Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

Reactive power compensation by EPSO technique

This paper presents a methodology to address reactive power compensation using Evolutionary Particle Swarm Optimization (EPSO) technique programmed in the MATLAB environment. The main objective is to find the best operation point minimizing power losses with reactive power compensation, subjected to all operational constraints, namely full AC power flow equations, active and reactive power generation constraints. The methodology has been tested with the IEEE 14 bus test system demonstrating the ability and effectiveness of the proposed approach to handle the reactive power compensation problem.

Comparison between deterministic and meta-heuristic methods applied to ancillary services dispatch

This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.

ANN based day-ahead ancillary services forecast for electricity market simulation

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.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

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.

Ancillary services dispatch using linear programming and genetic algorithm approaches

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.

Processing XML with Java – a performance benchmark

Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files

Performance analysis of Java APIS for XML processing

Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files.

Interfaces inovadores para a aprendizagem musical

Mestrado em Engenharia Informática

Auto-regulação na gestão de conflitos em retalho

Mestrado em Engenharia Informática

Reeducação pré e pós-operatória numa lesão múltipla (fractura do prato tibial medial, ruptura do ligamento cruzado anterior e do corno anterior do menisco medial) do joelho - relato de caso

O presente estudo tem por objectivo principal relatar o caso duma atleta de esqui na montanha com 18 anos de idade, com uma lesão do Ligamento Cruzado Anterior (LCA), lesão do menisco medial e fractura do prato tibial medial que foi submetida a tratamento cirúrgico, realizando tratamento de fisioterapia no pré e pós-operatório. O programa de reabilitação tinha como objectivo reduzir o edema e conquistar a amplitude de movimento livre de dor assim como reestabelecer os níveis de controlo neuromuscular prévios à lesão. A atleta passou por cinco reavaliações durante seu o período de reabilitação e como parâmetros utilizaram-se as escalas de funcionalidade de Cinccinatti e Lisholm, a perimetria da coxa, os graus de amplitude de movimento e a sua força muscular pelo método de 1RM. Os resultados foram os esperados para cada fase da sua reabilitação. No pré-operatório a atleta apresentava um déficit na força muscular do membro inferior lesionado, principalmente no quadricípite ( 3+ inicialmente e 4 na reavaliação antes da cirurgia), discrepância na perimetria muscular da coxa (-2,5 centímetros em relação ao membro contralateral medidos a 5 centímetros acima do bordo superior da patela, e -1,5 centímetros após o programa de reabilitação pré-operatória). No pós-operatório, a força muscular do quadricípite era de 3 inicialmente e de 5 no final do programa de reabilitação, a diferença de 2,5 centímetros de perimetria em relação ao membro contralateral inicialmente encontrada no pós-operatório foi reduzida a uma mínima diferença na sua última avaliação. Quanto à funcionalidade, a atleta inicialmente apresentava valores de 120 e 61 nas escalas de Cinccinatti e Lysholm e no final do programa de reabilitação de 320 e 95, respectivamente. Por fim, conclui-se que a atleta no final de quatro meses, apresentou melhorias sensíveis no seu quadro e muito provavelmente retornará às competições de forma integral.

User modeling and recommendation strategies for tourism

Mestrado em Engenharia Informática

Projecto, optimização e gestão de redes MAIS

Mestrado em Engenharia Electrotécnica e de Computadores

Intelligent recommendation system for e-learning platforms

As more and more digital resources are available, finding the appropriate document becomes harder. Thus, a new kind of tools, able to recommend the more appropriated resources according the user needs, becomes even more necessary. The current project implements an intelligent recommendation system for elearning platforms. The recommendations are based on one hand, the performance of the user during the training process and on the other hand, the requests made by the user in the form of search queries. All information necessary for decision-making process of recommendation will be represented in the user model. This model will be updated throughout the target user interaction with the platform.

Estudo do tratamento de águas contaminadas com tricloroetileno, usando ferro zerovalente

A tecnologia de barreiras reactivas é uma alternativa possível de ser implementada para tratamento de águas contaminadas com compostos organoclorados, nomeadamente o tricloroetileno (TCE). O recurso a ferro zerovalente (Fe0) como meio reactivo tem na actualidade inúmeras aplicações, tratando-se de uma reacção de desalogenação por mecanismo de oxidação-redução. Neste trabalho fizeram-se estudos em batch da reacção entre o Fe0 e o TCE de forma a conhecer os parâmetros cinéticos. A natureza e a área da superfície do ferro provaram ser determinantes na velocidade da reacção. Foi possível verificar que para o sistema ferro comercial / TCE a ordem da reacção é inferior a um, e a constante cinética da ordem de 10-2 Lm-2h-1. Para simular uma barreira reactiva, projectaram-se e construíram-se colunas, as quais foram cheias com areia e ferro depois de devidamente misturados, uma vez que se tratou da disposição a que corresponderam melhores eficiências de redução do TCE. Não foi possível estabelecer o mecanismo da reacção, nem conhecer os parâmetros cinéticos, pelas dificuldades experimentais encontradas na análise do TCE e pelo facto de se tratar de uma reacção muito lenta. A cromatografia gasosa com detector de ionização de chama provou ser o método mais apropriado para doseamento do TCE em águas contaminadas, nas condições usadas neste estudo. A elevada volatilização do TCE e a baixa solubilidade em água contribuíram para as dificuldades operacionais encontradas.