Nyquist Frequency in Sequentially Sampled Data

This paper studies the sequential sampling scheme as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value. Sequential sampling is analyzed and it is proved that when the sampling ratio is an integral number, the associated spectral estimates give a Nyquist frequency . This sampling scheme can, therefore, be employed to yield a required cut- off frequency.Nyquist Freqency; cut-off frequency; Sequential Sampling; Spectral Density Function

On the Economic Value and Price-Responsiveness of Ramp-Constrained Storage

The primary concerns of this paper are twofold: to understand the economic value of storage in the presence of ramp constraints and exogenous electricity prices, and to understand the implications of the associated optimal storage management policy on qualitative and quantitative characteristics of storage response to real-time prices. We present an analytic characterization of the optimal policy, along with the associated finite-horizon time-averaged value of storage. We also derive an analytical upperbound on the infinite-horizon time-averaged value of storage. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. While the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, we first present computational experiments that suggest that optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price, but little or no elasticity far from it. We then present a computational framework for understanding the behavior of storage as a function of price and the amount of stored energy, and for characterization of the buy/sell phase transition region in the price-state plane. Finally, we study the impact of market-based operation of storage on the required reserves, and show that the reserves may need to be expanded to accommodate market-based storage

Nyquist Frequency in Sequentially Sampled Data

This paper studies the sequential sampling scheme as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value. Sequential sampling is analyzed and it is proved that when the sampling ratio is an integral number, the associated spectral estimates give a Nyquist frequency . This sampling scheme can, therefore, be employed to yield a required cut- off frequency

Nyquist Frequency in Sequentially Sampled Data

This paper studies the sequential sampling scheme as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value. Sequential sampling is analyzed and it is proved that when the sampling ratio is an integral number, the associated spectral estimates give a Nyquist frequency . This sampling scheme can, therefore, be employed to yield a required cut- off frequency

Stochastic dynamic optimization of consumption and the induced price elasticity of demand in smart grids

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 75-77).This thesis presents a mathematical model of consumer behavior in response to stochastically-varying electricity prices, and a characterization of price-elasticity of demand created by optimal utilization of storage and the flexibility to shift certain demands to periods of lower prices. The approach is based on analytical characterization of the consumer's optimal policy and the associated value function in a finite-horizon stochastic dynamic programming framework. A general model is first presented, which incorporates both load-shifting and storage, and then, the model is decoupled into two subproblems, one for load-shifting and the other for storage. The study of optimal utilization of storage, which is performed analytically and in the presence of ramp constraints, reveals, as a particularly compelling finding, that the value function is a convex piece-wise linear function of the storage state. Moreover, it is shown that the expected monetary value of storage increases with price volatility, and that when the ramping rate is finite, the value of storage saturates quickly as the capacity increases, regardless of price volatility. Furthermore, it is shown that although the demand for electricity is often deemed to be highly inelastic, optimal utilization of local storage capacity induces a considerable amount of price elasticity of demand. The study of the load-shifting problem is performed under both perfect and partial information about price distribution. It is shown that load-shifting induces considerable consumer savings that increase with price volatility. Furthermore, it is shown that the opportunity to optimally schedule the shiftable loads creates a considerable amount of price elasticity, even when the aggregate consumption over a long period remains insensitive to price variations.by Ali Faghih.S.M

Effect of Spectral Bandwidths on Linear Feature Extraction: An Evaluation of Landsat ETM+ and OLI Sensors

Hitherto there have been many studies comparing the usefulness of OLI and ETM+ sensors for linear feature extraction. However, not too much attention has been paid to the differences in the bandwidth of the two sensors. In this study, the suitability of Landsat ETM+ and OLI sensors for automatic detection of linear features by LINE algorithm was compared. In this study, eight regions in northern, central and southern parts of Iran were selected based on the diversity of lithology, the pristine status, and lack of human activities for the comparison of the two datasets. Results revealed that LINE algorithm performed better on the images with higher standard deviation. The ETM+ datasets are more suitable for linear feature extraction because ETM+ panchromatic band and first principal component analysis image (PC1 image) of ETM+ datasets have higher standard deviation compared to OLI datasets

Ultra-Fast, High-Performance 8x8 Approximate Multipliers by a New Multicolumn 3,3:2 Inexact Compressor and its Derivatives

Multiplier, as a key role in many different applications, is a time-consuming, energy-intensive computation block. Approximate computing is a practical design paradigm that attempts to improve hardware efficacy while keeping computation quality satisfactory. A novel multicolumn 3,3:2 inexact compressor is presented in this paper. It takes three partial products from two adjacent columns each for rapid partial product reduction. The proposed inexact compressor and its derivates enable us to design a high-speed approximate multiplier. Then, another ultra-fast, high-efficient approximate multiplier is achieved utilizing a systematic truncation strategy. The proposed multipliers accumulate partial products in only two stages, one fewer stage than other approximate multipliers in the literature. Implementation results by Synopsys Design Compiler and 45 nm technology node demonstrates nearly 11.11% higher speed for the second proposed design over the fastest existing approximate multiplier. Furthermore, the new approximate multipliers are applied to the image processing application of image sharpening, and their performance in this application is highly satisfactory. It is shown in this paper that the error pattern of an approximate multiplier, in addition to the mean error distance and error rate, has a direct effect on the outcomes of the image processing application.Comment: 21 Pages, 18 Figures, 6 Table

Computational Analysis of Natural Ventilation Flows in Geodesic Dome Building in Hot Climates

For centuries, dome roofs were used in traditional houses in hot regions such as the Middle East and Mediterranean basin due to its thermal advantages, structural benefits and availability of construction materials. This article presents the computational modelling of the wind- and buoyancy-induced ventilation in a geodesic dome building in a hot climate. The airflow and temperature distributions and ventilation flow rates were predicted using Computational Fluid Dynamics (CFD). The three-dimensional Reynolds-Averaged Navier-Stokes (RANS) equations were solved using the CFD tool ANSYS FLUENT15. The standard k-epsilon was used as turbulence model. The modelling was verified using grid sensitivity and flux balance analysis. In order to validate the modelling method used in the current study, additional simulation of a similar domed-roof building was conducted for comparison. For wind-induced ventilation, the dome building was modelled with upper roof vents. For buoyancy-induced ventilation, the geometry was modelled with roof vents and also with two windows open in the lower level. The results showed that using the upper roof openings as a natural ventilation strategy during winter periods is advantageous and could reduce the indoor temperature and also introduce fresh air. The results also revealed that natural ventilation using roof vents cannot satisfy thermal requirements during hot summer periods and complementary cooling solutions should be considered. The analysis showed that buoyancy-induced ventilation model can still generate air movement inside the building during periods with no or very low wind