Planeamento de redes de distribuição de energia

O planeamento de redes de distribuição tem como objetivo assegurar a existência de capacidade nas redes para a fornecimento de energia elétrica com bons níveis de qualidade de serviço tendo em conta os fatores económicos associados. No âmbito do trabalho apresentado na presente dissertação, foi elaborado um modelo de planeamento que determina a configuração de rede resultante da minimização de custos associados a: 1) perdas por efeito de joule; 2) investimento em novos componentes; 3) energia não entregue. A incerteza associada ao valor do consumo de cada carga é modelada através de lógica difusa. O problema de otimização definido é resolvido pelo método de decomposição de benders que contempla dois trânsitos de potências ótimos (modelo DC e modelo AC) no problema mestre e escravo respectivamente para validação de restrições. Foram também definidos critérios de paragem do método de decomposição de benders. O modelo proposto classifica-se como programação não linear inteira mista e foi implementado na ferramenta de otimização General Algebraic Modeling System (GAMS). O modelo desenvolvido tem em conta todos componentes das redes para a otimização do planeamento, conforme podemos analisar nos casos de estudo implementados. Cada caso de estudo é definido pela variação da importância que cada uma das variáveis do problema toma, tendo em vista cobrir de alguma todos os cenários de operação expetáveis. Através destes casos de estudo verifica-se as várias configurações que a rede pode tomar, tendo em conta as importâncias atribuídas a cada uma das variáveis, bem como os respetivos custos associados a cada solução. Este trabalho oferece um considerável contributo no âmbito do planeamento de redes de distribuição, pois comporta diferentes variáveis para a execução do mesmo. É também um modelo bastante robusto não perdendo o ‘norte’ no encontro de solução para redes de grande dimensão, com maior número de componentes.

Characterization and optimization of bovine Echinococcus granulosus cyst fluid to be used in immunodiagnosis of hydatid disease by ELISA

The aim of this work was to assess the influence in the diagnostic value for human hydatid disease of the composition of bovine hydatid cyst fluid (BHCF) obtained from fertile (FC) and non-fertile cysts (NFC). Eight batches from FC and 5 from NFC were prepared and analysed with respect to chemical composition: total protein, host-derived protein, carbohydrate and lipid contents. No differences were observed in the first two parameters but carbohydrate and lipid contents were shown to be higher in batches from FC than in those from NFC. Bands of 38 and 116 kD in SDS-PAGE profiles were observed to be present in BHCF from FC only. Two pools were prepared from BHCF batches obtained from FC (PFC) and NFC (PNFC), respectively. Antigen recognition patterns were analysed by immunoblot. Physicochemical conditions for adsorption of antigens to the polystyrene surface (ELISA plates) were optimized. The diagnostic value of both types of BHCF as well as the diagnostic relevance of oxidation of their carbohydrate moieties with periodate were assessed by ELISA using 42 serum samples from hydatid patients, 41 from patients with other disorders, and 15 from healthy donors. Reactivity of all sera against native antigen were tested with and without free phosphorylcholine. The best diagnostic efficiency was observed using BHCF from periodate-treated PFC using glycine buffer with strong ionic strength to coat ELISA plates.

Probabilistic maintenance and optimization strategies for deteriorating civil infrastructures

In developed countries, civil infrastructures are one of the most significant investments of governments, corporations, and individuals. Among these, transportation infrastructures, including highways, bridges, airports, and ports, are of huge importance, both economical and social. Most developed countries have built a fairly complete network of highways to fit their needs. As a result, the required investment in building new highways has diminished during the last decade, and should be further reduced in the following years. On the other hand, significant structural deteriorations have been detected in transportation networks, and a huge investment is necessary to keep these infrastructures safe and serviceable. Due to the significant importance of bridges in the serviceability of highway networks, maintenance of these structures plays a major role. In this paper, recent progress in probabilistic maintenance and optimization strategies for deteriorating civil infrastructures with emphasis on bridges is summarized. A novel model including interaction between structural safety analysis,through the safety index, and visual inspections and non destructive tests, through the condition index, is presented. Single objective optimization techniques leading to maintenance strategies associated with minimum expected cumulative cost and acceptable levels of condition and safety are presented. Furthermore, multi-objective optimization is used to simultaneously consider several performance indicators such as safety, condition, and cumulative cost. Realistic examples of the application of some of these techniques and strategies are also presented.

Selection Constructive based Hyper-heuristic for Dynamic Scheduling

A função de escalonamento desempenha um papel importante nos sistemas de produção. Os sistemas de escalonamento têm como objetivo gerar um plano de escalonamento que permite gerir de uma forma eficiente um conjunto de tarefas que necessitam de ser executadas no mesmo período de tempo pelos mesmos recursos. Contudo, adaptação dinâmica e otimização é uma necessidade crítica em sistemas de escalonamento, uma vez que as organizações de produção têm uma natureza dinâmica. Nestas organizações ocorrem distúrbios nas condições requisitos de trabalho regularmente e de forma inesperada. Alguns exemplos destes distúrbios são: surgimento de uma nova tarefa, cancelamento de uma tarefa, alteração na data de entrega, entre outros. Estes eventos dinâmicos devem ser tidos em conta, uma vez que podem influenciar o plano criado, tornando-o ineficiente. Portanto, ambientes de produção necessitam de resposta imediata para estes eventos, usando um método de reescalonamento em tempo real, para minimizar o efeito destes eventos dinâmicos no sistema de produção. Deste modo, os sistemas de escalonamento devem de uma forma automática e inteligente, ser capazes de adaptar o plano de escalonamento que a organização está a seguir aos eventos inesperados em tempo real. Esta dissertação aborda o problema de incorporar novas tarefas num plano de escalonamento já existente. Deste modo, é proposta uma abordagem de otimização – Hiper-heurística baseada em Seleção Construtiva para Escalonamento Dinâmico- para lidar com eventos dinâmicos que podem ocorrer num ambiente de produção, a fim de manter o plano de escalonamento, o mais robusto possível. Esta abordagem é inspirada em computação evolutiva e hiper-heurísticas. Do estudo computacional realizado foi possível concluir que o uso da hiper-heurística de seleção construtiva pode ser vantajoso na resolução de problemas de otimização de adaptação dinâmica.

Trade-Off Performance Regions of Slotted ALOHA Protocol using Multi-Objective Optimization

10th Conference on Telecommunications (Conftele 2015), Aveiro, Portugal.

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

A Real-Time Optimization for 2R Manipulators

This work proposes a real-time algorithm to generate a trajectory for a 2 link planar robotic manipulator. The objective is to minimize the space/time ripple and the energy requirements or the time duration in the robot trajectories. The proposed method uses an off line genetic algorithm to calculate every possible trajectory between all cells of the workspace grid. The resultant trajectories are saved in several trees. Then any trajectory requested is constructed in real-time, from these trees. The article presents the results for several experiments.

Optimization of random amplified polymorphic DNA techniques for use in genetic studies of Cuban triatominae

Random amplified polymorphic DNA (RAPD) technique is a simple and reliable method to detect DNA polymorphism. Several factors can affect the amplification profiles, thereby causing false bands and non-reproducibility of assay. In this study, we analyzed the effect of changing the concentration of primer, magnesium chloride, template DNA and Taq DNA polymerase with the objective of determining their optimum concentration for the standardization of RAPD technique for genetic studies of Cuban Triatominae. Reproducible amplification patterns were obtained using 5 pmoL of primer, 2.5 mM of MgCl2, 25 ng of template DNA and 2 U of Taq DNA polymerase in 25 µL of the reaction. A panel of five random primers was used to evaluate the genetic variability of T. flavida. Three of these (OPA-1, OPA-2 and OPA-4) generated reproducible and distinguishable fingerprinting patterns of Triatominae. Numerical analysis of 52 RAPD amplified bands generated for all five primers was carried out with unweighted pair group method analysis (UPGMA). Jaccard's Similarity Coefficient data were used to construct a dendrogram. Two groups could be distinguished by RAPD data and these groups coincided with geographic origin, i.e. the populations captured in areas from east and west of Guanahacabibes, Pinar del Río. T. flavida present low interpopulation variability that could result in greater susceptibility to pesticides in control programs. The RAPD protocol and the selected primers are useful for molecular characterization of Cuban Triatominae.

Chaotic Phenomena and Performance Optimization in the Trajectory Control of Redundant Manipulators

Redundant manipulators have some advantages when compared with classical arms because they allow the trajectory optimization, both on the free space and on the presence of abstacles, and the resolution of singularities. For this type of manipulators, several kinetic algorithms adopt generalized inverse matrices. In this line of thought, the generalized inverse control scheme is tested through several experiments that reveal the difficulties that often arise. Motivated by theseproblems this paper presents a new method that ptimizes the manipulability through a least squre polynomialapproximation to determine the joints positions. Moreover, the article studies influence on the dynamics, when controlling redundant and hyper-redundant manipulators. The experiment confirm the superior performance of the proposed algorithm for redundant and hyper-redundant manipulators, revealing several fundamental properties of the chaotic phenomena, and gives a deeper insight towards the future development of superior trajectory control algorithms.

Optimization of the Sybr Green real time PCR for the detection of Human Herpes Virus type 6 (HHV-6)

HHV-6 is the etiological agent of Exanthem subitum which is considered the sixth most frequent disease in infancy. In immuno-compromised hosts, reactivation of latent HHV-6 infection may cause severe acute disease. We developed a Sybr Green Real Time PCR for HHV-6 and compared the results with nested conventional PCR. A 214 pb PCR derived fragment was cloned using pGEM-T easy from Promega system. Subsequently, serial dilutions were made in a pool of negative leucocytes from 10-6 ng/µL (equivalent to 2465.8 molecules/µL) to 10-9 (equivalent to 2.46 molecules/µL). Dilutions of the plasmid were amplified by Sybr Green Real Time PCR, using primers HHV3 (5' TTG TGC GGG TCC GTT CCC ATC ATA 3)'and HHV4 (5' TCG GGA TAG AAA AAC CTA ATC CCT 3') and by conventional nested PCR using primers HHV1 (outer): 5'CAA TGC TTT TCT AGC CGC CTC TTC 3'; HHV2 (outer): 5' ACA TCT ATA ATT TTA GAC GAT CCC 3'; HHV3 (inner) and HHV4 (inner) 3'. The detection threshold was determined by plasmid serial dilutions. Threshold for Sybr Green real time PCR was 24.6 molecules/µL and for the nested PCR was 2.46 molecules/µL. We chose the Real Time PCR for diagnosing and quantifying HHV-6 DNA from samples using the new Sybr Green chemistry due to its sensitivity and lower risk of contamination.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Optimization of the Tartrate-Resistant Acid Phosphatase Detection by Histochemical Method

According to the new KDIGO (Kidney Disease Improving Global Outcomes) guidelines, the term of renal osteodystrophy, should be used exclusively in reference to the invasive diagnosis of bone abnormalities. Due to the low sensitivity and specificity of biochemical serum markers of bone remodelling,the performance of bone biopsies is highly stimulated in dialysis patients and after kidney transplantation. The tartrate-resistant acid phosphatase (TRACP) is an iso-enzyme of the group of acid phosphatases, which is highly expressed by activated osteoclasts and macrophages. TRACP in osteoclasts is in intracytoplasmic vesicles that transport the products of bone matrix degradation. Being present in activated osteoclasts, the identification of this enzyme by histochemistry in undecalcified bone biopsies is an excellent method to quantify the resorption of bone. Since it is an enzymatic histochemical method for a thermolabile enzyme, the temperature at which it is performed is particularly relevant. This study aimed to determine the optimal temperature for identification of TRACP in activated osteoclasts in undecalcified bone biopsies embedded in methylmethacrylate. We selected 10 cases of undecalcified bone biopsies from hemodialysis patients with the diagnosis of secondary hyperparathyroidism. Sections of 5 μm were stained to identify TRACP at different incubation temperatures (37º, 45º, 60º, 70º and 80ºC) for 30 minutes. Activated osteoclasts stained red and trabecular bone (mineralized bone) was contrasted with toluidine blue. This approach also increased the visibility of the trabecular bone resorption areas (Howship lacunae). Unlike what is suggested in the literature and in several international protocols, we found that the best results were obtained with temperatures between 60ºC and 70ºC. For technical reasons and according to the results of the present study, we recommended that, for an incubation time of 30 minutes, the reaction should be carried out at 60ºC. As active osteoclasts are usually scarce in a bone section, the standardization of the histochemistry method is of great relevance, to optimize the identification of these cells and increase the accuracy of the histomosphometric results. Our results, allowing an increase in osteoclasts contrast, also support the use of semi-automatic histomorphometric measurements.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

Towards Human-like Bimanual Movements in Anthropomorphic Robots: A Nonlinear Optimization Approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

Modelling and optimization of the ion exchange membrane bioreactor for removal of anionic pollutants from drinking water streams

Dissertação para obtenção do Grau de Doutor em Engenharia Química, especialidade de Engenharia Bioquímica