Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Analysis and visualization of seismic data using mutual information

Seismic data is difficult to analyze and classical mathematical tools reveal strong limitations in exposing hidden relationships between earthquakes. In this paper, we study earthquake phenomena in the perspective of complex systems. Global seismic data, covering the period from 1962 up to 2011 is analyzed. The events, characterized by their magnitude, geographic location and time of occurrence, are divided into groups, either according to the Flinn-Engdahl (F-E) seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Two methods of analysis are considered and compared in this study. In a first method, the distributions of magnitudes are approximated by Gutenberg-Richter (G-R) distributions and the parameters used to reveal the relationships among regions. In the second method, the mutual information is calculated and adopted as a measure of similarity between regions. In both cases, using clustering analysis, visualization maps are generated, providing an intuitive and useful representation of the complex relationships that are present among seismic data. Such relationships might not be perceived on classical geographic maps. Therefore, the generated charts are a valid alternative to other visualization tools, for understanding the global behavior of earthquakes.

Elements of scalable data processing

Cooperating objects (COs) is a recently coined term used to signify the convergence of classical embedded computer systems, wireless sensor networks and robotics and control. We present essential elements of a reference architecture for scalable data processing for the CO paradigm.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Calculation of fractional derivatives of noisy data with genetic algorithms

This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

A Distributed System for the Dissemination of DGPS Data through the Internet

In this paper we describe a low cost distributed system intended to increase the positioning accuracy of outdoor navigation systems based on the Global Positioning System (GPS). Since the accuracy of absolute GPS positioning is insufficient for many outdoor navigation tasks, another GPS based methodology – the Differential GPS (DGPS) – was developed in the nineties. The differential or relative positioning approach is based on the calculation and dissemination of the range errors of the received GPS satellites. GPS/DGPS receivers correlate the broadcasted GPS data with the DGPS corrections, granting users increased accuracy. DGPS data can be disseminated using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to provide mobile platforms within our campus with DGPS data for precise outdoor navigation. To achieve this objective, we designed and implemented a three-tier client/server distributed system that, first, establishes Internet links with remote DGPS sources and, then, performs campus-wide dissemination of the obtained data. The Internet links are established between data servers connected to remote DGPS sources and the client, which is the data input module of the campus-wide DGPS data provider. The campus DGPS data provider allows the establishment of both Intranet and wireless links within the campus. This distributed system is expected to provide adequate support for accurate outdoor navigation tasks.

Transporte marítimo de curta distância na União Europeia e em Portugal

O transporte marítimo sempre assumiu uma importância primordial no transporte, quer de pessoas como de mercadorias. O uso das vias marítimas para o transporte de mercadorias é uma prática utilizada desde os tempos antigos. O transporte marítimo na Europa sempre foi uma forma eficaz e de baixo custo de transportar passageiros e mercadorias de um local para outro. Atualmente, todos os modos de transporte necessitam de melhorar a sua eficiência e reduzir o montante de poluentes que libertam para o meio-ambiente. O transporte marítimo de curta distância (TMCD) é parte essencial no sistema de transporte multimodal Europeu representando cerca de 37% das transações intracomunitárias (tkm). Os resultados alcançados advêm desde que, em 2001, a European Shortsea Network (ESN) em parceria com os Shortsea Promotion Centres (SPC) de cada Estado-Membro da União Europeia (EU) conseguiram efetuar progressos significativos na promoção e desenvolvimento do transporte por esta via. Esta tese de mestrado pretende caraterizar o TMCD na EU e em Portugal e a sua articulação com os outros meios de transporte de mercadorias. Será também analisada a situação Portuguesa ao nível do transporte marítimo de mercadorias fazendo especial relevância à mercadoria contentorizada, às infraestruturas atualmente existentes em Portugal assim como às perspetivas futuras para o setor. A metodologia utilizada inclui a revisão de literatura da investigação efetuada sobre o setor, a recolha de informação primária através do instrumento inquérito e a recolha de informação estatística a partir de fontes secundárias, permitindo a caraterização do setor. O inquérito foi desenvolvido e partilhado com mais de um milhar de empresas a operar em Portugal, nas que se incluem as empresas transportadoras, operadores logísticos, agentes de navegação e as principais empresas exportadoras/importadoras a operar em Portugal, tendo-se obtido 106 respostas válidas. A nível nacional, o inquérito realizado permitiu confirmar que os principais portos logísticos para a movimentação internacional de mercadorias são os portos de Leixões, Lisboa, Sines e Setúbal, estando a maioria das empresas inquiridas localizadas no hinterland destes portos. O inquérito permitiu também concluir que o facto de o transporte rodoviário ser um meio de transporte rápido, de baixo custo para curtas e médias distâncias, de elevada frequência de transporte, de oferecer elevada capacidade e diversos tipos de carga transportada, de oferecer serviços Porta-a-Porta, da elevada flexibilidade e mobilidade oferecida, assim como a rapidez das operações de carga e descarga continuam a contribuir para a elevada competitividade deste modo de transporte de mercadorias, sendo as razões pelo qual este modo é escolhido, pese embora, ser o modo mais poluente por tonelada transportada. Os modos de transporte TMCD e ferroviário apenas são alvo de escolha, como modo de transporte de mercadorias, por parte das empresas mais responsáveis socialmente e ambiental. O inquérito permitiu ainda concluir que, para haver uma melhor articulação entre o TMCD com outros meios de transporte, é necessário que sejam disponibilizados novos serviços, portos e terminais logísticos com serviços privatizados, assim como a redução das tarifas aplicáveis TMCD.

Analysis of Consumption Data to Detect Commercial Losses Using Performance Evaluation Methods in a Smart Grid

Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.