370 resultados para THERMOELECTRIC-POWER


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Quaternary chalcogenide compounds Cu2+ xZnSn1-xSe4 (0 <= x <= 0.15) were prepared by solid state synthesis. Rietveld powder X-ray diffraction (XRD) refinements combined with Electron Probe Micro Analyses (EPMA, WDS-Wavelength Dispersive Spectroscopy) and Raman spectra of all samples confirmed the stannite structure (Cu2FeSnS4-type) as the main phase. In addition to the main phase, small amounts of secondary phases like ZnSe, CuSe and SnSe were observed. Transport properties of all samples were measured as a function of temperature in the range from 300 K to 720 K. The electrical resistivity of all samples decreases with an increase in Cu content except for Cu2.1ZnSn0.9Se4, most likely due to a higher content of the ZnSe. All samples showed positive Seebeck coefficients indicating that holes are the majority charge carriers. The thermal conductivity of doped samples was high compared to Cu2ZnSnSe4 and this may be due to the larger electronic contribution and the presence of the ZnSe phase in the doped samples. The maximum zT = 0.3 at 720 K occurs for Cu2.05ZnSn0.95Se4 for which a high-pressure torsion treatment resulted in an enhancement of zT by 30% at 625 K. Copyright 2013 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4794733]

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On the backdrop of climate change scenario, there is emphasis on controlling emission of greenhouse gases such as CO2. Major thrust being seen worldwide as well as in India is for generation of electricity from renewable sources like solar and wind. Chitradurga area of Karnataka is identified as a suitable location for the production of electricity from wind turbines because of high wind-energy resource. The power generated and the performance of 18 wind turbines located in this region are studied based on the actual field data collected over the past seven years. Our study shows a good prospect for expansion of power production using wind turbines.

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In this paper, we discuss the issues related to word recognition in born-digital word images. We introduce a novel method of power-law transformation on the word image for binarization. We show the improvement in image binarization and the consequent increase in the recognition performance of OCR engine on the word image. The optimal value of gamma for a word image is automatically chosen by our algorithm with fixed stroke width threshold. We have exhaustively experimented our algorithm by varying the gamma and stroke width threshold value. By varying the gamma value, we found that our algorithm performed better than the results reported in the literature. On the ICDAR Robust Reading Systems Challenge-1: Word Recognition Task on born digital dataset, as compared to the recognition rate of 61.5% achieved by TH-OCR after suitable pre-processing by Yang et. al. and 63.4% by ABBYY Fine Reader (used as baseline by the competition organizers without any preprocessing), we achieved 82.9% using Omnipage OCR applied on the images after being processed by our algorithm.

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Supercritical carbon dioxide based Brayton cycle for possible concentrated solar power applications is investigated and compared with trans- and sub-critical operations of the same fluid. Thermal efficiency, specific work output and magnitude of irreversibility generation are used as some of the performance indicators. While the thermal efficiency increases almost linearly with low side pressure in the sub- and trans-critical cycles, it attains a maximum in the supercritical regime at 85 bar after which there are diminishing returns on increasing the low side pressure. It is also found that supercritical cycle is capable of producing power with a thermal efficiency of >30% even at a lower source temperature (820K) and accounting for foreseeable non-idealities albeit with a higher turbine inlet pressure (similar to 300 bar) which is not matched by a conventional sub-critical cycle even with a high source temperature of 978K. The reasons for lower efficiency than in an ideal cycle are extracted from an irreversibility analysis of components, namely, compressor, regenerator, turbine and gas cooler. Low sensitivity to the source temperature and extremely small volumetric flow rates in the supercritical cycle could offset the drawback of high pressures through a compact system.

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This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

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Ingots with compositions CrSi2-x (with 0 < x < 0.1) were synthesized by vacuum arc melting followed by uniaxial hot pressing for densification. This paper reports the temperature and composition dependence of the electrical resistivity, Seebeck coefficient, and thermal conductivity of CrSi2-x samples in the temperature range of 300 K to 800 K. The silicon-deficient samples exhibited substantial reductions in resistivity and Seebeck coefficient over the measured temperature range due to the formation of metallic secondary CrSi phase embedded in the CrSi2 matrix phase. The thermal conductivity was seen to exhibit a U-shaped curve with respect to x, exhibiting a minimum value at the composition of x = 0.04. However, the limit of the homogeneity range of CrSi2 suppresses any further decrease of the lattice thermal conductivity. As a consequence, the maximum figure of merit of ZT = 0.1 is obtained at 650 K for CrSi1.98.

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Amplify-and-forward (AF) relay based cooperation has been investigated in the literature given its simplicity and practicality. Two models for AF, namely, fixed gain and fixed power relaying, have been extensively studied. In fixed gain relaying, the relay gain is fixed but its transmit power varies as a function of the source-relay (SR) channel gain. In fixed power relaying, the relay's instantaneous transmit power is fixed, but its gain varies. We propose a general AF cooperation model in which an average transmit power constrained relay jointly adapts its gain and transmit power as a function of the channel gains. We derive the optimal AF gain policy that minimizes the fading- averaged symbol error probability (SEP) of MPSK and present insightful and tractable lower and upper bounds for it. We then analyze the SEP of the optimal policy. Our results show that the optimal scheme is up to 39.7% and 47.5% more energy-efficient than fixed power relaying and fixed gain relaying, respectively. Further, the weaker the direct source-destination link, the greater are the energy-efficiency gains.

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Wafer/microcrystallites of oxidized Ge with holes/nanoholes synthesized by thermal oxidation strategy from Ge wafer/microcrystallites can convert one wavelength to another. Both oxidized Ge wafer and microcrystallites shows excitation- and power-dependent luminescence. Red-shift is observed as the excitation wavelength is increased, while blue-shift is observed as power density is increased. Over all, blue-green-yellow-orange luminescence is observed depending on the excitation wavelength and the morphology of oxidized Ge. The various defects level associated with germanium-oxygen vacancies in GeO2 and Ge/GeO2 interface are responsible for the excitation-dependent luminescence. Being a light-conversion material, oxidized Ge is expected to find potential applications in solid-state lighting, photovoltaic devices and photocatalysis.

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We propose power allocation algorithms for increasing the sum rate of two and three user interference channels. The channels experience fast fading and there is an average power constraint on each transmitter. Our achievable strategies for two and three user interference channels are based on the classification of the interference into very strong, strong and weak interferences. We present numerical results of the power allocation algorithm for two user Gaussian interference channel with Rician fading with mean total power gain of the fade Omega = 3 and Rician factor kappa = 0.5 and compare the sum rate with that obtained from ergodic interference alignment with water-filling. We show that our power allocation algorithm increases the sum rate with a gain of 1.66dB at average transmit SNR of 5dB. For the three user Gaussian interference channel with Rayleigh fading with distribution CN(0, 0.5), we show that our power allocation algorithm improves the sum rate with a gain of 1.5dB at average transmit SNR of 5dB.

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We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.

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We consider a discrete time system with packets arriving randomly at rate lambda per slot to a fading point-to-point link, for which the transmitter can control the number of packets served in a slot by varying the transmit power. We provide an asymptotic characterization of the minimum average delay of the packets, when average transmitter power is a small positive quantity V more than the minimum average power required for queue stability. We show that the minimum average delay will grow either as log (1/V) or 1/V when V down arrow 0, for certain sets of values of lambda. These sets are determined by the distribution of fading gain, the maximum number of packets which can be transmitted in a slot, and the assumed transmit power function, as a function of the fading gain and the number of packets transmitted. We identify a case where the above behaviour of the tradeoff differs from that obtained from a previously considered model, in which the random queue length process is assumed to evolve on the non-negative real line.

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A DC micro-grid essentially consists of power ports, bidirectional power converter and a controller structure that enables the control of dynamic power flow. In this paper, a prototype of a micro-grid structure using a recently proposed multi-winding transformer based power converter has been implemented. The power converter topology is further extended to multiple transformer cores in order to form a growing micro-grid structure. Additionally, modifications have been made in order to incorporate a battery charge controller with the main power circuit. All the other advantages of the power converter and its control scheme are still preserved.

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CrSi and Cr1-x Fe (x) Si particles embedded in a CrSi2 matrix have been prepared by hot pressing from CrSi1.9, CrSi2, and CrSi2.1 powders produced by ball milling using either WC or stainless steel milling media. The samples were characterized by powder X-ray diffraction, scanning, and transmission electron microscopy and electron microprobe analysis. The final crystallite size of CrSi2 obtained from the XRD patterns is about 40 and 80 nm for SS- and WC-milled powders, respectively, whereas the size of the second phase inclusions in the hot pressed samples is about 1-5 mu m. The temperature dependence of the electrical resistivity, Seebeck coefficient, thermal conductivity, and figure of merit (ZT) were analyzed in the temperature range from 300 to 800 K. While the ball-milling process results in a lower electrical resistivity and thermal conductivity due to the presence of the inclusions and the refinement of the matrix microstructure, respectively, the Seebeck coefficient is negatively affected by the formation of the inclusions which leads to a modest improvement of ZT.

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State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

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This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.