Electrical Faults Modeling of the Photovoltaic Generator

International audienceIn this paper, we presented a new methodology for the mathematical modeling of the photovoltaic generator's characteristics based on known electrical laws. This proposed new methodology in this work consists of a three new algorithms, each one presents the characteristic of the cell, group of cells, module, string and generator, when one or more of its components : cells, bypass diodes and blocking diodes subjected to these types of defaults: reversed polarity, open circuit, short circuit or impedance. The three new algorithms obtained can facilitate the prediction for the prognosis or the detection for the diagnosis of these photovoltaic generator's defaults

Pour une démocratie socio-environnementale : cadre pour une plate-forme participative « transition écologique »

Contribution publiée in Penser une démocratie alimentaire Volume II – Proposition Lascaux entre ressources naturelles et besoins fondamentaux, F. Collart Dutilleul et T. Bréger (dir), Inida, San José, 2014, pp. 87-111.International audienceL’anthropocène triomphant actuel, avec ses forçages environnementaux et sociaux, est à l’origine de l’accélération des dégradations des milieux de vie sur Terre et de l’accentuation des tensions sociales et géopolitiques. Passer à un anthropocène de gestion équitable, informé et sobre vis-à-vis de toutes les ressources et dans tous les secteurs d’activité (slow anthropocene), impose une analyse préalable sur l’ensemble des activités et des rapports humains. Cette transition dite « écologique », mais en réalité à la fois sociétale et écologique, est tout sauf un ajustement technique de secteurs dits prioritaires et technocratiques. Elle est avant tout culturelle, politique et philosophique au sens propre du terme. Elle est un horizon pour des trajectoires de développement humain, pour des constructions sociales et économiques, censées redéfinir socialement richesse, bien-être, travail etc. La dénomination « transition écologique » est largement véhiculée, mais ses bases conceptuelles ne sont pas entièrement acquises ni même élaborées. Dans ce contexte, les étudiants en première année de Master BioSciences à l’Ecole Normale Supérieure (ENS) de Lyon ont préparé une première étude analytique de ce changement radical et global de société pour mieux comprendre dans quelle société ils souhaitent vivre, en donnant du sens aux activités humaines présentes et à venir. Une trentaine de dossiers sur divers secteurs d’activités et acteurs de la société ont été produits et ont servis de support à cette synthèse. Plus largement, le but est de construire un socle conceptuel et une plate-forme de travail sur lesquels les questions de fond, mais aussi opérationnelles, peuvent être posées et étudiées en permanence. Cette démarche participative est ouverte à la collectivité sur le site http://institutmichelserres.ens-lyon.fr/

Exposing Deep Representations to a Recurrent Expansion with Multiple Repeats for Fuel Cells Time Series Prognosis

International audienceThe green conversion of proton exchange membrane fuel cells (PEMFCs) has received particular attention in both stationary and transportation applications. However, the poor durability of PEMFC represents a major problem that hampers its commercial application since dynamic operating conditions, including physical deterioration, have a serious impact on the cell performance. Under these circumstances, prognosis and health management (PHM) plays an important role in prolonging durability and preventing damage propagation via the accurate planning of a condition-based maintenance (CBM) schedule. In this specific topic, health deterioration modeling with deep learning (DL) is the widely studied representation learning tool due to its adaptation ability to rapid changes in data complexity and drift. In this context, the present paper proposes an investigation of further deeper representations by exposing DL models themselves to recurrent expansion with multiple repeats. Such a recurrent expansion of DL (REDL) allows new, more meaningful representations to be explored by repeatedly using generated feature maps and responses to create new robust models. The proposed REDL, which is designed to be an adaptive learning algorithm, is tested on a PEMFC deterioration dataset and compared to its deep learning baseline version under time series analysis. Using multiple numeric and visual metrics, the results support the REDL learning scheme by showing promising performances

Smart Algorithm Based on the Optimization of SVR Technique by k-NNR Method for the Prognosis of the Open-Circuit and the Reversed Polarity Faults in a PV Generator

International audience– This paper deals with a new smart algorithm allowing open-circuit and reversed polarity faults prognosis in photovoltaic generators. Its contribution lies on the optimization of support vector regression (SVR) technique by a k-NN regression tool (k-NNR) for undetermined outputs. To testing the performance of the proposed algorithm, we used a significant data base containing the generator functioning history, and as indicators we selected variance, standard deviation, Confidence interval, absolute and relative errors. Nomenclature PV Photovoltaic SVM Support Vector Machines SVR Support Vector Regression k-NNR k-Nearest Neighbor Regression X SVR input vector Y SVR output vector f Linear function Ф Nonlinear mapping function w Weight vector e Squared loss function x Problem variable x * New problem variable α Lagrange multipliers N Number of classes m Number of index of minimum distances I / V Current / Voltage IPH Photocurren

Development of a New Methodology for Modeling the PV Generator Behavior in the Presence of Open-Circuit and Short-Circuit Faults

International audience— In this paper, we proposed a new methodology for the faults photovoltaic generator modeling, especially when it subjected to the open-circuit and short-circuit faults at its components: cells, bypass diodes and blocking diodes. The highlight of the proposed algorithm focused on the mathematical modeling that based on known electrical laws, of the IV characteristic of the faulty PV generator. This model is able to develop a rich database , containing six electrical faults types, which can uses in the diagnosis area of the photovoltaic generators. NOMENCLATURE I_SRC = String Reversed Current. I_SSC = String Supplied Current. I_Cell = Cell Current. V_Cell = Cell Voltage. I_Cell_Short_Circuit = Cell Short Circuit Current. V_Cell_Open_Circuit = Cell Open Circuit Voltage. nc = Cells Number. I_Group = Group Current. V_Group = Group Voltage. I_Bypass_Diode = Bypass Diode Current. ng = Groups Number. I_Module = Module Current. V_Module = Module Voltage. nm = Modules Number. I_String = String Current. V_String = String Voltage. ns = Strings Number. I_PV = Generator Current. V_PV = Generator Voltage. PHI = Photo-Current. I 0 = Reverse Saturation Current. DTV = Diode Thermal Voltage. a = Diode Ideality Factor. R S = Cell Series Resistance. R SH = Cell Shunt Resistance. V / I = Voltage / Current. V imposed = Voltage Imposed

Optimization of SVM Classifier by k-NN for the Smart Diagnosis of the Short-Circuit and Impedance Faults in a PV Generator

International audienceThis paper deals with a new algorithm allowing short-circuit and impedance faults smart diagnosis of PV generators. It is based on the use of the SVM technique for the classification of observations not located in its margin, otherwise the proposed algorithm is used a k-NN method. A PV generator database containing observations distributed over classes is used for testing the new algorithm performance, which shows therefore its contribution and its effectiveness in the diagnosis area. * Parameter j of new observation x *. I' Identity matrix. J Tuning parameter for error accepted. I Current. V Voltage. P Power. PH Photocurrent. I/V Cell Current / Voltage of PV cell. I/V Group Current / Voltage of PV group. I/V Module Current / Voltage of PV module. I/V String Current / Voltage of PV string. I Bypass_Diode Bypass diode current. R s series resistance. t Temperature

Faults modeling of the impedance and reversed polarity types within the PV generator operation

International audience— In this paper, we proposed a new mathematical model of the I-V characteristic of a faulty photovoltaic generator. It presents its behavior in normal and faulty operations. In particular, when its basic components such as cells, bypass and blocking diodes are subjected to the impedance or reversed polarity faults. The developed model of the faulty PV generator will allow studying of the I-V characteristic, measures the tolerances of the technical functions, avoids numerous experiments, and ensure better assessment of fault consequences. NOMENCLATURE I ph = Photocurrent standard condition. I 0 = Reverse saturation current of the diode. Z = Electrical impedance R S = Cell series resistance. nc: ncg / ncp = Cell number: good / defective. ng: ngg / ngp = Group number: good / defective. nm: nmg / nmp = Module number: good / defective. ns: nsg / nsp = String number: good / defective. nfg / nfp = Good / defective generator. N Cells = Number of cells in each group. N Groups = Number of groups in each module. N Modules = Number of modules in each string. N Strings = Number of strings in each generator. V / I = Voltage / current. P = Power. I Bypass_Diode = Bypass diode current. V Cell_Imposed = Voltage imposed. a = Diode ideality factor. V t = Diode Thermal voltage

New Algorithm for the IV Characteristic Modeling of the Photovoltaic Generator Malfunction within Impedance and Reversed Polarity Faults

International audience— In this paper, we proposed a new methodology that can improved and developed the faults detection and diagnosis methods of the photovoltaic generator, especially when it subjected to the impedance and reversed polarity defects. This proposed algorithm is based on the mathematical modeling of the IV characteristic, of the faulty photovoltaic generator hierarchies as: cell, cells group, module, string and the entire generator, when they submitted to one or more of: cells, bypass and blocking diodes in impedance and reversed polarity faults. This new methodology can facilitated the study of the faulty generator characteristics, and obtained a database for the learning phase and the classification of the new observations collected on the system during its operation. NOMENCLATURE I_phi = Photo-Current. N_Cells = Cells Number in Each Group. N_Groups = Groups Number in Each Module. N_Modules = Modules Number in Each String. N_Strings = Strings Number in the Generator. V_Cell_Imp = Cell Voltage Imposed. I_Cells = Cell Current. V_Cells = Cell Voltage. I_PV = Generator Current. V_PV = Generator Voltage. R_S = Cell Series Resistance. R_SH = Cell Shunt Resistance. I_S1 = Reverse Saturation Current of 1 st Diode. I_S2 = Reverse Saturation Current of 2 nd Diode. m1 = Ideality Factors of 1 st Diode. m2 = Ideality Factors of 2 nd Diode

Modeling the PV generator behavior submit to the open-circuit and the short-circuit faults

International audience— In this paper, we proposed a new mathematical model of a faulty photovoltaic generator operation. It presents its behavior, when it's subjected to the open-circuit and the short-circuit faults at its basic components as: cells, bypass diodes and blocking diodes. Such kind of modeling will allow developing fault detection and diagnosis methods. Indeed, the proposed model will be used to set normal and fault operation conditions database, which will facilitate learning and classifications phases. NOMENCLATURE PV = Photovoltaic Generator. phi = Photocurrent. V Cell_Open-circuit = Open-Circuit Voltage of Cell. I Cell_Short-circuit = Short-Circuit Current of Cell. I 0 = Reverse Saturation Current of the Diode. R S = Cell Series Resistance. R SH = Cell Shunt Resistance. nc: ncg / ncp = Cell Number: Good / Defective. ng: ngg / ngp = Group Number: Good / Defective. nm: nmg / nmp = Module Number: Good / Defective. ns: nsg / nsp = String Number: Good / Defective. nfg / nfp = Good / Defective Generator. N Cells = Cells Number in each Group. N Groups = Groups Number in each Module. N Modules = Modules Number in each String. N Strings = Strings Number in the Generator. V / I = Voltage / Current. P = Power. V Cell_imposed = Voltage Imposed. DTV = Diode Thermal Voltage. a = Diode Ideality Factor

Diagnosis and management of asymptomatic bacteriuria in kidney transplant recipients: a survey of current practice in Europe

International audienceBackgroundAsymptomatic bacteriuria is frequent in kidney transplant recipients (KTRs). However, there is no consensus on diagnosis or management. We conducted a European survey to explore current practice related to the diagnosis and management of asymptomatic bacteriuria in adult KTRs.MethodsA panel of experts from the European Renal Association–European Dialysis Transplant Association/Developing Education Science and Care for Renal Transplantation in European States working group and the European Study Group for Infections in Compromised Hosts of the European Society of Clinical Microbiology and Infectious Diseases designed this cross-sectional, questionnaire-based, self-administered survey. Invitations to participate were e-mailed to European physicians involved in the care of KTRs.ResultsTwo hundred and forty-four participants from 138 institutions in 25 countries answered the survey (response rate 30%). Most participants [72% (176/244)] said they always screen for asymptomatic bacteriuria in KTRs. Six per cent (15/240) reported never treating asymptomatic bacteriuria with antibiotics. When antimicrobial treatment was used, 24% of the participants (53/224) said they would start with empirical antibiotics. For an episode of asymptomatic bacteriuria caused by a fully susceptible microorganism and despite no contraindications, a majority of participants (121/223) said they would use a fluoroquinolone (n = 56), amoxicillin/clavulanic acid (n = 38) or oral cephalosporins (n = 27).ConclusionsScreening for and treating asymptomatic bacteriuria are common in KTRs despite uncertainties around the benefits and harms. In an era of antimicrobial resistance, further studies are needed to address the diagnosis and management of asymptomatic bacteriuria in these patients