The experimental granuloma: a hypothesis to explain the persistence of the lesion

Granulomatous inflammation is the morphological substrate of a variety of important infectious diseases such as tuberculosis, leprosy, schistosomiasis and others. Nevertheless, although many aspects of this special type of inflammation are known, fundamental questions concerning granuloma formation, persistence, fate and significance for host-parasite relationships still remain to be elucidated. In this brief review, the basic and more relevant literature related to experimental investigations on granuloma physiopathology is presented. Based on recent investigations performed in our laboratory showing that MDF (Macrophage Deactivating Fator) secreted by epithelioid cells and characterized as the calcium-binding protein protein MRP-14 deactivates activated macrophages, a hypothesis to explain the persistence of granulomatous inflammation is put forward

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

MASCEM Restructuring: Ontologies For Scenarios Generation in Power Systems Simulators

The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Geospatial database generation from digital newspapers: use case for risk and disaster domains.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Remuneration Structure Definition for Distributed Generation Units and Demand Response Participants Aggregation

The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

Impact of Distributed Generation in the Transmission System Expansion Planning

In this work, the impact of distributed generation in the transmission expansion planning will be simulated through the performance of an optimization process for three different scenarios: the first without distributed generation, the second with distributed generation equivalent to 1% of the load, and the third with 5% of distributed generation. For modeling the expanding problem the load flow linearized method using genetic algorithms for optimization has been chosen. The test circuit used is a simplification of the south eastern Brazilian electricity system with 46 buses.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Voltage Analysis and Load Curtailment Minimization in Sub-transmission Networks with Distributed Generation

Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

MICROCIRCULATION AND CHAGAS' DISEASE: HYPOTHESIS AND RECENT RESULTS

This review focuses on studies that support the microvascular hypothesis, as well as on immunological and neurogenic mechanisms, and the role of the parasite itself, to explain further the pathology and clinical course of myocardial involvement in chagasic cardiomyopathy. The salient features of coronary microcirculation and Chagas' disease are discussed.

Melhoria da eficiência energética nos ascensores: a recuperação de energia

A presente tese descreve diferentes soluções que permitem a reutilização da energia recuperada em ascensores eléctricos de roda de aderência dotados de conversores electrónicos de frequência e dessa forma contribuir para a melhoria da eficiência energética nos ascensores. Nos ascensores, a energia potencial é constantemente transferida enquanto a cabina está em movimento. Se a cabina se estiver a movimentar em sentido descendente com plena carga, ou em sentido ascendente, mas vazia, o motor estará em modo gerador. Quando a cabina se movimenta em sentido descendente, e o peso na cabina é superior ao peso do contrapeso, então o binário do motor encontra-se em sentido contrário à velocidade, isto é, o motor está a travar, havendo lugar à recuperação de energia. Igualmente, se a cabina subir vazia, também se poderá recuperar energia eléctrica. A energia acumulada em forma de energia potencial nas pessoas e no contrapeso pode ser recuperada, dado que o motor estará a funcionar como um gerador. De modo a estudar a viabilidade técnica e económica das diferentes soluções foram realizadas medições a uma amostra representativa de ascensores eléctricos de roda de aderência. Esta amostra é constituída por 39 ascensores que estão instalados em diferentes tipos de edifícios e que pertencem a diferentes categorias de utilização, de acordo com a norma VDI 4707:2009. Para cada ascensor foi medida a energia consumida e a energia gerada para uma manobra completa – a descida e a subida da cabina sem carga. A partir das medições, e com base na norma VDI 4707:2009 foram calculados os valores anualizados de energia eléctrica consumidos e produzidos por cada ascensor. A partir das 5 hipóteses identificadas para a utilização da energia recuperada (carregamento de bateria para alimentação dos circuitos em stand-by; carregamento de supercondensador para alimentação dos circuitos em stand-by; carregamento de supercondensador para alimentar o barramento DC; reinjecção da energia no barramento DC de um conjunto de ascensores em grupo; reinjecção da energia na rede eléctrica do edifício onde o ascensor está instalado) foi realizada a avaliação técnica e a avaliação económico-financeira para cada um dos ascensores. Por último, foi desenvolvido um simulador que permite definir a solução de recuperação de energia que seja técnica e economicamente mais viável, para um dado ascensor eléctrico de roda de aderência instalado, mediante a introdução dos parâmetros técnicos do ascensor em avaliação.