Teoria de carteiras e a alocação de parques eólicos offshore

The consumption of energy on the planet is currently based on fossil fuels. They are responsible for adverse effects on the environment. Renewables propose solutions for this scenario, but must face issues related to the capacity of the power supply. Wind energy offshore emerging as a promising alternative. The speed and stability are greater winds over oceans, but the variability of these may cause inconvenience to the generation of electric power fluctuations. To reduce this, a combination of wind farms geographically distributed was proposed. The greater the distance between them, the lower the correlation between the wind velocity, increasing the likelihood that together achieve more stable power system with less fluctuations in power generation. The efficient use of production capacity of the wind park however, depends on their distribution in marine environments. The objective of this research was to analyze the optimal allocation of wind farms offshore on the east coast of the U.S. by Modern Portfolio Theory. The Modern Portfolio Theory was used so that the process of building portfolios of wind energy offshore contemplate the particularity of intermittency of wind, through calculations of return and risk of the production of wind farms. The research was conducted with 25.934 observations of energy produced by wind farms 11 hypothetical offshore, from the installation of 01 simulated ocean turbine with a capacity of 5 MW. The data show hourly time resolution and covers the period between January 1, 1998 until December 31, 2002. Through the Matlab R software, six were calculated minimum variance portfolios, each for a period of time distinct. Given the inequality of the variability of wind over time, set up four strategies rebalancing to evaluate the performance of the related portfolios, which enabled us to identify the most beneficial to the stability of the wind energy production offshore. The results showed that the production of wind energy for 1998, 1999, 2000 and 2001 should be considered by the portfolio weights calculated for the same periods, respectively. Energy data for 2002 should use the weights derived from the portfolio calculated in the previous time period. Finally, the production of wind energy in the period 1998-2002 should also be weighted by 1/11. It follows therefore that the portfolios found failed to show reduced levels of variability when compared to the individual production of wind farms hypothetical offshore

Oxygen variance and meridional oxygen supply in the Tropical North East Atlantic oxygen minimum zone

The distribution of the mean oceanic oxygen concentration results from a balance between ventilation and consumption. In the eastern tropical Pacific and Atlantic, this balance creates extended oxygen minimum zones (OMZ) at intermediate depth. Here, we analyze hydrographic and velocity data from shipboard and moored observations, which were taken along the 23°W meridian cutting through the Tropical North East Atlantic (TNEA) OMZ, to study the distribution and generation of oxygen variability. By applying the extended Osborn-Cox model, the respective role of mesoscale stirring and diapycnal mixing in producing enhanced oxygen variability, found at the southern and upper boundary of the OMZ, is quantified. From the well-ventilated equatorial region toward the OMZ core a northward eddy-driven oxygen flux is observed whose divergence corresponds to an oxygen supply of about 2.4 µmol kg-1 year-1 at the OMZ core depth. Above the OMZ core, mesoscale eddies act to redistribute low- and high-oxygen waters associated with westward and eastward currents, respectively. Here, absolute values of the local oxygen supply >10 mmol kg-1 year-1 are found, likely balanced by mean zonal advection. Combining our results with recent studies, a refined oxygen budget for the TNEA OMZ is derived. Eddy-driven meridional oxygen supply contributes more than 50 % of the supply required to balance the estimated oxygen consumption. The oxygen tendency in the OMZ, as given by the multidecadal oxygen decline, is maximum slightly above the OMZ core and represents a substantial imbalance of the oxygen budget reaching about 20 % of the magnitude of the eddy-driven oxygen supply.

A possible explanation of the Maunder minimum from a flux transport dynamo model

We propose that the poloidal field at the end of the last sunspot cycle before the Maunder minimum fell to a very low value due to fluctuations in the Babcock-Leighton process. With this assumption, a flux transport dynamo model is able to explain various aspects of the historical records of the Maunder minimum remarkably well by suitably choosing the parameters of the model to give the correct growth time.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Noncoherent Integration for Signal Detection: Analysis Under Model Uncertainties

The performance of postdetection integration (PDI) techniques for the detection of Global Navigation Satellite Systems (GNSS) signals in the presence of uncertainties in frequency offsets, noise variance, and unknown data-bits is studied. It is shown that the conventional PDI techniques are generally not robust to uncertainty in the data-bits and/or the noise variance. Two new modified PDI techniques are proposed, and they are shown to be robust to these uncertainties. The receiver operating characteristics (ROC) and sample complexity performance of the PDI techniques in the presence of model uncertainties are analytically derived. It is shown that the proposed methods significantly outperform existing methods, and hence they could become increasingly important as the GNSS receivers attempt to push the envelope on the minimum signal-to-noise ratio (SNR) for reliable detection.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Optimal fiscal policy in a multisector model with minimum expenditure requirements

This paper investigates optimal fiscal policy in a static multisector model. A Ramsey type planner chooses tax rates on each good type as well as spending levels on each good type subject to an exogenous total expenditure constraint and requirements that some minimum amount of spending be undertaken in each sector. It is shown that optimal policy does not equally spend in each sector but instead results in one of the minimum expenditure constraints binding.

Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework

Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

Generate disaggregated soil allocation data using a Minimum Cross Entropy Model

Montado ecosystem in the Alentejo Region, south of Portugal, has enormous agro-ecological and economics heterogeneities. A definition of homogeneous sub-units among this heterogeneous ecosystem was made, but for them is disposal only partial statistical information about soil allocation agro-forestry activities. The paper proposal is to recover the unknown soil allocation at each homogeneous sub-unit, disaggregating a complete data set for the Montado ecosystem area using incomplete information at sub-units level. The methodological framework is based on a Generalized Maximum Entropy approach, which is developed in thee steps concerning the specification of a r order Markov process, the estimates of aggregate transition probabilities and the disaggregation data to recover the unknown soil allocation at each homogeneous sub-units. The results quality is evaluated using the predicted absolute deviation (PAD) and the "Disagegation Information Gain" (DIG) and shows very acceptable estimation errors.

Model-based appraisal of minimum unit pricing for alcohol in Northern Ireland

In 2009, the Sheffield Alcohol Research Group (SARG) at Sheffield University developed the Sheffield Alcohol Policy Model version 2.0 (SAPM) to appraise the potential impact of alcohol policies, including different levels of MUP, for the population of England. In 2013, SARG were commissioned by the DHSSPS and the Department for Social Development to adapt the Sheffield Model to NI in order to appraise the potential impact of a range of alcohol pricing policies. The present report represents the results of this work. Estimates from the Northern Ireland (NI) adaptation of the Sheffield Alcohol Policy Model - version 3 - (SAPM3) suggest: 1. Minimum Unit Pricing (MUP) policies would be effective in reducing alcohol consumption, alcohol related harms (including alcohol-related deaths, hospitalisations, crimes and workplace absences) and the costs associated with those harms. 2. A ban on below-cost selling (implemented as a ban on selling alcohol for below the cost of duty plus the VAT payable on that duty) would have a negligible impact on alcohol consumption or related harms. 3. A ban on price-based promotions in the off-trade, either alone or in tandem with an MUP policy would be effective in reducing alcohol consumption, related harms and associated costs. 4. MUP and promotion ban policies would only have a small impact on moderate drinkers at all levels of income. Somewhat larger impacts would be experienced by increasing risk drinkers, with the most substantial effects being experienced by high risk drinkers. 5. MUP and promotion ban policies would have larger impacts on those in poverty, particularly high risk drinkers, than those not in poverty. However, those in poverty also experience larger relative gains in health and are estimated to marginally reduce their spending due to their reduced drinking under the majority of policies åÊ

Testing dynamic variance-sensitive foraging using individual differences in basal metabolic rates of zebra finches

Social foragers can alternate between searching for food (producer tactic), and searching for other individuals that have located food in order to join them (scrounger tactic). Both tactics yield equal rewards on average, but the rewards generated by producer are more variable. A dynamic variance-sensitive foraging model predicts that social foragers should increase their use of scrounger with increasing energy requirements and/or decreased food availability early in the foraging period. We tested whether natural variation in minimum energy requirements (basal metabolic rate or BMR) is associated with differences in the use of producer–scrounger foraging tactics in female zebra finches Taeniopygia guttata. As predicted by the dynamic variance-sensitive model, high BMR individuals had significantly greater use of the scrounger tactic compared with low BMR individuals. However, we observed no effect of food availability on tactic use, indicating that female zebra finches were not variance-sensitive foragers under our experimental conditions. This study is the first to report that variation in BMR within a species is associated with differences in foraging behaviour. BMR-related differences in scrounger tactic use are consistent with phenotype-dependent tactic use decisions. We suggest that BMR is correlated with another phenotypic trait which itself influences tactic use decisions.

A Note on the Asymptotic Variance of Survival Function in the Semi-Markov Model

In Malani and Neilsen (1992) we have proposed alternative estimates of survival function (for time to disease) using a simple marker that describes time to some intermediate stage in a disease process. In this paper we derive the asymptotic variance of one such proposed estimator using two different methods and compare terms of order 1/n when there is no censoring. In the absence of censoring the asymptotic variance obtained using the Greenwood type approach converges to exact variance up to terms involving 1/n. But the asymptotic variance obtained using the theory of the counting process and results from Voelkel and Crowley (1984) on semi-Markov processes has a different term of order 1/n. It is not clear to us at this point why the variance formulae using the latter approach give different results.

Utilizing Gaussian-Schell model beams to mitigate atmospheric turbulence in free space optical communications / by Kyle R. Drexler.

Turbulence affects traditional free space optical communication by causing speckle to appear in the received beam profile. This occurs due to changes in the refractive index of the atmosphere that are caused by fluctuations in temperature and pressure, resulting in an inhomogeneous medium. The Gaussian-Schell model of partial coherence has been suggested as a means of mitigating these atmospheric inhomogeneities on the transmission side. This dissertation analyzed the Gaussian-Schell model of partial coherence by verifying the Gaussian-Schell model in the far-field, investigated the number of independent phase control screens necessary to approach the ideal Gaussian-Schell model, and showed experimentally that the Gaussian-Schell model of partial coherence is achievable in the far-field using a liquid crystal spatial light modulator. A method for optimizing the statistical properties of the Gaussian-Schell model was developed to maximize the coherence of the field while ensuring that it does not exhibit the same statistics as a fully coherent source. Finally a technique to estimate the minimum spatial resolution necessary in a spatial light modulator was developed to effectively propagate the Gaussian-Schell model through a range of atmospheric turbulence strengths. This work showed that regardless of turbulence strength or receiver aperture, transmitting the Gaussian-Schell model of partial coherence instead of a fully coherent source will yield a reduction in the intensity fluctuations of the received field. By measuring the variance of the intensity fluctuations and the received mean, it is shown through the scintillation index that using the Gaussian-Schell model of partial coherence is a simple and straight forward method to mitigate atmospheric turbulence instead of traditional adaptive optics in free space optical communications.