61 resultados para Deterministic walk
em Instituto Polit
Resumo:
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.
Resumo:
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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Objectivo: Pretendeu-se avaliar as modificações no comportamento neuro-motor a nível da funcionalidade do membro superior predominantemente afectado e a sua influência no ciclo da marcha de dois indivíduos com Acidente Vascular Cerebral, face a um programa de intervenção em fisioterapia, segundo uma abordagem baseada no Conceito de Bobath. Foi também objectivo averiguar o impacto qualitativo nos componentes e estados de saúde. Metodologia: A avaliação foi realizada em dois indivíduos com sequelas de Acidente Vascular Cerebral, antes e após o plano de intervenção segundo o Conceito de Bobath, através do registo observacional, da Classificação Internacional de Funcionalidade, Incapacidade e Saúde, da Performance-Oriented Mobility Assessment POMA I, da Time Up and Go Test, da Motor Assessement Scale e da Motor Evaluation Scale for Upper Extremity in Patients. Resultados: Obteve-se um incremento da funcionalidade do membro superior predominantemente afectado, com uma atribuição na Classificação Internacional de Funcionalidade, Incapacidade e Saúde de qualificadores correspondentes a dificuldade ligeira a moderada ao nível da mobilidade e dos auto cuidado após o plano de intervenção, repercutindo-se assim numa diminuição da restrição na participação e limitação da actividade. Houve um aumento de score total em todos os instrumentos e escalas de medidas de avaliação utilizadas, tendo os indivíduos alcançado uma maior funcionalidade do membro superior e um padrão de marcha mais eficiente, com uma menor necessidade de recorrer a estratégias compensatórias de movimento. Conclusão: O plano de intervenção, baseado numa abordagem segundo o Conceito de Bobath, essencialmente dirigido para a obtenção de ganhos funcionais ao nível do membro superior predominantemente afectado nos indivíduos em estudo, parece ter contribuído para induzir mudanças no comportamento neuro-motor, verificando-se uma influência no ciclo de marcha ao nível da qualidade e eficiência do movimento.
Resumo:
História Clínica: Um paciente com história de diversas lesões nos membros inferiores foi intervencionado em ambos os pés, onde realizou uma tenossinovectomia dos peroneais com reparação de ruptura desses tendões (ao pé direito em 2006 sendo actualmente ao esquerdo). Avaliação Objectiva: Apresentava dor, edema, limitação articular de todos os movimentos da tibio-társica, fraqueza muscular, pés cavos e alterações do padrão de marcha e do equilíbrio. Objectivo: foi verificar se a mobilização com movimento (MWM) do astrágalo e da articulação tibio-peroneal inferior levava a uma diminuição da dor e aumentava a amplitude de dorsiflexão e inversão neste doente com pé cavo. Intervenção: foi realizada MWM do astrágalo e do perónio na articulação tibioperoneal inferior em descarga e em semi-carga, sendo mantida essa nova posição com uma ligadura de tape. Resultados: o paciente aumentou as amplitudes articulares em descarga e em carga, diminuiu o edema da perna e pé, aumentou a funcionalidade, mas em termos de força muscular não foram quantificadas alterações. Conclusão: mesmo o paciente tendo pé cavo e sequelas de uma tenossinovectomia dos peroneais, as manobras de mobilização com movimento do astrágalo e da articulação tíbio-peroneal inferior levaram a uma eliminação da dor e a um aumento da amplitude articular.
Resumo:
Objectivo: A realização deste estudo tem como objectivo identificar a capacidade de modificação dos parâmetros do ciclo da marcha após intervenção a nível dos componentes do membro inferior e uma abordagem na reeducação da marcha no tapete rolante (treadmill). Métodos: Este estudo é um estudo de série de casos, constituído por três indivíduos com sequelas de Acidente Vascular Encefálico (AVE), com comprometimento a nível do membro inferior, capazes de realizar marcha. Os instrumentos de avaliação foram o teste de marcha de 10 metros (10-M), o teste de marcha de 6 minutos (6-Min) e o Time Up and Go (TUG). Os indivíduos receberam intervenção da fisioterapia baseada no conceito de Bobath e na reeducação de marcha no treadmill. Resultados: Após a intervenção verificou-se um aumento da velocidade e cadência da marcha, assim como uma maior tolerância e resistência na capacidade da sua realização. Conclusão: A intervenção realizada a nível dos componentes do membro inferior e na reeducação da marcha utilizando o treadmill permitiu modificar alguns parâmetros espaço-temporais do ciclo da marcha, aumentando a velocidade e cadência da marcha. A utilização conjunta de diferentes abordagens na intervenção ao indivíduo com sequelas de AVE deve ser sempre considerada uma vez que pode trazer benefícios na sua independência e qualidade de vida.
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Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por: Prof. Dr. Pedro Godinho
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The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.
Resumo:
The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.
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The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.
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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.
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In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM – a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids.
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With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.
Resumo:
Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.
Resumo:
The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.