Percorrer por autor "Azevedo, Filipe"
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- Análise Completa dos Motores Trifásicos Ligados em Triângulo sob Condições de DefeitoPublication . Azevedo, FilipeEste trabalho apresenta uma análise detalhada do comportamento de motores trifásicos com enrolamentos em configuração triângulo (Δ) sob diferentes condições de defeito. São estudados dois cenários específicos: a saída de serviço de um enrolamento do motor e a abertura de uma das linhas de alimentação (perda da fase B). Desenvolvemos o estudo comparando o regime equilibrado normal com os regimes desequilibrados resultantes de cada tipo de defeito. Todas as correntes e tensões são derivadas rigorosamente com demonstrações passo-a-passo, complementadas por diagramas fasoriais explicativos. São incluídos exemplos numéricos e uma análise comparativa dos diferentes regimes de funcionamento, destacando as implicações práticas de cada defeito no desempenho do motor, incluindo efeitos térmicos, mecânicos e a redistribuição das correntes no sistema. Este estudo é essencial para a compreensão dos efeitos dos desequilíbrios em motores trifásicos, possibilitando o correto dimensionamento de sistemas de proteção e diagnóstico de defeitos em instalações industriais.
- Analysis of Electricity Market Prices Using Multidimensional ScalingPublication . Azevedo, Filipe; Machado, J. A. TenreiroThis paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.
- Analysis of Electricity Markets Using Multidimensional ScalingPublication . Azevedo, Filipe; Machado, J. A. TenreiroThis paper studies the impact of the energy upon electricity markets using Multidimensional Scalling (MDS). MDS is a computational and statistical technique that produces a spatial representation of similarity between objects through factors of relatedness. MDS represents in a low dimensional map data points whose similarities are defined in a higher dimensional space. Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.
- A Clustering Neural Network Model Applied to Electricity Price Range ForecastPublication . Azevedo, Filipe; Vale, Zita; Oliveira, P. B. MouraWith electricity markets birth, electricity price volatility becomes one of the major concerns for their participants and in particular, for the producers. Whether or not to hedge, what type of portfolio is ade-quate, and how to manage that portfolio are important considerations for electricity market agents. To achieve that, load and electricity price forecast have a high impor-tance. This paper provides an approach applied to price range forecast. Making use of artificial neural networks (ANN), the methodology presented here has as main con-cern finding the maximum and the minimum System Mar-ginal Price (SMP) for a specific programming period, with a certain confidence level. To train the neural networks, probabilistic information from past years is used. To in-crease accuracy and turning ANN training more efficient, a K-Means clustering method is previously applied. Re-sults from real data are presented and discussed in detail.
- A decision-support system based on particle swarm optimization for multiperiod hedging in electricity marketsPublication . Azevedo, Filipe; Vale, Zita; Oliveira, P. B. MouraThis paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.
- Decision-Support Tool for the Establishment of Contracts in the Electricity MarketPublication . Azevedo, Filipe; Vale, Zita; Vale, António A.The Pool, in many countries, was adopted for the participants of the electricity market to trade the electrical energy in a basis of each half-hour or one hour of the next day. However, like the traditional markets, the agents of electrical market are now exposed to the volatility of market price. In some countries, to face that problem and to turn the market more liquid, the derivatives markets – futures and options - were introduced to negotiate products with electrical energy as underlying active. In this context, there is a need of decisionsupport tools to assist those agents for the use of derivatives markets with the objective of practicing the hedge. In this paper, we present a decision model that supports producers to establish contracts with the objective to maximize the profit expected utility.
- Dimensionamento de Descarregadores de Sobretensões (DSTs) para Redes de Média, Alta e Muito Alta Tensão: Metodologia, Normas e Aplicações.Publication . Azevedo, FilipeEste documento fornece uma metodologia completa para o dimensionamento de Descarregadores de Sobretensões (DSTs) em redes de Média Tensão (MT), Alta Tensão (AT) e Muito Alta Tensão (MAT). Abordam-se as normas aplicáveis (portuguesas, europeias, internacionais e E-Redes), critérios técnicos, seleção de fabricantes e um estudo de caso prático. O objetivo é capacitar o leitor a dimensionar DSTs com elevado profissionalismo, garantindo a proteção eficaz de redes elétricas contra sobretensões transitórias.
- Dimensionamento de um Relé Buchholz para Transformadores de Potência com Isolamento a ÓleoPublication . Azevedo, FilipeEste artigo apresenta um estudo detalhado sobre o dimensionamento de relés Buchholz para transformadores de potência com isolamento a óleo. São abordados os princípios de funcionamento, os critérios de seleção, a instalação e os procedimentos de testes e manutenção. O objetivo é fornecer uma orientação prática e rigorosa que contribua para a segurança e fiabilidade dos sistemas de proteção.
- Electricity Price Forecasting Methods Applied to Spanish Electricity MarketPublication . Ortiz, M.; Ukar, O.; Azevedo, Filipe; Mugica, A.Forecasting electricity prices is a fundamental task for all type of markets participants including electricity markets. There are factors that bring unce1tainty to price formation, such as demand forecasting, fuel prices, player's strategies, regulatory changes, weather conditions and technical restrictions and generation availability. In addition, the particular characteristics of electricity (supply must be in balance with demand) make this task more complicated. So, it is necessary to develop accurate and robust techniques on a sho1t-term (days) and long-term basis (months). This work presents two methodologies to be applied to long-term electricity prices forecasting (months) in Spanish electricity market for a glven period. A study case with real data is presented and discussed in detail.
- Forecasting Electricity Prices with Historical Statistical Information using Neural Networks and Clustering TechniquesPublication . Azevedo, Filipe; Vale, ZitaFactors such as uncertainty associated to fuel prices, energy demand and generation availability, are on the basis of the agents major concerns in electricity markets. Facing that reality, price forecasting has an increasing impact in agents’ activity. The success on bidding strategies or on price negotiation for bilateral contracts is directly dependent on the accuracy of the price forecast. However, taking decisions based only on a single forecasted value is not a good practice in risk management. The work presented in this paper makes use of artificial neural networks to find the market price for a given period, with a certain confidence level. Historical information was used to train the neural networks and the number of neural networks used is dependent of the number of clusters found on that data. K-Means clustering method is used to find clusters. A study case with real data is presented and discussed in detail.
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