Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

O fim de um ciclo? A coconstrução da articulação curricular entre o 1.º e o 2.º Ciclos do Ensino Básico

Dissertação Apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação - Especialidade Supervisão em Educação

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.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

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.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Futuros: estudo de caso sobre futuros cambiais

Mestrado em Contabilidade

Relação entre o envelhecimento e o campo visual binocular em tarefas do quotidiano

RESUMO: Introdução – O envelhecimento pode estar relacionado com a perda de autonomia e declínio da capacidade funcional dos indivíduos, o que tende a comprometer a execução de tarefas do quotidiano e consequentemente leva a repercussões na qualidade de vida, afetando-a de forma negativa. Objetivos – Rever a bibliografia atualmente disponível no que respeita às repercussões do envelhecimento no campo visual binocular e atencional e à influência do campo visual binocular na leitura, escrita e marcha/locomoção em idosos. Metodologia – Este estudo é uma revisão de literatura. Procedeu-se à análise de 37 artigos científicos, que posteriormente foram organizados numa grelha de observação e numa tabela comparativa. Resultados – Dos artigos analisados, 32,43% (n=12) apontam para uma diminuição da extensão do campo visual binocular e atencional relacionada com o envelhecimento. Repercussões da diminuição da extensão do campo visual binocular sem fator atencional nas atividades quotidianas são referidas em 54,05% (n=20) dos artigos. Neste grupo de artigos 40,53% (n=15) apontam para a existência de uma relação entre o campo visual binocular com o desempenho na leitura, escrita ou marcha/locomoção. Do total de artigos analisados, dos 45,95% (n=17) que descrevem o campo visual binocular com fator atencional, 10,81% (n=4) apontam para a mesma relação. Discussão/Conclusões – O envelhecimento provoca um decréscimo no campo visual binocular, sendo este mais acentuado na periferia. Este decréscimo, na presença de uma atenção visual diminuída, influencia o desempenho na leitura, escrita e marcha/locomoção.

A doença oncológica no fórum da História: breve síntese sobre a evolução da luta anticancerosa em Portugal

Introdução – A doença oncológica tem sido assunto de abordagem historiográfica particularmente abundante no contexto internacional. No caso português só recentemente começaram a surgir os primeiros trabalhos em redor desta ampla temática. Objetivos – Revolvendo em torno da emergência e estruturação da luta anticancerosa no âmbito internacional, pretende-se apresentar uma breve síntese sobre a evolução deste fenómeno em Portugal na primeira metade do século XX. Metodologia – Análise documental. Qualitativa e heurística. Resultados/Discussão/Considerações finais – A luta contra a doença oncológica em Portugal não destoou do contexto médico-científico e do movimento internacional anticanceroso da primeira metade do século XX. No entanto, a emergência e a institucionalização do projeto anticanceroso nacional apresentou algumas particularidades. Inserido entre uma especialidade médica em processo de afirmação e as necessidades assistenciais dos cancerosos, resultou da conjugação de uma série de fatores que ultrapassam a mera assimilação de novas tecnologias médicas ou da criação de um espaço próprio para a prática da oncologia. Tornou-se também num meio para realizar um trabalho intenso de educação para a saúde, num instrumento de ponta na formação médica especializada e numa referência de modernidade científica no contexto do Estado Novo.

Efetividade do Pnf-Chi® na funcionalidade do membro superior e na qualidade de vida, em mulheres submetidas a tratamento cirúrgico por cancro da mama

Mestrado em Fisioterapia.

Tradução de artigos científicos no domínio da medicina: especificidades

Relatório de Estágio apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Tradução e Interpretação Especializada, sob orientação de Doutor Manuel Fernando Moreira da Silva

Ethical dilemmas in scientific publication: pitfalls and solutions for editors

Editors of scientific journals need to be conversant with the mechanisms by which scientific misconduct is amplified by publication practices. This paper provides definitions, ways to document the extent of the problem, and examples of editorial attempts to counter fraud. Fabrication, falsification, duplication, ghost authorship, gift authorship, lack of ethics approval, non-disclosure, 'salami' publication, conflicts of interest, auto-citation, duplicate submission, duplicate publications, and plagiarism are common problems. Editorial misconduct includes failure to observe due process, undue delay in reaching decisions and communicating these to authors, inappropriate review procedures, and confounding a journal's content with its advertising or promotional potential. Editors also can be admonished by their peers for failure to investigate suspected misconduct, failure to retract when indicated, and failure to abide voluntarily by the six main sources of relevant international guidelines on research, its reporting and editorial practice. Editors are in a good position to promulgate reasonable standards of practice, and can start by using consensus guidelines on publication ethics to state explicitly how their journals function. Reviewers, editors, authors and readers all then have a better chance to understand, and abide by, the rules of publishing.