A Smart Algorithm for the Diagnosis of Short-Circuit Faults in a Photovoltaic Generator

International audienceThis paper deals with a smart algorithm allowing short-circuit faults detection and diagnosis of PV generators. The proposed algorithm is based on the hybridization of a support vector machines (SVM) technique optimized by a k-NN tool for the classification of observations on the classifier itself or located in its margin. To test the proposed algorithm performance, a PV generator database containing observations distributed over classes is used for simulation purposes

A Regression Algorithm for the Smart Prognosis of a Reversed Polarity Fault in a Photovoltaic Generator

International audienceThis paper deals with a smart algorithm allowing reversed polarity fault diagnosis and prognosis in PV generators. The proposed prognosis (prediction) approach is based on the hybridization of a support vector regression (SVR) technique optimized by a k-NN regression tool (K-NNR) for undetermined outputs. To test the proposed algorithm performance, a PV generator database containing sample data is used for simulation purposes

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

Contribution des emetteurs recepteurs infra rouge a la navigation d'un robot tailleur de vigne

SIGLECNRS TD Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Strong formulations for a capacitated multi-vehicle Production-distribution Problem

International audienc

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

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

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

Strong formulations for a capacitated multi-vehicle Production-distribution Problem

International audienc

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