57 resultados para customers retention


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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

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The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

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The scope of this paper is to adapt the standard mean-variance model of Henry Markowitz theory, creating a simulation tool to find the optimal configuration of the portfolio aggregator, calculate its profitability and risk. Currently, there is a deep discussion going on among the power system society about the structure and architecture of the future electric system. In this environment, policy makers and electric utilities find new approaches to access the electricity market; this configures new challenging positions in order to find innovative strategies and methodologies. Decentralized power generation is gaining relevance in liberalized markets, and small and medium size electricity consumers are also become producers (“prosumers”). In this scenario an electric aggregator is an entity that joins a group of electric clients, customers, producers, “prosumers” together as a single purchasing unit to negotiate the purchase and sale of electricity. The aggregator conducts research on electricity prices, contract terms and conditions in order to promote better energy prices for their clients and allows small and medium customers to benefit improved market prices.

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Mestrado em Controlo de Gestão e dos Negócios

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Mestrado em Controlo e Gestão dos Negócios

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Mestrado em Gestão e Empreendedorismo

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Mestrado em Contabilidade e Gestão de Instituições Financeiras

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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.

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Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.

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Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.

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Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

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The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

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Nickel-copper metallic foams were electrodeposited from an acidic electrolyte, using hydrogen bubble evolution as a dynamic template. Their morphology and chemical composition was studied by scanning electron microscopy and related to the deposition parameters (applied current density and deposition time). For high currents densities (above 1 A cm(-2)) the nickel-copper deposits have a three-dimensional foam-like morphology with randomly distributed nearly-circular pores whose walls present an open dendritic structure. The nickel-copper foams are crystalline and composed of pure nickel and a copper-rich phase containing nickel in solid solution. The electrochemical behaviour of the material was studied by cyclic voltammetry and chronopotentiometry (charge-discharge curves) aiming at its application as a positive electrode for supercapacitors. Cyclic voltammograms showed that the Ni-Cu foams have a pseudocapacitive behaviour. The specific capacitance was calculated from charge-discharge data and the best value (105 F g(-1) at 1 mA cm(-2)) was obtained for nickel-copper foams deposited at 1.8 A cm(-2) for 180 s. Cycling stability of these foams was also assessed and they present a 90 % capacitance retention after 10,000 cycles at 10 mA cm(-2).

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A strain of Pleurotus ostreatus was grown in tomato pomace as sole carbon source for production of laccase. The culture of P. ostreatus revealed a peak of laccase activity (147 U/L of fermentation broth) on the 4th day of culture with a specific activity of 2.8 U/mg protein. Differential chromatographic behaviour of laccase was investigated on affinity chromatographic matrices containing either urea, acetamide, ethanolamine or IDA as affinity ligands. Laccase exhibited retention on such affinity matrices and it was purified on a Sepharose 6B-BDGE-urea column with final enzyme recoveries of about 60%, specific activity of 6.0 and 18.0 U/mg protein and purification factors in the range of 14-46. It was also possible to demonstrate that metal-free laccase did not adsorb to Sepharose 6B-BDGE-urea column which suggests that adsorption of native laccase on this affinity matrix was apparently due to the specific interaction of carbonyl groups available on the matrix with the active site Cu (II) ions of laccase. The kinetic parameters (V (max), K (m) , K (cat), and K (cat)/K (m) ) of the purified enzyme for several substrates were determined as well as laccase stability and optimum pH and temperature of enzyme activity. This is the first report describing the production of laccase from P. ostreatus grown on tomato pomace and purification of this enzyme based on affinity matrix containing urea as affinity ligand.

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As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.