Sistema de Torre de Refrigeração

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

Otimização Energética do Sistema de Refrigeração da máquina de impregnar ZELL

Esta dissertação teve como objetivo fundamental a otimização energética do sistema de refrigeração da máquina de impregnar tela ZELL e, como objetivo adicional, a avaliação da qualidade da água do circuito, justificada pela acentuada degradação dos rolos devido à corrosão provocada pela recirculação da água de arrefecimento. Inicialmente fez-se o levantamento de informações do processo produtivo para caracterizar o funcionamento do sistema de refrigeração, tendo-se selecionado duas telas de poliéster designadas neste estudo por P1 e P2 e, também, uma tela de nylon designada por N. Foram efetuados ensaios, um para cada tela, para a atual temperatura de setpoint da água à saída da torre de arrefecimento (30ºC). Realizou-se outro ensaio para a tela N mas com uma temperatura de setpoint de 37ºC, ao qual se chamou N37. Deste modo, determinou-se as potências térmicas removidas pela água de refrigeração e as potências térmicas perdidas por radiação e por convecção, tendo-se verificado que na generalidade dos rolos as referências P1 e P2 apresentam valores mais elevados. Em termos percentuais, a potência térmica removida pela água de refrigeração nos grupos tratores 1 e 3 e no conjunto de rolos de R1 a R29 corresponde a 48%, 10% e 70%, respetivamente. Com a avaliação às necessidades de arrefecimento da máquina ZELL, confirmou-se que os caudais atuais de refrigeração dos rolos garantem condições, mais que suficientes, de funcionamento dos rolamentos. Assim sendo, fez-se uma análise no sentido da diminuição do caudal total que passou de 10,25 L/s para 7,65 L/s. Considerando esta redução, determinou-se o caudal de ar húmido a ser introduzido na torre de arrefecimento. O valor determinado foi de 4,6 m3ar húmido/s, o que corresponde a uma redução de cerca de 32% em relação ao caudal atual que é de 6,8 m3ar húmido/s. Com os resultados das análises efetuadas à água do circuito de refrigeração, concluiu-se que a água de reposição e a água de recirculação possuem má qualidade para uso na generalidade dos sistemas de refrigeração, principalmente devido aos elevados valores de concentração de ferro e condutividade elétrica, responsáveis pela intensificação da corrosão no interior dos rolos.

Finite Element Analysis (FEA) applied to heat transfer optimization process of pultrusion die systems

The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

Proposta de modelo para obtenção do Work Index das rochas

Este trabalho pretende estabelecer uma relação entre o Work Index e algumas propriedades das rochas. Através da pesquisa bibliográfica foram identificadas varias propriedades com possível influência no valor do Work Index, das quais foram seleccionadas a massa volúmica aparente, a resistência à carga pontual, a composição química, a composição mineralógica e a abrasividade. Adicionalmente a porosidade aberta e resistência à compressão também foram analisadas. Assim foram analisadas 10 amostras de rocha, quatro de granitos, uma de quartzodiorito, uma de ardósia, uma de serpentinito, uma de calcário, uma de mármore e uma de sienito nefelínico, sobre as quais já eram conhecidos os valores de cinco das propriedades referidas previamente, tendo sido determinados os valores das ainda desconhecidas, resistência à carga pontual e a abrasividade que está representada através do resultado do ensaio capon. Devido à dificuldade de execução do ensaio de determinação do Work Index de Bond foram recolhidos dados bibliográficos de valores do Work Index para as amostras de rocha seleccionadas e adoptado o valor médio para cada uma. Os dados obtidos foram tratados estatisticamente através do método de análise de componentes principais assim como através de regressões lineares simples e múltiplas. A análise de componentes principais permitiu identificar várias propriedades da rocha com possível influência sobre o Work Index de entre as analisadas. Foi possível estabelecer uma relação entre o Work Index e quatro das propriedades seleccionadas, designadamente a porosidade aberta, a resistência à compressão, a resistência à carga pontual e a abrasividade.

Force and pressure analysis during occasional loaded gait

O documento em anexo encontra-se na versão pre-print (versão inicial enviada para o editor).

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

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.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

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.

Efeito agudo do exercício físico na rigidez arterial

Este estudo pretendeu reproduzir uma tarefa da vida diária (marcha com transporte de peso nos membros superiores) realizada de forma rotineira e até aconselhada no contexto da prevenção e reabilitação de patologia cardiovascular, desta forma, teve como objectivo avaliar o efeito agudo de uma sessão de exercício aeróbio associado a exercício isométrico na rigidez arterial em indivíduos jovens. Foram recrutados 14 indivíduos do sexo masculino com média de idade de 30,3±3,6 anos. Foram realizadas duas sessões de exercício com uma semana de intervalo. Em ambas as sessões de exercício, os sujeitos caminharam num tapete rolante a uma velocidade de 5,0 km/h por um período de dez minutos, sendo que, numa das sessões, determinada aleatoriamente, carregaram o equivalente a 10% do seu peso corporal distribuído igualmente pelos dois membros superiores em dois garrafões de água. Avaliou-se em repouso e imediatamente após o exercício, a pressão arterial periférica, a frequência cardíaca e a rigidez arterial. A análise da rigidez arterial foi efectuada na artéria radial do membro superior direito com um sistema transdutor automático de pressão. Os parâmetros reportados neste estudo são a frequência cardíaca, a pressão arterial sistólica e diastólica, a pressão arterial média, a pressão central (aórtica) sistólica, a pressão de pulso central, a pressão de aumentação e o índice de aumentação a 75 bmp (Aix@75). Em repouso, não se verificaram diferenças significativas entre as duas sessões de exercício nos parâmetros avaliados. O principal resultado do presente estudo indica que a rigidez arterial aumenta de forma aguda com a realização de caminhada (exercício aeróbio) apenas quando esta é acompanhada do transporte nos membros superiores de uma carga externa (exercício isométrico) [Aix@75: -5.5(8.4) para -1.36(8.17)%, p<0.05]. Relativamente ao protocolo exclusivamente aeróbio não se verificaram diferenças significativas na rigidez arterial [Aix@75: -4.2(9.1) para -4.69(7.93)%, p>0.05]. Em conclusão, os resultados do presente estudo indicam que a rigidez arterial, em indivíduos jovens e aparentemente saudáveis, aumenta de forma significativa apenas quando o exercício aeróbio é acompanhado de exercício isométrico de membros superiores com transporte de carga adicional.