Dinâmica monetária eficiente sob encontros aleatórios: uma classe de métodos numéricos que exploram concavidade

A dificuldade em se caracterizar alocações ou equilíbrios não estacionários é uma das principais explicações para a utilização de conceitos e hipóteses que trivializam a dinâmica da economia. Tal dificuldade é especialmente crítica em Teoria Monetária, em que a dimensionalidade do problema é alta mesmo para modelos muito simples. Neste contexto, o presente trabalho relata a estratégia computacional de implementação do método recursivo proposto por Monteiro e Cavalcanti (2006), o qual permite calcular a sequência ótima (possivelmente não estacionária) de distribuições de moeda em uma extensão do modelo proposto por Kiyotaki e Wright (1989). Três aspectos deste cálculo são enfatizados: (i) a implementação computacional do problema do planejador envolve a escolha de variáveis contínuas e discretas que maximizem uma função não linear e satisfaçam restrições não lineares; (ii) a função objetivo deste problema não é côncava e as restrições não são convexas; e (iii) o conjunto de escolhas admissíveis não é conhecido a priori. O objetivo é documentar as dificuldades envolvidas, as soluções propostas e os métodos e recursos disponíveis para a implementação numérica da caracterização da dinâmica monetária eficiente sob a hipótese de encontros aleatórios.

Um método eficiente para resolução do problema de Despacho Ótimo de Reativos com controle discreto do TAP dos transformadores

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efficient heuristic algorithm used for optimal capacitor placement in distribution systems

An efficient heuristic algorithm is presented in this work in order to solve the optimal capacitor placement problem in radial distribution systems. The proposal uses the solution from the mathematical model after relaxing the integrality of the discrete variables as a strategy to identify the most attractive bus to add capacitors to each step of the heuristic algorithm. The relaxed mathematical model is a nonlinear programming problem and is solved using a specialized interior point method, The algorithm still incorporates an additional strategy of local search that enables the finding of a group of quality solutions after small alterations in the optimization strategy. Proposed solution methodology has been implemented and tested in known electric systems getting a satisfactory outcome compared with metaheuristic methods.The tests carried out in electric systems known in specialized literature reveal the satisfactory outcome of the proposed algorithm compared with metaheuristic methods. (C) 2009 Elsevier Ltd. All rights reserved.

Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

VAr planning using genetic algorithm and linear programming

A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

Planejamento de Fontes Reativas em Sistemas de Energia Elétrica utilizando a técnica de Decomposição de Benders e o algoritmo de Branch-and-Bound

This paper presents the Benders decomposition technique and Branch and Bound algorithm used in the reactive power planning in electric energy systems. The Benders decomposition separates the planning problem into two subproblems: an investment subproblem (master) and the operation subproblem (slave), which are solved alternately. The operation subproblem is solved using a successive linear programming (SLP) algorithm while the investment subproblem, which is an integer linear programming (ILP) problem with discrete variables, is resolved using a Branch and Bound algorithm especially developed to resolve this type of problem.

Multiarea optimal power flow using multiobjective evolutionary algorithm

In this work the multiarea optimal power flow (OPF) problem is decoupled into areas creating a set of regional OPF subproblems. The objective is to solve the optimal dispatch of active and reactive power for a determined area, without interfering in the neighboring areas. The regional OPF subproblems are modeled as a large-scale nonlinear constrained optimization problem, with both continuous and discrete variables. Constraints violated are handled as objective functions of the problem. In this way the original problem is converted to a multiobjective optimization problem, and a specifically-designed multiobjective evolutionary algorithm is proposed for solving the regional OPF subproblems. The proposed approach has been examined and tested on the RTS-96 and IEEE 354-bus test systems. Good quality suboptimal solutions were obtained, proving the effectiveness and robustness of the proposed approach. ©2009 IEEE.

Comportamento ingestivo de novilhos de corte sob diferentes alturas de pastejo do capim Tanzânia1

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Planejamento e despacho ótimo de reativos (VAr) em sistemas de energia elétrica multi-áreas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Matemática financeira contextualizada em sistemas de amortização e impostos de renda

Pós-graduação em Matemática em Rede Nacional - IBILCE

Instrumentação eletrônica para experimentação do modelo Bouncer Ball dissipativo

In our experiments, we studied the classical dynamic of a particle in vertical motion subject to a constant gravitational field and the partial shock with an elastic wall with oscillatory motion located below the particle. The motion of the particle was confined to the vertical direction by a glass guide tube, which was initially evacuated, allowing viscous drag forces to be disregarded. The time between impacts, as well as the time between the reference phase of the movement of the base and the moment of impact and the period of oscillation of the base will be acquired by a hardware and software to obtain the phases space to be compared later with the description of the system through mapping discrete variables via the 'particle velocity immediately after shock 'and' phase of the movement of the base at the instant of shock 'obtained by computer simulation. This requires developing an electronic analog system followed by Digital implemented in reconfigurable logic, more specifically a sequential machine able to discriminate the impact with the metal base from the impacts of the glass guide tube, based on the frequency spectrum of the response of the microphone to these different impacts

Mixed-integer convex model for VAr expansion planning

This paper presents a mixed-integer convex-optimization-based approach for optimum investment reactive power sources in transmission systems. Unlike some convex-optimization techniques for the reactive power planning solution, in the proposed approach the taps settings of under-load tap-changing of transformers are modeled as a mixed-integer linear set equations. Are also considered the continuous and discrete variables for the existing and new capacitive and reactive power sources. The problem is solved for three significant demand scenarios (low demand, average demand and peak demand). Numerical results are presented for the CIGRE-32 electric power system.

Resolução do problema de fluxo de potência ótimo pela meta-heurística algoritmo dos fogos de artifício de busca dinâmica com mutação de covariância

Pós-graduação em Engenharia Elétrica - FEIS

Funções penalidade para o tratamento das variáveis discretas do problema de fluxo de potência ótimo reativo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Crystalline Confinement

We show that exotic phases arise in generalized lattice gauge theories known as quantum link models in which classical gauge fields are replaced by quantum operators. While these quantum models with discrete variables have a finite-dimensional Hilbert space per link, the continuous gauge symmetry is still exact. An efficient cluster algorithm is used to study these exotic phases. The (2+1)-d system is confining at zero temperature with a spontaneously broken translation symmetry. A crystalline phase exhibits confinement via multi stranded strings between chargeanti-charge pairs. A phase transition between two distinct confined phases is weakly first order and has an emergent spontaneously broken approximate SO(2) global symmetry. The low-energy physics is described by a (2 + 1)-d RP(1) effective field theory, perturbed by a dangerously irrelevant SO(2) breaking operator, which prevents the interpretation of the emergent pseudo-Goldstone boson as a dual photon. This model is an ideal candidate to be implemented in quantum simulators to study phenomena that are not accessible using Monte Carlo simulations such as the real-time evolution of the confining string and the real-time dynamics of the pseudo-Goldstone boson.