36 resultados para Gamification Human-Vehicle HCI Energy-management


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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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Ao longo dos tempos que a economia tem sofrido mudanças a nível global, e é possível verificar que as empresas estão constantemente a adaptar-se a essa mudança. Fruto dessa adaptação, os recursos humanos, que são uma das partes fundamentais de uma empresa pois representam a sua mão-de-obra, têm tido um papel junto da mesma significativamente alterado ao longo do tempo. De facto, não só o papel dos recursos humanos tem sido diferente ao longo do tempo, a própria gestão de recursos humanos evoluiu significativamente, a par da própria evolução das várias estruturas organizacionais. Tudo isto se relaciona com a necessidade de encontrar métodos de diferenciação, de adquirir vantagem competitiva, ou de conseguir obter mais valor num mercado cada vez mais competitivo a todos os níveis. Assim, embora hoje em dia se assuma de um modo geral que os recursos humanos são realmente uma fonte de valor, capazes de fazer com que a sua empresa se diferencie, e capazes de criar vantagem competitiva, a verdade é que para que tal seja possível é necessário uma gestão dos mesmos que o possibilite. A gestão de recursos humanos traduz-se sobretudo nas suas práticas, tais como o recrutamento ou a formação, e para que essas práticas tenham o melhor efeito possível é necessário que as mesmas sejam avaliadas de forma imparcial, ou seja, independente. É neste contexto que surge a Auditoria de Recursos Humanos, que se pode resumir a uma avaliação aos recursos humanos e à sua gestão dos pontos de vista legal, funcional, e estratégico. Com o objectivo de verificar se, no contexto português, as empresas pensam nos seus recursos humanos como um recurso que acrescenta valor se gerido adequadamente, e se apostam neste tipo de auditoria como forma de avaliar o paradigma dos seus recursos humanos, foi elaborado um questionário e enviado a empresas distinguidas com os estatutos PME Líder 2014 e PME Excelência 2014 pelo IAPMEI. As conclusões do estudo indicaram que embora as empresas acreditem que os recursos humanos acrescentam valor, apostando na sua motivação, formação, avaliação de desempenho e satisfação, as mesmas não fazem questão em obter a certificação dos seus sistemas de gestão de recursos humanos e não utilizam a auditoria de recursos humanos como uma ferramenta de gestão.

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A presente dissertação é o resultado de um estudo realizado entre Março de 2015 e Março de 2016 centrado no tema Eficiência Energética nos Edifícios, no âmbito da Dissertação do 2º ano do Mestrado em Engenharia Eletrotécnica – Sistemas Elétricos de Energia no Instituto Superior de Engenharia do Porto (ISEP). Atualmente, os edifícios são responsáveis por cerca de 40% do consumo de energia na maioria dos países da europa. Energia consumida, principalmente, no aquecimento, arrefecimento e na alimentação de aparelhos elétricos. Os hospitais, como grandes edifícios, são grandes consumidores de energia e, na maioria dos países europeus, situam-se entre os edifícios públicos menos eficientes. Neste contexto, representam um tipo de edifícios cuja atividade apresenta um potencial de poupança energético importante. O tipo de atividade aí desenvolvida, aliada às especificidades do sector da saúde, faz deste tipo de edifícios um alvo de análise e otimização energética bastante apetecível. O presente trabalho passa pelo estudo do potencial para a eficiência energética de um hospital situado na zona do Porto. Foi, inicialmente, efetuado um levantamento das necessidades energéticas, de modo a identificar os sectores prioritários de atuação. Este estudo conta com a análise dos consumos obtidos através do processo de monitorização, substituição da iluminação existente por uma mais eficiente, a instalação de painéis solares para reduzir o consumo destinado às águas quentes sanitárias, a substituição de caldeira a diesel por caldeira a biomassa, substituição de um chiller por um mais eficiente, entre outros. Os consumos registados no hospital em estudo serão comparados com um plano nacional (Eficiência Energética e Hídrica no Sistema Nacional de Saúde), para, desta forma, se perceber quais os consumos do hospital em estudo, quando comparados com outros hospitais.

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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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This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

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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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This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

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Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

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Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

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The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

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Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

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Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.