943 resultados para Power take-off optimization
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper, short term hydroelectric scheduling is formulated as a network flow optimization model and solved by interior point methods. The primal-dual and predictor-corrector versions of such interior point methods are developed and the resulting matrix structure is explored. This structure leads to very fast iterations since it avoids computation and factorization of impedance matrices. For each time interval, the linear algebra reduces to the solution of two linear systems, either to the number of buses or to the number of independent loops. Either matrix is invariant and can be factored off-line. As a consequence of such matrix manipulations, a linear system which changes at each iteration has to be solved, although its size is reduced to the number of generating units and is not a function of time intervals. These methods were applied to IEEE and Brazilian power systems, and numerical results were obtained using a MATLAB implementation. Both interior point methods proved to be robust and achieved fast convergence for all instances tested. (C) 2004 Elsevier Ltd. All rights reserved.
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This article presents a new approach to minimize the losses in electrical power systems. This approach considers the application of the primal-dual logarithmic barrier method to voltage magnitude and tap-changing transformer variables, and the other inequality constraints are treated by augmented Lagrangian method. The Lagrangian function aggregates all the constraints. The first-order necessary conditions are reached by Newton's method, and by updating the dual variables and penalty factors. Test results are presented to show the good performance of this approach.
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This paper presents a new approach to solve the Optimal Power Flow problem. This approach considers the application of logarithmic barrier method to voltage magnitude and tap-changing transformer variables and the other constraints are treated by augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. (C) 2005 Elsevier Ltd. All rights reserved.
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We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.
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This paper presents a new algorithm for optimal power flow problem. The algorithm is based on Newton's method which it works with an Augmented Lagrangian function associated with the original problem. The function aggregates all the equality and inequality constraints and is solved using the modified-Newton method. The test results have shown the effectiveness of the approach using the IEEE 30 and 638 bus systems.
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In this work, thermodynamic and economic analyses are applied to a Brazilian thermal power plant operating with natural gas. The analyses are performed in two cases: the current configuration and the future configuration. The current configuration is constituted by four gas turbines which operate in open cycle. The future configuration is obtained by a plant repowering by addition of four recovery boilers, two steam turbines and others equipment and accessories necessary to operate in combined cycle. In order to obtain the performance parameters, energetic and exergetic analyses for each case considered are carried out. on the other hand, thermoeconomic analysis provides means to evaluate the influences of the capital and fuel costs in the composition of the electricity costs. Techniques of investment analysis are also applied to the new configuration and from the results obtained it is possible to verify the advantages of the modifications.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Symbolic power is discussed with reference to mathematics and formal languages. Two distinctions are crucial for establishing mechanical and formal perspectives: one between appearance and reality, and one between sense and reference. These distinctions include a nomination of what to consider primary and secondary. They establish the grammatical format of a mechanical and a formal world view. Such views become imposed on the domains addressed by means of mathematics and formal languages. Through such impositions symbolic power of mathematics becomes exercised. The idea that mathematics describes as it prioritises is discussed with reference to robotting and surveillance. In general, the symbolic power of mathematics and formal languages is summarised through the observations: that mathematics treats parts and properties as autonomous, that it dismembers what it addresses and destroys the organic unity around things, and that it simplifies things and reduces them to a single feature. But, whatever forms the symbolic power may take, it cannot be evaluated along a single good-bad axis.
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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.
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In a collaborative work carried out by the Spanish and Portuguese ISFG Working Group (GEP-ISFG), a polymerase chain reaction multiplex was optimized in order to type ten X-chromosome short tandem repeats (STRs) in a single reaction, including: DXS8378, DXS9902, DXS7132, DXS9898, DXS6809, DXS6789, DXS7133, GATA172D05, GATA31E08, and DXS7423. Using this X-decaplex, each 17 of the participating laboratories typed a population sample of approximately 200 unrelated individuals (100 males and 100 females). In this work, we report the allele frequencies for the ten X-STRs in 15 samples from Argentina (Buenos Aires, CA(3)rdoba, Rio Negro, Entre Rios, and Misiones), Brazil (SA o pound Paulo, Rio de Janeiro, Parana, and Mato Grosso do Sul), Colombia (Antioquia), Costa Rica, Portugal (Northern and Central regions), and Spain (Galicia and Cantabria). Gene diversities were calculated for the ten markers in each population and all values were above 56%. The average diversity per locus varied between 66%, for DXS7133, and 82%, for DXS6809. For this set of STRs, a high discrimination power was obtained in all populations, both in males (a parts per thousand yen1 in 5 A- 10(5)) and females (a parts per thousand yen1 in 3 A- 10(9)), as well as high mean exclusion chance in father/daughter duos (a parts per thousand yen99.953%) and in father/mother/daughter trios (a parts per thousand yen99.999%). Genetic distance analysis showed no significant differences between northern and central Portugal or between the two Spanish samples from Galicia and Cantabria. Inside Brazil, significant differences were found between Rio de Janeiro and the other three populations, as well as between SA o pound Paulo and Parana. For the five Argentinean samples, significant distances were only observed when comparing Misiones with Entre Rios and with Rio Negro, the only two samples that do not differ significantly from Costa Rica. Antioquia differed from all other samples, except the one from Rio Negro.
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We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.
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The role of dimensional regularization is discussed and compared with that of cut-off regularization in some quantum mechanical problems with ultraviolet divergence in two and three dimensions with special emphasis on the nucleon-nucleon interaction. Both types of renormalizations are performed for attractive divergent one- and two-term separable potentials, a divergent tensor potential, and the sum of a delta function and its derivatives. We allow energy-dependent couplings, and determine the form that these couplings should take if equivalence between the two regularization schemes is to be enforced. We also perform renormalization of an attractive separable potential superposed on an analytic divergent potential.
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A new approach to solving the Optimal Power Flow problem is described, making use of some recent findings, especially in the area of primal-dual methods for complex programming. In this approach, equality constraints are handled by Newton's method inequality constraints for voltage and transformer taps by the logarithmic barrier method and the other inequality constraints by the augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. © 2001 IEEE.