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The photovoltaic literature contains a wide range of methods for translating the I–V curves of a solar device to other conditions of irradiance and cell temperature, different from those under which the measurements were performed. Some of these translation methods are included as part of the International Standard IEC 60891. In this paper, these techniques are classified, reviewed, and implemented to perform a deep comparative analysis between them and to discuss their suitability for converting the I–V curves of photovoltaic modules under different scenarios of irradiance and temperature. From the analysis conducted, it can be seen that the interpolation method proposed in IEC 60891 achieves accurate results when it is applied to correct small and medium irradiance and temperature gaps. If no interpolation is possible and for large irradiance corrections, other procedures described in IEC 60891 can be applied. However, certain explicit methods based on the single-diode model or on the double-diode model can overcome the most well-known approaches proposed by the standard. [ABSTRACT FROM AUTHOR]

The nine papers in this special section focus on photovoltaic module and sub-module level power electronics. Grid connected photovoltaic energy systems have experienced an explosive growth over the last decade, with a cumulative installed capacity surpassing the 400 GW milestone as of 2017. Among PV system configurations, distributed module-level converter architectures can lead to a higher energy yield by mitigating partial shading, persistent shading (soiling, snow, bird droppings, and fallen leaves), mismatch, and aging, through a higher maximum power point tracking (MPPT) efficiency. Also, distributed electronics might be the key for implementing diagnostic and prognostic actions at a module level. Among these configurations, microinverters (also known as ac-module inverter), which connect a single PV module to the grid, and PV power optimizers, which are dc–dc converters performing the MPPT function at a module level, have attracted the academic and industrial interest in the last decade. So much so, that both microinverters and dc–dc power optimizers are commercialized by tens of companies around the world, with a great variety of circuit topologies, which comprise combinations of one or more power stages, interleaved converters, resonant converters, topologies with and without isolation, etc. [ABSTRACT FROM AUTHOR]

In this paper, the use of the Dual Kalman Filter for the identification of photovoltaic system parameters is presented. The system includes the photovoltaic source, the dc/dc converter and the battery/dc bus and both its states and parameters in the actual operating conditions are identified. In particular, the proposed approach gives the confidence interval for the system settling time, which is used for the real-time optimization of the perturbative maximum power point tracking algorithm. The proposed technique is implemented by using a Field-Programmable Gate Array and it is validated by means of both simulation and experimental results. [ABSTRACT FROM PUBLISHER]

The long power production warranties guaranteed by the manufacturers of photovoltaic (PV) modules (25 years) are a vital factor for the economical viability of PV systems. Nevertheless, recent studies have demonstrated that the modules may experience an early degradation, which turns into the reduction of the power production or even the damage of the entire PV module. In this paper, a method aimed at detecting the module degradation is introduced. It detects and quantifies the degradation by means of two indicators, which are aimed at estimating the increment of the modules series resistance, this parameter being one of the most affected by some degradation mechanisms. The increase of the series resistance value is estimated through the evaluation of the error in predicting the position of the maximum power point, which is obtained by comparing the experimental measurements with the single-diode model. The proposed method is experimentally validated, and it is compared with other methods reported in the literature. The results show that the proposed indicators are able to accurately estimate the increments of the series resistance with a low sensitivity to the irradiance and temperature values. This feature improves the accuracy and the reliability of the diagnosis processes and monitoring systems. [ABSTRACT FROM PUBLISHER]

In practical photovoltaic (PV) installations the operating conditions of the panels the PV array is made of are different owing to different factors. Such irregular conditions are known as 'mismatching conditions' and produce multiple maxima in the power-voltage curves of any PV array. The traditional maximum power point tracking (MPPT) techniques are able to track one of those maxima, but they cannot guarantee the extraction of the maximum power the PV array would be able to deliver. To overcome this problem, many techniques have been presented in the literature: they use one converter for the entire array (centralised MPPT), one converter for each part of the array (distributed MPPT) or they reconfigure the PV array (RMPPT). This paper presents the general architectures used by 61 different MPPT techniques, by discussing their main advantages and disadvantages, in order to give to the reader a comprehensive view of both the control strategies and the architectures for extracting the maximum power from a mismatched PV field. Moreover, the widely adopted techniques for each hardware structure are presented in a structured and compact way, thus providing to the reader some guidelines regarding the technique's operation principle and hardware requirements. [ABSTRACT FROM AUTHOR]

This paper introduces a novel maximum power point tracking (MPPT) technique aimed at maximizing the power produced by photovoltaic (PV) systems. The largest part of the MPPT approaches presented in the literature are based on the sensing of the PV generator voltage. On the contrary, in this paper, a current-based technique is proposed: the sensing of the current in the capacitor placed in parallel with the PV source is one of the innovative aspects of the proposal. A dual control technique based on an inner current loop plus an outer voltage loop allows to take profit of the fast current tracking capability of the inner current loop while the voltage loop benefits from the logarithmic dependency of the PV voltage on the irradiation level. The features of the proposed algorithm, particularly in terms of tracking of irradiation variations and disturbance rejection, are supported by theoretical analysis, simulations, and experimental results. The technique described in this paper is patent pending. [ABSTRACT FROM PUBLISHER]

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In this paper, a novel maximum power point tracking algorithm based on the perturb-and-observe (P&O) technique is introduced. The novelty of the approach is represented by the perturbation of more control variables, rather than just one. This allows the increase of the power extracted from the photovoltaic (PV) field as compared to the case of perturbation of a single control variable. The proposed technique overcomes the limitations of any existing tracking technique dedicated to PV arrays exhibiting a unique maximum power point, thus not only of the P&O approach, whenever dynamic constraints ensuring the correct system behavior must be fulfilled too. The proposed multivariable approach is described by means of its application to a single-stage one-cycle controlled PV inverter. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by Maffezzoni and colleagues on an electrothermal macromodel for photovoltaic (PV) module, one by Velasco-Quesada and colleagues on an electrical array configuration approach on the PV plant and another by Romero-Cadaval and colleagues on a grid-connected PV system which employs two parallel-connected inverters.

In double-stage grid-connected photovoltaic (PV) in. verters, the dynamic interactions among the dc/dc and dc/ac stages and the maximum power point tracking (MPPT) controller may reduce the system performances. In this paper, the detrimental effects, particularly in terms of system efficiency and MPPT performances, of the oscillations of the PV array voltage, taking place at the second harmonic of the grid frequency are evidenced. The use of a proper compensation network acting on the error signal between a reference signal provided by the MPPT controller and a signal that is proportional to the PV array voltage is proposed. The guidelines for the proper joint design of the compensation network (which is able to cancel out the PV voltage oscillations) and of the main MPPT parameters are provided in this paper. Simulation results and experimental measurements confirm the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The DC-link capacitor is one of the components that are more prone to faults in energy-distributed systems based on voltage source inverters. A predictive maintenance approach should allow to foresee the risk of an unexpected system shutdown. In this study, a two-stage diagnostic approach that is aimed at determining the health status of the DC-link capacitor in a single-phase grid-connected PV system was proposed. The equivalent series resistance (ESR) and the capacitance (C) values were used as indicators in the estimation of the degradation stage. Electrochemical impedance spectroscopy (EIS) was used to estimate the impedance curve of the DC-link capacitor, and a multi-fitting algorithm allowed us to determine the ESR and C parameters. A comparison between the estimated values C and ESR and the nominal values was used to quantify the fault severity. It was demonstrated that the EIS allowed the determination of the capacitor impedance regardless of the actual operating conditions of the photovoltaic generator, such as during irradiance changes and with the maximum power point algorithm turned off. By using the capacitor simplified model and a multi-fitting algorithm, the C and ESR values were estimated with an error that was lower than 1%. An analysis of the hardware required to implement the proposed approach in real applications by achieving the desired accuracy was also proposed. [ABSTRACT FROM AUTHOR]

Power processing systems will be a key factor of future photovoltaic (PV) applications. They will play a central role in transferring, to the load and/or to the grid, the electric power produced by the high-efficiency PV cells of the next generation. In order to come up the expectations related to the use of solar energy for producing electrical energy, such systems must ensure high efficiency, modularity, and, particularly, high reliability. The goal of this paper is to provide an overview of the open problems related to PV power processing systems and to focus the attention of researchers and industries on present and future challenges in this field. [ABSTRACT FROM AUTHOR]

In this paper, the design of the one-cycle controller of a single-stage inverter for photovoltaic applications is carried out by means of a multiobjective strategy to optimize inverter performance at both high and low insolation levels. Design constraints that account for different weather conditions are adopted. The optimization algorithm also provides useful information concerning the system sensitivity with respect to each of the controller parameters. This allows the design of a maximum power point tracking perturb and observe controller that significantly improves inverter performance. Experimental measurements confirm the predictions of theoretical and simulation results. [ABSTRACT FROM AUTHOR]

One of the major drawbacks of photovoltaic (PV) systems is represented by the effect of module mismatching and of partial shading of the PV field. Distributed maximum power point tracking (DMPPT) is a very promising technique that allows the increase of efficiency and reliability of such systems. Modeling and designing a PV system with DMPPT is remarkably more complex than implementing a standard MPPT technique. In this paper, a DMPPT system for PV arrays is proposed and analyzed. A dc and small-signal ac model is derived to analyze steady-state behavior, as well as dynamics and stability, of the whole system. Finally, simulation results are reported and discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • A neural network is used to detect faults in photovoltaic modules. • According to the shape of the current vs voltage curve, the faults are classified. • The training uses synthetic curves and the test is performed also on experimental data. • The points are normalized and resampled radially to improve the results. • With two hidden layers of 100 neurons each, the hit rate reaches more than 98.5%. In this paper a model-based procedure for fault detection and diagnosis of photovoltaic modules is presented. A four-layered feedforward artificial neural network learns the correlation between the features of the current vs. voltage curve and the environmental variables, which are the irradiance and the temperature. This correlation describes the behavior of the module at normal conditions. Moreover, the effect of anomalous variation of some parameters is learnt and correlated to the shape of the same curve, thus associated to a specific failure mechanism and to some assigned ranges quantifying the fault severity. The neural network is trained by using synthetic curves simulated by employing the single diode model and some well assessed and validated translation formulae. The obtained results over the simulated set of curves with different failures allow to achieve a classification error lower than 1.5%. The proposed approach has been also validated for detecting anomalous increases of the series resistance in a large experimental set of curves; in this case, a classification error of 2.7% has been achieved. [ABSTRACT FROM AUTHOR]

The articles in this special section focus on photovoltaic power systems (PVS). The market for photovoltaic power systems has increased exponentially, but the government subsidies have been reduced dramatically in recent years. The return of the investment mainly relies on selling the energy produced during the PV plant lifetime. Thus, the PV system must be designed and controlled properly in order to ensure its lifetime and reliability but also new features are required: 1) real-time monitoring of the energy production; 2) on-site diagnostic functions; and 3) estimation of the residual life. The degradation of electronic components and PV cells can be accelerated by various unpredictable and unavoidable phenomena. [ABSTRACT FROM PUBLISHER]

[Display omitted] • Novel method to identify the SDM parameters and operating conditions of a PV module. • It does not require irradiance nor temperature, but identifies both accurately. • The method can be applied using only a small portion of the curve around the MPP. • Fort the first time, a comparison of various fitting approaches is presented. • It is proven that fitting approach is a factor to be considered for I – V curve fitting. One solution for online condition monitoring of photovoltaic (PV) modules is to identify single-diode model parameter values from measured current–voltage (I – V) curves. By this way, use of expensive thermal cameras and radiometric sensors utilized in traditional monitoring methods can be avoided. Unfortunately, most of the parameter identification methods require measurements of the operating conditions, i.e., irradiance and temperature. This article proposes a novel procedure for identification of the single-diode model parameter values along with the operating irradiance and temperature values from measured I – V curves without needing any other measurement. The only inputs of the proposed procedure are the I – V curve measurements at the actual operating conditions together with the parameter values of the module model in standard test conditions. The proposed procedure is experimentally validated using I – V curves of three PV module types measured from two different locations. Both the whole I – V curves or only a part of them, in a limited voltage range, are considered. Moreover, I – V curve measurements with an emulated increase of the series resistance are used to demonstrate the correctness of the identified series resistance values. It is shown that the procedure identifies the operating irradiance and temperature with high accuracy even during sharp irradiance transitions and low irradiance conditions and identifies series and shunt resistances very reliably under nearly constant high irradiance conditions. Moreover, for the first time, a comprehensive comparison of various fitting approaches based on root-mean-square error (RMSE) minimization, including two novel approaches, is presented. The results show that the different fitting approaches based on RMSE minimization affect the accuracy of the parameters identification in a different way, this meaning that the used fitting approach is a factor that should be considered when implementing model parameter identification by curve fitting. [ABSTRACT FROM AUTHOR]

The performance of four thin-film photovoltaic modules is analyzed after an initial stabilization period and a subsequent outdoor exposition. The seasonal variations and the degradation rates of a single-junction hydrogenated amorphous silicon (a-Si:H) module, a tandem amorphous microcrystalline Silicon (a-Si/ μ c-Si) module, a heterostructure cadmium sulfide-cadmium telluride (CdS/CdTe) module and a copper indium gallium selenide (CIGS) are examined and correlated to spectral changes. The I–V curves have been measured every 5 min; the electrical parameters and parasitic resistances have been identified. By exploiting a number of experimental measurements acquired within a narrow interval of irradiance and cell temperature, a novel mathematical model has been developed and fitted: it considers a stationary seasonal variation component and a linear long-term degradation component. The results show annual power degradation rates of 4.0% for the a-Si:H module, 3.4% for the a-Si/ μ c-Si and 3.5% for the CdS/CdTe, whereas for the CIGS module the annual degradation is not significant, i.e. 0.2%. [Display omitted] [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) arrays are usually formed by strings of panels connected in parallel creating the series-parallel (SP) configuration. Additional connections can be implemented among the strings of the SP configuration to mitigate a particular mismatching profile. Those connections may follow regular or irregular patterns to form regular configurations , e.g. Total Cross-Tied (TCT), Honey-Comb (HC) or Bridge-Linked (BL), or irregular configurations , respectively. In literature there are proposed models for particular array configurations; however, there has not been reported yet a general model capable to describe the behavior of any regular or irregular configuration. Therefore, testing multiple configurations require to parameterize or design multiple models. This paper introduces a procedure for reproducing the electrical behavior of any PV array operating under uniform or mismatched conditions, which eliminates the requirement of using multiple models to evaluate different configurations. The procedure is based in dividing the array into sub-arrays to construct a system of non-linear equations for each sub-array, which is solved by using the Trust-Region Dogleg method. The proposed approach is validated by comparing the results provided by the proposed model with the circuital implementation of the same PV array in a commercial software and with the data produced with an experimental test bed. Such comparisons put into evidence the satisfactory performance of the general modeling procedure in the reproduction of the electrical behavior of both regular and irregular arrays. [ABSTRACT FROM AUTHOR]