994 resultados para Utility optimization


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Optimal fault ride-through (FRT) conditions for a doubly-fed induction generator (DFIG) during a transient grid fault are analyzed with special emphasis on improving the active power generation profile. The transition states due to crowbar activation during transient faults are investigated to exploit the maximum power during the fault and post-fault period. It has been identified that operating slip, severity of fault and crowbar resistance have a direct impact on the power capability of a DFIG, and crowbar resistance can be chosen to optimize the power capability. It has been further shown that an extended crowbar period can deliver enhanced inertial response following the transient fault. The converter protection and drive train dynamics have also been analyzed while choosing the optimum crowbar resistance and delivering enhanced inertial support for an extended crowbar period.

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A PMU based WAMS is to be placed on a weakly coupled section of distribution grid, with high levels of distributed generation. In anticipation of PMU data a Siemens PSS/E model of the electrical environment has been used to return similar data to that expected from the WAMS. This data is then used to create a metric that reflects optimization, control and protection in the region. System states are iterated through with the most desirable one returning the lowest optimization metric, this state is assessed against the one returned by PSS/E under normal circumstances. This paper investigates the circumstances that trigger SPS in the region, through varying generation between 0 and 110% and compromising the network through line loss under summer minimum and winter maximum conditions. It is found that the optimized state can generally tolerate an additional 2 MW of generation (3% of total) before encroaching the same thresholds and in one instance moves the triggering to 100% of generation output.

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This article introduces a resource allocation solution capable of handling mixed media applications within the constraints of a 60 GHz wireless network. The challenges of multimedia wireless transmission include high bandwidth requirements, delay intolerance and wireless channel availability. A new Channel Time Allocation Particle Swarm Optimization (CTA-PSO) is proposed to solve the network utility maximization (NUM) resource allocation problem. CTA-PSO optimizes the time allocated to each device in the network in order to maximize the Quality of Service (QoS) experienced by each user. CTA-PSO introduces network-linked swarm size, an increased diversity function and a learning method based on the personal best, Pbest, results of the swarm. These additional developments to the PSO produce improved convergence speed with respect to Adaptive PSO while maintaining the QoS improvement of the NUM. Specifically, CTA-PSO supports applications described by both convex and non-convex utility functions. The multimedia resource allocation solution presented in this article provides a practical solution for real-time wireless networks.

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This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.

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Efficacy of inverse planning is becoming increasingly important for advanced radiotherapy techniques. This study's aims were to validate multicriteria optimization (MCO) in RayStation (v2.4, RaySearch Laboratories, Sweden) against standard intensity-modulated radiation therapy (IMRT) optimization in Oncentra (v4.1, Nucletron BV, the Netherlands) and characterize dose differences due to conversion of navigated MCO plans into deliverable multileaf collimator apertures. Step-and-shoot IMRT plans were created for 10 patients with localized prostate cancer using both standard optimization and MCO. Acceptable standard IMRT plans with minimal average rectal dose were chosen for comparison with deliverable MCO plans. The trade-off was, for the MCO plans, managed through a user interface that permits continuous navigation between fluence-based plans. Navigated MCO plans were made deliverable at incremental steps along a trajectory between maximal target homogeneity and maximal rectal sparing. Dosimetric differences between navigated and deliverable MCO plans were also quantified. MCO plans, chosen as acceptable under navigated and deliverable conditions resulted in similar rectal sparing compared with standard optimization (33.7 ± 1.8Gy vs 35.5 ± 4.2Gy, p = 0.117). The dose differences between navigated and deliverable MCO plans increased as higher priority was placed on rectal avoidance. If the best possible deliverable MCO was chosen, a significant reduction in rectal dose was observed in comparison with standard optimization (30.6 ± 1.4Gy vs 35.5 ± 4.2Gy, p = 0.047). Improvements were, however, to some extent, at the expense of less conformal dose distributions, which resulted in significantly higher doses to the bladder for 2 of the 3 tolerance levels. In conclusion, similar IMRT plans can be created for patients with prostate cancer using MCO compared with standard optimization. Limitations exist within MCO regarding conversion of navigated plans to deliverable apertures, particularly for plans that emphasize avoidance of critical structures. Minimizing these differences would result in better quality treatments for patients with prostate cancer who were treated with radiotherapy using MCO plans.

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In the current investigation, rubber/clay nanocomposites were prepared by two different methods using hydrogenated nitrile butadiene rubber (HNBR) and the organoclay namely Cloisite 15A (C15A). A new novel approach involving swelling of C15A by ulltrasonication in HNBR solution has been carried out for improving the exfoliation and compatibilization of organoclays with HNBR matrix. With the addition of 5phr of clay, the elongation at break and tear strength improved by 16% and 24% respectively. The effect of coupling agents namely amino functional silane and tetrasulfido silane on the nanocomposites have been investigated. The elongation at break and tear strength improved by 46% and 77% respectively with the use of silanes. The improvement in the mechanical properties attributes to improved interaction between the organoclays and HNBR matrix. This interaction has been studied by X-ray diffraction and transmission electron microscope. Pre-dispersion technique clearly suggests very good improvement in the dispersion and properties due to better filler-rubber compatibility. © 2010 American Institute of Physics.