Fault section estimation in electric power systems using an optimization immune algorithm

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

Modelo de programação matemática para controle do crescimento da vegetação sob redes de distribuição de energia elétrica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fault section estimation in automated distribution substations

In this paper, a methodology based on Unconstrained Binary Programming (UBP) model and Genetic Algorithms (GAs) is proposed for estimating fault sections in automated distribution substations. The UBP model, established by using the parsimonious set covering theory, looks for the match between the relays' protective alarms informed by the SCADA system and their expected states. The GA is developed to minimize the UBP model and estimate the fault sections in a swift and reliable manner. The proposed methodology is tested by utilizing a real-life automated distribution substation. Control parameters of the GA are tuned to achieve maximum computational efficiency and reduction of processing time. Results show the potential and efficiency of the methodology for estimating fault section in real-time at Distribution Control Centers. ©2009 IEEE.

Alocação otimizada de dispositivos de proteção em sistema de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Metodologia para análise e interpretação de alarmes em tempo real de sistemas de distribuição de energia elétrica

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

Localização de faltas em alimentadores de distribuição de energia elétrica usando medições esparsas de tensões

Pós-graduação em Engenharia Elétrica - FEIS

Índices de confiabilidade devido a vegetação e planejamento de podas de árvores em redes de distribuição

Pós-graduação em Engenharia Elétrica - FEIS

Multistage Transmission Expansion Planning Considering Fixed Series Compensation Allocation

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

Fast fault section estimation in distribution control centers using adaptive genetic algorithm

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

Binary integer programming formulations for scheduling in market-driven foundries

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.

Allocation of protective devices in distribution circuits using nonlinear programming models and genetic algorithms

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.

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.

Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

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

Rheological, mechanical and mucoadhesive properties of thermoresponsive, bioadhesive binary mixtures composed of poloxamer 407 and carbopol 974P designed as platforms for implantable drug delivery systems for use in the oral cavity

This study described the formulation and characterisation of the viscoelastic, mechanical and mucoadhesive properties of thermoresponsive, binary polymeric systems composed of poloxamer (P407) and poly(acrylic acid, C974P) that were designed for use as a drug delivery platform within the oral cavity. Monopolymeric and binary polymeric formulations were prepared containing 10, 15 and 20% (w/w) poloxamer (407) and 0.10-0.25% (w/w) poly(acrylic acid, 934P). The flow theological and viscoelastic properties of the formulations were determined using controlled stress and oscillatory rheometry, respectively, the latter as a function of temperature. The mechanical and mucoadhesive properties (namely the force required to break the bond between the formulation and a pre-hydrated mucin disc) were determined using compression and tensile analysis, respectively. Binary systems composed of 10% (w/w) P407 and C934P were elastoviscous, were easily deformed under stress and did not exhibit mucoadhesion. Formulations containing 15 or 20% (w/w) Pluronic P407 and C934P exhibited a sol-gel temperature T(sol/gel), were viscoelastic and offered high elasticity and resistance to deformation at 37 degrees C. Conversely these formulations were elastoviscous and easily deformed at temperatures below the sol-gel transition temperature. The sol-gel transition temperatures of systems containing 15% (w/w) P407 were unaffected by the presence of C934P; however, increasing the concentration of C934P decreased the T(sol/gel) in formulations containing 20%(w/w) P407. Rheological synergy between P407 and C934P at 37 degrees C was observed and was accredited to secondary interactions between these polymers, in addition to hydrophobic interactions between P407 micelles. Importantly, formulations composed of 20% (w/w) P407 and C934P exhibited pronounced mucoadhesive properties. The ease of administration (below the T(sol/gel)) in conjunction with the viscoelastic (notably high elasticity) and mucoadhesive properties (at body temperature) render the formulations composed of 20% (w/w) P407 and C934P as potentially useful platforms for mucoadhesive, controlled topical drug delivery within the oral cavity. (c) 2009 Published by Elsevier B.V.