Unidade de Investigação - INESCC-DL – Instituto de Engenharia de Sistemas e Computadores de Coimbra [delegação Politécnico de Leiria]
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Browsing Unidade de Investigação - INESCC-DL – Instituto de Engenharia de Sistemas e Computadores de Coimbra [delegação Politécnico de Leiria] by Sustainable Development Goals (SDG) "07:Energias Renováveis e Acessíveis"
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- Analysis of Power Quality Disturbances in Industry in the Centre Region of PortugalPublication . Moreira, Licinio; Leitão, Sérgio; Vale, Zita; Galvão, João; Franco Marques, Pedro JoséPower quality issues have taken a more prominent role in power systems over the last years. These issues are of major concern for energy customers, primarily for customers with a widespread use of electronic devices in their manufacturing processes. Even though the quality of service is increasing, customers are becoming more demanding of the energy provider. This research aims to provide some industrial managers the technical support in deciding of investments in the mitigation of power quality disturbances, such as the use of less sensitive devices or the use of interface devices (UPS, DVR...) In order to recommend an appropriate solution, the problem is characterized. The technical and economic influences of the PQ disturbances in the manufacturing processes are assessed resorting to power quality audits in the customer facilities. This research covered a significant number of facilities in several industrial activities.
- Assessing the influence of uncertainty in land cover mapping and digital elevation models on flood risk mappingPublication . Gonçalves, Luísa M.S.; Fonte, Cidália C.; Gomes, RicardoThis paper proposes an approach to assess the influence of the uncertainty present in the parameters dependent on the land cover and elevation data over the peak flow values and the subsequent delineation of flooded areas. The proposed approach was applied to produce vulnerability and risk maps that integrate uncertainty for the urban area of Leiria, Portugal. A SPOT-4 satellite image and DEMs of the region were used. The peak flow was computed using the Soil Conservation Service method and HECHMS, HEC-RAS, Matlab and ArcGIS software programs were used. The analysis of the results obtained for the presented case study enables the identification of the order of magnitude of uncertainty associated to the watershed peak flow value and the identification of the areas which are more susceptible to flood risk to be identified.
- Autonomous Wireless Sensor with a Low Cost TEG for Application in Automobile VehiclesPublication . Costa, A.; Costa, D.; Morgado, J.; Santos, Helder; Ferreira, Carlos Daniel HenriquesThe present work consists in the development of an autonomous, low cost, reliable, energy scavenger sensor for automotive applications. Thermoelectric generators typically exhibit low efficiency but high reliability, making them suitable for autonomous, low average energy consumption, applications. A prototype sensor was developed for mounting in the engine exhaust pipe using a step-up voltage converter, a microcontroller, temperature and pressure sensing elements, conditioning electronics and a wireless transceiver, all powered by a low cost TEG (Peltier module TEC1-12706), through the scavenging of exhaust gases thermal energy. During the tests the prototype was able to sustain a regular signal transmission throughout the engine operation. The sensor was installed directly at the measuring point eliminating wired cables to hot and vibrating parts, thus, simplifying the installation of components and improving the reliability of the vehicle systems.
- Development of CART model for prediction of tuberculosis treatment loss to follow up in the state of São Paulo, Brazil: A case–control studyPublication . Yamaguti, Verena Hokino; Alves, Domingos; Rijo, Rui, Rui Pedro Charters Lopes; Miyoshi, Newton Shydeo Brandão; Ruffino-Netto, AntônioBackground: Tuberculosis is the leading cause of infectious disease-related death, surpassing even the immunodeficiency virus. Treatment loss to follow up and irregular medication use contribute to persistent morbidity and mortality. This increases bacillus drug resistance and has a negative impact on disease control. Objective: This study aims to develop a computational model that predicts the loss to follow up treatment in tuberculosis patients, thereby increasing treatment adherence and cure, reducing efforts regarding treatment relapses and decreasing disease spread. Methods: This is a case-controlled study. Included in the data set were 103,846 tuberculosis cases from the state of São Paulo. They were collected using the TBWEB, an information system used as a tuberculosis treatment monitor, containing samples from 2006 to 2016. This set was later resampled into 6 segments with a 1-1 ratio. This ratio was used to avoid any bias during the model construction. Results: The Classification and Regression Trees were used as the prediction model. Training and test sets accounted for 70% in the former and 30% in the latter of the tuberculosis cases. The model displayed an accuracy of 0.76, F-measure of 0.77, sensitivity of 0.80 and specificity of 0.71. The model emphasizes the relationship between several variables that had been identified in previous studies as related to patient cure or loss to follow up treatment in tuberculosis patients. Conclusion: It was possible to construct a predictive model for loss to follow up treatment in tuberculosis patients using Classification and Regression Trees. Although the fact that the ideal predictive ability was not achieved, it seems reasonable to propose the use of Classification and Regression Trees models to predict likelihood of treatment follow up to support healthcare professionals in minimising the loss to follow up.
- Energy management in municipal solid waste treatment: A case study of a mechanical biological treatment facilityPublication . Bernardo, Hermano; Oliveira, Filipe Tadeu; Quintal, EdgarOver the last few years, mechanical biological treatment systems for municipal solid waste have been introduced in many European countries. In most cases, this was driven by the European Union Landfill Directive, which requires the diversion of biodegradable municipal waste from landfill to alternative processes. Although this type of treatment allows energy recovery from municipal solid waste, the process of mechanical biological treatment appears to be an intensive energy consumer, due to high demand of electricity consumed by process equipment. This paper presents the main results of an energy audit performed to a Mechanical Biological Treatment facility in Portugal, which due to the amount of energy consumed must comply with the Portuguese Program called Intensive Energy Consumption Management System – SGCIE. The program was created in 2008 to promote energy efficiency and energy consumption monitoring in intensive energy facilities (energy consumption higher than 500 toe per year). Facilities operators are required to perform energy audits and take actions to draw up an action plan for energy efficiency, establishing targets for energy consumption reduction and greenhouse gases emissions indexes. To implement actions that improve energy efficiency, it is necessary for the facilities operation to be associated with an effective energy management methodology, as well as an efficient facilities management procedure. The implementation of any energy management system should start with an energy audit, which was carried out to identify potential energy conservation measures for improving energy efficiency, and also typical energy consumption patterns and sector/equipment load profiles. This tool gives managers the information to support decision making on improving energy performance and reducing greenhouse gas emissions. Results shown that there is a considerable potential for reducing energy consumption and greenhouse gases emissions on Mechanical Biological Treatment units. Here, as elsewhere in the industrial sector, energy efficiency can only be achieved through a continuous energy monitoring and management system.
- High Sensitivity Micro-machined Piezoresistive Strain SensorPublication . Caseiro, D.; Santos, S.; Ferreira, Carlos Daniel Henriques; Neves, CarlosThis paper presents a micro-machined piezoresistive sensor capable of measuring very small strains. The sensor design, based on piezoresistive sensing technology, was optimized by the numerical method using Finite Element Method (FEM) to enhance sensibility. The high sensibility is achieved through a reduction of section and through the action of the bending moment. As a result, a sensor with a sensitivity of 569.4608 μV/V/με, which can be fabricated by the SensoNor MultiMEMS process, is proposed. Furthermore, practical essays with macro prototypes confirmed and validated the numerical analysis. Such a sensor can be a direct replacement for the strain gauges and its very high sensitivity opens the door to many other applications, that otherwise would not be possible.
- Impact of load and generation price uncertainties in spot pricesPublication . Gomes, Bruno A.; Saraiva, João T.; Pires Neves, LuísIn this paper it is presented a formulation for the DC Optimal Power Flow problem considering load and generation cost uncertainties and the corresponding solution algorithms. The paper also details the algorithms implemented to allow the integration of losses on the results as well the algorithm developed to compute the nodal marginal price in the presence of such uncertainties. Since loads and generation costs are represented by fuzzy numbers, nodal marginal prices are no longer represented by deterministic values, but instead, by membership functions. To illustrate the application of the proposed algorithms, this paper also includes results based on a small 3 bus system and on the IEEE 24 bus/38 branch test system.
- Indoor air quality audit in two office buildings in PortugalPublication . Ramos, Joao; Pinto, FernandoThe indoor air quality that a building presents is not always from our knowledge. In fact, we may find ourselves exposed to an indoor air which can be harmful to human health, affecting the quality of life and productivity, which also will have economic repercussions at this level. Given the Portuguese law for energy and indoor air quality (IAQ) certification of large service buildings, the indoor air quality requirements were here presented and, in addition, this paper provides an overview of the current Portuguese IAQ technical procedures to audit existent buildings. It was also intended with this study to evaluate the indoor air quality experienced by the occupants of two office buildings, an old and a recent, with the same activity and occupancy, without air-conditioning systems, where were carried out indoor air quality characterizations and, in particular, have been assessed the CO2 concentration and the typical renewal air exchange rates in different zones of the buildings, as a ventilation effectiveness monitoring. During the building's regular occupancy period, the authors have been done monitoring campaigns, which took place in winter and summer seasons. They have been detected that the values of some parameters under review were non-compliance situations in winter, in contrast with the summer due to the increase of ventilation promoted by the occupants taking advantage of the favourable conditions of the Mediterranean weather. Consequently, the proposed IAQ audit approach may be helpful to characterize indoor air pollutants, to evaluate the ventilation effectiveness and to correlate it with the indoor air quality perception and self-control actions of the occupants.
- Load forecasting based on neural networks and load profilingPublication . Sousa, João; Pires Neves, Luís; H. M. JorgeThis work presents a novel perspective of load forecasting based on neural networks and load profiling. In addition to the variables that are typically used to predict future load demand, such as past load values, meteorological variables, seasonal effects or macroeconomic indexes, it is expected that the use of load profiles and detailed information of individual consumers could favor the forecasting process. The methodology can be extended to different temporal horizons being predicted and the eventual threat of overparametrization is attenuated by the use of neural networks since the complexity of the model does not necessarily depends on the number of its weights and biases, as some of these parameters might be found irrelevant in the process. Another way to reduce the risk of overparametrization and overfitting is through the use of a considerable number of data points (whenever historical data is available) to train the network.
- Network reconfiguration to improve reliability and efficiency in distribution systemsPublication . Vitorino, Romeu; Pires Neves, Luís; Jorge, H. M.This paper presents a new method to improve reliability and also minimize active power losses in radial distribution systems (RDS) through a process of network reconfiguration. The methodology adopted to enhance reliability, uses the Monte Carlo (MC) simulation and an historical data of the network such as the severity of the potential contingencies in each branch. Due to the greater number of possible configurations and the need of an efficient search, is also used an improved genetic algorithm (IGA), with adaptive crossover and mutation probabilities and with other new features. The method analyses the RDS in a perspective of optimization considering no investment, and a perspective of optimization where is given the possibility to place a limited number of tie-switches, defined by a decision agent, in certain branches. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.