Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Reusability assessment of thermoset polymeric composite wastes as reinforcement and filler replacement for polymer concrete materials

The development and applications of thermoset polymeric composites, namely fiber reinforced polymers (FRP), have shifted in the last decades more and more into the mass market [1]. Production and consume have increased tremendously mainly for the construction, transportation and automobile sectors [2, 3]. Although the many successful uses of thermoset composite materials, recycling process of byproducts and end of lifecycle products constitutes a more difficult issue. The perceived lack of recyclability of composite materials is now increasingly important and seen as a key barrier to the development or even continued used of these materials in some markets.

New end-use application for GFRP recyclates as reinforcement for concrete-polymer materials’

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both: cross-linked nature of thermoset resins, which cannot be remolded, and complex composition of the composite itself, which includes glass fibres, matrix and different types of inorganic fillers. Presently, most of the GFRP waste is landfilled leading to negative environmental impacts and supplementary added costs. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. There are several methods to recycle GFR thermostable materials: (a) incineration, with partial energy recovery due to the heat generated during organic part combustion; (b) thermal and/or chemical recycling, such as solvolysis, pyrolisis and similar thermal decomposition processes, with glass fibre recovering; and (c) mechanical recycling or size reduction, in which the material is subjected to a milling process in order to obtain a specific grain size that makes the material suitable as reinforcement in new formulations. This last method has important advantages over the previous ones: there is no atmospheric pollution by gas emission, a much simpler equipment is required as compared with ovens necessary for thermal recycling processes, and does not require the use of chemical solvents with subsequent environmental impacts. In this study the effect of incorporation of recycled GFRP waste materials, obtained by means of milling processes, on mechanical behavior of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste materials, with distinct size gradings, were incorporated into polyester polymer mortars as sand aggregates and filler replacements. The effect of GFRP waste treatment with silane coupling agent was also assessed. Design of experiments and data treatment were accomplish by means of factorial design and analysis of variance ANOVA. The use of factorial experiment design, instead of the one-factor-at-a-time method is efficient at allowing the evaluation of the effects and possible interactions of the different material factors involved. Experimental results were promising toward the recyclability of GFRP waste materials as aggregates and filler replacements for polymer mortar, with significant gain of mechanical properties with regard to non-modified polymer mortars.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Experimental Reinforcement of Wood Beams

Rehabilitation is becoming more and more usual in the construction sector in Portugal. The introduction of newer construction materials and technical know-how of integrating different materials for achieving desired engineering goals is an important step to the development of the sector. Wood industry is also getting more and more adapted to composite technologies with the introduction of the so called “highly engineered wood products” and with the use of modification treatments. This work is an attempt to explain the viability of using stainless steel and glass fibre reinforced polymer (GFRP) as reinforcements in wood beams. This thesis specifically focuses on the flexural behaviour of Portuguese Pine unmodified and modified wood beams. Two types of modification were used: 1,3-dimethylol-4,5- dihydroxyethyleneurea (DMDHEU) resin and amid wax. The behaviour of the material was analysed with a nonlinear model. The latter model simulates the behaviour of the reinforced wood beams under flexural loading. Small-scale beams (1:15) were experimented in flexural bending and the experimental results obtained were compared with the analytical model results. The experiments confirm the viability of the reinforcing schemes and the working procedures. Experimental results showed fair agreement with the nonlinear model. A strength increase between 15% and 80% was achieved. Stiffness increased by 40% to 50% in beams reinforced with steel but no significant increase was achieved with the glass fibre reinforcement.

O impacto do uso da tala nocturna na funcionalidade do indivíduo com síndrome do túnel carpiano

A síndrome do túnel carpiano (STC) é considerada a neuropatia compressiva mais comum na população. É causada pela compressão directa sobre o nervo mediano no interior do túnel carpiano, que origina parestesias, dor na mão e disfunção muscular. Como consequência destes sintomas, os indivíduos vêem comprometida a sua funcionalidade ao nível das ocupações e, por consequência, alterado o seu desempenho ocupacional. Este trabalho tem como objectivo principal verificar de que forma a utilização da tala nocturna influencia a funcionalidade do indivíduo com STC. Concomitantemente pretende-se definir em que medida alterações das forças de preensão palmar e de pinças se relaciona com o uso da tala. Por último, identificar quais as variáveis sócio - demográficas e as que caracterizam a patologia que estão relacionadas com o problema em estudo e aos valores obtidos com as escalas do Boston Carpal Tunnel Questionnaire (BQTC), nos indivíduos dos grupos controlo e experimental. A amostra é constituída por 22 indivíduos no grupo controlo e 24 no grupo experimental, com diagnóstico de STC ligeiro e moderado. Foram aplicados o BCTQ, o dinamómetro e o pinch meter de Jamar. Os resultados deste estudo mostram uma diminuição significativa da sintomatologia da STC, após a aplicação da tala, nos momentos de reavaliação e follow up, (p=0,000 e p=0,004), assim como um aumento significativo da funcionalidade nos dois momentos (p=0,000 e p=0,004). Deste estudo conclui-se que a utilização da tala nocturna beneficia os indivíduos com STC ligeiro e moderado.

Relatório de estágio em terapia manual

Objectivo: descrever a intervenção em fisioterapia numa paciente com diagnóstico de epicondilalgia. Participantes e Métodos: estudo de caso de uma paciente que desenvolveu um quadro doloroso no cotovelo esquerdo no início de Janeiro de 2010 e em que a intervenção de fisioterapia teve início no princípio de Fevereiro de 2010. Foi utilizada uma variedade de técnicas articulares, nomeadamente a mobilização com movimento de Mulligan, aplicação de tape e manipulação cervical. O tratamento foi realizado em dias alternados e teve a duração total de duas semanas. Resultados: logo no final da primeira sessão a paciente referiu melhoria na dor à preensão. Na segunda sessão a paciente demonstrou capacidade de realizar auto-mobilização com movimento em casa. A regressão dos sintomas foi muito rápida durante as duas primeiras sessões, passou por uma fase de estabilização da terceira à quinta sessão, até à completa remissão no fim da sexta sessão. Conclusão: o processo de raciocínio clínico desenvolvido pelo fisioterapeuta durante as seis sessões de tratamento foi salientado. Após a recolha dos dados relativos à história e sua interpretação levantaram-se as primeiras hipóteses: epicondilalgia, disfunção cervical ou sindroma do túnel radial. No exame objectivo foram realizados testes para permitir a obtenção do diagnóstico diferencial – epicondilalgia; elaborou-se então um plano de intervenção em colaboração a paciente, que se mostrou eficaz, com resultados acima das expectativas.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Multiagent system for adaptive strategy formulation in electricity markets

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

O impacto do uso da tala nocturna na qualidade de vida do indivíduo com Síndrome do Túnel Carpiano

A Síndrome do Túnel Carpiano é uma neuropatia compressiva do nervo mediano que desencadeia défices motores e sensoriais que interferem com o desempenho dos papéis ocupacionais e, concomitantemente, com a Qualidade de Vida. Este trabalho tem como objectivo principal definir quais os benefícios do uso da tala nocturna e o impacto manifesto na Qualidade de Vida do indivíduo com esta patologia. Os resultados revelaram uma melhoria na percepção do estado de Saúde Geral, bem como uma diminuição do nível da dor no grupo ao qual se aplicou a tala, sugerindo que esta intervenção promove uma melhoria da Qualidade de Vida.

Futebol: o caminho de África até à Europa

Similarly to its past, Africa plays a similar role in the football world as it did during History, if we look at the creation of some of the most powerful empires in the world (the Portuguese, French or English, for example) – as an almost unlimited workforce ‘supplier’. Africa is still searching for its own place in the football world map. With a recent history filled with social conflicts, civil wars and racial discrimination, it was possibly in this continent that the sport was first seen as a means towards social evolution and as ‘peacemaker’. Although these problems also exist in African stadiums, supporters all over the continent go to matches to celebrate and socialize; in a reality constantly shrouded in conflicts and oppression, football is like a ‘light at the end of the tunnel’ to those who believe in a continent sustained by healthy political relations between countries, democratic values and a socially fair ‘use’ of a country’s potential – and always for the profit of its own people. But while see the attempt to use football with that objective, others see it as their ticket out of their country, to avoid getting involved in military conflicts and seek better life conditions for themselves and their families (both those who accompany them and those who remain in Africa). Others, still, try to make the most of others’ will to leave a less favourable social reality; Portugal, for its past as a colonizing country, also saw in the African players a way to develop the football phenomenon in its European territory. This article attempts to analyze the influence of Portuguese colonialism in the emigration of African players to Europe, since Portugal presents itself as one of the biggest ‘importers’ of these players.

Métodos de observação durante a execução de obras subterrâneas

Mestrado em Engenharia Geotécnica e Geoambiente