Polytechnic University of Catalonia

About: Polytechnic University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Finite element method & Population. The organization has 16006 authors who have published 45325 publications receiving 949306 citations. The organization is also known as: UPC - BarcelonaTECH & Technical University of Catalonia.

New positive-sequence voltage detector for grid synchronization of power converters under faulty grid conditions

Abstract: This paper deals with a fundamental aspect in the control of grid-connected power converters, i.e., the detection of the positive-sequence component at fundamental frequency of the utility voltage under unbalanced and distorted conditions. Accurate and fast detection of this voltage component under grid faults is essential to keep the control over the power exchange with the grid avoiding to trip the converter protections and allowing the ride-through of the transient fault. In this paper, the systematic use of well known techniques conducts to a new positive-sequence voltage detection system which exhibits a fast, precise, and frequency-adaptive response under faulty grid conditions. Three fundamental functional blocks make up the proposed detector, these are: i) the quadrature-signals generator (QSG), ii) the positive-sequence calculator (PSC), and iii) the phase-locked loop (PLL). A key innovation of the proposed system is the use of a dual second order generalized integrator (DSOGI) to implement the QSG. For this reason, the proposed positive-sequence detector is called DSOGI-PLL. A detailed study of the DSOGI-PLL and verification by simulation are performed in this paper. From the obtained results, it can be concluded that the DSOGI-PLL is a very suitable technique for characterizing the positive-sequence voltage under grid faults.

Framing vulnerability, risk and societal responses: the MOVE framework

Abstract: The paper deals with the development of a general as well as integrative and holistic framework to systematize and assess vulnerability, risk and adaptation. The framework is a thinking tool meant as a heuristic that outlines key factors and different dimensions that need to be addressed when assessing vulnerability in the context of natural hazards and climate change. The approach underlines that the key factors of such a common framework are related to the exposure of a society or system to a hazard or stressor, the susceptibility of the system or community exposed, and its resilience and adaptive capacity. Additionally, it underlines the necessity to consider key factors and multiple thematic dimensions when assessing vulnerability in the context of natural and socio-natural hazards. In this regard, it shows key linkages between the different concepts used within the disaster risk management (DRM) and climate change adaptation (CCA) research. Further, it helps to illustrate the strong relationships between different concepts used in DRM and CCA. The framework is also a tool for communicating complexity and stresses the need for societal change in order to reduce risk and to promote adaptation. With regard to this, the policy relevance of the framework and first results of its application are outlined. Overall, the framework presented enhances the discussion on how to frame and link vulnerability, disaster risk, risk management and adaptation concepts.

Large-scale topological and dynamical properties of the Internet

Abstract: We study the large-scale topological and dynamical properties of real Internet maps at the autonomous system level, collected in a 3-yr time interval. We find that the connectivity structure of the Internet presents statistical distributions settled in a well-defined stationary state. The large-scale properties are characterized by a scale-free topology consistent with previous observations. Correlation functions and clustering coefficients exhibit a remarkable structure due to the underlying hierarchical organization of the Internet. The study of the Internet time evolution shows a growth dynamics with aging features typical of recently proposed growing network models. We compare the properties of growing network models with the present real Internet data analysis.

Hybrid metaheuristics in combinatorial optimization: A survey

Abstract: Research in metaheuristics for combinatorial optimization problems has lately experienced a noteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problem-oriented. Nowadays the focus is on solving the problem at hand in the best way possible, rather than promoting a certain metaheuristic. This has led to an enormously fruitful cross-fertilization of different areas of optimization. This cross-fertilization is documented by a multitude of powerful hybrid algorithms that were obtained by combining components from several different optimization techniques. Hereby, hybridization is not restricted to the combination of different metaheuristics but includes, for example, the combination of exact algorithms and metaheuristics. In this work we provide a survey of some of the most important lines of hybridization. The literature review is accompanied by the presentation of illustrative examples.

Generation of uncorrelated random scale-free networks

Abstract: Uncorrelated random scale-free networks are useful null models to check the accuracy and the analytical solutions of dynamical processes defined on complex networks. We propose and analyze a model capable of generating random uncorrelated scale-free networks with no multiple and self-connections. The model is based on the classical configuration model, with an additional restriction on the maximum possible degree of the vertices. We check numerically that the proposed model indeed generates scale-free networks with no two- and three-vertex correlations, as measured by the average degree of the nearest neighbors and the clustering coefficient of the vertices of degree k , respectively.