Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Power systems reliability calculation based on fuzzy data mining

This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Online versus postal questionnaires: a comparison between two data collection methods

Objectives : The purpose of this article is to find out differences between surveys using paper and online questionnaires. The author has deep knowledge in the case of questions concerning opinions in the development of survey based research, e.g. the limits of postal and online questionnaires. Methods : In the physician studies carried out in 1995 (doctors graduated in 1982-1991), 2000 (doctors graduated in 1982-1996), 2005 (doctors graduated in 1982-2001), 2011 (doctors graduated in 1977-2006) and 457 family doctors in 2000, were used paper and online questionnaires. The response rates were 64%, 68%, 64%, 49% and 73%, respectively. Results : The results of the physician studies showed that there were differences between methods. These differences were connected with using paper-based questionnaire and online questionnaire and response rate. The online-based survey gave a lower response rate than the postal survey. The major advantages of online survey were short response time; very low financial resource needs and data were directly loaded in the data analysis software, thus saved time and resources associated with the data entry process. Conclusions : The current article helps researchers with planning the study design and choosing of the right data collection method.

SmartClean: an incremental data cleaning tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the data quality problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool's validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.

Influence of environmental temperature and humidity on the acute ventilatory response to exercise in asthmatic adolescents

Asthma is a chronic inflammatory disorder of the respiratory airways affecting people of all ages, and constitutes a serious public health problem worldwide (6). Such a chronic inflammation is invariably associated with injury and repair of the bronchial epithelium known as remodelling (11). Inflammation, remodelling, and altered neural control of the airways are responsible for both recurrent exacerbations of asthma and increasingly permanent airflow obstruction (11, 29, 34). Excessive airway narrowing is caused by altered smooth muscle behaviour, in close interaction with swelling of the airway walls, parenchyma retractile forces, and enhanced intraluminal secretions (29, 38). All these functional and structural changes are associated with the characteristic symptoms of asthma – cough, chest tightness, and wheezing –and have a significant impact on patients’ daily lives, on their families and also on society (1, 24, 29). Recent epidemiological studies show an increase in the prevalence of asthma, mainly in industrial countries (12, 25, 37). The reasons for this increase may depend on host factors (e.g., genetic disposition) or on environmental factors like air pollution or contact with allergens (6, 22, 29). Physical exercise is probably the most common trigger for brief episodes of symptoms, and is assumed to induce airflow limitations in most asthmatic children and young adults (16, 24, 29, 33). Exercise-induced asthma (EIA) is defined as an intermittent narrowing of the airways, generally associated with respiratory symptoms (chest tightness, cough, wheezing and dyspnoea), occurring after 3 to 10 minutes of vigorous exercise with a maximal severity during 5 to 15 minutes after the end of the exercise (9, 14, 16, 24, 33). The definitive diagnosis of EIA is confirmed by the measurement of pre- and post-exercise expiratory flows documenting either a 15% fall in the forced expiratory volume in 1 second (FEV1), or a ≥15 to 20% fall in peak expiratory flow (PEF) (9, 24, 29). Some types of physical exercise have been associated with the occurrence of bronchial symptoms and asthma (5, 15, 17). For instance, demanding activities such as basketball or soccer could cause more severe attacks than less vigorous ones such as baseball or jogging (33). The mechanisms of exercise-induced airflow limitations seem to be related to changes in the respiratory mucosa induced by hyperventilation (9, 29). The heat loss from the airways during exercise, and possibly its post-exercise rewarming may contribute to the exercise-induced bronchoconstriction (EIB) (27). Additionally, the concomitant dehydration from the respiratory mucosa during exercise leads to an increased interstitial osmolarity, which may also contribute to bronchoconstriction (4, 36). So, the risk of EIB in asthmatically predisposed subjects seems to be higher with greater ventilation rates and the cooler and drier the inspired air is (23). The incidence of EIA in physically demanding coldweather sports like competitive figure skating and ice hockey has been found to occur in up to 30 to 35% of the participants (32). In contrast, swimming is often recommended to asthmatic individuals, because it improves the functionality of respiratory muscles and, moreover, it seems to have a concomitant beneficial effect on the prevalence of asthma exacerbations (14, 26), supporting the idea that the risk of EIB would be smaller in warm and humid environments. This topic, however, remains controversial since the chlorified water of swimming pools has been suspected as a potential trigger factor for some asthmatic patients (7, 8, 20, 21). In fact, the higher asthma incidence observed in industrialised countries has recently been linked to the exposition to chloride (7, 8, 30). Although clinical and epidemiological data suggest an influence of humidity and temperature of the inspired air on the bronchial response of asthmatic subjects during exercise, some of those studies did not accurately control the intensity of the exercise (2, 13), raising speculation of whether the experienced exercise overload was comparable for all subjects. Additionally, most of the studies did not include a control group (2, 10, 19, 39), which may lead to doubts about whether asthma per se has conditioned the observed results. Moreover, since the main targeted age group of these studies has been adults (10, 19, 39), any extrapolation to childhood/adolescence might be questionable regarding the different lung maturation. Considering the higher incidence of asthma in youngsters (30) and the fact that only the works of Amirav and coworkers (2, 3) have focused on this age group, a scarcity of scientific data can be identified. Additionally, since the main environmental trigger factors, i.e., temperature and humidity, were tested separately (10, 28, 39) it would be useful to analyse these two variables simultaneously because of their synergic effect on water and heat loss by the airways (31, 33). It also appears important to estimate the airway responsiveness to exercise within moderate environmental ranges of temperature and humidity, trying to avoid extreme temperatures and humidity conditions used by others (2, 3). So, the aim of this study was to analyse the influence of moderate changes in air temperature and humidity simultaneously on the acute ventilatory response to exercise in asthmatic children. To overcome the above referred to methodological limitations, we used a 15 minute progressive exercise trial on a cycle ergometer at 3 different workload intensities, and we collected data related to heart rate, respiratory quotient, minute ventilation and oxygen uptake in order to ensure that physiological exercise repercussions were the same in both environments. The tests were done in a “normal” climatic environment (in a gymnasium) and in a hot and humid environment (swimming pool); for the latter, direct chloride exposition was avoided.

Os preços de transferência e o âmbito de intervenção do auditor: abordagem e enquadramento

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do obtenção do grau de Mestre em Auditoria Auditoria, sob orientação de Adalmiro Álvaro Malheiro de Castro Andrade

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Data envelopment analysis: eficiência relativa das unidades de tomada de decisão

A avaliação das organizações e a deterntinação da performance obtida pelo exercício da gestão, tem sido uma preocupação constante de gestores e accionistas, embora com objectivos diversos. Nos dias de hoje, a questão coloca-se com maior acuidade quer pela competitividade acrescida quer pela dimensão e complexidade actual das empresas. Pretendemos com este trabalho fazer uma descrição da metodologia DEA - Data Envelopment Analysis - nas suas formulações iniciais mais simples. A metodologia do DEA, pretende obter uma medida única e simples de avaliação da eficiência, combinando um conjunto de outputs e de inputs relativos às diferentes unidades homogéneas que se pretendem avaliar. O método DEA é um método não paramétrico que pelas suas características é particularmente adequado à avaliação de unidades homogéneas não necessariamente lucrativas. Concluímos, em geral, que são úteis e constituem um avanço importante, as informações obtidas através do DEA mas que outros métodos, designadamente rácios e análises de regressão, podem dar um contributo importante para complementar aquela análise.

Software de apoio à implementação de sistemas híbridos de produção de energia eléctrica baseados em energias renováveis

O aumento da população Mundial, particularmente em Países emergentes como é o caso da China e da Índia, tem-se relevado um problema adicional no que confere às dificuldades associadas ao consumo mundial de energia, pois esta situação limita inequivocamente o acesso destes milhões de pessoas à energia eléctrica para os bens básicos de sobrevivência. Uma das muitas formas de se extinguir esta necessidade, começa a ser desenvolvida recorrendo ao uso de recursos renováveis como fontes de energia. Independentemente do local do mundo onde nos encontremos, essas fontes de energia são abundantes, inesgotáveis e gratuitas. O problema reside na forma como esses recursos renováveis são geridos em função das solicitações de carga que as instalações necessitam. Sistemas híbridos podem ser usados para produzir energia em qualquer parte do mundo. Historicamente este tipo de sistemas eram aplicados em locais isolados, mas nos dias que correm podem ser usados directamente conectados à rede, permitindo que se realize a venda de energia. Foi neste contexto que esta tese foi desenvolvida, com o objectivo de disponibilizar uma ferramenta informática capaz de calcular a rentabilidade de um sistema híbrido ligado à rede ou isolado. Contudo, a complexidade deste problema é muito elevada, pois existe uma extensa panóplia de características e distintos equipamentos que se pode adoptar. Assim, a aplicação informática desenvolvida teve de ser limitada e restringida aos dados disponíveis de forma a poder tornar-se genérica, mas ao mesmo tempo permitir ter uma aplicabilidade prática. O objectivo da ferramenta informática desenvolvida é apresentar de forma imediata os custos da implementação que um sistema híbrido pode acarretar, dependendo apenas de três variáveis distintas. A primeira variável terá de ter em consideração o local de instalação do sistema. Em segundo lugar é o tipo de ligação (isolado ou ligado à rede) e, por fim, o custo dos equipamentos (eólico, solar e restantes componentes) que serão introduzidos. Após a inserção destes dados a aplicação informática apresenta valores estimados de Payback e VAL.

eTourism – Mobile Data Interface (Sistema de Apoio On-Line ao Turista em Dispositivos Móveis com Adaptação de Tours Personalizados)

O intuito principal desta Tese é criar um interface de Dados entre uma fonte de informação e fornecimento de Rotas para turistas e disponibilizar essa informação através de um sistema móvel interactivo de navegação e visualização desses mesmos dados. O formato tecnológico será portátil e orientado à mobilidade (PDA) e deverá ser prático, intuitivo e multi-facetado, permitindo boa usabilidade a públicos de várias faixas etárias. Haverá uma componente de IA (Inteligência Artificial), que irá usar a informação fornecida para tomar decisões ponderadas tendo em conta uma diversidade de aspectos. O Sistema a desenvolver deverá ser, assim, capaz de lidar com imponderáveis (alterações de rota, gestão de horários, cancelamento de pontos de visita, novos pontos de visita) e, finalmente, deverá ajudar o turista a gerir o seu tempo entre Pontos de Interesse (POI – Points os Interest). Deverá também permitir seguir ou não um dado percurso pré-definido, havendo possibilidade de cenários de exploração de POIs, sugeridos a partir de sugestões in loco, similares a Locais incluídos no trajecto, que se enquadravam no perfil dos Utilizadores. O âmbito geográfico de teste deste projecto será a zona ribeirinha do porto, por ser um ex-líbris da cidade e, simultaneamente, uma zona com muitos desafios ao nível geográfico (com a inclinação) e ao nível do grande número de Eventos e Locais a visitar.

Indexação e pesquisa de informação com base em ontologias interligadas

Tecnologias da Web Semântica como RDF, OWL e SPARQL sofreram nos últimos anos um forte crescimento e aceitação. Projectos como a DBPedia e Open Street Map começam a evidenciar o verdadeiro potencial da Linked Open Data. No entanto os motores de pesquisa semânticos ainda estão atrasados neste crescendo de tecnologias semânticas. As soluções disponíveis baseiam-se mais em recursos de processamento de linguagem natural. Ferramentas poderosas da Web Semântica como ontologias, motores de inferência e linguagens de pesquisa semântica não são ainda comuns. Adicionalmente a esta realidade, existem certas dificuldades na implementação de um Motor de Pesquisa Semântico. Conforme demonstrado nesta dissertação, é necessária uma arquitectura federada de forma a aproveitar todo o potencial da Linked Open Data. No entanto um sistema federado nesse ambiente apresenta problemas de performance que devem ser resolvidos através de cooperação entre fontes de dados. O standard actual de linguagem de pesquisa na Web Semântica, o SPARQL, não oferece um mecanismo para cooperação entre fontes de dados. Esta dissertação propõe uma arquitectura federada que contém mecanismos que permitem cooperação entre fontes de dados. Aborda o problema da performance propondo um índice gerido de forma centralizada assim como mapeamentos entre os modelos de dados de cada fonte de dados. A arquitectura proposta é modular, permitindo um crescimento de repositórios e funcionalidades simples e de forma descentralizada, à semelhança da Linked Open Data e da própria World Wide Web. Esta arquitectura trabalha com pesquisas por termos em linguagem natural e também com inquéritos formais em linguagem SPARQL. No entanto os repositórios considerados contêm apenas dados em formato RDF. Esta dissertação baseia-se em múltiplas ontologias partilhadas e interligadas.