62 resultados para multiobjective programming
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.
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An invex constrained nonsmooth optimization problem is considered, in which the presence of an abstract constraint set is possibly allowed. Necessary and sufficient conditions of optimality are provided and weak and strong duality results established. Following Geoffrion's approach an invex nonsmooth alternative theorem of Gordan type is then derived. Subsequently, some applications on multiobjective programming are then pursued. © 2000 OPA (Overseas Publishers Association) N.V. Published by license under the Gordon and Breach Science Publishers imprint.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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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This article deals with a vector optimization problem with cone constraints in a Banach space setting. By making use of a real-valued Lagrangian and the concept of generalized subconvex-like functions, weakly efficient solutions are characterized through saddle point type conditions. The results, jointly with the notion of generalized Hessian (introduced in [Cominetti, R., Correa, R.: A generalized second-order derivative in nonsmooth optimization. SIAM J. Control Optim. 28, 789–809 (1990)]), are applied to achieve second order necessary and sufficient optimality conditions (without requiring twice differentiability for the objective and constraining functions) for the particular case when the functionals involved are defined on a general Banach space into finite dimensional ones.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector. (C) 2010 Elsevier Ltd. All rights reserved.
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The optimized allocation of protective devices in strategic points of the circuit improves the quality of the energy supply and the system reliability index. This paper presents a nonlinear integer programming (NLIP) model with binary variables, to deal with the problem of protective device allocation in the main feeder and all branches of an overhead distribution circuit, to improve the reliability index and to provide customers with service of high quality and reliability. The constraints considered in the problem take into account technical and economical limitations, such as coordination problems of serial protective devices, available equipment, the importance of the feeder and the circuit topology. The use of genetic algorithms (GAs) is proposed to solve this problem, using a binary representation that does (1) or does not (0) show allocation of protective devices (reclosers, sectionalizers and fuses) in predefined points of the circuit. Results are presented for a real circuit (134 busses), with the possibility of protective device allocation in 29 points. Also the ability of the algorithm in finding good solutions while improving significantly the indicators of reliability is shown. (C) 2003 Elsevier B.V. All rights reserved.
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This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.
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The aim of this work was to present organizational models for optimizing the reduction of crop residue generated by the sugarcane culture. The first model consisted of the selection of varieties of sugarcane to be planted meeting the mill requirements and, at the same time, to minimize the quantity of residue produced. The second model discussed the use of residue to produce energy. This is related to the selection of variety and quantity to be planted, in order to meet the requirements of the mill, to reduce the quantity of residue, and to maximize as much as possible the energy production. The use of linear programming was proposed. The two models presented similar results in this study, and both may be used to define the varieties and areas to be cultivated. (C) 2001 Published by Elsevier B.V. Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)