988 resultados para investment costs


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This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

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O trabalho faz uma análise sobre as taxas de juros brasileiras, além das principais características da curva soberana de juros nominais, dando ênfase aos títulos pré-fixados emitidos pelo governo em moeda local, no mercado doméstico e externo, onde notamos a ocorrência de um fenômeno bastante peculiar, que é o diferencial de rendimento e de maturidade existentes entre os dois mercados. Arida, Bacha e Lara-Resende (2004) conjecturam sobre a existência de um risco inerente ao país, chamado por eles de “incerteza jurisdicional”, relacionado às instituições brasileiras, e que estaria por trás das altas taxas de juros e da inexistência de um mercado de crédito doméstico de longo prazo. É feito um diagnóstico mais detalhado sobre as possíveis causas do fenômeno de maior maturidade e menor rendimento dos títulos emitidos no mercado externo em relação aos títulos do mercado interno, notando-se que ambos os fenômenos – dos altos juros brasileiros e da inexistência de um mercado juros de longo prazo – estão diretamente relacionados. As conclusões sobre as possíveis causas para o diferencial de rendimento entre os títulos locais e externos emitidos em Reais dizem respeito tanto aos fatores quantitativos, relacionados aos custos de investimento no Brasil e ao risco de conversibilidade, que contribuem em parte para aumentar as taxas exigidas para os títulos locais, bem como aos fatores qualitativos, como piores instituições no Brasil em relação às instituições externas. A diferença de maturidade entre os títulos também advém de questões institucionais, o que reafirma de certo modo a teoria de “incerteza jurisdicional” para explicar este fenômeno.

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The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained by conventional optimisation based methods; (b) mutation approach inspired in the simulated annealing technique, the proposed method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Excellent performance is reported in the test results section of the paper for a difficult large-scale real-life problem: a substantial reduction in investment costs has been obtained with regard to previous solutions obtained via conventional optimisation methods and simulated annealing algorithms; statistical comparison procedures have been employed in benchmarking different versions of the genetic algorithm and simulated annealing methods.

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A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

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This paper presents a methodology and a mathematical model to solve the expansion planning problem that takes into account the effect of contingencies in the planning stage, and considers the demand as a stochastic variable within a specified range. In this way, it is possible to find a solution that minimizes the investment costs guarantying reliability and minimizing future load shedding. The mathematical model of the expansion planning can be represented by a mixed integer nonlinear programming problem. To solve this problem a specialized Genetic Algorithm combined with Linear Programming was implemented.

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This paper presents the application of a new metaheuristic algorithm to solve the transmission expansion planning problem. A simple heuristic, using a relaxed network model associated with cost perturbation, is applied to generate a set of high quality initial solutions with different topologies. The population is evolved using a multi-move path-relinking with the objective of finding minimum investment cost for the transmission expansion planning problem employing the DC representation. The algorithm is tested on the southern Brazilian system, obtaining the optimal solution for the system with better performance than similar metaheuristics algorithms applied to the same problem. ©2010 IEEE.

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This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS) transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP) problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process. Copyright © 2012 Celso T. Miasaki et al.

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This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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In this study, an attempt is made to assess the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A methodological approach proposed by Dell et al. (2008) is used in preference to the traditional Integrated Assessment Models. The evolution of climate variables and of the macroeconomy of each of the nine countries over the period 1970 to 2006 is analyzed and preliminary evidence of a relationship between the macroeconomy and climate change is examined. The preliminary investigation uses correlation, Granger causality and simple regression methods. The preliminary evidence suggests that there is some relationship but that the direction of causation between the macroeconomy and the climate variables is indeterminate. The main analysis involves the use of a panel data (random effects) model which fits the historical data (1971-2007) very well. Projections of economic growth from 2008 to 2099 are done on the basis of four climate scenarios: the International Panel on Climate Change A2, B2, a hybrid A2B2 (the mid-point of A2 and B2), and a ‘baseline’ or ‘Business as Usual’ scenario, which assumes that the growth rate in the period 2008-2099 is the same as the average growth rate over the period 1971-2007. The best average growth rate is under the B2 scenario, followed by the hybrid A2B2 and A2 scenarios, in that order. Although negative growth rates eventually dominate, they are largely positive for a long time. The projections all display long-run secular decline in growth rates notwithstanding short-run upward trends, including some very sharp ones, moving eventually from declining positive rates to negative ones. The costs associated with the various scenarios are all quite high, rising to as high as a present value (2007 base year) of US$14 billion in 2099 (constant 1990 prices) for the B2 scenario and US$21 billion for the BAU scenario. These costs were calculated on the basis of very conservative estimates of the cost of environmental degradation. Mitigation and adaptation costs are likely to be quite high though a small fraction of projected total investment costs.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS