21 resultados para PV plants

em Universidad Politécnica de Madrid


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Field data of soiling energy losses on PV plants are scarce. Furthermore, since dirt type and accumulation vary with the location characteristics (climate, surroundings, etc.), the available data on optical losses are, necessarily, site dependent. This paper presents field measurements of dirt energy losses (dust) and irradiance incidence angle losses along 2005 on a solar-tracking PV plant located south of Navarre (Spain). The paper proposes a method to calculate these losses based on the difference between irradiance measured by calibrated cells on several trackers of the PV plant and irradiance calculated from measurements by two pyranometers (one of them incorporating a shadow ring) regularly cleaned. The equivalent optical energy losses of an installation incorporating fixed horizontal modules at the same location have been calculated as well. The effect of dirt on both types of installations will accordingly be compared.

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The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

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This paper details an investigation into the appearance of hot-spots in two large grid-connected photovoltaics (PV) plants, which were detected after the visual inspection of trackers whose energy output was decreasing at anomalous rate. Detected hot-spots appeared not only in the solar cells but also in resistive solder bonds (RSB) between cells and contact ribbons. Both types cause similar irreversible damage to the PV modules, but the latter are the main responsible for the detected decrease in energy output, which was confirmed in an experimental testing campaign. The results of this investigation, for example, how hot-spots were detected or their impact on the output power of PV modules, may be of interest for the routine maintenance of large grid-connected PV plants.

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The PVCROPS project (PhotoVolta ic Cost r€duction, Reliability, Operational performance, Prediction and Simulation), cofinanced by European Commission in the frame of Seventh Framework Programme, has compiled in the “Good and bad practices: Manual to improve the quality and reduce the cost of PV systems” a collection of good and bad practices in actual PV plants . All the situations it collects represent the state-of-the-art of existing PV installations all around Europe. They show how the different parts of an installation can be implem ented properly or not. The aim of this manual is to represent a reference text which can help any PV actor (installers, electricians, maintenance operators, owners, etc.) not only to check and improve an already existing installation but will also, and mainly, avoid the previously known bad practices for the construction of a new PV installation. Thus, solving a priori the known errors, new PV installations will be more reliable, efficient and cost-effective and can recover the initial investment in a shorter time. The manual is going to be free available in the PVCROPS website in several languages.

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Strict technical quality assurance procedures are essential for PV plant bankability. When large-scale PV plants are concerned, this is typically accomplished in three consecutive phases: an energy yield forecast, that is performed at the beginning of the project and is typically accomplished by means of a simulation exercise performed with dedicated software; a reception test campaign, that is performed at the end of the commissioning and consists of a set of tests for determining the efficiency and the reliability of the PV plant devices; and a performance analysis of the first years of operation, that consists in comparing the real energy production with the one calculated from the recorded operating conditions and taking into account the maintenance records. In the last six years, IES-UPM has offered both indoor and on-site quality control campaigns for more than 60 PV plants, with an accumulated power of more than 300 MW, in close contact with Engineering, Procurement and Construction Contractors and financial entities. This paper presents the lessons learned from such experience.

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Actual system performance of a PV system can differ from its expected behaviour.. This is the main reason why the performance of PV systems should be monitored, analyzed and, if needed, improved on. Some of the current testing procedures relating to the electrical behaviour of PV systems are appropriated for detecting electrical performance losses, but they are not well-suited to reveal hidden defects in the modules of PV plants and BIPV, which can lead to future losses. This paper reports on the tests and procedures used to evaluate the performance of PV systems, and especially on a novel procedure for quick on-site measurements and defect recognition caused by overheating in PV modules located in operating PV installations.

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Esta tesis doctoral presenta un procedimiento integral de control de calidad en centrales fotovoltaicas, que comprende desde la fase inicial de estimación de las expectativas de producción hasta la vigilancia del funcionamiento de la instalación una vez en operación, y que permite reducir la incertidumbre asociada su comportamiento y aumentar su fiabilidad a largo plazo, optimizando su funcionamiento. La coyuntura de la tecnología fotovoltaica ha evolucionado enormemente en los últimos años, haciendo que las centrales fotovoltaicas sean capaces de producir energía a unos precios totalmente competitivos en relación con otras fuentes de energía. Esto hace que aumente la exigencia sobre el funcionamiento y la fiabilidad de estas instalaciones. Para cumplir con dicha exigencia, es necesaria la adecuación de los procedimientos de control de calidad aplicados, así como el desarrollo de nuevos métodos que deriven en un conocimiento más completo del estado de las centrales, y que permitan mantener la vigilancia sobre las mismas a lo largo del tiempo. Además, los ajustados márgenes de explotación actuales requieren que durante la fase de diseño se disponga de métodos de estimación de la producción que comporten la menor incertidumbre posible. La propuesta de control de calidad presentada en este trabajo parte de protocolos anteriores orientados a la fase de puesta en marcha de una instalación fotovoltaica, y las complementa con métodos aplicables a la fase de operación, prestando especial atención a los principales problemas que aparecen en las centrales a lo largo de su vida útil (puntos calientes, impacto de la suciedad, envejecimiento…). Además, incorpora un protocolo de vigilancia y análisis del funcionamiento de las instalaciones a partir de sus datos de monitorización, que incluye desde la comprobación de la validez de los propios datos registrados hasta la detección y el diagnóstico de fallos, y que permite un conocimiento automatizado y detallado de las plantas. Dicho procedimiento está orientado a facilitar las tareas de operación y mantenimiento, de manera que se garantice una alta disponibilidad de funcionamiento de la instalación. De vuelta a la fase inicial de cálculo de las expectativas de producción, se utilizan los datos registrados en las centrales para llevar a cabo una mejora de los métodos de estimación de la radiación, que es la componente que más incertidumbre añade al proceso de modelado. El desarrollo y la aplicación de este procedimiento de control de calidad se han llevado a cabo en 39 grandes centrales fotovoltaicas, que totalizan una potencia de 250 MW, distribuidas por varios países de Europa y América Latina. ABSTRACT This thesis presents a comprehensive quality control procedure to be applied in photovoltaic plants, which covers from the initial phase of energy production estimation to the monitoring of the installation performance, once it is in operation. This protocol allows reducing the uncertainty associated to the photovoltaic plants behaviour and increases their long term reliability, therefore optimizing their performance. The situation of photovoltaic technology has drastically evolved in recent years, making photovoltaic plants capable of producing energy at fully competitive prices, in relation to other energy sources. This fact increases the requirements on the performance and reliability of these facilities. To meet this demand, it is necessary to adapt the quality control procedures and to develop new methods able to provide a more complete knowledge of the state of health of the plants, and able to maintain surveillance on them over time. In addition, the current meagre margins in which these installations operate require procedures capable of estimating energy production with the lower possible uncertainty during the design phase. The quality control procedure presented in this work starts from previous protocols oriented to the commissioning phase of a photovoltaic system, and complete them with procedures for the operation phase, paying particular attention to the major problems that arise in photovoltaic plants during their lifetime (hot spots, dust impact, ageing...). It also incorporates a protocol to control and analyse the installation performance directly from its monitoring data, which comprises from checking the validity of the recorded data itself to the detection and diagnosis of failures, and which allows an automated and detailed knowledge of the PV plant performance that can be oriented to facilitate the operation and maintenance of the installation, so as to ensure a high operation availability of the system. Back to the initial stage of calculating production expectations, the data recorded in the photovoltaic plants is used to improved methods for estimating the incident irradiation, which is the component that adds more uncertainty to the modelling process. The development and implementation of the presented quality control procedure has been carried out in 39 large photovoltaic plants, with a total power of 250 MW, located in different European and Latin-American countries.

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This paper reports on the IES-UPM experience from 2006 to 2010 in the field of the characterization of PV arrays of commercial large PV plants installed in Spain within the framework of the profitable economic scenarios associated to feed-in tariff laws. This experience has extended to 200 MW and has provided valuable lessons to minimize uncertainty, which plays a key role in quality assurance procedures. The paper deals not only with classic I–V measurements but also with watt-metering-based procedures. Particular attention is paid to the selection of irradiance and cell temperature sensors

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The power generated by large grid-connected photovoltaic (PV) plants depends greatly on the solar irradiance. This paper studies the effects of the solar irradiance variability analyzing experimental 1-s data collected throughout a year at six PV plants, totaling 18 MWp. Each PV plant was modeled as a first order filter function based on an analysis in the frequency domain of the irradiance data and the output power signals. An empiric expression which relates the filter parameters and the PV plant size has been proposed. This simple model has been successfully validated precisely determining the daily maximum output power fluctuation from incident irradiance measurements.

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The quality and the reliability of the power generated by large grid-connected photovoltaic (PV) plants are negatively affected by the source characteristic variability. This paper deals with the smoothing of power fluctuations because of geographical dispersion of PV systems. The fluctuation frequency and the maximum fluctuation registered at a PV plant ensemble are analyzed to study these effects. We propose an empirical expression to compare the fluctuation attenuation because of both the size and the number of PV plants grouped. The convolution of single PV plants frequency distribution functions has turned out to be a successful tool to statistically describe the behavior of an ensemble of PV plants and determine their maximum output fluctuation. Our work is based on experimental 1-s data collected throughout 2009 from seven PV plants, 20 MWp in total, separated between 6 and 360 km.

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To date, the majority of quality controls performed at PV plants are based on the measurement of a small sample of individual modules. Consequently, there is very little representative data on the real Standard Test Conditions (STC) power output values for PV generators. This paper presents the power output values for more than 1300 PV generators having a total installed power capacity of almost 15.3 MW. The values were obtained by the INGEPER-UPNA group, in collaboration with the IES-UPM, through a study to monitor the power output of a number of PV plants from 2006 to 2009. This work has made it possible to determine, amongst other things, the power dispersion that can be expected amongst generators made by different manufacturers, amongst generators made by the same manufacturer but comprising modules of different nameplate ratings and also amongst generators formed by modules with the same characteristics. The work also analyses the STC power output evolution over time in the course of this 4-year study. The values presented here could be considered to be representative of generators with fault-free modules.

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This study develops a proposal of method of calculation useful to estimate the energy produced by a PV grid-connected system making use of irradiance-domain integrals and denition of statistical moment. Validation against database of real PV plants performance data shows that acceptable energy estimation can be obtained with rst to fourth statistical moments and some basic system parameters. This way, only simple calculations at the reach of pocket calculators, are enough to estimate AC energy.

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Thin film photovoltaic (TF) modules have gained importance in the photovoltaic (PV) market. New PV plants increasingly use TF technologies. In order to have a reliable sample of a PV module population, a huge number of modules must be measured. There is a big variety of materials used in TF technology. Some of these modules are made of amorphous or microcrystalline silicon. Other are made of CIS or CdTe. Not all these materials respond the same under standard test conditions (STC) of power measurement. Power rates of the modules may vary depending on both the extent and the history of sunlight exposure. Thus, it is necessary a testing method adapted to each TF technology. This test must guarantee repeatability of measurements of generated power. This paper shows responses of different commercial TF PV modules to sunlight exposure. Several test procedures were performed in order to find the best methodology to obtain measurements of TF PV modules at STC in the easiest way. A methodology for indoor measurements adapted to these technologies is described.

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A number of findings have shown that the test procedures currently available to determine the reliability and durability of photovoltaic (PV) modules are insufficient to detect certain problems. To improve these procedures, ongoing research into the actual performance of the modules in the field is required. However, scientific literature contains but few references to field studies of defective modules. This article studies two different localized heating phenomena affecting the PV modules of two large-scale PV plants in Spain. The first problem relates to weak solder joints whilst the second is due to microcracks on the module cells. For both cases, the cause is identified, and consideration is given with regard to the effect on performance, the potential deterioration over time, and a way to detect the problems identified. The findings contained in this paper will prove to be of considerable interest to maintenance personnel at large-scale PV plants and also to those responsible for setting module quality standards and specifications, and even the PV module manufacturers themselves.

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Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.