Planejamento de médio e longo prazo de sistemas de distribuição de energia elétrica com geradores distribuídos (GDs) considerando custos de confiabilidade, operação e expansão

Pós-graduação em Engenharia Elétrica - FEIS

Maximizing the utility of bio-based diisocyanate and chain extenders in crystalline segmented thermoplastic polyester urethanes: effect of polymerization protocol

High molecular weight semi crystalline thermoplastic poly(ester urethanes), TPEUs, were prepared from a vegetable oil-based diisocyanate, aliphatic diol chain extenders and poly(ethylene adipate) macro diol using one-shot, pre-polymer and multi-stage polyaddition methods. The optimized polymerization reaction achieved ultra-high molecular weight TPEUs (>2 million as determined by GPC) in a short time, indicating a very high HPMDI diol reactivity. TPEUs with very well controlled hard segment (HS) and soft segment (SS) blocks were prepared and characterized with DSC, TGA, tensile analysis, and WAXD in order to reveal structure property relationships. A confinement effect that imparts elastomeric properties to otherwise thermoplastic TPEUs was revealed. The confinement extent was found to vary predictably with structure indicating that one can custom engineer tougher polyurethane elastomers by "tuning" soft segment crystallinity with suitable HS block structure. Generally, the HPMDI-based TPEUs exhibited thermal stability and mechanical properties comparable to entirely petroleum-based TPEUs. (C) 2014 Elsevier Ltd. All rights reserved.

Automatic dimming multi-lamp fluorescent management system with active input power factor corrector stage

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

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Planejamento de reativos em sistemas elétricos de potência multi-área através de modelos estocásticos

Pós-graduação em Engenharia Elétrica - FEIS

Quantitative characterization of multi-phase materials by digital image processing

An automatic image processing and analysis technique has been developed for quantitative characterization of multi-phase materials. For the development of this technique is used the Khoros system that offers the basic morphological tools and a flexible, visual programming language. These techniques are implemented in a highly user oriented image processing environment that allows the user to adapt each step of the processing to his special requirements.To illustrate the implementation and performance of this technique, images of two different materials are processed for microstructure characterization. The result is presented through the determination of volume fraction of the different phases or precipitates.

Lymphoproliferative response and T lymphocyte subsets in a medium-term multi-organ bioassay for carcinogenesis in Wistar rats

The lymphoproliferative response and T lymphocyte subsets were evaluated at different stages of carcinogenesis in male Wistar, rats sequentially initiated with N-diethylnitrosamine (DEN), N-butyl-N-4(hydroxybutyl)nitrosamine (BBN), N-methyl-N-nitrosourea (MNU), dihydroxy-di-N-propylnitrosamine (DHPN) and N,N'-dimethylhydrazine (DMH) (DMBDD initiation). One group was evaluated at the 4th week and other initiated group at the 30th week. Two initiated groups were also exposed through diet to 7-acetylaminofluorene (2-AAF) or phenobarbital (PB), from the 6th until the 30th week. Two groups received only 2-AAF or PB until the 30th week. Five groups were studied to evaluate the effects of each initiator. The lymphoproliferative response was induced in vitro by concanavalin A and the percentage of T lymphocyte subsets was determined by flow cytometry, All groups submitted to initiation only, initiation plus promotion, or promotion only, developed significantly more preneoplastic: lesions than the untreated control group. The main target organs for tumor development were the liver, colon, urinary bladder, kidneys and Zymbal glands, mainly in the group treated with DMBDD + 2-AAF, There were no alterations of the lymphoproliferative response and of the T lymphocyte subsets percentage in the DMBDD-treated group at the 4th and 30th weeks. At the 30th week, the T lymphocyte subsets percentage was also not affected in the initiated groups after treatments with 2-AAF or PB. The lymphoproliferative response, however, was decreased in the DMBDD + 2-AAF group and in the groups treated only with 2-AAF or PB, the present results indicate that the initiating chemicals used in the DMBDD initiation protocol do not exert any influence on the immune system. The alteration of lymphoproliferative response induced at the advanced stage of carcinogenesis without alteration of T lymphocyte subsets may indicate that the influence of 2-AAF and PB on the immune system is functional and not toxic. (C) 2000 Elsevier B.V. Ireland Ltd. All rights reserved.

Multi-method Study on Aquatic Humic Substances from the Rio Negro - Amazonas State/Brazil: Emphasis on Molecular-Size Classification of their Metal Contents

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

Aggregation-based decomposition for multi-divisional models

The aggregation theory of mathematical programming is used to study decentralization in convex programming models. A two-level organization is considered and a aggregation-disaggregation scheme is applied to such a divisionally organized enterprise. In contrast to the known aggregation techniques, where the decision variables/production planes are aggregated, it is proposed to aggregate resources allocated by the central planning department among the divisions. This approach results in a decomposition procedure, in which the central unit has no optimization problem to solve and should only average local information provided by the divisions.

Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft drink plants

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

Una metodología eficiente para manejo de restricciones en algoritmos evolutivos multi-objetivo

This paper presents a new approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal programming. A two-phase methodology for solving COP using a multi-objective strategy is used. In the first phase, the objective function is completely disregarded and the entire search effort is directed towards finding a single feasible solution. In the second phase, the problem is treated as a bi-objective optimization problem, turning the constraint optimization into a two-objective optimization. The two resulting objectives are the original objective function and the constraint violation degree. In the first phase a methodology based on progressive hardening of soft constraints is proposed in order to find feasible solutions. The performance of the proposed methodology was tested on 11 well-known benchmark functions.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

Flujo de potencia AC descentralizado para sistemas de potencia multi-área usando un método de descomposición basado en relajación Lagrangiana

A decentralized solution method to the AC power flow problem in power systems with interconnected areas is presented. The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of adjacent areas, being only necessary to exchange border information related to the interconnection lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. A 9-bus didactic system, the IEEE Three Area RTS-96 and the IEEE 118 bus test systems are used in order to show the operation and effectiveness of the distributed AC power flow.

Decentralized AC power flow for real-time multi-TSO power system operation

This paper adjusts decentralized OPF optimization to the AC power flow problem in power systems with interconnected areas operated by diferent transmission system operators (TSO). The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. To allow better visualization of the concept of independent operation of each TSO, an artificial neural network have been used for computing border information of the interconnected TSOs. A multi-area Power Flow tool can be seen as a basic building block able to address a large number of problems under a multi-TSO competitive market philosophy. The IEEE RTS-96 power system is used in order to show the operation and effectiveness of the decentralized AC Power Flow. ©2010 IEEE.

Distribution system restoration in a DG environment using a heuristic constructive multi-start algorithm

This paper proposes a heuristic constructive multi-start algorithm (HCMA) to distribution system restoration in real time considering distributed generators installed in the system. The problem is modeled as nonlinear mixed integer and considers the two main goals of the restoration of distribution networks: minimizing the number of consumers without power and the number of switching. The proposed algorithm is implemented in C++ programming language and tested using a large real-life distribution system. The results show that the proposed algorithm is able to provide a set of feasible and good quality solutions in a suitable time for the problem. © 2011 IEEE.