To ensure the optimization of the energy generated by grid connected PV (photovoltaic) systems is necessary to plan a strategy of automatic fault detection. The analysis of current and voltage indicators have demonstrated effectiveness in the detection of permanent faults in the PV array in real time as short-circuits or open circuits present in the system. In this paper, the analysis of the evolution of these indicators is focused on the detection of temporary faults due to partial shade on the PV array or disconnection of the inverter in case of grid fluctuations of voltage or frequency to prevent islanding. These situations can be identified by observation of the evolution of both indicators and power losses due to these effects can be evaluated from them. The analysis and experimental validation were carried out in two grid connected PV systems in Spain and Algeria.Peer ReviewedPostprint (author's final draft

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Photovoltaic (PV) systems based on multistring configuration are the best effective solution, given its advantages in terms of system availability, reliability, and energy efficiency. In this particular configuration each substring has its own dc-dc converter and a dedicated maximum power search algorithm which increase the cost and complexity. In this article, an efficient centralized global maximum power tracking (GMPPT) algorithm for multistring PV array subject to partial shading conditions is proposed. The algorithm is based on artificial bee colony (ABC) as an optimization approach to provide the optimal duty cycles allowing the extraction of the optimal global maximum power from each substring. In particular, the proposed approach allows significant reduction of the required sensors to only one pair of current and voltage sensors, at the common point of connection of the overall PV strings. The simulation study has been carried out under Cadence/Pspice and MATLAB/Simulink platforms on the I-V curves to confirm the effectiveness of the proposed algorithm when several shading patterns occur. In addition, complex shading pattern of a daily profile has been also carried out to demonstrate the GMPPT finding in dynamically variable conditions. Performance comparison against particle swarm optimization based maximum power point tracking algorithm and the traditional perturb and observe method has also been carried out. The obtained simulation and experimental results have shown the effectiveness and a good tracking capability of the proposed ABC algorithm in a multistring PV array configuration under uniform and nonuniform irradiance. Index Terms-Artificial bee colony (ABC) algorithm, digital signal processor (DSP), global maximum power tracking

One of the main difficulties involved in monitoring systems is the inability to add new devices or new ways of evaluating the performance of these systems without significantly changing the topology of the monitoring system. Firstly, the incorporation of new devices, in the absence of standard communication protocols, requires the development of software for acquiring data from these devices and it is also necessary to add the functionality of each of the data that are acquired. Moreover, in photovoltaic (PV) plants connected to the grid each inverter has its own communication protocol and issues its own program online or locally to access data and plant information. These programs do not allow the inclusion of data from other inverters or for other plants even in the case of inverters from the same manufacturer. Also, it is not possible to AbstractThis paper presents a new approach for automatic supervision and remote fault detection of grid connected photovoltaic (PV) systems by means of OPC technology-based monitoring. The use of standard OPC for monitoring enables data acquisition from a set of devices that use different communication protocols as inverters or other electronic devices present in PV systems enabling universal connectivity and interoperability. Using the OPC standard allows promoting interoperation of software objects in distributed-heterogeneous environments and also allows incorporating in the system remote supervision and diagnosis for the evaluation of grid connected PV facilities. The supervision system analyses the monitored data and evaluates the expected behaviour of main parameters of the PV array: Output voltage, current and power. The monitored data and evaluated parameters are used by the fault detection procedure in order to identify possible faults present in the PV system. The methodology presented has been experimentally validated in the supervision of a grid connected PV system located in Spain. Results obtained show that the combination of OPC monitoring along with the supervision and fault detection procedure is a robust tool that can be very useful in the field of remote supervision and diagnosis of grid connected PV systems. The RMSE between real monitored data and results obtained from the modelling of the PV array were below 3.6% for all parameters even in cloudy days.

The present study analyses the degradation of thin film photovoltaic modules corresponding to four technologies: a-Si:H, a-Si:H/μc-Si:H, CIS and CdTe, under 5 years of outdoor long term exposure in Leganés, Spain. The period of outdoor exposure ranges from January 2011 to December 2015. The degradation rate and the stabilization period are analysed by using two different techniques. Moreover, the evolution of the fill factor and performance ratio is assessed. The CdTe module was found to have the highest degradation rate: −4.45%/year, while the CIS module appears to be the most stable with a degradation rate of −1.04%/year. The a-Si:H and a-Si:H/μc-Si:H modules present stabilization periods of 24 and 6 months respectively. The CdTe module degrades significantly for a period of 32 months, while the CIS module is the least degraded PV specimen over the whole experimental campaign.

Simulation is of primal importance in the prediction of the produced power and automatic fault detection in PV grid-connected systems (PVGCS). The accuracy of simulation results depends on the models used for main components of the PV system, especially for the PV module. The present paper compares two PV array models, the five-parameter model (5PM) and the Sandia Array Performance Model (SAPM). Five different algorithms are used for estimating the unknown parameters of both PV models in order to see how they affect the accuracy of simulations in reproducing the outdoor behavior of three PVGCS. The arrays of the PVGCS are of three different PV module technologies: Crystalline silicon (c-Si), amorphous silicon (a-Si:H) and micromorph silicon (a-Si:H/µc-Si:H).\ud \ud The accuracy of PV module models based on the five algorithms is evaluated by means of the Route Mean Square Error (RMSE) and the Normalized Mean Absolute Error (NMAE), calculated for different weather conditions (clear sky, semi-cloudy and cloudy days). For both models considered in this study, the best accuracy is obtained from simulations using the estimated values of unknown parameters delivered by the ABC algorithm. Where, the maximum error values of RMSE and NMAE stay below 6.61% and 2.66% respectively.Peer ReviewedPostprint (author's final draft

The analysis of the degradation of tandem amorphous silicon (a-Si:H) and microcrystalline silicon ( -Si:H): Micromorph thin-film photovoltaic (TFPV) modules and its impact on the output power of a PV array under outdoor long term exposure located in Jaén (Spain) is addressed in this work. Furthermore, the evolution of main solar cell model parameters is evaluated by means of parameters extraction techniques from monitored data of the PV system in real operation of work. The degradation rate and the stabilization period of micromorph TFPV modules, as well as the results of the evolution of each of the solar cell model parameters along the outdoor long-term exposure are analysed in order to gain a better understanding of changes in performance of micromorph TFPV modules and the behaviour of the output power of the PV generator.

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