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.

A educação de adultos: um novo desafio organizacional na escola pública

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação Especialização em Administração Escolar

O papel da auditoria interna na monitorização do processo de governação das organizações

Mestrado em Auditoria

Conhecimentos sobre VIH sida nos clientes de um hospital de Lakes State, Sudão do Sul

Enquadramento: O VIH/Sida exige uma ação direcionada na vertente da prevenção, cujo suporte integra a transmissão de conhecimentos promotores da adoção e manutenção de comportamentos seguros, em conformidade com as características sociais e culturais dos indivíduos. Objetivos: Validar, para a população do Sudão do Sul, a Escala de Conhecimentos sobre VIH/Sida, The HIV Knowledge Questionnaire: HIV-KQ-45, de Carey et al. (1997); analisar de que forma as variáveis sociodemográficas influenciam os conhecimentos sobre VIH/Sida, dos cidadãos de Mapuordit Sudão do Sul; verificar se a frequência de formação sobre VIH/Sida influencia o seu nível de conhecimentos. Metodologia: Estudo quantitativo, descritivo-analítico e transversal, com 232 clientes do Mary Immaculate de Mapuordit Hospital. Foi utilizado um Questionário de caracterização sociodemográfica e do contexto de formação sobre o VIH/Sida, e o HIV Knowledge Questionnaire (HVI-K-Q) de Carey, Morrison-Beedy e Johnson (1997). Resultados: Amostra é maioritariamente masculina (74.6%), com uma média de idade 22,83 (±5.793 anos). A análise fatorial confirmatória do HIV-K-Q permitiu apurar 5 fatores, cujos valores médios mais significativos foram nos fatores preconceitos/medos (média=80.60%), conhecimentos sobre os comportamentos de risco (média=76.58%) e vias de transmissão (média=70.36%). Os sudaneses pontuaram maioritariamente com razoáveis conhecimentos sobre a Sida (média=68.08%). As mulheres, os participantes mais velhos, com companheiro(a), mais escolarizados, profissionalmente ativos, a distar do hospital =<20 Km, deslocando-se num veículo não motorizado e com diagnóstico de VIH relataram mais conhecimentos sobre a Sida. Os participantes com informação sobre a prevenção do VIH/Sida e frequência em workshop na área demonstraram melhores conhecimentos. Revelaram-se preditivas dos conhecimentos acerca da doença as habilitações literárias (β=0.32) e o diagnóstico de VIH/Sida (β=0.14) revelou-se preditor dos conhecimentos sobre os comportamentos de risco. Conclusão: As casuísticas significativas do VIH/Sida justificam considerar as habilitações literárias e a presença de diagnóstico VIH/Sida como variáveis a avaliar previamente ao planeamento estratégico das ações de educação para a prevenção do VIH/Sida no Sudão do Sul. Palavras-chave: Conhecimentos; VIH/Sida; Sudão do Sul.

ß-Lactams: chemical structure, mode of action and mechanisms of resistance

This synopsis summarizes the key chemical and bacteriological characteristics of β-lactams, penicillins, cephalosporins, carbanpenems, monobactams and others. Particular notice is given to first-generation to fifth-generation cephalosporins. This review also summarizes the main resistance mechanism to antibiotics, focusing particular attention to those conferring resistance to broad-spectrum cephalosporins by means of production of emerging cephalosporinases (extended-spectrum β-lactamases and AmpC β-lactamases), target alteration (penicillin-binding proteins from methicillin-resistant Staphylococcus aureus) and membrane transporters that pump β-lactams out of the bacterial cell.

Implementação da estratégia de marketing sensorial: uma abordagem empírica

Dissertação de Mestrado, Ciências Económicas e Empresariais, 16 de Dezembro 2013, Universidade dos Açores.

Corporate brand identity management – proposal of a new framework

The term “corporate brand” has been widely used in literature since the eighties. According to Balmer (1998) this concept tends to be used as an alternative to the concept of corporate identity. The author argues that the use of branding principles to discuss corporate identity has tended to align the area more closely with marketing. However, the literature on brand management (Aaker, 1991; Kapferer, 1991 and de Chernatony and McDonald, 1992), gives little attention to the corporate brand” (p. 985). Based on the concepts of corporate brand, brand identity and B2B relationship, the authors are interested in eliminating this gap in literature by designing a framework of corporate brand identity management. The aim of this investigation is to investigate the impact of B2B relationships in corporate brand identity management. The methodology used is quantitative analysis of surveys and scale development. The originality of this paper is to investigate the influence of the relationship between brands in corporate brand identity. This investigation is very important to help the decisions of the corporate brand managers and academics. According to literature, namely on corporate brands (Balmer 2002b, Hatch and Schultz, 2001, 2003) and on brand identity (Kapferer, 1991, 2008, Aaker, 1996, de Chernatony, 1999) the authors developed a corporate brand identity management framework considering relationships between brands a context variable with definite impact on identity management as stated by Hakansson and Snehota (1989, 1995). These authors consider that organisations´ identity management is pursued under a relational perspective with impact on identity management. Most researchers on identity and corporate brand emphasise the importance of external influences (Kennedy, 1977; King, 1991; de Chernatony, 1999; Balmer and Gray, 2000; Balmer, 2002a). Those influences concern legislation, concurrence, political issues... and stakeholders’ perceptions and reputations (due to the holistic approach demanded by corporate brands). In this context the authors claim the importance of another influence: B2B relationships. This decision is inspired in sociological studies (Mannheim, 1950; and Tajfel and Turner, 1979) regarding individual identity. These authors claim that individuals form their personality by interacting in the social field. The authors argue that corporate brand identity also develops itself under a relational approach. The relationships selected to pursue this investigation are the ones that are developed by Portuguese universities and investigation centres that cooperate by developing investigation. Those centres are administrative and financially autonomous