Abdérafi Charki

Lifetime Estimation of a Photovoltaic Module Subjected to Corrosion Due to Damp Heat Testing

In this paper, a methodology is presented for estimating the lifetime of a photovoltaic (PV) module. Designers guarantee an acceptable level of power (80% of the initial power) up to 25 yr for solar panels without having sufficient feedback to validate this lifetime. Accelerated life testing (ALT) can be carried out in order to determine the lifetime of the equipment. Severe conditions are used to accelerate the ageing of components and the reliability is then deduced in normal conditions, which are considered to be stochastic rather than constant. Environmental conditions at normal operations are simulated using IEC 61725 standard and meteorological data. The mean lifetime of a crystalline-silicon photovoltaic module that meets the minimum power requirement is estimated. The main results show the influence of lifetime distribution and Peck model parameters on the estimation of the lifetime of a photovoltaic module.

Accelerated degradation testing of a photovoltaic module

Abstract. There are a great many photovoltaic (PV) modules installed around the world. Despite this, not enough is known about the reliability of these modules. Their electrical power output decreases with time mainly as a result of the effects of corrosion, encapsulation discoloration, and solder bond failure. The failure of a PV module is defined as the point where the electrical power degradation reaches a given threshold value. Accelerated life tests (ALTs) are commonly used to assess the reliability of a PV module. However, ALTs provide limited data on the failure of a module and these tests are expensive to carry out. One possible solution is to conduct accelerated degradation tests. The Wiener process in conjunction with the accelerated failure time model makes it possible to carry out numerous simulations and thus to determine the failure time distribution based on the aforementioned threshold value. By this means, the failure time distribution and the lifetime (mean and uncertainty) can be evaluated.

Bayesian estimation in accelerated life testing

A common problem of high-reliability computing is, on the one hand, the magnitude of total testing time required, particularly in the case of high-reliability components; and, on the other hand, the number of devices under testing. In both cases, the objective is to minimise the costs involved in testing without reducing the quality of the data obtained. One solution is based on Accelerated Life Testing (ALT) techniques which permit decreasing the testing time. Another solution is to incorporate prior beliefs, engineering experience, or previous data into the testing framework. It is in this spirit that the use of a Bayesian approach can, in many cases, significantly reduce the number of devices required. This paper presents a study of the Arrhenius-Exponential model by an evaluation of parameters using Maximum Likelihood (ML) and Bayesian methods. A Monte Carlo simulation is performed to examine the asymptotic behaviour of these different estimators.

Functional and dysfunctional analysis of a mechatronic system

A study of system reliability is generally preceded by a functional analysis, which consists of defining the material limits, the various functions and operations realized by the system and the various configurations. This stage does not give information about the modes of failure and their effects. It is necessary to complete it by a second one taking into account the dysfunctions in order to model suitably a complex system with Petri networks. In this paper, we propose to employ SADT, FMEA, SEEA and Petri networks methods to study a mechatronic system.

A Circuit-Based Approach to Simulate the Characteristics of a Silicon Photovoltaic Module With Aging

The aging of photovoltaic modules results inevitably in a decrease of their efficiency all through their lifetime utilization. An approach to simulate the evolution of electrical characteristics of a photovoltaic module with aging is presented. The photovoltaic module is modeled by an equivalent electrical circuit whose components have time-dependent characteristics determined under accelerated tests. By entering sun irradiance and temperature, I–V and P–V curves as well as efficiency evolution can be simulated over years assuming equivalent time. The methodology is applied for the case of a monocrystalline photovoltaic module modeled by a one-diode circuit and aging laws are determined with experimental results of damp heat (DH) tests 85 °C/85% RH performed by Hulkoff (2009, “Usage of Highly Accelerated Stress Test (HAST) in Solar Module Aging Procedures,” M.S. thesis, Chalmers University of Technology, Goteborg, Sweden). A power degradation rate of 0.53%/yr is found. A parametric study shows that the rundown of optical transmittance of the upper layers with aging has the most important impact by reducing the initial efficiency by 11.5% over a 25-year exposure contrary to electrical degradations which cause a decrease of 1.85% of the initial efficiency.

Bayesian estimation in accelerated life testing application on exponential-arrhenius model

A common problem of high reliability computing is, on one hand, the magnitude of total testing time required, particularly in the case of high reliability components and, on the other hand, the number of devices under test. In both cases, the objective is to minimize the costs involved in testing without reducing the quality of the data obtained. One solution is based on accelerated life testing techniques which permit to decrease testing time. Another solution is to incorporate prior beliefs, engineering experience, or previous data into the testing framework. It is in this spirit that the use of a Bayesian approach can, in many cases, significantly reduce the amount of devices required. This paper presents the study of exponential-Arrhenius model by an evaluation of parameters using maximum likelihood and Bayesian methods. A Monte Carlo simulation has been performed to examine the asymptotic behavior of these different estimators

Lifetime assessment of a photovoltaic system using stochastic Petri nets

Abstract The lifetime estimation of photovoltaic (PV) systems is an important consideration in their life cycle. This paper presents a multi-level methodology to estimate the availability and the lifetime of a PV system using stochastic Petri networks and taking into account the time distribution to failure and to repair. The following components – module, wires, and inverter – are modeled with a Petri network. The evolution of the MTBF, availability, and outages over a 30-year period is simulated for different series/parallel configurations of connected PV modules. Findings are in agreement with reported experimental results, namely the evolution of the availability which tends to be near 96% for long times. Numerical results show that the highest MTBF is 3.2 years and the lowest outage is of 11.84 days/year, which are both obtained for the string configuration. The approach is interesting for the dimensioning of a PV plant or an installation.

Behavior analysis of machines and system air hemispherical spindles using finite element modeling

Purpose – The spindle behavior of machines and systems depends largely on the choice and design quality of the mechanical components used for the displacement between different parts. As far as very high technology is concerned, air bearings are suitable, for instance, for machining a telescope mirror or for systems used in medical applications that require a micro and nanometric resolution in displacement. Therefore, air bearings play a crucial role in ensuring spindle stability in machines and systems. The static and dynamic behavior of air spindles is dependent on several parameters, such as external load, dimensions, supply pressure, manufacturing capability and fluid properties.Design/methodology/approach – This paper presents a methodology for the calculation and analysis of the stability and reliability of machine and system spindles supported by air hemispherical bearings. The static and dynamic characteristics of air spindles are calculated using the finite element method (FEM). The stochastic Re...

Reliability Estimation in Random Environment: Different Approaches

For most of the products, a real time depending variation of stress study implies the random environment approach. Several possible treatments are available to the users and each method offers different results for the same input data. The use of the equivalent constant stress, for example, gives a strong pessimism while the use of cumulative damage model requires strong computation resources. Whatever method one might choose, approximations and/or estimations are to be done in order to extend the field observed stresses values over the whole life of the product. The present paper proposes a comparison of the possible methods. A field validation is proposed and may be the subject of incoming work

Photovoltaic system lifetime prediction using Petri networks method

Photovoltaic modules and systems lifetime and availability are difficult to determine and not really well-known. This information is an important data to insure the installation performance of such a system and to prepare its recycling. The aim of this article is to present a methodology for the availability and lifetime evaluation of a photovoltaic system using the Petri networks method. Each component - module, wires and inverter - is detailed in Petri networks and several laws are used in order to estimate the reliability. Several guides (FIDES, MIL-HDBK-217 ...) allow determining the reliability of electronic components using collections of data. For photovoltaic modules, accelerated life testing are carried out for the evaluation of the lifetime which is described by a Weibull distribution. Results obtained show that Petri networks are very useful to simulate lifetime thanks to its intrinsic modularity.