11 resultados para ALCÁNTARA BRUNO, PEDRO
em Instituto Politécnico do Porto, Portugal
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Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Prof. Doutor José Freitas Santos
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Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.
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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.
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Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.
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Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.
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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.
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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.
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Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.
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Mestrado em Engenharia Electrotécnica e de Computadores - Área de Especialização de Telecomunicações
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Os crescentes custos ligados ao consumo elétrico, não apenas de cariz financeiro mas também ambiental, despertam cada vez mais para a importância da definição de estratégias de melhor utilização de recursos e eficiência energética. Esta importância tem sido reforçada pela definição de decretos-lei que vêm colocar metas e limites relativamente às despesas energéticas. Estes diplomas são também acompanhados por programas de incentivo para um setor ligado à eficiência energética. Em Portugal as medidas ligadas ao setor tem vindo a ser redirecionadas para o consumo final de energia, com a definição de metas para as instalações de maior consumo. As instalações hospitalares são grandes centros de consumo energético devido não só ao elevado número de utentes que recebem mas também pelos diversos tipos de equipamentos elétricos usados para a prestação dos serviços médicos. Como consequência disso, os investimentos e os custos operacionais são elevados, o que reforça a necessidade de gerir os gastos e consumos energéticos com a procura constante de melhoria na recolha de informação sobre todo o sistema e na adequação de intervenções com vista a uma maior eficiência energética. O Hospital Pedro Hispano vem desde algum tempo a investir no sentido de conhecer mais e melhor toda a instalação bem como os consumos energéticos a ela associados. Algumas medidas foram tomadas nesse sentido nomeadamente a instalação de analisadores de energia, de modo a obter um retrato mais fiel e fidedigno dos principais vetores de consumo. Neste momento a gestão técnica do hospital tem em análise uma grande parte da instalação recolhendo dados do consumo elétrico real do hospital. Nesta dissertação procurou-se fazer uma análise e enquadramento dos programas e metas ligados ao setor energético com ênfase nos diplomas que visão e abrangem as instalações hospitalares. Dos vários programas de incentivo à adoção de políticas de maior eficiência energética é dado especial destaque ao programa ECO.AP que visa a celebração de contratos para implementação de medidas de poupança energética ao setor público. Em colaboração com o HPH, iniciaram-se os trabalhos pelo estudo e identificação das principais fases e ferramentas utilizadas na gestão energética do edifício tendo como objetivo a reavaliação dos vetores energéticos já identificados no HPH e a criação e contabilização de novos grupos de consumo. Através de várias medições do consumo elétrico, num total superior a 650 horas de funcionamento, foi possível a criação do mapa de desagregação de consumos para o ano de 2013. A desagregação realizada conta com 3 novos vetores energéticos e com a reavaliação do peso relativo de mais 5 grupos de consumo. Das medições efetuadas destaca-se a reavaliação do consumo da central de bombagem onde a parcela considerada até à data estava 3 vezes acima do valor real medido. Com base na desagregação feita foram apontadas e estudadas medidas de implementação com o objetivo de reduzir os consumos energético em todo o hospital, destacando-se a solução apresentada para a central de bombagem. Esta medida traria um grande impacto em toda a fatura energética, não só pela sua viabilidade, mas também porque atuaria num grande centro de consumo onde até ao momento nenhuma ação do género foi implementada.
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The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.