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.

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.

The importance of qualitative methodology in management empirical research

Purpose: The aim of this paper is to highlight the importance of qualitative research within the scope of management scientific studies, referring to its philosophy, nature and instruments. It also confronts it with quantitative methodology, approaching its differences as well as its complementariness and synergies, with the purpose of explaining, from a more analytic point of view, the relevance of qualitative methodology in the course of an authentic and real research despite its complexity. Design/methodology/approach: Regardless of its broad application, one may attest the scarcity literature that focuses on qualitative research applied to the management scientific area, as opposed to the large amount that refers to quantitative research. Findings: The paper shows the influence that qualitative research has on management scientific research. Originality/value:. Qualitative research assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.

A linguagem do espaço em Henry James: a fase madura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A educação artística e o desenvolvimento da criatividade e autonomia dos alunos de um curso profissional

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na Especialização de Artes Plásticas na Educação

Development of a SPME-GC-ECD methodology for selected pesticides in must and wine samples

A method for the determination of some pesticide residues in must and wine samples was developed using solid-phase microextraction (SPME) and gas chromatography – electron capture detection (GC/ECD). The procedure only needs dilution as sample pre-treatment and is therefore simple, fast and solvent-free. Eight fungicides (vinclozolin, procymidone, iprodione, penconazole, fenarimol, folpet, nuarimol and hexaconazole), one insecticide (chlorpyriphos) and two acaricides (bromopropylate and tetradifon) can be quantified. Good linearity was observed for all the compounds in the range 5–100 µg/L. The reproducibility of the measurements was found acceptable (with RSD’s below 20%). Detection limits of 11 µg/L, on average, are sufficiently below the proposed maximum residue limits (MRL’s) for these compounds in wine. The analytical method was applied to the determination of these compounds in Portuguese must and wine samples from the Demarcated Region of Alentejo, where any residues could be detected.

Agar extraction from integrated multitrophic aquacultured Gracilaria vermiculophylla: Evaluation of a microwave-assisted process using response surface methodology

Microwave-assisted extraction (MAE) of agar from Gracilaria vermiculophylla, produced in an integrated multitrophic aquaculture (IMTA) system, from Ria de Aveiro (northwestern Portugal), was tested and optimized using response surface methodology. The influence of the MAE operational parameters (extraction time, temperature, solvent volume and stirring speed) on the physical and chemical properties of agar (yield, gel strength, gelling and melting temperatures, as well as, sulphate and 3,6-anhydro-Lgalactose contents) was evaluated in a 2^4 orthogonal composite design. The quality of the extracted agar compared favorably with the attained using traditional extraction (2 h at 85ºC) while reducing drastically extraction time, solvent consumption and waste disposal requirements. Agar MAE optimum results were: an yield of 14.4 ± 0.4%, a gel strength of 1331 ± 51 g/cm2, 40.7 ± 0.2 _C gelling temperature, 93.1 ± 0.5ºC melting temperature, 1.73 ± 0.13% sulfate content and 39.4 ± 0.3% 3,6-anhydro-L-galactose content. Furthermore, this study suggests the feasibility of the exploitation of G. vermiculophylla grew in IMTA systems for agar production.

Determination of ochratoxin A in bread: evaluation of microwave-assisted extraction using an orthogonal composite design coupled with response surface methodology

An analytical method using microwave-assisted extraction (MAE) and liquid chromatography (LC) with fluorescence detection (FD) for the determination of ochratoxin A (OTA) in bread samples is described. A 24 orthogonal composite design coupled with response surface methodology was used to study the influence of MAE parameters (extraction time, temperature, solvent volume, and stirring speed) in order to maximize OTA recovery. The optimized MAE conditions were the following: 25 mL of acetonitrile, 10 min of extraction, at 80 °C, and maximum stirring speed. Validation of the overall methodology was performed by spiking assays at five levels (0.1–3.00 ng/g). The quantification limit was 0.005 ng/g. The established method was then applied to 64 bread samples (wheat, maize, and wheat/maize bread) collected in Oporto region (Northern Portugal). OTAwas detected in 84 % of the samples with a maximum value of 2.87 ng/g below the European maximum limit established for OTA in cereal products of 3 ng/g.

Psychological impact of diagnostic exams

Introduction: Anxiety is a common problem in primary care and specialty medical settings. Treating an anxious patient takes more time and adds stress to staff. Unrecognized anxiety may lead to exam repetition, and impedance of exam performance. Objective: The aim of the study was to examine the anxiety levels of patients who are to undergo diagnostic exams related to cancer diagnostic: PET/CT and mammography. Methods: Two hundred and thirty two patients who undergo PET/CT and one hundred thirteen women who undergo mammography filled out one questionnaire after the procedure to determine their concerns, expectations and perceptions of anxiety. Results: Our results show that the main causes of anxiety in patients who are having a PET/CT is the fear of the procedure itself and fear of the results. Patients who suffered from greater anxiety were those who were scanned during the initial stage of an oncological disease. On the other hand, the diagnostic is the main cause of anxiety in women who are requiring a mammography. 28% of the women reported having experienced pain or intense pain. Conclusions: The performance of diagnostic exams related to cancer diagnostic like a PET/CT and a mammography are important and statistically generators of anxiety. Patients are often poorly informed and present with a range of anxieties that may ultimately affect examination quality. These results provide expertise that can be used in the development of future training programs to integrate post-graduate courses of health professionals.

A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Máscaras da (in)capacidade: projeto desenvolvido numa instituição de apoio a pessoas com deficiência intelectual

Neste relatório apresenta-se o projeto de Educação e Intervenção Social intitulado “Máscaras da (In)Capacidade”, que assentou na metodologia de Investigação-Ação Participativa. Caracterizando-se pela análise dos contextos, pela ação, pela reflexão profunda e contínua, e pela avaliação, sempre numa perspetiva de participação, esta metodologia possibilita ao investigador social conhecer e envolver-se na realidade de uma maneira muito mais efetiva. O presente trabalho constitui, assim, um olhar retrospetivo sobre o trabalho desenvolvido num contexto institucional de acolhimento de pessoas com deficiência intelectual. O projeto desenvolvido teve como principal finalidade: “Melhorar as dinâmicas relacionais e de funcionamento existentes na instituição, de forma a proporcionar um maior bem-estar físico e psicológico das pessoas que trabalham, vivem e/ou frequentam a instituição”. Neste sentido, promovendo sempre a participação efetiva de pessoas com incapacidade e seus cuidadores, procedeu-se à utilização de técnicas que permitiram conhecer, analisar e trabalhar no contexto, tendo em vista a concretização dos objetivos gerais do projeto. Esses objetivos, de uma forma sinóptica, tinham como intenção promover uma melhor interação entre todas as pessoas do CAO, e melhorar o funcionamento do Centro de Atividades Ocupacionais (CAO) da Instituição. Assim, procurando sempre uma mudança construída e refletida por todos, num processo de avaliação contínua, é possível afirmar que existiu uma melhoria tanto a nível das dinâmicas relacionais, como ao nível de alguns aspetos relacionados com o funcionamento da valência