Influência do tipo de chuteira em variáveis preditoras do risco de entorse lateral do tornozelo

Introdução: No futebol, a entorse lateral do tornozelo (ELT) destaca-se como sendo a lesão mais prevalente. Potenciada pela variedade de chuteiras disponíveis no mercado e pela crescente utilização de relvados sintéticos, a interação entre o terreno e o calçado tem assumido elevada relevância como fator de risco para a ELT. A maior incidência de lesões na 2ª parte do jogo traduz a necessidade do estudo dessa interação durante tarefas que envolvam fadiga. Objetivo: Estudar a influência das chuteiras em variáveis preditoras do risco de ELT em relvado sintético sob duas condições: sem e com fadiga dos músculos eversores do tornozelo Métodos: Foi utilizada uma amostra de atletas saudáveis. Todos os indivíduos realizaram 3 séries de 5 saltos médio-laterais uni-podálicos, cada uma com 1 de 3 modelos de chuteiras (Turf, Hard e Firm ground) em duas condições: sem e com fadiga induzida pelo dinamómetro isocinético. Durante a tarefa, a atividade eletromiográfica do longo e curto peroniais, o valor das forças de reação do solo e o movimento do retro-pé (plano frontal), foram recolhidos e usados para calcular variáveis cinemáticas (eversão/inversão do tornozelo, o deslocamento e velocidade do centro de pressão), cinéticas (taxa de crescimento das forças de reação do solo) e neuromusculares (tempo de ativação muscular dos peroniais). Resultados: À exceção do tempo de ativação do curto peronial com o modelo Hard ground (sem fadiga vs com fadiga (p=0,050), não foram identificadas diferenças estatisticamente significativas nas variáveis preditoras de lesão, entre chuteiras, nem entre as duas condições avaliadas. Conclusão: Para o teste funcional escolhido e executado por atletas saudáveis em sintético de 3ª geração, nenhuma das chuteiras apresenta maior risco de lesão (com e sem fadiga), tendo em conta as variáveis em estudo.

Valorização energética do biogás de um aterro de resíduos sólidos urbanos

Actualmente, a sociedade depara-se com um enorme desafio: a gestão dos resíduos sólidos urbanos. A sua produção tem vindo a aumentar devido à intensificação das actividades humanas nas últimas décadas. A criação de um sistema de gestão dos resíduos é fundamental para definir prioridades nas acções e metas para que haja uma prevenção na produção de resíduos. Os resíduos sólidos urbanos quando dispostos de forma inadequada podem provocar graves impactos ambientais, tendo sido neste trabalho demonstrado que através de uma gestão eficiente destes é possível aproveitar o potencial energético do biogás e consequentemente diminuir o consumo de combustíveis fósseis reduzindo o impacto ambiental. Os aterros sanitários devem funcionar como a ultima etapa do sistema de tratamento dos resíduos sólidos urbanos e são uma alternativa a ter em conta se forem tomadas todas as medidas necessárias. Estima-se que os aterros sejam responsáveis pela produção de 6-20% do metano existente e que contribuam com 3-4% da produção anual de gases efeito de estufa provenientes de actividades antropogénicas1. É, portanto, fundamental proceder a uma impermeabilização do solo e à criação de condições para recolha do biogás produzido durante a decomposição dos resíduos. Foi estimada a produção de biogás, de acordo com o modelo “LandGEM”, no entanto comparando esta produção com a produção medida pelo explorador, constatou-se uma diferença significativa que pode ser justificada pelo: modo de funcionamento do aterro (longos períodos de paragem); desvio dos resíduos rapidamente biodegradáveis para valorização; a existência de uma percentagem superior ao normal de oxigénio no biogás; a utilização de escórias e cinzas, e a correspondente redução da humidade devido ao compactamento exercido sobre os resíduos durante a sua deposição. Visto tratar-se de um estudo de viabilidade económica da valorização do biogás, foram propostos três cenários para a valorização do biogás. O 1º cenário contempla a instalação de um sistema gerador de energia para comercialização junto da Rede Eléctrica Nacional. O 2º Cenário contempla a instalação de um sistema alternativo de alimentação à caldeira da central de valorização energética de forma a substituir o combustível utilizado actualmente. E o 3º Cenário vem de encontro com os resultados observados actualmente onde se verifica uma reduzida produção/recolha de biogás no aterro. Assim é proposto um sistema gerador de energia que garanta o auto-consumo da exploração do aterro (26 MWh/ano). Qualquer um dos cenários apresenta uma VAL negativa o que leva a concluir que não são viáveis. No entanto, através da análise de sensibilidade, verificamos que estes são claramente afectados por factores como o benefício e o investimento anual, concluindo-se que com alterações nos factores de cálculo, como por exemplo, um aumento no consumo de combustível auxiliar da caldeira (2º cenário), ou com um aumento da factura eléctrica (3º cenário), ou com o aumento do tempo de retorno do investimento inicial(1º cenário), os projectos podem-se tornar viáveis. Por fim importa referir que independentemente da valorização é fundamental continuar a eliminar a máxima quantidade de metano produzida para tentar diminuir o impacto que este tem sobre o ambiente.

A preliminary idea for an 8-competitive, log2 DMAX + log2 log2 1/U asymptotic-space, interface generation algorithm for two-level hierarchical scheduling of constrained-deadline sporadic tasks on a uniprocessor

Consider a single processor and a software system. The software system comprises components and interfaces where each component has an associated interface and each component comprises a set of constrained-deadline sporadic tasks. A scheduling algorithm (called global scheduler) determines at each instant which component is active. The active component uses another scheduling algorithm (called local scheduler) to determine which task is selected for execution on the processor. The interface of a component makes certain information about a component visible to other components; the interfaces of all components are used for schedulability analysis. We address the problem of generating an interface for a component based on the tasks inside the component. We desire to (i) incur only a small loss in schedulability analysis due to the interface and (ii) ensure that the amount of space (counted in bits) of the interface is small; this is because such an interface hides as much details of the component as possible. We present an algorithm for generating such an interface.

JamLab: augmenting sensornet testbeds with realistic and controlled interference generation

Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

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.

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.