Controlo preditivo distribuído em edifícios para conforto térmico e alocação de cargas

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Impacto económico, energético e ambiental da produção renovável na Ilha Terceira

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

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.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Genetic and Antigenic Analysis of Adenovirus Type 3 Strains Showing Intermediate Behavior in Standard Seroneutralization Test

During an epidemiological survey of acute respiratory infection in Rio de Janeiro, among 208 adenovirus isolates, we found two strains that we were not able, by a standard neutralization procedure, to distinguish between type 3 or 7. However, DNA restriction pattern for the two strains with different enzymes were analyzed and showed a typical Ad3h profile. Using a cross-neutralization test in which both Ad3p and Ad7p antisera were used in different concentration against 100 TCID50 of each adenovirus standard and both isolates, we were able to confirm that the two isolates belong to serotype 3. An hemagglutination inhibition test also corroborated the identification of both strains as adenovirus type 3. Comparing Ad3h and Ad3p genome, we observed 16 different restriction enzyme sites, three of which were located in genomic regions encoding polypeptides involved in neutralization sites

Analysis of genetic diversity of Trypanosoma cruzi: an application of riboprinting and gradient gel electrophoresis methods

Analysis of restriction fragment length polymorphism (RFLP) profiles derived from digestion of polymerase chain reaction (PCR) products of the ribosomal 18S from Trypanosoma cruzi yields a typical `riboprint' profile that can vary intraspecifically. A selection of 21 stocks of T. cruzi and three outgroup taxa: T. rangeli, T. conorhini and Leishmania braziliensis were analysed by riboprinting to assess divergence within and between taxa. T. rangeli, T. conorhini and L. braziliensis could be easily differentiated from each other and from T. cruzi. Phenetic analysis of PCR-RFLP profiles indicated that, with one or two exceptions, stocks of T. cruzi could be broadly partitioned into two groups that formally corresponded to T. cruzi I and T. cruzi II respectively. To test if ribosomal 18S sequences were homogeneous within each taxon, gradient gel electrophoresis methods were employed utilising either chemical or temperature gradients. Upon interpretation of the melting profiles of riboprints and a section of the 18S independently amplified by PCR, there would appear to be at least two divergent 18S types present within T. cruzi. Heterogeneity within copies of the ribosomal 18S within a single genome has therefore been demonstrated and interestingly, this dimorphic arrangement was also present in the outgroup taxa. Presumably the ancestral duplicative event that led to the divergent 18S types preceded that of speciation within this group. These divergent 18S paralogues may have, or had, different functional pressures or rates of molecular evolution. Whether or not these divergent types are equally transcriptionally active throughout the life cycle, remain to be assessed.

Short-term forecasting of power demand in the Nord Pool market

Sähkönkulutuksen lyhyen aikavälin ennustamista on tutkittu jo pitkään. Pohjoismaisien sähkömarkkinoiden vapautuminen on vaikuttanut sähkönkulutuksen ennustamiseen. Aluksi työssä perehdyttiin aiheeseen liittyvään kirjallisuuteen. Sähkönkulutuksen käyttäytymistä tutkittiin eri aikoina. Lämpötila tilastojen käyttökelpoisuutta arvioitiin sähkönkulutusennustetta ajatellen. Kulutus ennusteet tehtiin tunneittain ja ennustejaksona käytettiin yhtä viikkoa. Työssä tutkittiin sähkönkulutuksen- ja lämpötiladatan saatavuutta ja laatua Nord Poolin markkina-alueelta. Syötettävien tietojen ominaisuudet vaikuttavat tunnittaiseen sähkönkulutuksen ennustamiseen. Sähkönkulutuksen ennustamista varten mallinnettiin kaksi lähestymistapaa. Testattavina malleina käytettiin regressiomallia ja autoregressiivistä mallia (autoregressive model, ARX). Mallien parametrit estimoitiin pienimmän neliösumman menetelmällä. Tulokset osoittavat että kulutus- ja lämpötiladata on tarkastettava jälkikäteen koska reaaliaikaisen syötetietojen laatu on huonoa. Lämpötila vaikuttaa kulutukseen talvella, mutta se voidaan jättää huomiotta kesäkaudella. Regressiomalli on vakaampi kuin ARX malli. Regressiomallin virhetermi voidaan mallintaa aikasarjamallia hyväksikäyttäen.

Differential patterns of myosin Va expression during the ontogenesis of the rat hippocampus

Myosin Va is an actin-based, processive molecular motor protein highly enriched in the nervous tissue of vertebrates. It has been associated with processes of cellular motility, which include organelle transport and neurite outgrowth. The in vivo expression of myosin Va protein in the developing nervous system of mammals has not yet been reported. We describe here the immunolocalization of myosin Va in the developing rat hippocampus. Coronal sections of the embryonic and postnatal rat hippocampus were probed with an affinity-purified, polyclonal anti-myosin Va antibody. Myosin Va was localized in the cytoplasm of granule cells in the dentate gyrus and of pyramidal cells in Ammon's horn formation. Myosin Va expression changed during development, being higher in differentiating rather than already differentiated granule and pyramidal cells. Some of these cells presented a typical migratory profile, while others resembled neurons that were in the process of differentiation. Myosin Va was also transiently expressed in fibers present in the fimbria. Myosin Va was not detected in germinative matrices of the hippocampus proper or of the dentate gyrus. In conclusion, myosin Va expression in both granule and pyramidal cells showed both position and time dependency during hippocampal development, indicating that this motor protein is under developmental regulation.

Design, testing, and simulation of fibre composite leaf springs for heavy axle loads

This paper summarizes the design, manufacturing, testing, and finite element analysis (FEA) of glass-fibre-reinforced polyester leaf springs for rail freight vehicles. FEA predictions of load-deflection curves under static loading are presented, together with comparisons with test results. Bending stress distribution at typical load conditions is plotted for the springs. The springs have been mounted on a real wagon and drop tests at tare and full load have been carried out on a purpose-built shaker rig. The transient response of the springs from tests and FEA is presented and discussed.

The co-occurrence of autism and Williams syndrome: a case study report

This paper describes a longitudinal case study detailing the communication profile of one child with both Williams syndrome (WS) and autism. The participant was administered two standardized assessments of language and general cognitive abilities. His parents completed the Pre-Verbal Communication Schedule; and a sample of the child's spontaneous interaction was analyzed. The results show that this child presents with markedly delayed language and communication skills and that his communication profile is the opposite of the assumed 'typical' WS profile. The conclusion is that clinicians need to be aware of the co-occurrence of genetic disorders, such as WS and autism in order to facilitate accurate diagnosis and effective treatment.

Design method for solar heating systems in combination with pellet boilers/stoves

In this study an optimization method for the design of combined solar and pellet heating systems is presented and evaluated. The paper describes the steps of the method by applying it for an example of system. The objective of the optimization was to find the design parameters that give the lowest auxiliary energy (pellet fuel + auxiliary electricity) and carbon monoxide (CO) emissions for a system with a typical load, a single family house in Sweden. Weighting factors have been used for the auxiliary energy use and CO emissions to give a combined target function. Different weighting factors were tested. The results show that extreme weighting factors lead to their own minima. However, it was possible to find factors that ensure low values for both auxiliary energy and CO emissions.

Evaluation of a Micro PV-Diesel Hybrid System in Tanzania

In April 2011 a monitoring system was installed to enable studies of the performance and the usage of a micro PV-Diesel Hybrid system at the Ihushi Development Center (IDC) near Mwanza in Tanzania. Estimations of the load have been obtained by a survey of installed appliances and interviews with users of installed equipment. The load profile obtained by measurements has been analyzed and compared to estimations of the energy use. Further, the system size and performance were studied.

Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.