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.

Interior point algorithm for linear programming used in transmission network synthesis

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.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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

ALGORITHM FOR PROBABILISTIC ANALYSIS of DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATION

In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

Association of diabetes and cigarette smoke exposure on the glycemia and liver glycogen of pregnant Wistar rats

Purpose: To evaluate cigarette smoke exposure and/or diabetes association effects on the glycemia and liver glycogen levels of pregnant Wistar rats. Methods: 60 adult rats were randomly distributed into (n= 10/group): non-diabetic exposed to filtered air (G1); non-diabetic exposed to cigarette smoke only before pregnancy (G2); non-diabetic exposed to cigarette smoke before and during pregnancy (G3); diabetic exposed to filtered air (G4); diabetic exposed to cigarette smoke only before pregnancy (G5), and diabetic exposed to cigarette smoke before and during pregnancy (G6). Glycemia was determined at days 0 and 21 of pregnancy. Liver samples were collected for liver glycogen determinations. Results: At day 21 of pregnancy, glycemia was higher in G5 and G6 compared to G4 group. G2 (2.43 +/- 0.43), G3 (3.20 +/- 0.49), G4 (2.62 +/- 0.34), G5 (2.65 +/- 0.27) and G6 groups (1.94 +/- 0.35) presented decreased liver glycogen concentrations compared to G1 (4.20 +/- 0.18 mg/100mg liver tissue) (p<0.05). G5 and G6 groups presented decreased maternal weight gain and litter weight. Conclusions: Severe diabetes and cigarette smoke exposure, alone or associated, caused impairment in liver glycogen storage at term pregnancy. Due to the fact that liver glycogen storages were considered determinant for glucose tolerance, it is relevant to point out a rigid clinical glycemic control and to stop smoking so earlier in pregnancy programming.

Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy

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.

Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration

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

Heterogeneity correction in the construction of optimized planning in radiotherapy using linear programming

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

Optimization Strategies Based on Sequential Quadratic Programming Applied for a Fermentation Process for Butanol Production

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

Cryptic sexual populations account for genetic diversity and ecological success in a widely distributed, asexual fungus-growing ant

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

C programs for solving the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

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

Evaluating distributed generation impacts with a multiobjective index

Evaluating the technical impacts associated with connecting distributed generation to distribution networks is a complex activity requiring a wide range of network operational and security effects to be qualified and quantified. One means of dealing with such complexity is through the use of indices that indicate the benefit or otherwise of connections at a given location and which could be used to shape the nature of the contract between the utility and distributed generator. This paper presents a multiobjective performance index for distribution networks with distributed generation which considers a wide range of technical issues. Distributed generation is extensively located and sized within the IEEE-34 test feeder, wherein the multiobjective performance index is computed for each configuration. The results are presented and discussed.

Design and management optimization of trickle irrigation systems using non-linear programming

A non-linear model is presented which optimizes the lay-out, as well as the design and management of trickle irrigation systems, to achieve maximum net benefit. The model consists of an objective function that maximizes profit at the farm level, subject to appropriate geometric and hydraulic constraints. It can be applied to rectangular shaped fields, with uniform or zero slope. The software used is the Gams-Minos package. The basic inputs are the crop-water-production function, the cost function and cost of system components, and design variables. The main outputs are the annual net benefit and pipe diameters and lengths. To illustrate the capability of the model, a sensitivity analysis of the annual net benefit for a citrus field is evaluated with respect to irrigated area, ground slope, micro-sprinkler discharge and shape of the field. The sensitivity analysis suggests that the greatest benefit is obtained with the smallest microsprinkler discharge, the greatest area, a square field and zero ground slope. The costs of the investment and energy are the components of the objective function that had the greatest effect in the 120 situations evaluated. (C) 1996 Academic Press Limited

THEORY OF ELECTRICAL CHARACTERISTICS OF A SCHOTTKY-BARRIER HAVING EXPONENTIALLY DISTRIBUTED IMPURITY STATES AND METAL-INSULATOR METAL STRUCTURES

The metal-insulator or metal-amorphous semiconductor blocking contact is still not well understood. Here, we discuss the steady state characteristics of a non-intimate metal-insulator Schottky barrier. We consider an exponential distribution (in energy) of impurity states in addition to impurity states at a single energy level within the depletion region. We present analytical expressions for the electrical potential, field, thickness of depletion region, capacitance, and charge accumulated in the depletion region. We also discuss ln I versus V(ap) data. Finally, we compare the characteristics in three cases: (i) impurity states at only a single energy level; (ii) uniform energy distribution of impurity states; and (iii) exponential energy distribution of impurity states.In general, the electrical characteristics of Schottky barriers and metal-insulator-metal structures with Schottky barriers depend strongly on the energy distribution of impurity states.