944 resultados para annual investments to Finnish wind power
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http://digitalcommons.colby.edu/atlasofmaine2005/1022/thumbnail.jpg
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http://digitalcommons.colby.edu/atlasofmaine2009/1031/thumbnail.jpg
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.
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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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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.
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This letter presents an approach for a geometrical solution of an optimal power flow (OPF) problem for a two-bus system (slack and PV busses). The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program.
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In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.
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Includes bibliography
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Balancing power production and environmental conservation can be problematic. The objective of this study was to investigate the abundance of marsh deer in the Paraná River Basin, above the Sergio Motta (Porto Primavera) Dam, before and after the impact of the dam closure. A fixed-wing, flat window aircraft was used to survey study transects. Observations were recorded based on the distance sampling line transect method, assuming that the detection probability decreases with increased distance. The abundance of marsh deer in the survey region prior to flooding was estimated to be 974 individuals (CV = 0.23). The overall abundance dropped from 974 to 444 (CV = 0.26) individuals after flooding, an overall reduction of 54%. This reduction can be attributed to the direct impact of the flooding process, but it was likely exacerbated by indirect effects, such as increased disease, hunting, and reduction in food availability. Prior to flooding, the marsh deer was distributed widely throughout the dam's catchment area; however, the marsh deer habitat was almost completely destroyed by the flooding process. This situation highlights the need to implement management strategies that ensure the survival of the remaining fragmented population.
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The aim of this study was to evaluate the use of the running anaerobic sprint test (RAST) as a predictor of anaerobic capacity, compare it to the maximal accumulated oxygen deficit (MAOD) and to compare the RAST's parameters with the parameters of 30-s all-out tethered running on a treadmill. 39 (17.0±1.4 years) soccer players participated in this study. The participants underwent an incremental test, 10 submaximal efforts [50-95% of velocity correspondent to VO2MAX (vVO2MAX)] and one supramaximal effort at 110% of vVO2MAX for the determination of MAOD. Furthermore, the athletes performed the RAST. In the second stage the 30-s all-out tethered running was performed on a treadmill (30-s all-out), and compared with RAST. No significant correlation was observed between MAOD and RAST parameters. However, significant correlations were found between the power of the fifth effort (P5) of RAST with peak and mean power of 30-s all-out (r=0.73 and 0.50; p<0.05, respectively). In conclusion, the parameters from RAST do not have an association with MAOD, suggesting that this method should not be used to evaluate anaerobic capacity. Although the correlations between RAST parameters with 30-s all-out do reinforce the RAST as an evaluation method of anaerobic metabolism, such as anaerobic power.
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Recent reports have shown an increase in potentially harmful phytoplankton in Santos bay (Southeastern Brazilian Coast), located in a highly urbanised estuarine complex. Prediction of blooms is, thus, essential but the phytoplankton community structure in very dynamic regions is difficult to determine. In the present work, we discriminate bloom forming microphytoplankton dominance and their relationship to physical and meteorological variables to look for patterns observed in different tides and seasons. Comparing 8 distinct situations, we found five scenarios of dominance that could be related to winds, tides and rainfall: i) Surfers, diatoms occurring during high surf zone energies; ii) Sinkers, represented by larger celled diatoms during spring tide, after periods of high precipitation rates; iii) Opportunistic mixers, composed of chain forming diatoms with small or elongate cells occurring during neap tides; iv) Local mixers, microplanktonic diatoms and dinoflagellates which occurred throughout the 298 sampling stations; and v) Mixotrophic dinoflagellates, after intense estuarine discharges. Results suggest alterations in the temporal patterns for some bloom-forming species, while others appeared in abundances above safe limits for public health. This approach can also illustrate possible impacts of changes in freshwater discharge in highly urbanised estuaries.
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Solar thermal power plants are usually installed in locations with high yearly average solar radiation, often deserts. In such conditions, cooling water required for thermodynamic cycles is rarely available. Moreover, when solar radiation is high, ambient temperature is very high as well; this leads to excessive condensation temperature, especially when air-condensers are used, and decreases the plant efficiency. However, temperature variation in deserts is often very high, which drives to relatively low temperatures during the night. This fact can be exploited with the use of a closed cooling system, so that the coolant (water) is chilled during the night and store. Chilled water is then used during peak temperature hours to cool the condenser (dry cooling), thus enhancing power output and efficiency. The present work analyzes the performance improvement achieved by night thermal cool storage, compared to its equivalent air cooled power plant. Dry cooling is proved to be energy-effective for moderately high day–night temperature differences (20 °C), often found in desert locations. The storage volume requirement for different power plant efficiencies has also been studied, resulting on an asymptotic tendency.
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A wavelet-based approach for large wind power ramp characterisation