Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Conceptos y métodos de la programación por zonas para el desarrollo de la comunidad = Concepts and methods of area programming for community development

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The programming of short-term financing

Includes bibliography

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

Rural development and urban food programming

Includes bibliography

Fault current limiter using transformer and modular device of YBCO coated conductor

In this work, we report on the evaluation of a superconducting fault current limiter (SFCL). It is consisted of a modular superconducting device combined with a short-circuited transformer with a primary copper winding connected in series to the power line and the secondary side short-circuited by the superconducting device. The basic idea is adding a magnetic component to contribute to the current limitation by the impedance reflected to the line after transition of the superconducting device. The evaluation tests were performed with a prospective current up to 2 kA, with the short-circuited transformer of 2.5 kVA, 220 V/660 V connected to a test facility of 100 kVA power capacity. The resistive SFCL using a modular superconducting device was tested without degradation for a prospective fault current of 1.8 kA, achieving the limiting factor 2.78; the voltage achieved 282 V corresponding to an electric field of 11 V/m. The test performed with the combined SFCL (xsuperconducting device + transformer) using series and toroidal transformers showed current limiting factor of 3.1 and 2 times, respectively. The test results of the combined SFCL with short-circuited transformer showed undesirable influence of the transformer impedance, resulting in reduction of the fault current level. © 2002-2011 IEEE.

programming by sectors and by regions, and preparation, presentation and evaluation of projects

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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.

Estudio preliminar sobre la técnica de programación del desarrollo económico = Preliminary study of the technique of programming economic development

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