. This thesis proposes the use of optimization techniques to model PV systems and achieve MPPT under varying conditions of weather. A comprehensive literature review is conducted to identify the relevant optimization techniques and MPPT algorithms. A mathematical model of a PV system is developed that captures its behavior under varying weather conditions, and the selected optimization algorithms are integrated into the model to achieve MPPT. The performance of the optimization techniques and MPPT algorithms is validated using real data from a real PV system, and the results are compared with conventional MPPT techniques. The proposed approach demonstrates the effectiveness of optimization techniques in modeling PV systems and achieving MPPT, and provides insights into the design and optimization of PV systems for practical applications. Keywords: PV Modules , Optmization Techniques, Maximum Power Point Tracking (MPPT), Metaheuristic Algorithms.
546			_aText in English, abstracts in English and Arabic
650		4	_aMSD _9317
655		7	_2NULIB _aDissertation, Academic _9187
690			_aMSD _9317
942			_2ddc _cTH
999			_c10514 _d10514