Behaviour and fate of metals in urban wastewater treatment plants: a review

The concerns on metals in urban wastewater treatment plants (WWTPs) are mainly related to its contents in discharges to environment, namely in the final effluent and in the sludge produced. In the near future, more restrictive limits will be imposed to final effluents, due to the recent guidelines of the European Water Framework Directive (EUWFD). Concerning the sludge, at least seven metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) have been regulated in different countries, four of which were classified by EUWFD as priority substances and two of which were also classified as hazardous substances. Although WWTPs are not designed to remove metals, the study of metals behaviour in these systems is a crucial issue to develop predictive models that can help more effectively the regulation of pre-treatment requirements and contribute to optimize the systems to get more acceptable metal concentrations in its discharges. Relevant data have been published in the literature in recent decades concerning the occurrence/fate/behaviour of metals in WWTPs. However, the information is dispersed and not standardized in terms of parameters for comparing results. This work provides a critical review on this issue through a careful systematization, in tables and graphs, of the results reported in the literature, which allows its comparison and so its analysis, in order to conclude about the state of the art in this field. A summary of the main consensus, divergences and constraints found, as well as some recommendations, is presented as conclusions, aiming to contribute to a more concerted action of future research. © 2015, Islamic Azad University (IAU).

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

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.

GAIC: Um sistema inteligente e flexível para simulação e apoio à participação de pequenos e médios consumidores na gestão ativa de cargas no âmbito de smart grids

A liberalização dos mercados de energia e a utilização intensiva de produção distribuída tem vindo a provocar uma alteração no paradigma de operação das redes de distribuição de energia elétrica. A continuidade da fiabilidade das redes de distribuição no contexto destes novos paradigmas requer alterações estruturais e funcionais. O conceito de Smart Grid vem permitir a adaptação das redes de distribuição ao novo contexto. Numa Smart Grid os pequenos e médios consumidores são chamados ao plano ativo das participações. Este processo é conseguido através da aplicação de programas de demand response e da existência de players agregadores. O uso de programas de demand response para alcançar benefícios para a rede encontra-se atualmente a ser estudado no meio científico. Porém, existe a necessidade de estudos que procurem benefícios para os pequenos e médios consumidores. O alcance dos benefícios para os pequenos e médios consumidores não é apenas vantajoso para o consumidor, como também o é para a rede elétrica de distribuição. A participação, dos pequenos e médios consumidores, em programas de demand response acontece significativamente através da redução de consumos energéticos. De modo a evitar os impactos negativos que podem provir dessas reduções, o trabalho aqui proposto faz uso de otimizações que recorrem a técnicas de aprendizagem através da utilização redes neuronais artificiais. Para poder efetuar um melhor enquadramento do trabalho com as Smart Grids, será desenvolvido um sistema multiagente capaz de simular os principais players de uma Smart Grid. O foco deste sistema multiagente será o agente responsável pela simulação do pequeno e médio consumidor. Este agente terá não só que replicar um pequeno e médio consumidor, como terá ainda que possibilitar a integração de cargas reais e virtuais. Como meio de interação com o pequeno e médio consumidor, foi desenvolvida no âmbito desta dissertação um sistema móvel. No final do trabalho obteve-se um sistema multiagente capaz de simular uma Smart Grid e a execução de programas de demand response, sSendo o agente representante do pequeno e médio consumidor capaz de tomar ações e reações de modo a poder responder autonomamente aos programas de demand response lançados na rede. O desenvolvimento do sistema permite: o estudo e análise da integração dos pequenos e médios consumidores nas Smart Grids por meio de programas de demand response; a comparação entre múltiplos algoritmos de otimização; e a integração de métodos de aprendizagem. De modo a demonstrar e viabilizar as capacidades de todo o sistema, a dissertação inclui casos de estudo para as várias vertentes que podem ser exploradas com o sistema desenvolvido.

Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Upper Ontology for Multi-Agent Energy Systems’ Applications

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors research group has developed three multi-agent systems: MASCEM, which simulates the electricity markets; ALBidS that works as a decision support system for market players; and MASGriP, which simulates the internal operations of smart grids. To take better advantage of these systems, their integration is mandatory. For this reason, is proposed the development of an upper-ontology which allows an easier cooperation and adequate communication between them. Additionally, the concepts and rules defined by this ontology can be expanded and complemented by the needs of other simulation and real systems in the same areas as the mentioned systems. Each system’s particular ontology must be extended from this top-level ontology.

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

Real-Time Simulation of energy Management in a Domestic Consumer

Recent and future changes in power systems, mainly in the smart grid operation context, are related to a high complexity of power networks operation. This leads to more complex communications and to higher network elements monitoring and control levels, both from network’s and consumers’ standpoint. The present work focuses on a real scenario of the LASIE laboratory, located at the Polytechnic of Porto. Laboratory systems are managed by the SCADA House Intelligent Management (SHIM), already developed by the authors based on a SCADA system. The SHIM capacities have been recently improved by including real-time simulation from Opal RT. This makes possible the integration of Matlab®/Simulink® real-time simulation models. The main goal of the present paper is to compare the advantages of the resulting improved system, while managing the energy consumption of a domestic consumer.

Engineering Temporal and Spatial Aspects in OWL using Patterns

WWW is a huge, open, heterogeneous system, however its contents data is mainly human oriented. The Semantic Web needs to assure that data is readable and “understandable” to intelligent software agents, though the use of explicit and formal semantics. Ontologies constitute a privileged artifact for capturing the semantic of the WWW data. Temporal and spatial dimensions are transversal to the generality of knowledge domains and therefore are fundamental for the reasoning process of software agents. Representing temporal/spatial evolution of concepts and their relations in OWL (W3C standard for ontologies) it is not straightforward. Although proposed several strategies to tackle this problem but there is still no formal and standard approach. This work main goal consists of development of methods/tools to support the engineering of temporal and spatial aspects in intelligent systems through the use of OWL ontologies. An existing method for ontology engineering, Fonte was used as framework for the development of this work. As main contributions of this work Fonte was re-engineered in order to: i) support the spatial dimension; ii) work with OWL Ontologies; iii) and support the application of Ontology Design Patterns. Finally, the capabilities of the proposed approach were demonstrated by engineering time and space in a demo ontology about football.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Previsão de avarias em transformadores de potência através da análise de ensaios físico-químicos

Os Transformadores de potência são máquinas de elevada importância ao nível dos Sistemas Elétricos de Energia (SEE) uma vez que são estas máquinas que possibilitam a interligação dos diferentes níveis de tensão da rede e a transmissão de energia elétrica em Corrente Alternada (CA). Geralmente, estas máquinas são de grandes dimensões e de elevado nível de complexidade construtiva. Caracterizam-se por possuírem períodos de vida útil bastante elevados (vinte a trinta anos) e preços elevados, o que conduz a um nível de exigência de fiabilidade muito elevada, uma vez que não e viável a existência de muitos equipamentos de reserva nos SEE. Com o objetivo de tentar maximizar o período de vida útil dos transformadores de potência e a sua fiabilidade, tenta-se, cada vez mais, implementar conceitos de manutenção preventiva a este tipo de máquinas. No entanto, a gestão da sua vida útil e extremamente complexa na medida em que, estas máquinas têm vários componentes cruciais e suscetiveis de originar falhas e, quase todos eles, encontram-se no interior de uma cuba. Desta forma, não e possível obter uma imagem do seu estado, em tempo real, sem colocar o transformador fora de serviço, algo que acarreta custos elevados. Por este motivo, desenvolveu-se uma técnica que permite obter uma indicação do estado do transformador, em tempo real, sem o retirar de serviço, colhendo amostras do óleo isolante e procedendo a sua análise físico-química e Analise Gases Dissolvidos (DGA). As análises aos óleos isolantes tem vindo a adquirir uma preponderância muito elevada no diagnóstico de falhas e na analise do estado de conservação destes equipamentos tendo-se desenvolvido regras para interpretação dos parâmetros dos óleos com carácter normativo. Considerando o conhecimento relativo a interpretação dos ensaios físico-químicos e DGA ao oleol, e possível desenvolver ferramentas capazes de otimizar essas mesmas interpretações e aplicar esse conhecimento no sentido de prever a sua evolução, assim como o surgimento de possíveis falhas em transformadores, para assim otimizar os processos de manutenção. Neste campo as Redes Neuronais Artificiais (RNAs) têm um papel fundamental

Fractional Calculus: Application in modeling and control

This contribution introduces the fractional calculus (FC) fundamental mathematical aspects and discuses some of their consequences. Based on the FC concepts, the chapter reviews the main approaches for implementing fractional operators and discusses the adoption of FC in control systems. Finally are presented some applications in the areas of modeling and control, namely fractional PID, heat diffusion systems, electromagnetism, fractional electrical impedances, evolutionary algorithms, robotics, and nonlinear system control.

Dynamical Analysis of Non-Repetitive Trajectories in Robotic Manipulation

A new method for the study and optimization of manu«ipulator trajectories is developed. The novel feature resides on the modeling formulation. Standard system desciptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyze. Moreover, the derived algorithms are suited to "deterministic" tasks, such as those appearing in a repetitivework, and are not well adapted to a "random" operation that occurs in intelligent systems interacting with a non-structured and changing environment. These facts motivate the development of alternative models based on distinct concepts. The proposed embedding of statistics and Fourier trasnform gives a new perspective towards the calculation and optimization of the robot trajectories in manipulating tasks.