This work introduces an experimental comparison of four Maximum Power Point Tracking (MPPT) algorithms for photovoltaic (PV) systems: Incremental Conductance (INC), Perturb and Observe (P&O), Artificial Neural Network (ANN) and Fuzzy Logic Controller (FLC).The study assesses each method based on its response time, tracking efficiency, and oscillation behavior under both constant irradiation and partial shading conditions. Experiments were conducted on two identical PV test benches with control implemented via MATLAB/Simulink and dSPACE hardware. Results show that although the P&O method is easy to be implemented, it exhibits from significant fluctuations near the Maximum Power Point (MPP). INC achieves similar efficiency but with improved voltage stability. FLC eliminates oscillations and enhances efficiency, while ANN demonstrates superior robustness and highest efficiency under partial shading by maintaining a stable duty cycle. The findings highlight the advantages of intelligent MPPT algorithms, particularly FLC and ANN, in maximizing PV energy yield and operational stability in variable environmental conditions.

Mismatch losses significantly reduce the output power of photovoltaic (PV) arrays. Among available mismatch mitigate techniques, the dynamic reconfigurable photovoltaic array (DRPVA) architectures can be considered as a promising technique to compensate the power losses. In contrast to fixed photovoltaic architectures, the DRPVA architectures modify dynamically the interconnections between the PV modules of the same PV array (PVA) according to the operating conditions. This paper presents the different approaches of DRPVA architectures proposed in the literature. These approaches are classified according to the reconfiguration strategy adopted and compared in terms of power enhancement, topology used, and additional material required. Through this study, the main constraints limiting the DRPVA efficiency are determined and discussed.

In the present study, Abaqus finite element modelling was used to explore the durability of cardiovascular stent made of AISI 316L under bending loading. In order to achieve this purpose, two geometries of stent are explored: the U-shaped and Ω-shaped stent. The cyclic loading of blood pressure doesn’t cause fracture. This result was confirmed by many studies. However, when subjected to bending loading the stent was found to experience an in-service failure. The last proved to the artery movement and depends on the increase of bending loading. However, the Ω-shape stunt permits a better distribution of load than the U-shape one.

The objective of this chapter is to describe in VHDL the design of sequential logic circuits such as latches, flip-flops, shift registers and various counters. The operation of each circuit is verified through the simulation results obtained by using the ModelSim tool. This chapter also cover the implementation and validation of the operation of sequential logic circuits in the FPGA platform.

In this chapter, five laboratory projects have been presented, namely: simple calculator design (Arithmetic Logic Unit), digital clock, traffic light control system, design and implementation of vending machine and control of a 4-phase step motor (Direction and Speed). The operation of the projects has been verified by using ModelSim simulation and subsequently implemented into an FPGA platform.

In this chapter, the FPGA technology is introduced. First, the evolution history of FPGA circuits and the fields of its application are reviewed. Then, an overview of the basic FPGA architecture is presented. A comparison of the performances between FPGA circuits and their ASIC counterparts is then established. Finally, the whole design of FPGAs as well as the different steps required for the design and the associated tools are described.

In this paper, an experimental analysis and validation of a simple reconfigurable photovoltaic (PV) array is carried out. An assessment of a new reconfiguration method based on fuzzy logic (FL) under partial shading conditions is introduced. Furthermore, a recursive least squares based irradiance estimator is proposed aiming to reduce the investment cost of the dynamic PV array. An experimental comparison with other estimators showed the high precision of the proposed estimator. The estimation error has decreased by an average of 10% compared to the first estimator (based on the PV current and voltage measurement) and by 4.28%compared to the second estimator(based on the PV current measurement). On the other hand, the results validated the FL Controller ability to switch to the appropriate configuration under prevailing shading conditions. The method was tested for a simple configuration, however it could be generalized for small-scale configurations as residential house (average power output equal to 5 kWh). To evaluate the performance of the FL method an extended simulation of dynamic PV array of 16 PV modules is also realized. The mismatch loss is mitigated by nearly 50% compared to fixed Total Cross-Tied and 8% compared to basic Irradiance Equalization techniques. (c) 2021 Elsevier Ltd. All rights reserved.

This chapter proposes a new method for reconfiguring the dynamic photovoltaic (PV) array under repeating shade conditions. The repeating shades are often caused in photovoltaic installations, especially in residential installations where PV modules can be subjected to shades occurred by nearby buildings or trees. The proposed method is based on logic gates and aims to minimize the processing time in the way that controller does not have to perform an exhaustive calculations at each shade condition to achieve the optimal configuration of the PV generator . Simulation of 2 × 2 size dynamic photovoltaic array has been carried out. Experimental tests of 1 × 1 size Dynamic Photovoltaic array under different irradiance conditions have been also conducted. The simulation and experimental tests have validated the proposed method in identification of the optimal configuration with less processing time and with an improvement in reducing power losses.

This paper presents the modeling, control and optimization of a photovoltaic water pumping system. The system consists of a DC-DC Boost converter, which is used as a link between a Solar Photovoltaic (SPV) panels and the three-phase inverter (VSI) to feed the BLDC motor. A centrifugal pump is connected to this motor in order to use the water pumped afterwards to multiple applications. Maximum Power Point Tracking (MPPT) control techniques are an essential part of improving the efficiency of photovoltaic (PV) systems. It is principally used to extract maximum possible power of the PV modules under any condition of solar irradiation. For this reason, P&O algorithm is used due to its high performance and its simplicity of implementation. The DC-DC Boost converter, compared to the various common DC-DC converters (Buck, Buck-Boost, SEPIC, Cuk…) has many benefits in SPV based applications, such as limiting the starting current of the motors. Using a BLDC motor is found to be the best option because of its high efficiency and reliability, better performance, and requires low maintenance. The considered system as well as the control strategies has been implemented in MATLAB-Simulink environment. The results show the effectiveness of the studied photovoltaic water pumping system.

When the panels in a photovoltaic generator (PVG) are subjected to Partial Shading (PS), some bypass diodes may turn on, and consequently multiple peaks in the Power -Voltage (P-V) characteristic are produced which reduces the output power. For an optimal GPV power extraction, one of emerging PS mitigation techniques is to reconfigure the PVG by altering the electrical connections between panels according to prevailing conditions. This paper presents a reconfigurable PV architecture based on irradiance equalization row approach for a PVG connected on Total cross tied (TCT) scheme. The proposed technique uses fuzzy logic as an optimization tool to obtain uniform shade dispersion throughout the PVG, either keeping the same number of panels in each row or forming rows with different number of PV panels. To evaluate the effectiveness of proposed fuzzy logic controller (FLC), extensive simulations with different shade patterns are carried out on Matlab/Simulink. Thorough analysis with the help of characteristics curves and the results obtained for the full PV chain conversion are performed. Results of simulation show that the proposed reconfiguration method exhibit superior results as compared to fixed TCT interconnection and enhanced irradiance equalization (IEq) method in terms of efficiency, power loss and response time.

Dust deposition on the front of photovoltaic /thermal collectors presents greatest issues in some regions (desertic regions). It's considered as key parameter affecting much more collector's performances. In the present work, a particular attention has been paid to dust deposition effect on the electrical and thermal performances of photovoltaic /thermal collector PV/T.A model of sheet-and-tubes PV/ T collector is developed and validated with experimental data available in literature. The obtained results show that the dust significantly affects the electrical and thermal efficiencies. An increase of dust deposition of 8g/m2 causes an electrical and a thermal output reduction respectively of 28% and 21%. Better electrical and thermal performances have been noted for PV/ T without dust. Moreover, a good agreement has been observed between obtained results and the presented results available in literature.

Photovoltaic (PV) modules suffer from a reduction of electric conversion due to the high operating temperatures of the PV cells. Hybrid photovoltaic/thermal (PV/T) technology represents an effective solution for cooling the PV cells. This paper discusses a theoretical study on a novel bi-fluid PV/T collector. One dimensional steady-state numerical model is developed, and computer simulations are performed using MATLAB. This numerical model is based on a pilot PV/T plant, installed in the Campus of the University of Catania, and was experimentally validated. The design of the proposed bi-fluid PV/T is based on a commercial WISC PV/T collector, to which are added an air channel, an aluminum absorber with fins, and a layer of thermal insulation. The analysis of the thermal behavior of the proposed collector is carried out as a function of the flow rate of the two heat transfer fluids (air and water). Finally, the comparative analysis between the conventional water-based PV/T collector, namely PV/T, and the bi-fluid (water/air-based) WISC PVT, namely PV/Tb, is presented for both winter and summer days. For the investigated winter day, the numerical results show an overall improvement of the performance of the bi-fluid PV/T module, with an increase of thermal energy transferred to the liquid side of 20%, and of 15.3% for the overall energy yield in comparison to the conventional PV/T collector. Instead, a loss of 0.2% of electricity is observed. No performance improvements were observed during the summer day.

In the case of partial shadowing or photovoltaic (PV) module failure, the power provided by photovoltaic solar array significantly decreases. A promising technique to mitigate these power losses is based on the dynamic reconfiguration of the electrical connections between the PV modules. This article proposes a reconfigurable PV architecture based on Total-Cross-Tied (TCT) configuration and improved irradiance equalization (IrEq) algorithm. The PV architecture with the proposed optimization algorithm was simulated using Matlab/Simulink environment and compared to the basic equalization irradiance algorithm. The advantages of the proposed algorithm are simplicity and meaningful provision improvements in array power generation, along with the reduced processing time.

In solar photovoltaic system, tracking the maximum power point (MPP) is challenging task due to varying climatic conditions. Moreover, the tracking algorithm becomes more complicated under the condition of partial shading due to the presence of multiple peaks in the power voltage characteristics. This paper introduces a novel method to track the global maximum power point under partially shaded conditions. The method combines an artificial neural network controller with a scanning algorithm. The PV system along with the proposed MPPT algorithm was simulated using Matlab/Simulink environment. The simulated system was evaluated under uniform and non-uniform irradiation conditions. For comparison, an improved variable step P&O with global scanning (PO&GS) and incremental conductance controller based on a fuzzy duty cycle change estimator (FLE) with direct control were used and the results show that the proposed approach is effective in tracking the MPP and presents fast response time.