810 resultados para Job demand-resources model
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Energy resource scheduling is becoming increasingly important, such as the use of more distributed generators and electric vehicles connected to the distribution network. This paper proposes a methodology to be used by Virtual Power Players (VPPs), regarding the energy resource scheduling in smart grids and considering day-ahead, hour-ahead and realtime time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used.
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The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.
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The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.
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Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.
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Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.
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Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.
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Consumer-electronics systems are becoming increasingly complex as the number of integrated applications is growing. Some of these applications have real-time requirements, while other non-real-time applications only require good average performance. For cost-efficient design, contemporary platforms feature an increasing number of cores that share resources, such as memories and interconnects. However, resource sharing causes contention that must be resolved by a resource arbiter, such as Time-Division Multiplexing. A key challenge is to configure this arbiter to satisfy the bandwidth and latency requirements of the real-time applications, while maximizing the slack capacity to improve performance of their non-real-time counterparts. As this configuration problem is NP-hard, a sophisticated automated configuration method is required to avoid negatively impacting design time. The main contributions of this article are: 1) An optimal approach that takes an existing integer linear programming (ILP) model addressing the problem and wraps it in a branch-and-price framework to improve scalability. 2) A faster heuristic algorithm that typically provides near-optimal solutions. 3) An experimental evaluation that quantitatively compares the branch-and-price approach to the previously formulated ILP model and the proposed heuristic. 4) A case study of an HD video and graphics processing system that demonstrates the practical applicability of the approach.
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We consider a symmetric Stackelberg model in which there is asymmetric demand information owned by first and second movers. We analyse the advantages of leadership and flexibility, and prove that when the leading firm faces demand uncertainty, but the follower does not, the first mover does not necessarily have advantage over the second mover. Moreover, we show that the advantage of one firm over the other depends upon the demand fluctuation and also upon the degree of substitutability of the products.
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Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.
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RESUMO - Assistimos hoje a um contexto marcado (i) pelo progressivo envelhecimento das sociedades ocidentais, (ii) pelo aumento da prevalência das doenças crónicas, de que as demências são um exemplo, (iii) pelo significativo aumento dos custos associados a estas patologias, (iv) por orçamentos públicos fortemente pressionadas pelo controlo da despesa, (v) por uma vida moderna que dificulta o apoio intergeracional, tornando o suporte proporcionado pelos filhos particularmente difícil, (vi) por fortes expectativas relativamente à prestação de cuidados de saúde com qualidade. Teremos assim de ser capazes de conseguir melhorar os serviços de saúde, ao mesmo tempo que recorremos a menos recursos financeiros e humanos, pelo que a inovação parece ser crítica para a sustentabilidade do sistema. Contudo a difusão das Assistive Living Technologies, apesar do seu potencial, tem sido bastante baixa, nomeadamente em Portugal. Porquê? Hamer, Plochg e Moreira (2012), no editorial do International Journal of Healthcare Management, enquadram a Inovação como “podendo ser imprevisível e mesmo dolorosa, pelo que talvez possamos não ficar surpreendidos se surgirem resistências e que, inovações bastante necessárias, capazes de melhorar os indicadores de saúde, tenham sido de adoção lenta ou que tenham mesmo sido insustentáveis”. Em Portugal não há bibliografia que procure caracterizar o modelo de difusão da inovação em eHealth ou das tecnologias de vivência assistida. A bibliografia internacional é igualmente escassa. O presente projeto de investigação, de natureza exploratória, tem como objetivo principal, identificar barreiras e oportunidades para a implementação de tecnologias eHealth, aplicadas ao campo das demências. Como objetivos secundários pretendemse identificar as oportunidades e limitações em Portugal: mapa de competências nacionais, e propor medidas que possa acelerar a inovação em ALT, no contexto nacional. O projeto seguirá o modelo de um estudo qualitativo. Para o efeito foram conduzidas entrevistas em profundidade junto de experts em ALT, procurando obter a visão daqueles que participam do lado da Oferta- a Indústria; do lado da Procura- doentes, cuidadores e profissionais de saúde; bem como dos Reguladores. O instrumento utilizado para a recolha da informação pretendida foi o questionário não estruturado. A análise e interpretação da informação recolhida foram feitas através da técnica de Análise de Conteúdo. Os resultados da Análise de Conteúdo efetuada permitiram expressar a dicotomia barreira/oportunidade, nas seguintes categorias aqui descritas como contextos (i) Contexto Tecnológico, nas subcategorias de Acesso às Infraestruturas; Custo da Tecnologia; Interoperabilidade, (ii) Contexto do Valor Percecionado, nas subcategorias de Utilidade; Eficiência; Divulgação, (iii) Contexto Político, compreendendo a Liderança; Organização; Regulação; Recursos, (iv) Contexto Sociocultural, incluindo nomeadamente Idade; Literacia; Capacidade Económica, (v) Contexto Individual, incluindo como subcategorias, Capacidade de Adaptação a Novas tecnologias; Motivação; Acesso a equipamentos (vi) Contexto Específico da Doença, nomeadamente o Impacto Cognitivo; Tipologia Heterogénea e a Importância do Cuidador. Foi proposto um modelo exploratório, designado de Modelo de Contextos e Forças, que estudos subsequentes poderão validar. Neste modelo o Contexto Tecnológico é um Força Básica ou Fundamental; o Contexto do Valor Percecionado, constitui-se numa Força Crítica para a adoção de inovação, que assenta na sua capacidade para oferecer valor aos diversos stakeholders da cadeia de cuidados. Temos também o Contexto Político, com capacidade de modelar a adoção da inovação e nomeadamente com capacidade para o acelerar, se dele emitir um sinal de urgência para a mudança. O Contexto Sociocultural e Individual expressam uma Força Intrínseca, dado que elas são características internas, próprias e imutáveis no curto-prazo, das sociedade e das pessoas. Por fim há que considerar o Contexto Específico da Doença, nesta caso o das demências. Das conclusões do estudo parece evidente que as condições tecnológicas estão medianamente satisfeitas em Portugal, com evidentes progressos nos últimos anos (exceção para a interoperabilidade aonde há necessidade de maiores progressos), não constituindo portanto barreira à introdução de ALT. Aonde há necessidade de investir é nas áreas do valor percebido. Da análise feita, esta é uma área que constitui uma barreira à introdução e adoção das ALT em Portugal. A falta de perceção do valor que estas tecnologias trazem, por parte dos profissionais de saúde, doentes, cuidadores e decisores políticos, parece ser o principal entrave à sua adoção. São recomendadas estratégias de modelos colaborativos de Investigação e Desenvolvimento e de abordagens de cocriação com a contribuição de todos os intervenientes na cadeia de cuidados. Há também um papel que cabe ao estado no âmbito das prioridades e da mobilização de recursos, sendo-lhe requerida a expressão do sentido de urgência para que esta mudança aconteça. Foram também identificadas oportunidades em diversas áreas, como na prevenção, no diagnóstico, na compliance medicamentosa, na terapêutica, na monitorização, no apoio à vida diária e na integração social. O que é necessário é que as soluções encontradas constituam respostas àquilo que são as verdadeiras necessidades dos intervenientes e não uma imposição tecnológica que só por si nada resolve. Do estudo resultou também a perceção de que há que (i) continuar a trabalhar no sentido de aproximar a comunidade científica, da clínica e do doente, (ii) fomentar a colaboração entre centros, com vista à criação de escala a nível global. Essa colaboração já parece acontecer a nível empresarial, tendo sido identificadas empresas Portuguesas com vocação global. A qualidade individual das instituições de ensino, dos centros de investigação, das empresas, permite criar as condições para que Portugal possa ser país um piloto e um case-study internacional em ALT, desde que para tal pudéssemos contar com um trabalho colaborativo entre instituições e com decisões políticas arrojadas.
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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.
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The following work project illustrates the strategic issues There App, a mobile application, faces regarding the opportunity to expand from its current state as a product to a multisided platform. Initially, a market analysis is performed to identify the ideal customer groups to be integrated in the platform. Strategic design issues are then discussed on how to best match its value proposition with the identified market opportunity. Suggestions on how the company should organize its resources and operational processes to best deliver on its value proposition complete the work.
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Double degree