883 resultados para Exceeding electrical energy


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The present paper offers a methodological approach towards the estimation and definition of enthalpies constituting an energy balance around a fast pyrolysis experiment conducted in a laboratory scale fluid bed with a capacity of 1 kg/ h. Pure N2 was used as fluidization medium at atmospheric pressure and the operating temperature (∼500°C) was adjusted with electrical resistors. The biomass feedstock type that was used was beech wood. An effort was made to achieve a satisfying 92.5% retrieval of products (dry basis mass balance) with the differences mainly attributed to loss of some bio-oil constituents into the quenching medium, ISOPAR™. The chemical enthalpy recovery for bio-oil, char and permanent gases is calculated 64.6%, 14.5% and 7.1%, respectively. All the energy losses from the experimental unit into the environment, namely the pyrolyser, cooling unit etc. are discussed and compared to the heat of fast pyrolysis that was calculated at 1123.5 kJ per kg of beech wood. This only represents 2.4% of the biomass total enthalpy or 6.5% its HHV basis. For the estimation of some important thermo-physical properties such as heat capacity and density, it was found that using data based on the identified compounds from the GC/MS analysis is very close to the reference values despite the small fraction of the bio-oil components detected. The methodology and results can help as a starting point for the proper design of fast pyrolysis experiments, pilot and/or industrial scale plants.

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Extensive numerical investigations are undertaken to analyze and compare, for the first time, the performance, techno-economy, and power consumption of three-level electrical Duobinary, optical Duobinary, and PAM-4 modulation formats as candidates for high-speed next-generation PONs supporting downstream 40 Gb/s per wavelength signal transmission over standard SMFs in C-band. Optimization of transceiver bandwidths are undertaken to show the feasibility of utilizing low-cost and band-limited components to support next-generation PON transmissions. The effect of electro-absorption modulator chirp is examined for electrical Duobinary and PAM-4. Electrical Duobinary and optical Duobinary are powerefficient schemes for smaller transmission distances of 10 km SMFs and optical Duobinary offers the best receiver sensitivity albeit with a relatively high transceiver cost. PAM-4 shows the best power budget and costefficiency for larger distances of around 20 km, although it consumes more power. Electrical Duobinary shows the best trade-off between performance, cost and power dissipation.

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This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

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High efficiency of power converters placed between renewable energy sources and the utility grid is required to maximize the utilization of these sources. Power quality is another aspect that requires large passive elements (inductors, capacitors) to be placed between these sources and the grid. The main objective is to develop higher-level high frequency-based power converter system (HFPCS) that optimizes the use of hybrid renewable power injected into the power grid. The HFPCS provides high efficiency, reduced size of passive components, higher levels of power density realization, lower harmonic distortion, higher reliability, and lower cost. The dynamic modeling for each part in this system is developed, simulated and tested. The steady-state performance of the grid-connected hybrid power system with battery storage is analyzed. Various types of simulations were performed and a number of algorithms were developed and tested to verify the effectiveness of the power conversion topologies. A modified hysteresis-control strategy for the rectifier and the battery charging/discharging system was developed and implemented. A voltage oriented control (VOC) scheme was developed to control the energy injected into the grid. The developed HFPCS was compared experimentally with other currently available power converters. The developed HFPCS was employed inside a microgrid system infrastructure, connecting it to the power grid to verify its power transfer capabilities and grid connectivity. Grid connectivity tests verified these power transfer capabilities of the developed converter in addition to its ability of serving the load in a shared manner. In order to investigate the performance of the developed system, an experimental setup for the HF-based hybrid generation system was constructed. We designed a board containing a digital signal processor chip on which the developed control system was embedded. The board was fabricated and experimentally tested. The system's high precision requirements were verified. Each component of the system was built and tested separately, and then the whole system was connected and tested. The simulation and experimental results confirm the effectiveness of the developed converter system for grid-connected hybrid renewable energy systems as well as for hybrid electric vehicles and other industrial applications.

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Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

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Recently, energy efficiency or green IT has become a hot issue for many IT infrastructures as they attempt to utilize energy-efficient strategies in their enterprise IT systems in order to minimize operational costs. Networking devices are shared resources connecting important IT infrastructures, especially in a data center network they are always operated 24/7 which consume a huge amount of energy, and it has been obviously shown that this energy consumption is largely independent of the traffic through the devices. As a result, power consumption in networking devices is becoming more and more a critical problem, which is of interest for both research community and general public. Multicast benefits group communications in saving link bandwidth and improving application throughput, both of which are important for green data center. In this paper, we study the deployment strategy of multicast switches in hybrid mode in energy-aware data center network: a case of famous fat-tree topology. The objective is to find the best location to deploy multicast switch not only to achieve optimal bandwidth utilization but also to minimize power consumption. We show that it is possible to easily achieve nearly 50% of energy consumption after applying our proposed algorithm.

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We describe a low-energy glow-discharge process using reactive ion etching system that enables non-circular device patterns, such as squares or hexagons, to be formed from a precursor array of uniform circular openings in polymethyl methacrylate, PMMA, defined by electron beam lithography. This technique is of a particular interest for bit-patterned magnetic recording medium fabrication, where close packed square magnetic bits may improve its recording performance. The process and results of generating close packed square patterns by self-limiting low-energy glow-discharge are investigated. Dense magnetic arrays formed by electrochemical deposition of nickel over self-limiting formed molds are demonstrated.

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The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. ^ To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. ^ Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.^ Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures. ^

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This dissertation studies the manipulation of particles using acoustic stimulation for applications in microfluidics and templating of devices. The term particle is used here to denote any solid, liquid or gaseous material that has properties, which are distinct from the fluid in which it is suspended. Manipulation means to take over the movements of the particles and to position them in specified locations. Using devices, microfabricated out of silicon, the behavior of particles under the acoustic stimulation was studied with the main purpose of aligning the particles at either low-pressure zones, known as the nodes or high-pressure zones, known as anti-nodes. By aligning particles at the nodes in a flow system, these particles can be focused at the center or walls of a microchannel in order to ultimately separate them. These separations are of high scientific importance, especially in the biomedical domain, since acoustopheresis provides a unique approach to separate based on density and compressibility, unparalleled by other techniques. The study of controlling and aligning the particles in various geometries and configurations was successfully achieved by controlling the acoustic waves. Apart from their use in flow systems, a stationary suspended-particle device was developed to provide controllable light transmittance based on acoustic stimuli. Using a glass compartment and a carbon-particle suspension in an organic solvent, the device responded to acoustic stimulation by aligning the particles. The alignment of light-absorbing carbon particles afforded an increase in visible light transmittance as high as 84.5%, and it was controlled by adjusting the frequency and amplitude of the acoustic wave. The device also demonstrated alignment memory rendering it energy-efficient. A similar device for suspended-particles in a monomer enabled the development of electrically conductive films. These films were based on networks of conductive particles. Elastomers doped with conductive metal particles were rendered surface conductive at particle loadings as low as 1% by weight using acoustic focusing. The resulting films were flexible and had transparencies exceeding 80% in the visible spectrum (400-800 nm) These films had electrical bulk conductivities exceeding 50 S/cm.

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Con la presente tesi viene esaminato un metodo per modificare la frequenza di risonanza di trasduttori piezoelettrici mediante applicazione di carichi elettrici esterni. L'elaborato inizia con la presentazione dei cristalli utilizzati nel lavoro di tesi, concentrandosi sul processo di fabbricazione di un bimorph cantilever impiegato come convertitore elettromeccanico di energia, la cui frequenza di risonanza è modellizzata analiticamente mediante la legge di Newton e il modello di Euler-Bernoulli. Su tale struttura vengono condotte misure mediante shaker elettrodinamico e analizzatore d'impedenza, ai fini di giusticare il modello analitico presentato. Con lo scopo di sincronizzare la frequenza di risonanza del cantilever con la vibrazione dell'ambiente per massimizzare la potenza disponibile, viene proposto un algoritmo MPPT secondo l'approccio Perturba e Osserva (P&O), al quale è fornita in ingresso la tensione efficace di un layer di materiale piezoelettrico. Valutare la sua risposta in tensione, presenta dei limiti applicativi che hanno portato a prendere in considerazione un approccio totalmente diff�erente, basato sullo sfasamento tra la tensione di un trasduttore piezoelettrico e il segnale di accelerazione impiegato come eccitazione. Misure sperimentali sono state condotte con l'obiettivo di validare l'efficacia di quest'ultimo approccio qualora si voglia sincronizzare la frequenza di risonanza dei piezo con segnali di vibrazione reali.

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Recently thermo-electrical nanoantennas, also known as Seebeck nanoantennas, have been proposed as an alternative for solar energy harvesting applications. In this work we present the optical and thermal analysis of metallic nanoantennas operating at infrared wavelengths, this study is performed by numerical simulations using COMSOL Multiphysics. Several different nanoantenna designs were analyzed including dipoles, bowties and square spiral antennas. Results show that metallic nanoantennas can be tuned to absorb electromagnetic energy at infrared wavelengths, and that numerical simulation can be useful in optimizing the performance of these types of nanoantennas at optical and infrared wavelengths.

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While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

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This paper analyzes the impact of transceiver impairments on outage probability (OP) and throughput of decode-and-forward two-way cognitive relay (TWCR) networks, where the relay is self-powered by harvesting energy from the transmitted signals. We consider two bidirectional relaying protocols namely, multiple access broadcast (MABC) protocol and time division broadcast (TDBC) protocol, as well as, two power transfer policies namely, dual-source (DS) energy transfer and single-fixed-source (SFS) energy transfer. Closed-form expressions for OP and throughput of the network are derived in the context of delay-limited transmission. Numerical results corroborate our analysis, thereby we can quantify the degradation of OP and throughput of TWCR networks due to transceiver hardware impairments. Under the specific parameters, our results indicate that the MABC protocol achieves asymptotically a higher throughput by 0.65 [bits/s/Hz] than the TDBC protocol, while the DS energy transfer scheme offers better performance than the SFS policy for both relaying protocols.

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Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

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This paper studies the energy efficiency (EE) of a point-to-point rank-1 Ricean fading multiple-input-multiple-output (MIMO) channel. In particular, a tight lower bound and an asymptotic approximation for the EE of the considered MIMO system are presented, under the assumption that the channel is unknown at the transmitter and perfectly known at the receiver. Moreover, the effects of different system parameters, namely, transmit power, spectral efficiency (SE), and number of transmit and receive antennas, on the EE are analytically investigated. An important observation is that, in the high signal-to-noise ratio regime and with the other system parameters fixed, the optimal transmit power that maximizes the EE increases as the Ricean-K factor increases. On the contrary, the optimal SE and the optimal number of transmit antennas decrease as K increases.