Thermophysical Properties Research Literature Retrieval Guide Edited by Y. S. Touloukian, J. K. Gerritsen and N. Y. Moore Second edition, revised and expanded. Book 1: Pp. xxi + 819. Book 2: Pp.621. Book 3: Pp. ix + 1315. (New York: Plenum Press, 1967.) n.p.

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Heat and Mass Transfer

In Photovoltaic (PV) systems, maximum power point tracking (MPPT) is an indispensable task. To date, various MPPT techniques have been proposed in the literature using classical and artificial intelligence methods. However, those techniques are tested on different PV systems and under different environmental conditions. In this work, we attempt to summarize and to give a comprehensive comparative study of the most adopted Artificial Intelligence (AI)-based MPPT techniques. The MPPT techniques which will be described are based on: Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), Artificial Neural Network (ANN), Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The developed MPPT controllers are tested under the same weather profile in the same photovoltaic system which is composed of a PV module, a DC-DC Buck-Boost converter and a DC load. Initially, Modelling and simulation of the system is performed using the MATLAB/Simulink environment. Thereafter, the sliding mode control is applied to the converter in order to improve its performance. In a further stage, the different steps of development for each MPPT technique are presented. Simulation is performed to confirm the validity of the proposed controllers under the same variable temperature and solar irradiance conditions. Finally, a comparative study is carried out in order to evaluate the developed techniques regarding two principal criteria: the performance and the implementation cost. The performance is evaluated using comparative analysis of the tracking speed, the average tracking error, the variance and the efficiency. To estimate the implementation cost, a classification is carried out according to the type of the used sensors, the type of circuitry and the software level complexity. Recommendations that expected to be useful for researchers in the MPPT area about the validity of each MPPT technique are given in the last section.

Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study

Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems

Second order sliding mode-based MPPT control for photovoltaic applications

The durability, reliability, and robustness of photoelectrochemical (PEC) devices are key factors for advancing the practical large-scale implementation of cost-competitive solar fuel production. We review the known degradation mechanisms occurring in water-splitting photoelectrochemical devices. The degradation of single components is discussed in detail, and the parameters and conditions which influence it are presented. Device short-term durability depends on the semiconductor material and its interface with the electrolyte. Catalyst and electrolyte degradations are considerable challenges for long-term durability. We highlight how PEC device design choices can affect the salience of alternative degradation mechanisms. The PEC device architecture and the initial operating design point are crucial for observed device performance loss. Device degradation behavior is further impacted by irradiation intensity and concentration, and by current density and concentration. Enhancing a physical understanding of degradation phenomena and investigating their effect on component properties is of utmost importance for predicting performance loss and tackling the durability challenge of PEC devices.

https://iopscience.iop.org/article/10.1088/1361-6463/aa5b11/pdf

Degradation in photoelectrochemical devices: review with an illustrative case study

Analysis and Characterization of Faults in PV Panels

Contribution to the Modeling of Ageing Effects in PV Cells and Modules

In this paper, we develop a new real-time thermoelectrical model of a photovoltaic (PV) panel that takes degradations into consideration. The degradation modes under study are the potential-induced degradation, the light-induced degradation, the ultraviolet light degradation, the moisture-induced degradation, and the cell cracks. The effect of each degradation mode on the equivalent circuit of PV cells is described by equations as a function of environmental conditions and time. The thermal behavior of the PV panels is also addressed by building a thermal model of PV panels taking into consideration the environmental and operational conditions as well as the internal heat sources. At the end, we present a complete thermoelectrical model that treats the degradations as additional events. To assess the degradation impact on the cells, the normalized efficiency is taken as the key performance index.

Real-Time Thermoelectrical Model of PV Panels for Degradation Assessment

VSAS (Variable Structure Automatic Systems) control methodology is applied to clarify the rationale behind Maximum Power Point Tracking and get the best optimization algorithm. Two algorithms are developed the Modified and Enhanced Perturb and Observe Algorithm (MEPO) the Robust Unified Control Algorithm (RUCA). The maximum power is computed online using a very simple algorithm. Compared to the other algorithms like Perturb and Observe (PO), Hill Climbing, Incremental Encoder (InCod) and and SMC approach it is proven more efficient and faster despite using low frequency commutation. The proposed MPPT has several advantages: simplicity, high convergence speed and is independent on PV array characteristics. The obtained results have proven that the MPPT is tracked even under sudden change of irradiation level.

The best MPPT algorithms by VSAS approach for Renewable Energy Sources (RES)

Autism Spectrum Disorder is a multi-parametric disorder affecting people and specially children. It is important to detect autistic children as soon as possible to conduct adequate treatment. In this paper we develop a skin conductance device capable of measuring the galvanic skin conductance and help diagnosing autistic children from the first weeks after their born. As skin conductance is directly affected by the emotional arousal. With the development of cloud services it is important that advances in technology help physicians in diagnosing autistic people.

Bechara Nehme

Papers

Analysis and Characterization of Faults in PV Panels

Contribution to the Modeling of Ageing Effects in PV Cells and Modules

Real-Time Thermoelectrical Model of PV Panels for Degradation Assessment

The best MPPT algorithms by VSAS approach for Renewable Energy Sources (RES)

Developing a skin conductance device for early Autism Spectrum Disorder diagnosis