965 resultados para government consumption expenditure shocks


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This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

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Energy efficiency plays an important role to the CO2 emissions reduction, combating climate change and improving the competitiveness of the economy. The problem presented here is related to the use of stand-alone diesel gen-sets and its high specific fuel consumptions when operates at low loads. The variable speed gen-set concept is explained as an energy-saving solution to improve this system efficiency. This paper details how an optimum fuel consumption trajectory based on experimentally Diesel engine power map is obtained.

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RESUMO - Assiste-se a um crescimento exponencial das despesas em saúde, quer na Europa como nos Estados Unidos. Em Portugal, os gastos totais com a saúde ascenderam a 10,2% do PIB, em 2006, contra os 8,8% registados no início da década anterior. É importante perceber o que motiva este crescimento quer em termos globais, quer no que diz respeito ao consumo de recursos, bem como até em termos da despesa pública. Este projecto tem dois objectivos fundamentais: em primeiro lugar, contribuir para o estudo dos factores determinantes da procura de cuidados de saúde em Portugal e, consequentemente, determinar as elasticidades procura – preço para diferentes tipos de cuidados de saúde. Metodologia: Estudo observacional baseado na análise empírica de dados administrativos (claims) respeitantes à utilização dos cuidados de saúde por parte de 12.230 indivíduos detentores de um plano de seguro de saúde individual, numa seguradora privada em Portugal. As elasticidades procura – preço para os diferentes tipos de cuidados de saúde obtiveram-se utilizando as variações percentuais das quantidades dos diferentes cuidados de saúde, antes e depois da variação do preço pago pelo indivíduo, para cada tipo de cuidado de saúde. Resultados: De acordo com a teoria económica tradicional o aumento do preço a pagar reduz o consumo de cuidados de saúde, e a procura é elástica, ou seja, os valores da elasticidade procura – preço obtidos são superiores a 1, em valor absoluto, logo o aumento do preço levou a uma redução mais do que proporcional das quantidades procuradas. A procura de cuidados de saúde em ambulatório é mais sensível à variação do preço do que a procura de cuidados de internamento. ------- ABSTRACT - We are witnessing an exponential growth of health care expenditures around the world. In Portugal, the total expenditure on health amounted to 10.2% of GDP in 2006, against 8.8% at the beginning of previous decade. It is important to understand what motivates this growth both in overall terms, with respect to resource consumption, and even in terms of public spending. This study was designed two achieve two objectives: first, to contribute to the study of demand for health care and, more specifically, to analyze the effect of price changes on the utilization of health care services; and secondly, to estimate the demand elasticity for different types of heath care. Methodology: Observational study based on empirical analysis of administrative data (claims) from a private health insurance Company in Portugal. The sample used had information regarding 12.230 individuals. Demand elasticity for the different types of health care services was obtained by the quotient between the percentage changes in the quantity of health care services, before and after the change in the price paid by the corresponding percentage change in the price. Results: This study showed that, for all medical services, price increases were associated with reductions in the quantity of care consumed as predicted by neoclassical demand theory, and we are in the presence of an elastic demand. This means that price elasticity is greater than 1 in absolute value so the increase in the price led to a more than proportional reduction in the quantity demanded. Demand elasticity was more responsive to changes in the price of specialist and emergency care than to changes in the price of inpatient care.

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Critical Issues in Environmental Taxation: International and Comparative Perspectives: Volume VI, 699-715

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Desde o final do século XVIII, quando se iniciou a revolução industrial, o crescimento económico tem sido assente num consumo elevado de combustíveis fósseis que libertam gases com efeito de estufa. A emissão destes gases e a escassez dos combustíveis fósseis são temas que, desde as últimas duas décadas do século XX, ocupam um lugar de destaque nas agendas de política mundial. A produção de energia através de fontes renováveis surge como alternativa e poderá ser a solução para países com escassos recursos de origem fóssil, como é o caso de Portugal, minimizando também a sua dependência energética do exterior. Uma das medidas de incentivo lançada pelo Governo Português em 2007, foi a criação de um regime simplificado aplicável à microprodução descentralizada de eletricidade através de fontes de energia renováveis e de cogeração. À semelhança da maioria dos países europeus, o principal meio de promoção destes sistemas em Portugal foram as Feed-in-Tariffs, que consistem numa tarifa de venda de energia elétrica de origem renovável acima da tarifa de mercado. Estas tarifas permitiram, sobretudo, o crescimento do setor fotovoltaico em Portugal. Atualmente, o amadurecimento da tecnologia fotovoltaica, associado ao constante aumento das tarifas de energia elétrica, permite que se torne vantajosa a instalação de sistemas fotovoltaicos para autoconsumo. Neste contexto, o atual Governo Português, criou recentemente um regime jurídico aplicável à produção de eletricidade para autoconsumo. O objetivo deste trabalho é demonstrar, com base na minha experiência profissional, a metodologia de dimensionamento de uma central fotovoltaica ligada à Rede Elétrica de Serviço Público. Será utilizado como objeto de estudo um projeto constituído por 28 centrais fotovoltaicas de Miniprodução de 100 kW, dispersas por Portugal Continental, para o qual será efetuada a análise financeira do investimento. Pretende-se ainda apresentar o novo enquadramento legislativo para o Autoconsumo e Pequena Produção distribuída, detalhar as suas principais caraterísticas e efetuar um estudo económico para cada um destes regimes.

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Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

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Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

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The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

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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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The current practices in the consumption metering by electricity utilities is currently largely based on monthly consumption reading. The consumption metering device is always calculating the cumulative consumption. Then, it is possible to calculate the difference between the actual and the previous consumption evaluation in order to estimate the monthly consumption. The power systems planning needs in many aspects to handle consumption data obtained for shorter periods, namely in the Demand Response programs planning. The work presented in this paper is based on the application of typical consumption profiles that are previously defined for a certain power system area. Such profiles are then used in order to estimate the 15 minutes consumption for a certain consumer or consumer type.

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The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.

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Demand Response has been taking over the years an extreme importance. There’s a lot of demand response programs, one of them proposed in this paper, using air conditioners that could increase the power quality and decrease the spent money in many ways like: infrastructures and customers energy bill reduction. This paper proposes a method and a study on how air conditioners could integrate demand response programs. The proposed method has been modelled as an energy resources management optimization problem. This paper presents two case studies, the first one with all costumers participating and second one with some of costumers. The results obtained for both case studies have been analyzed.

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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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The recent changes on power systems paradigm requires the active participation of small and medium players in energy management. With an electricity price fluctuation these players must manage the consumption. Lowering costs and ensuring adequate user comfort levels. Demand response can improve the power system management and bring benefits for the small and medium players. The work presented in this paper, which is developed aiming the smart grid context, can also be used in the current power system paradigm. The proposed system is the combination of several fields of research, namely multi-agent systems and artificial neural networks. This system is physically implemented in our laboratories and it is used daily by researchers. The physical implementation gives the system an improvement in the proof of concept, distancing itself from the conventional systems. This paper presents a case study illustrating the simulation of real-time pricing in a laboratory.

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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciência Política e Relações Internacionais, área de especialização em Ciência Política