Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

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.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

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 simu-lator 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 pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

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.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive 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 an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Three essays on the psychology of investment and financial markets

Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

Strategian toimeenpanokeinot muuttuvissa toimintaympäristöissä

Nykyinen strategia ajattelu perustuu filosofiaan, jossa yrityksen aineeton pääoma muuttuu aineelliseksi tulokseksi organisaatioiden resursseja, kyvykkyyksiä ja osaamista hyödyntämällä. Strategisissa tuloskorteissa oppimisen ja kasvun näkökulma kuvaa, miten ihmiset, teknologia ja organisaatioilmapiiri voivat toimia yhdessä strategian toimeenpanemiseksi. Oppimisen ja kasvun tulosten paraneminen ennakoi parannusta myös sisäisiin prosesseihin, asiakasnäkökulmaan ja taloudelliseen menestykseen. Työn teoriaosuudessa luotiin laaja katsaus eri strategiakoulukuntiin, keskittyen etenkin Mintzbergin konfiguraatio strategiakoulukunnan oppeihin. Tämän pohjalta tehtiin määritys strategia ajattelulle; strategiaprosessille ja strategialle muuttuvissa toimintaympäristöissä. Strategiaprosessin kriittiset alueet, sekä strategialähtöisen organisaation periaatteet huomioon ottaen, tehtiin kirjallisuuskartoitusta strategian toimeenpanokeinoista ja käytännön tutkimus niiden käytön yleisyydestä eri organisaatioissa. Tulosten mukaisesti monet keinot ovat aktiivisessa käytössä, mutta toisaalta on nähtävissä, että erilaiset yrityskulttuurit, organisaatioiden "elämäntilanteet" ja resurssien erilaisuudet tarjoavat erilaiset mahdollisuudet strategian toimeenpanoon ja organisaation osaamisen lisäämiseen. Nopeasti muuttuva toimintaympäristö korostaa joustavaa strategian ja sen toimeenpanon tarvetta. Osaamisen kehittäminen johtaa kasvuun; sen varmistamiseksi on löydettävä omalle organisaatioille sopivat keinot jatkuvaan oppimiseen, muutoskykyisyyden ja sitä kautta kilpailukyvyn saavuttamiseen ja ylläpitämiseen.

Desenvolvimento de sistema de educação continuada a distância e interconsulta em hepatites virais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A educação física no ensino médio em escolas particulares: as perspectivas de alunos, diretores, coordenadores e professores de educação física

Although physical education is regulated by law and recognized as a mandatory component of basic education class, which includes high school, there are many reports that these classes do not actually happen. Such evidence shows the situation experienced by the author of this study, which brought this research to the attention. Therefore, the objective was to investigate and understand the perspective of students, physical education teachers, principals and coordinators forward their ideas to this reality, about the high school physical education in private schools. The research made use of qualitative approach, guided by an exploratory study. The technique was undertaken to collect the questionnaire with open and closed questions, involving 263 students enrolled in high school of four schools in two cities in the state of Sao Paulo and also the director, coordinator and professor of physical education of each one of these institutions, resulting in 12 education professionals. The categories of analysis were defined as: 1. Regarding physical education in high school, 2. The occurrence of physical rducation in high school, 3. Content and dynamic strategies developed in class 4. Student participation in class. The results show that despite, although some schools have physical education classes, there are still many students who do not take them. This reveals a double challenge to the area, which is: although it is essential that such a curriculum component is included in the grades (respecting the regional law legal system) that is not enough students that actually participate in it. As teachers, coordinators and directors recognize the importance of effective physical education, there are numerous of factors that deserve consideration to better understand this reality. One relates to the content of sportivization, another contrast to the period of occurrence of classes in relation to other curriculum components. Additionally, some others are relat...

SAPO campus: aprendizagem, ensino e pessoas em rede

As escolas portuguesas do ensino não superior estão dotadas com infraestruturas e equipamentos que permitem trazer o mundo para dentro da sala de aula, tornando o processo de ensino e de aprendizagem mais rico e motivador para os alunos. A adoção institucional de uma plataforma que segue os princípios da web social, o SAPO Campus (SC), definida pela abertura, partilha, integração, inovação e personalização, pode ser catalisadora de processos de mudança e inovação. O presente estudo teve como finalidade acompanhar o processo de adoção do SC em cinco escolas, bem como analisar o impacto no processo de ensino e de aprendizagem e a forma como os alunos e professores se relacionam com esta tecnologia. As escolas envolvidas foram divididas em dois grupos: o primeiro grupo, constituído por três escolas onde o acompanhamento teve uma natureza mais interventiva e presente, enquanto que no segundo grupo, composto por duas escolas, foram apenas observadas as dinâmicas que se desenvolveram no processo de adoção e utilização do SC. No presente estudo, que se assume como um estudo longitudinal de multicasos, foram aplicadas técnicas de tratamento de dados como a estatística descritiva, a análise de conteúdo e a Social Network Analysis (SNA), com o objetivo de, através de uma triangulação permanente, proceder a uma análise dos impactos observados pela utilização do SC. Estes impactos podem ser situados em três níveis diferentes: relativos à instituição, aos professores e aos alunos. Ao nível da adoção institucional de uma tecnologia, verificou-se que essa adoção passa uma mensagem a toda a organização e que, no caso do SC, apela à participação coletiva num ambiente aberto onde as hierarquias se dissipam. Verificou-se ainda que deve implicar o envolvimento dos alunos em atividades significativas e a adoção de estratégias dinâmicas, preferencialmente integradas num projeto mobilizador. A adoção do SC foi ainda catalisadora de dinâmicas que provocaram mudanças nos padrões de consumo e de produção de conteúdos bem como de uma atitude diferente perante o papel da web social no processo de ensino e aprendizagem. As conclusões apontam ainda no sentido da identificação de um conjunto de fatores, observados no estudo, que tiveram impacto no processo de adoção como o papel das lideranças, a importância da formação de professores, a cultura das escolas, a integração num projeto pedagógico e, a um nível mais primário, as questões do acesso à tecnologia. Algumas comunidades construídas à volta do SAPO Campus, envolvendo professores, alunos e a comunidade, evoluíram no sentido da autossustentação, num percurso de reflexão sobre as práticas pedagógicas e partilha de experiências.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Nash equilibrium strategies in discrete-time finite-horizon dynamic games with risk-and effort-averse players

The objective of this paper is to re-examine the risk-and effort attitude in the context of strategic dynamic interactions stated as a discrete-time finite-horizon Nash game. The analysis is based on the assumption that players are endogenously risk-and effort-averse. Each player is characterized by distinct risk-and effort-aversion types that are unknown to his opponent. The goal of the game is the optimal risk-and effort-sharing between the players. It generally depends on the individual strategies adopted and, implicitly, on the the players' types or characteristics.

Improving basic math skills through integrated dynamic representation strategies

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