Photonics Active Filters Based on SiC Multi layer Structures: A Two Stage Active Circuit

Characteristics of tunable wavelength filters based on a-SiC:H multi-layered stacked cells are studied both theoretically and experimentally. Results show that the light-activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal. The sensor is a bias wavelength current-controlled device that make use of changes in the wavelength of the background to control the power delivered to the load, acting a photonic active filter. Its gain depends on the background wavelength that controls the electrical field profile across the device.

User perception and influencing factors of technology in everyday life

An increasing amount of research is being developed in the area where technology and humans meet. The success or failure of technologies and the question whether technology helps humans to fulfill their goals or whether it hinders them is in most cases not a technical one. User Perception and Influencing Factors of Technology in Everyday Life addresses issues of human and technology interaction. The research in this work is interdisciplinary, ranging from more technical subjects such as computer science, engineering, and information systems, to non-technical descriptions of technology and human interaction from the point of view of sociology or philosophy. This book is perfect for academics, researchers, and professionals alike as it presents a set of theories that allow us to understand the interaction of technology and humans and to put it to practical use.

Estratégias de comercialização de energia para negociação bilateral em mercados de energia eléctrica multi-agente

As recentes e crescentes modificações no sector eléctrico, tanto nacional como mundial, tornam actualmente os mercados de electricidade um caso de estudo singular e interessante. De facto, o desenvolvimento de ferramentas de análise que permitem avaliar a evolução dos comportamentos que estes mercados adoptam face à dinâmica das suas constantes transformações é, à partida, uma mais valia para as suas principais entidades. Muitas vezes os negociadores deste sector ficam satisfeitos com o resultado final. Contudo, se investigarmos mais minuciosamente, dinheiro e recursos são desperdiçados e potenciais ganhos permanecem por descobrir. Uma negociação automática, que utilize agentes computacionais autónomos, promete um elevado nível de eficiência e acordos de maior qualidade. Muitos modelos de mercado actuais são simulados através de ferramentas computacionais, algumas das quais baseadas em tecnologia multi-agente. Esta dissertação apresenta um simulador que permite ajudar a resolver vários problemas inerentes à contratação bilateral de energia. O simulador envolve dois agentes do mercado de retalho, um comprador e um vendedor de energia eléctrica, e suporta a negociação bilateral multidimensional. Cada agente tem no seu portefólio um conjunto de opções que modelam o seu comportamento individual. A essas opções dá-se o nome de estratégias de negociação. O simulador é composto por estratégias de concessão e imitativas. As estratégias de concessão ditam a velocidade de cedência que cada agente terá, enquanto que as estratégias imitativas têm em conta o comportamento passado do oponente, antes da formulação de uma nova oferta. A validação experimental do simulador foi efectuada através da realização de uma experiência computacional. O método experimental consistiu na experimentação controlada. A experiência teve como principal objectivo validar as estratégias através da verificação, em computador, de um conjunto de hipóteses formuladas através de diversas observações e conclusões da negociação real. Os resultados confirmaram as hipóteses, permitindo concluir que a estratégia de concessão baseada no volume de energia conduz a um melhor benefício para ambos os negociadores, enquanto que a estratégia de concessão baseada na prioridade dos itens conduz à troca de um maior número de propostas negociais.

Negociação bilateral em mercados de energia eléctrica multi-agente com participação activa dos consumidores

Nos últimos anos, o sector elétrico tem sofrido profundas alterações decorrentes do processo de reestruturação. Como consequência, surgiram diferentes estruturas de mercado, tais como em bolsa, contratos bilaterais e mistos, tendo como objectivo o aumento da competitividade. Nos mercados competitivos, os consumidores de electricidade podem escolher livremente os seus fornecedores de energia, em função de possíveis vantagens económicas e da qualidade do serviço. A comercialização de electricidade pode ser realizada em mercados organizados ou através de contratação bilateral entre comercializadores e consumidores. Actualmente, existem várias ferramentas de simulação baseadas em técnicas multiagente que permitem modelar, parcialmente ou na totalidade, os mercados de electricidade, possibilitando simulações de negociação de preços e volumes através de contratos bilaterais, transacções em bolsas de energia, etc. No entanto, estas ferramentas apresentam algumas limitações devido à complexidade dos sistemas elétricos. Neste contexto, esta dissertação tem como principal objectivo desenvolver um simulador de contratos bilaterais em mercados de energia elétrica, baseado na tecnologia multi-agente. O simulador inclui dois tipos de entidades: retalhistas e consumidores de electricidade com diferentes perfis de carga. Além disso, é composto por várias estratégias de negociação, que têm como objectivo maximizar o benefício dos agentes retalhistas e minimizar o custo dos consumidores finais de electricidade. Uma das estratégias, referente ao consumidor, é direccionada para a eficiência no consumo, sendo baseada na conhecida técnica de Participação Activa dos Consumidores (ou Demand Response). O teste do simulador foi efectuado através da resolução de dois casos práticos, baseados em dados do MIBEL. De forma sucinta, os resultados obtidos com as estratégias permitem concluir que os intervenientes no mercado apresentam um comportamento esperado na gestão de preços e volumes de energia, constatando-se que a ferramenta desenvolvida constitui um auxiliar importante à tomada de decisão inerente à negociação bilateral em mercados de electricidade.

Projecto de uma instalação de AVAC de um edifício de escritórios e multi-usos

Neste trabalho são apresentados o dimensionamento e os resultados comparativos para um edifício de serviços (escritórios), na vertente económica de aquisição, instalação, exploração e manutenção, de um sistema de climatização a água, com um sistema de climatização a volume de refrigerante variável como alternativa. Utilizando um software de simulação dinâmica para determinar as cargas térmicas a que o edifício em estudo estará sujeito, de forma a dimensionar um sistema de climatização que respeite os regulamentos em vigor pelo actual sistema de certificação energética, foram dimensionados os dois sistemas de climatização dentro dos acima indicados, tento sido efectuados vários estudos comparativos, por forma a poderem ser futuramente utilizados como base de definição do sistema a adotar por parte dos projetistas do ramo.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

DITRANS - a multi-agent system for integrated diagnosis of power transformers

This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

MASCEM improvement for agent based coalitions

This paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.

Multi-criteria short-term maintenance outage scheduling in smart distribution systems

Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Multi-agent simulation of continental, regional, and micro electricity markets

Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

A user-centered interface for scheduling problem definition

In this paper we present a user-centered interface for a scheduling system. The purpose of this interface is to provide graphical and interactive ways of defining a scheduling problem. To create such user interface an evaluation-centered user interaction development method was adopted: the star life cycle. The created prototype comprises the Task Module and the Scheduling Problem Module. The first one allows users to define a sequence of operations, i.e., a task. The second one enables a scheduling problem definition, which consists in a set of tasks. Both modules are equipped with a set of real time validations to assure the correct definition of the necessary data input for the scheduling module of the system. The usability evaluation allowed us to measure the ease of interaction and observe the different forms of interaction provided by each participant, namely the reactions to the real time validation mechanism.

Agent-based simulation of electronic marketplaces with decision support

This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.