Review of the Performance of Residential PV systems in Belgium

The main objective of this paper is to review the state of the art of residential PV systems in Belgium by the analysis of the operational data of 993 installations. For that, three main questions are posed: how much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? This work brings answers to these questions. A middling commercial PV system, optimally oriented, produces a mean annual energy of 892 kWh/kWp. As a whole, the orientation of PV generators causes energy productions to be some 6% inferior to optimally oriented PV systems. The mean performance ratio is 78% and the mean performance index is 85%. That is to say, the energy produced by a typical PV system in Belgium is 15% inferior to the energy produced by a very high quality PV system. Finally, on average, the real power of the PV modules falls 5% below its corresponding nominal power announced on the manufacturer's datasheet. Differences between real and nominal power of up to 16% have been detected.

Review of the Performance of Residential PV systems in France

The main objective of this paper is to review the state of the art of residential PV systems in France. This is done analyzing the operational data of 6868 installations. Three main questions are posed. How much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? During the year 2010, the PV systems in France have produced a mean annual energy of 1163 kWh/kWp. As a whole, the orientation of PV generators causes energy productions to be some 7% inferior to optimally oriented PV systems. The mean Performance Ratio is 76% and the mean Performance Index is 85%. That is to say, the energy produced by a typical PV system in France is 15% inferior to the energy produced by a very high quality PV system. On average, the real power of the PV modules falls 4.9% below its corresponding nominal power announced on the manufacturer's datasheet. A brief analysis by PV modules technology has led to relevant observations about two technologies in particular. On the one hand, the PV systems equipped with heterojunction with intrinsic thin layer (HIT) modules show performances higher than average. On the other hand, the systems equipped with the copper indium (di)selenide (CIS) modules show a real power that is 16% lower than their nominal value.

Performance Analysis of 10,000 Residential PV Systems in France and Belgium

The main objective of this paper is to review the state of the art of residential PV systems in France and Belgium. This is done analyzing the operational data of 10650 PV systems (9657 located in France and 993 in Belgium). Three main questions are posed. How much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? During the year 2010, the PV systems in France have produced a mean annual energy of 1163 kWh/kWp in France and 852 kWh/kWp in Belgium. As a whole, the orientation of PV generators causes energy productions to be some 7% inferior to optimally oriented PV systems. The mean Performance Ratio is 76% in France and 78% in Belgium, and the mean Performance Index is 85% in both countries. On average, the real power of the PV modules falls 4.9% below its corresponding nominal power announced on the manufacturer?s datasheet. A brief analysis by PV modules technology has lead to relevant observations about two technologies in particular. On the one hand, the PV systems equipped with Heterojunction with Intrinsic. Thin layer (HIT) modules show performances higher than average. On the other hand, the systems equipped with Copper Indium (di)Selenide (CIS) modules show a real power that is 16 % lower than their nominal value.

Optimización de la producción de la fase de avance en el túnel de Seiró (Ourense)

Este proyecto desarrolla una metodología de toma de datos y análisis para la optimización de la producción de la fase de avance de construcción del túnel de Seiró. Este túnel forma parte de las obras de construcción de la línea ferroviaria de alta velocidad corredor norte-noroeste a su paso por la provincia de Ourense. Mediante el análisis de diversos parámetros del diseño de la voladura, en la construcción de un túnel de 73 m2 de sección, en roca granítica, se pretende optimizar el tiempo de ciclo de excavación. Se estudia la variación de la fragmentación, el contorno y el avance obtenido y la influencia sobre estos parámetros del esquema de tiro y el tipo de cuele empleados y sus repercusiones en el tiempo de ciclo. El resultado del análisis concluye que el esquema de tiro óptimo, entre los usados, está formado por 112 barrenos de 51 mm de diámetro, con un cuele de 4 barrenos vacíos, que da lugar a mejores resultados de avance, contorno y fragmentación sin afectar negativamente al tiempo de ciclo. ABSTRACT This project develops a methodology for excavation cycle optimization by collecting and analyzing operational data for Seiró Tunnel construction site. This tunnel is included in construction project of high speed railway, located in N-NW direction, in Ourense province. Analyzing several blasting design parameters from the construction of a 73 m2 tunnel, in granitic rock, allows the optimization of cycle time. Variations in fragmentation, contour and advance length and influence about those parameters from blasting design und cut type used and its impact in the cycle time. Analysis results show up the best blasting design, among used, is formed of 112 holes 51 mm diameter, and a parallel cut with 4 empty holes. This configuration achieves the best fragmentation, contour and advance length without negative effects in time cycle

Automatic detection of PV systems failures from monitoring validated on 10,000 BIPV systems in Europe

The installers and owners show a growing interest in the follow-up of the performance of their photovoltaic (PV) systems. The owners are requesting reliable sources of information to ensure that their system is functioning properly, and the installers are actively looking for efficient ways of providing them the most useful possible information from the data available. Policy makers are becoming increasingly interested in the knowledge of the real performance of PV systems and the most frequent sources of problems that they suffer to be able to target the identified challenges properly. The scientific and industrial PV community is also requiring an access to massive operational data to pursue the technological improvements further.

Transactional failure recovery for a distributed key-value store

With the advent of cloud computing, many applications have embraced the ensuing paradigm shift towards modern distributed key-value data stores, like HBase, in order to benefit from the elastic scalability on offer. However, many applications still hesitate to make the leap from the traditional relational database model simply because they cannot compromise on the standard transactional guarantees of atomicity, isolation, and durability. To get the best of both worlds, one option is to integrate an independent transaction management component with a distributed key-value store. In this paper, we discuss the implications of this approach for durability. In particular, if the transaction manager provides durability (e.g., through logging), then we can relax durability constraints in the key-value store. However, if a component fails (e.g., a client or a key-value server), then we need a coordinated recovery procedure to ensure that commits are persisted correctly. In our research, we integrate an independent transaction manager with HBase. Our main contribution is a failure recovery middleware for the integrated system, which tracks the progress of each commit as it is flushed down by the client and persisted within HBase, so that we can recover reliably from failures. During recovery, commits that were interrupted by the failure are replayed from the transaction management log. Importantly, the recovery process does not interrupt transaction processing on the available servers. Using a benchmark, we evaluate the impact of component failure, and subsequent recovery, on application performance.

Snapshot isolation for Neo4j

NoSQL data stores are becoming more and more popular. Graph databases are one of this kind of data stores. In this paper we present an overview of the implementation of snapshot isolation for Neo4j, a very popular graph database.

Monitorización inteligente de redes de comunicación

El avance tecnológico de los últimos años ha aumentado la necesidad de guardar enormes cantidades de datos de forma masiva, llegando a una situación de desorden en el proceso de almacenamiento de datos, a su desactualización y a complicar su análisis. Esta situación causó un gran interés para las organizaciones en la búsqueda de un enfoque para obtener información relevante de estos grandes almacenes de datos. Surge así lo que se define como inteligencia de negocio, un conjunto de herramientas, procedimientos y estrategias para llevar a cabo la “extracción de conocimiento”, término con el que se refiere comúnmente a la extracción de información útil para la propia organización. Concretamente en este proyecto, se ha utilizado el enfoque Knowledge Discovery in Databases (KDD), que permite lograr la identificación de patrones y un manejo eficiente de las anomalías que puedan aparecer en una red de comunicaciones. Este enfoque comprende desde la selección de los datos primarios hasta su análisis final para la determinación de patrones. El núcleo de todo el enfoque KDD es la minería de datos, que contiene la tecnología necesaria para la identificación de los patrones mencionados y la extracción de conocimiento. Para ello, se utilizará la herramienta RapidMiner en su versión libre y gratuita, debido a que es más completa y de manejo más sencillo que otras herramientas como KNIME o WEKA. La gestión de una red engloba todo el proceso de despliegue y mantenimiento. Es en este procedimiento donde se recogen y monitorizan todas las anomalías ocasionadas en la red, las cuales pueden almacenarse en un repositorio. El objetivo de este proyecto es realizar un planteamiento teórico y varios experimentos que permitan identificar patrones en registros de anomalías de red. Se ha estudiado el repositorio de MAWI Lab, en el que se han almacenado anomalías diarias. Se trata de buscar indicios característicos anuales detectando patrones. Los diferentes experimentos y procedimientos de este estudio pretenden demostrar la utilidad de la inteligencia de negocio a la hora de extraer información a partir de un almacén de datos masivo, para su posterior análisis o futuros estudios. ABSTRACT. The technological progresses in the recent years required to store a big amount of information in repositories. This information is often in disorder, outdated and needs a complex analysis. This situation has caused a relevant interest in investigating methodologies to obtain important information from these huge data stores. Business intelligence was born as a set of tools, procedures and strategies to implement the "knowledge extraction". Specifically in this project, Knowledge Discovery in Databases (KDD) approach has been used. KDD is one of the most important processes of business intelligence to achieve the identification of patterns and the efficient management of the anomalies in a communications network. This approach includes all necessary stages from the selection of the raw data until the analysis to determine the patterns. The core process of the whole KDD approach is the Data Mining process, which analyzes the information needed to identify the patterns and to extract the knowledge. In this project we use the RapidMiner tool to carry out the Data Mining process, because this tool has more features and is easier to use than other tools like WEKA or KNIME. Network management includes the deployment, supervision and maintenance tasks. Network management process is where all anomalies are collected, monitored, and can be stored in a repository. The goal of this project is to construct a theoretical approach, to implement a prototype and to carry out several experiments that allow identifying patterns in some anomalies records. MAWI Lab repository has been selected to be studied, which contains daily anomalies. The different experiments show the utility of the business intelligence to extract information from big data warehouse.

Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

Modal contribution and state space order selection in operational modal analysis

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

Growth data from a field trial of Quercus suber plants regenerated from selected trees and their half-sib progenies by somatic embryogenesis

The development of reliable clonal propagation technologies is a requisite for performing Multi-Varietal Forestry (MVF). Somatic embryogenesis is considered the tissue culture based method more suitable for operational breeding of forest trees. Vegetative propagation is very difficult when tissues are taken from mature donors, making clonal propagation of selected trees almost impossible. We have been able to induce somatic embryogenesis in leaves taken from mature oak trees, including cork oak (Quercus suber). This important species of the Mediterranean ecosystem produces cork regularly, conferring to this species a significant economic value. In a previous paper we reported the establishment of a field trial to compare the growth of plants of somatic origin vs zygotic origin, and somatic plants from mature trees vs somatic plants from juvenile seedlings. For that purpose somatic seedlings were regenerated from five selected cork oak trees and from young plants of their half-sib progenies by somatic embryogenesis. They were planted in the field together with acorn-derived plants of the same families. After the first growth period, seedlings of zygotic origin doubled the height of somatic seedlings, showing somatic plants of adult and juvenile origin similar growth. Here we provide data on height and diameter increases after two additional growth periods. In the second one, growth parameters of zygotic seedlings were also significantly higher than those of somatic ones, but there were not significant differences in height increase between seedlings and somatic plants of mature origin. In the third growth period, height and diameter increases of somatic seedlings cloned from the selected trees did not differ from those of zygotic seedlings, which were still higher than data from plants obtained from somatic embryos from the sexual progeny. Therefore, somatic seedlings from mature origin seem not to be influenced by a possible ageing effect, and plants from somatic embryos tend to minimize the initial advantage of plants from acorns

Importance of nuclear data uncertainties in criticality calculations

The aim of this paper is to study the importance of nuclear data uncertainties in the prediction of the uncertainties in keff for LWR (Light Water Reactor) unit-cells. The first part of this work is focused on the comparison of different sensitivity/uncertainty propagation methodologies based on TSUNAMI and MCNP codes; this study is undertaken for a fresh-fuel at different operational conditions. The second part of this work studies the burnup effect where the indirect contribution due to the uncertainty of the isotopic evolution is also analyzed.

Operational characterisation of a Micro-SME producing farmhouse cheese in the south of Venezuela

A piece of research is presented that was conducted on the Guayanes Farmhouse Telita Cheese Producers Network located in the Piar and Padre Chien rural municipalities of Bolivar state in Venezuela. Guayanes telita cheese is a regional dairy product. The producers are to be found in a rural area with a high potential for marketing the label in the Southern Common Market (MERCOSUR). This market is the focal point of the strategic importance of this study for the Region and the Country. The research is of a descriptive scope conducted in the field. A questionnaire based on good food production practice was used as a data gathering technique. The final sample comprised 30 production units. Statistical processing was performed with version 15.2 of the STATGRAPHICS Centurion computational tool. The results would appear to confirm previous studies that point to the existence of factors that prevent these Micro-SMEs from guaranteeing the food safety of the product. The results indicate that new lines of research need to be opened up. These are oriented towards formulating strategies for the continuous improvement of these micro-SMEs, including quality control indicators.

Qualitative operational risk software -development of a software tool for determining the root of operational risk

This article shows software that allows determining the statistical behavior of qualitative data originating surveys previously transformed with a Likert’s scale to quantitative data. The main intention is offer to users a useful tool to know statistics' characteristics and forecasts of financial risks in a fast and simple way. Additionally,this paper presents the definition of operational risk. On the other hand, the article explains different techniques to do surveys with a Likert’s scale (Avila, 2008) to know expert’s opinion with the transformation of qualitative data to quantitative data. In addition, this paper will show how is very easy to distinguish an expert’s opinion related to risk, but when users have a lot of surveys and matrices is very difficult to obtain results because is necessary to compare common data. On the other hand, statistical value representative must be extracted from common data to get weight of each risk. In the end, this article exposes the development of “Qualitative Operational Risk Software” or QORS by its acronym, which has been designed to determine the root of risks in organizations and its value at operational risk OpVaR (Jorion, 2008; Chernobai et al, 2008) when input data comes from expert’s opinion and their associated matrices.