Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Derivative-free nonlinear optimization filter simplex

The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.

Side information creation for efficient Wyner-Ziv video coding: Classifying and reviewing

Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

Funções penalidade para o tratamento das variáveis discretas do problema de fluxo de potência ótimo reativo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O impacto da reforma da administração pública na satisfação dos funcionários públicos : o caso dos Açores

Dissertação de Mestrado em Ciências Económicas e Empresariais.

Aferição do desempenho operacional de parques eólicos (Referência: D0708-047)

A verificação das Características Garantidas associadas aos equipamentos, em especial dos aerogeradores, incluídos no fornecimento de Parques Eólicos, reveste-se de particular importância devido, principalmente, ao grande volume de investimento em jogo, ao longo período necessário ao retorno do mesmo, à incerteza quanto à manutenção futura das actuais condições de remuneração da energia eléctrica produzida e ainda à falta de dados históricos sobre o período de vida útil esperado para os aerogeradores. Em face do exposto, é usual serem exigidas aos fornecedores, garantias do bom desempenho dos equipamentos, associadas a eventuais penalidades, quer para o período de garantia, quer para o restante período de vida útil, de modo a minimizar o risco associado ao investimento. No fornecimento de Parques Eólicos existem usualmente três tipos de garantias, nomeadamente, garantia de Curva de Potência dos aerogeradores, garantia de Disponibilidade dos equipamentos ou garantia de Produção de Energia. Estas poderão existir isoladamente ou em combinação, dependendo das condições contratuais acordadas entre o Adjudicatário e o Fornecedor. O grau de complexidade e/ou trabalho na implementação das mesmas é variável, não sendo possível afirmar qual delas é a mais conveniente para o Adjudicatário, nem qual a mais exacta em termos de resultados. Estas dúvidas surgem em consequência das dificuldades inerentes à recolha dos próprios dados e também da relativamente ampla margem de rearranjo dos resultados permitido pelas normas existentes, possibilitando a introdução de certo tipo de manipulações nos dados (rejeições e correlações), as quais podem afectar de forma considerável as incertezas dos resultados finais dos ensaios. Este trabalho, consistiu no desenvolvimento, execução, ensaio e implementação de uma ferramenta informática capaz de detectar de uma forma simples e expedita eventuais desvios à capacidade de produção esperada para os aerogeradores, em função do recurso verificado num dado período. Pretende ser uma ferramenta manuseável por qualquer operador de supervisão, com utilização para efeitos de reparações e correcção de defeitos, não constituindo contudo uma alternativa a outros processos abrangidos por normas, no caso de aplicação de penalidades. Para o seu funcionamento, são utilizados os dados mensais recolhidos pela torre meteorológica permanente instalada no parque e os dados de funcionamento dos aerogeradores, recolhidos pelo sistema SCADA. Estes são recolhidos remotamente sob a forma de tabelas e colocados numa directoria própria, na qual serão posteriormente lidos pela ferramenta.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Estratégias e internacionalização na manutenção e produção

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Methodology for in-game certification in serious games

Serious games are starting to attain a higher role as tools for learning in various contexts, but in particular in areas such as education and training. Due to its characteristics, such as rules, behavior simulation and feedback to the player's actions, serious games provide a favorable learning environment where errors can occur without real life penalty and students get instant feedback from challenges. These challenges are in accordance with the intended objectives and will self-adapt and repeat according to the student’s difficulty level. Through motivating and engaging environments, which serve as base for problem solving and simulation of different situations and contexts, serious games have a great potential to aid players developing professional skills. But, how do we certify the acquired knowledge and skills? With this work we intend to propose a methodology to establish a relationship between the game mechanics of serious games and an array of competences for certification, evaluating the applicability of various aspects in the design and development of games such as the user interfaces and the gameplay, obtaining learning outcomes within the game itself. Through the definition of game mechanics combined with the necessary pedagogical elements, the game will ensure the certification. This paper will present a matrix of generic skills, based on the European Framework of Qualifications, and the definition of the game mechanics necessary for certification on tour guide training context. The certification matrix has as reference axes: skills, knowledge and competencies, which describe what the students should learn, understand and be able to do after they complete the learning process. The guides-interpreters welcome and accompany tourists on trips and visits to places of tourist interest and cultural heritage such as museums, palaces and national monuments, where they provide various information. Tour guide certification requirements include skills and specific knowledge about foreign languages and in the areas of History, Ethnology, Politics, Religion, Geography and Art of the territory where it is inserted. These skills are communication, interpersonal relationships, motivation, organization and management. This certification process aims to validate the skills to plan and conduct guided tours on the territory, demonstrate knowledge appropriate to the context and finally match a good group leader. After defining which competences are to be certified, the next step is to delineate the expected learning outcomes, as well as identify the game mechanics associated with it. The game mechanics, as methods invoked by agents for interaction with the game world, in combination with game elements/objects allows multiple paths through which to explore the game environment and its educational process. Mechanics as achievements, appointments, progression, reward schedules or status, describe how game can be designed to affect players in unprecedented ways. In order for the game to be able to certify tour guides, the design of the training game will incorporate a set of theoretical and practical tasks to acquire skills and knowledge of various transversal themes. For this end, patterns of skills and abilities in acquiring different knowledge will be identified.

Uma introdução às coimas aplicáveis nos processos de direito da concorrência da União Europeia

Apresenta-se uma abordagem ao poder sancionatório aplicável nos pro­cedimentos conduzidos pela Comissão Europeia na aplicai;:ao das regras subs­tantivas e adjectivas de Direito da União Europeia em direito da concorrência.

A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

Linearizability and schedulability

Consider the problem of scheduling a set of tasks on a single processor such that deadlines are met. Assume that tasks may share data and that linearizability, the most common correctness condition for data sharing, must be satisfied. We find that linearizability can severely penalize schedulability. We identify, however, two special cases where linearizability causes no or not too large penalty on schedulability.