Dimensionamento de estacas baseado nos princípios da dinâmica de cravação do SPT

Este trabalho insere-se no domínio da calibração energética dos equipamentos SPT, dando seguimento ao disposto na norma EN ISO 22476-3, de aplicação obrigatória em Portugal. Para tal foi utilizada uma vara instrumentada, cuja instrumentação consiste em strain-gauges e acelerómetros piezoeléctricos. Esta instrumentação encontra-se fixa a um trecho de vara com comprimento de 60 cm e para a aquisição dos dados foi utilizado o sistema SPT Analyzer® comercializado pela firma PDI. O sistema permite registar os dados provenientes da instrumentação: sinais de um par de strain-gauges, transformados em registos de força (F1 e F2) e sinais de um par de acelerómetros, convertidos em registos de velocidade (V1 e V2) ao longo do tempo. O equipamento permite a avaliação, em tempo real, da qualidade dos registos e da energia máxima transmitida à vara em cada golpe e o conhecimento do deslocamento vertical do trem de varas ocorrido em cada golpe do martelo. Por outro lado, baseando-se no tema acima referido, pretende-se ainda desenvolver esforços no sentido de melhorar o novo método interpretativo dos resultados dos ensaios SPT e sua aplicação ao dimensionamento de estacas, dado que a previsão da capacidade de carga de estacas constitui um dos desafios da engenharia de fundações por requerer a estimativa de propriedades do solo, alterações pela execução da fundação e conhecimento do mecanismo de interacção solo-estaca. Este novo procedimento baseia-se nos princípios da dinâmica, rompendo com as metodologias até aqui consagradas, de natureza essencialmente empírica. A nova forma de interpretar os ensaios SPT, consubstanciada nos princípios de conservação de energia na cravação do amostrador SPT, irá permitir converter analiticamente o valor Nspt numa força dinâmica de reacção à penetração. A decomposição desta força dinâmica permite efectuar análises comparativas entre as resistências unitárias mobilizadas no amostrador SPT (modelo) e as mobilizadas na estaca (protótipo).

Estudo geotécnico dos solos do vale do Leça no âmbito de uma obra de requalificação portuária

A expansão da área ocupada pelo Porto de Leixões (Matosinhos e Leça da Palmeira), sobre solos muito compressíveis, de origem fluvial e marinha, leva a que seja necessário recorrer à engenharia para encontrar soluções adequadas à utilização de obras dos fins em vista. Assim, na zona do porto são muitos os projectos de engenharia civil/geotécnica executados nestes solos. Como exemplo, podem citar-se a Consolidação do Terrapleno e Construção dos Caminhos de Rolamento do Terminal de Contentores TC4S, a Reabilitação de um troço com 110m, do Cais Sul e do Cais Nascente da Doca nº 4 e a Construção da Portaria Principal do Porto de Leixões, todos no vale fóssil do rio Leça. São vastos os métodos a usar para o melhoramento destes solos, a colocação de colunas de brita, com o objectivo de reforçar o solo, aumentando a sua capacidade de carga e funcionando como drenos verticais, para solucionar o problema das deformações excessivas durante e após o final da obra, uma alternativa consiste em induzir a aceleração da consolidação da camada de solo mole, o uso de pré-carregamento e drenos verticais são usuais. Quando o tempo de concretização da obra exige que o aterro seja utilizado de imediato, uma solução viável é a colocação de estacas, que transferem o peso do aterro, ou parte dele, para camadas mais competentes. Também se pode proceder à retirada do solo original e substituí-lo por outro de qualidade superior. A mais recente técnica de melhoria de solos por injecção - jet grouting - é utilizada em diversas situações, incluindo obras provisórias e definitivas. O presente trabalho visa descrever, em função dos diversos factores, o comportamento do solo face aos vários métodos utilizados e os objectivos pretendidos que serão abordados no enquadramento empírico do trabalho.

Contribution of hospital effluents to the load of pharmaceuticals in urban wastewaters: Identification of ecologically relevant pharmaceuticals

The impact of effluent wastewaters from four different hospitals: a university (1456 beds), a general (350 beds), a pediatric (110 beds) and a maternity hospital (96 beds), which are conveyed to the same wastewater treatment plant (WWTP), was evaluated in the receiving urban wastewaters. The occurrence of 78 pharmaceuticals belonging to several therapeutic classes was assessed in hospital effluents and WWTP wastewaters (influent and effluent) as well as the contribution of each hospital in WWTP influent in terms of pharmaceutical load. Results indicate that pharmaceuticals are widespread pollutants in both hospital and urban wastewaters. The contribution of hospitals to the input of pharmaceuticals in urban wastewaters widely varies, according to their dimension. The estimated total mass loadings were 306 g d− 1 for the university hospital, 155 g d− 1 for the general one, 14 g d− 1 for the pediatric hospital and 1.5 g d− 1 for the maternity hospital, showing that the biggest hospitals have a greater contribution to the total mass load of pharmaceuticals. Furthermore, analysis of individual contributions of each therapeutic group showed that NSAIDs, analgesics and antibiotics are among the groups with the highest inputs. Removal efficiency can go from over 90% for pharmaceuticals like acetaminophen and ibuprofen to not removal for β-blockers and salbutamol. Total mass load of pharmaceuticals into receiving surface waters was estimated between 5 and 14 g/d/1000 inhabitants. Finally, the environmental risk posed by pharmaceuticals detected in hospital and WWTP effluents was assessed by means of hazard quotients toward different trophic levels (algae, daphnids and fish). Several pharmaceuticals present in the different matrices were identified as potentially hazardous to aquatic organisms, showing that especial attention should be paid to antibiotics such as ciprofloxacin, ofloxacin, sulfamethoxazole, azithromycin and clarithromycin, since their hazard quotients in WWTP effluent revealed that they could pose an ecotoxicological risk to algae.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Impacto da influência do ar novo na climatização de edifícios

Este trabalho surgiu do âmbito da Tese de Dissertação do Mestrado em Energias Sustentáveis do Instituto Superior de Engenharia do Porto, tendo o acompanhamento dos orientadores da empresa Laboratório Ecotermolab do Instituto de Soldadura e Qualidade e do Instituto Superior de Engenharia do Porto, de forma a garantir a linha traçada indo de acordo aos objectivos propostos. A presente tese abordou o estudo do impacto da influência do ar novo na climatização de edifícios, tendo como base de apoio à análise a simulação dinâmica do edifício em condições reais num programa adequado, acreditado pela norma ASHRAE 140-2004. Este trabalho pretendeu evidenciar qual o impacto da influência do ar novo na climatização de um edifício com a conjugação de vários factores, tais como, ocupação, actividades e padrões de utilização (horários), iluminação e equipamentos, estudando ainda a possibilidade do sistema funcionar em regime de “Free-Cooling”. O princípio partiu fundamentalmente por determinar até que ponto se pode climatizar recorrendo único e exclusivamente à introdução de ar novo em regime de “Free-Cooling”, através de um sistema tudo-ar de Volume de Ar Variável - VAV, sem o apoio de qualquer outro sistema de climatização auxiliar localizado no espaço, respeitando os caudais mínimos impostos pelo RSECE (Decreto-Lei 79/2006). Numa primeira fase foram identificados todos os dados relativos à determinação das cargas térmicas do edifício, tendo em conta todos os factores e contributos alusivos ao valor da carga térmica, tais como a transmissão de calor e seus constituintes, a iluminação, a ventilação, o uso de equipamentos e os níveis de ocupação. Consequentemente foram elaboradas diversas simulações dinâmicas com o recurso ao programa EnergyPlus integrado no DesignBuilder, conjugando variáveis desde as envolventes à própria arquitectura, perfis de utilização ocupacional, equipamentos e taxas de renovação de ar nos diferentes espaços do edifício em estudo. Obtiveram-se vários modelos de forma a promover um estudo comparativo e aprofundado que permitisse determinar o impacto do ar novo na climatização do edifício, perspectivando a capacidade funcional do sistema funcionar em regime de “Free-Cooling”. Deste modo, a análise e comparação dos dados obtidos permitiram chegar às seguintes conclusões: Tendo em consideração que para necessidades de arrefecimento bastante elevadas, o “Free-Cooling” diurno revelou-se pouco eficaz ou quase nulo, para o tipo de clima verificado em Portugal, pois o diferencial de temperatura existente entre o exterior e o interior não é suficiente de modo a tornar possível a remoção das cargas de forma a baixar a temperatura interior para o intervalo de conforto. Em relação ao “Free-Cooling” em horário nocturno ou pós-laboral, este revelou-se bem mais eficiente. Obtiveram-se prestações muito interessantes sobretudo durante as estações de aquecimento e meia-estação, tendo em consideração o facto de existir necessidades de arrefecimento mesmo durante a estação de aquecimento. Referente à ventilação nocturna, isto é, em períodos de madrugada e fecho do edifício, concluiu-se que tal contribui para um abaixamento do calor acumulado durante o dia nos materiais construtivos do edifício e que é libertado ou restituído posteriormente para os espaços em períodos mais tardios. De entre as seguintes variáveis, aumento de caudal de ar novo insuflado e o diferencial de temperatura existente entre o ar exterior e interior, ficou demonstrado que este último teria maior peso contributivo na remoção do calor. Por fim, é ponto assente que de um modo geral, um sistema de climatização será sempre indispensável devido a cargas internas elevadas, requisitos interiores de temperatura e humidade, sendo no entanto aconselhado o “Free- Cooling” como um opção viável a incorporar na solução de climatização, de forma a promover o arrefecimento natural, a redução do consumo energético e a introdução activa de ar novo.

Impact of prescribed fire on the chemical properties of soil

Prescribed fire is a common forest management tool used in Portugal to reduce the fuel load availability and minimize the occurrence of wildfires. In addition, the use of this technique also causes an impact to ecosystems. In this presentation we propose to illustrate some results of our project in two forest sites, both located in Northwest Portugal, where the effect of prescribed fire on soil properties were recorded during a period of 6 months. Changes in soil moisture, organic matter, soil pH and iron, were examined by Principal Component Analysis multivariate statistics technique in order to determine impact of prescribed fire on these soil properties in these two different types of soils and determine the period of time that these forest soils need to recover to their pre-fire conditions, if they can indeed recover. Although the time allocated to this study does not allow for a widespread conclusion, the data analysis clearly indicates that the pH values are positively correlated with iron values at both sites. In addition, geomorphologic differences between both sampling sites, Gramelas and Anjos, are relevant as the soils’ properties considered have shown different performances in time. The use of prescribed fire produced a lower impact in soils originated from more amended bedrock and therefore with a ticker humus covering (Gramelas) than in more rocky soils with less litter covering (Anjos) after six months after the prescribed fire occurrence.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.