Constructive heuristic algorithm for the DC model in network transmission expansion planning

A novel constructive heuristic algorithm to the network expansion planning problem is presented the basic idea comes from Garver's work applied to the transportation model, nevertheless the proposed algorithm is for the DC model. Tests results with most known systems in the literature are carried out to show the efficiency of the method.

Modulation of eosinophil generation and migration by Mangifera indica L. extract (Vimang (R))

The effects of Vimang((R)), an aqueous extract of the stem bark of Mangifera indica L. (Anacardiaccae), on cell migration in an experimental model of asthma was investigated. In vivo treatment of Toxocara canis-infected BALB/c mice for 18 days with 50 mg/kg Vimang((R)) reduced eosinophil migration into the bronchoalveolar space and peritoneal cavity. Also, eosinophil generation in bone marrow and blood eosinophilia were inhibited in infected mice treated with Vimang((R)). This reduction was associated with inhibition of IL-5 production in serum and eotaxin in lung homogenates. In all these cases the effects of Vimang((R)) were more selective than those observed with dexamethasone. Moreover, Virnang((R)) treatment is not toxic for the animals, as demonstrated by the normal body weight increase during infection. These data confirm the potent anti-inflammatory effect of Vimang R and support its potential use as an alternative therapeutic drug to the treatment of eosinophilic disorders including those caused by nematodes and allergic diseases. (c) 2006 Elsevier B.V. All rights reserved.

STOCHASTIC QUANTIZATION OF FERMIONIC THEORIES - RENORMALIZATION OF THE MASSIVE THIRRING MODEL

Using the Langevin approach for stochastic processes, we study the renormalizability of the massive Thirring model. At finite fictitious time, we prove the absence of induced quadrilinear counterterms by verifying the cancellation of the divergencies of graphs with four external lines. This implies that the vanishing of the renormalization group beta function already occurs at finite times.

Branch and bound algorithm for transmission system expansion planning using a transportation model

A method for optimal transmission network expansion planning is presented. The transmission network is modelled as a transportation network. The problem is solved using hierarchical Benders decomposition in which the problem is decomposed into master and slave subproblems. The master subproblem models the investment decisions and is solved using a branch-and-bound algorithm. The slave subproblem models the network operation and is solved using a specialised linear program. Several alternative implementations of the branch-and-bound algorithm have been rested. Special characteristics of the transmission expansion problem have been taken into consideration in these implementations. The methods have been tested on various test systems available in the literature.

Energy localization in the Peyrard-Bishop DNA model

We study energy localization on the oscillator chain proposed by Peyrard and Bishop to model DNA. We search numerically for conditions with initial energy in a small subgroup of consecutive oscillators of a finite chain and such that the oscillation amplitude is small outside this subgroup on a long time scale. We use a localization criterion based on the information entropy and verify numerically that such localized excitations exist when the nonlinear dynamics of the subgroup oscillates with a frequency inside the reactive band of the linear chain. We predict a mimium value for the Morse parameter (mu>2.25) (the only parameter of our normalized model), in agreement with the numerical calculations (an estimate for the biological value is mu=6.3). For supercritical masses, we use canonical perturbation theory to expand the frequencies of the subgroup and we calculate an energy threshold in agreement with the numerical calculations.

Power system transmission network expansion planning using AC model

An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.

Fluctuating dimension in a discrete model for quantum gravity based on the spectral principle

The spectral principle of Connes and Chamseddine is used as a starting point to define a discrete model for Euclidean quantum gravity. Instead of summing over ordinary geometries, we consider the sum over generalized geometries where topology, metric, and dimension can fluctuate. The model describes the geometry of spaces with a countable number n of points, and is related to the Gaussian unitary ensemble of Hermitian matrices. We show that this simple model has two phases. The expectation value , the average number of points in the Universe, is finite in one phase and diverges in the other. We compute the critical point as well as the critical exponent of . Moreover, the space-time dimension delta is a dynamical observable in our model, and plays the role of an order parameter. The computation of is discussed and an upper bound is found, < 2.

Incorporating voltage/reactive representation to short-term generation scheduling models

This paper proposes a methodology to incorporate voltage/reactive representation to Short Term Generation Scheduling (STGS) models, which is based on active/reactive decoupling characteristics of power systems. In such approach STGS is decoupled in both Active (AGS) and Reactive (RGS) Generation Scheduling models. AGS model establishes an initial active generation scheduling through a traditional dispatch model. The scheduling proposed by AGS model is evaluated from the voltage/reactive points of view, through the proposed RGS model. RGS is formulated as a sequence of T nonlinear OPF problems, solved separately but taking into account load tracking between consecutive time intervals. This approach considerably reduces computational effort to perform the reactive analysis of the RGS problem as a whole. When necessary, RGS model is capable to propose active generation redispatches, such that critical reactive problems (in which all reactive variables have been insufficient to control the reactive problems) can be overcome. The formulation and solution methodology proposed are evaluated in the IEEE30 system in two case studies. These studies show that the methodology is robust enough to incorporate reactive aspects to STGS problem.

HEAT-KERNEL EXPANSION AT FINITE TEMPERATURE

We show how the zero-temperature result for the heat-kernel asymptotic expansion can be generalized to the finite-temperature one. We observe that this general result depends on the interesting ratio square-root tau/beta, where tau is the regularization parameter and beta = 1/T, so that the zero-temperature limit beta --> infinity corresponds to the cutoff limit tau --> 0. As an example, we discuss some aspects of the axial model at finite temperature.

Analysis of heuristic algorithms for the transportation model in static and multistage planning in network expansion systems

The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

On a regular convex solver potential for an elastic-damage constitutive model: a theoretical analysis

This work is related with the proposition of a so-called regular or convex solver potential to be used in numerical simulations involving a certain class of constitutive elastic-damage models. All the mathematical aspects involved are based on convex analysis, which is employed aiming a consistent variational formulation of the potential and its conjugate one. It is shown that the constitutive relations for the class of damage models here considered can be derived from the solver potentials by means of sub-differentials sets. The optimality conditions of the resulting minimisation problem represent in particular a linear complementarity problem. Finally, a simple example is present in order to illustrate the possible integration errors that can be generated when finite step analysis is performed. (C) 2003 Elsevier Ltd. All rights reserved.

Transmission-expansion planning using the DC model and nonlinear-programming technique

The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved

Optimal Contract Pricing of Distributed Generation in Distribution Networks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.