14 resultados para electric system
em Digital Commons at Florida International University
Resumo:
Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.
Resumo:
Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^
Resumo:
A high frequency physical phase variable electric machine model was developed using FE analysis. The model was implemented in a machine drive environment with hardware-in-the-loop. The novelty of the proposed model is that it is derived based on the actual geometrical and other physical information of the motor, considering each individual turn in the winding. This is the first attempt to develop such a model to obtain high frequency machine parameters without resorting to expensive experimental procedures currently in use. The model was used in a dynamic simulation environment to predict inverter-motor interaction. This includes motor terminal overvoltage, current spikes, as well as switching effects. In addition, a complete drive model was developed for electromagnetic interference (EMI) analysis and evaluation. This consists of the lumped parameter models of different system components, such as cable, inverter, and motor. The lumped parameter models enable faster simulations. The results obtained were verified by experimental measurements and excellent agreements were obtained. A change in the winding arrangement and its influence on the motor high frequency behavior has also been investigated. This was shown to have a little effect on the parameter values and in the motor high frequency behavior for equal number of turns. An accurate prediction of overvoltage and EMI in the design stages of the drive system would reduce the time required for the design modifications as well as for the evaluation of EMC compliance issues. The model can be utilized in the design optimization and insulation selection for motors. Use of this procedure could prove economical, as it would help designers develop and test new motor designs for the evaluation of operational impacts in various motor drive applications.
Resumo:
Weakly electric fish produce a dual function electric signal that makes them ideal models for the study of sensory computation and signal evolution. This signal, the electric organ discharge (EOD), is used for communication and navigation. In some families of gymnotiform electric fish, the EOD is a dynamic signal that increases in amplitude during social interactions. Amplitude increase could facilitate communication by increasing the likelihood of being sensed by others or by impressing prospective mates or rivals. Conversely, by increasing its signal amplitude a fish might increase its sensitivity to objects by lowering its electrolocation detection threshold. To determine how EOD modulations elicited in the social context affect electrolocation, I developed an automated and fast method for measuring electroreception thresholds using a classical conditioning paradigm. This method employs a moving shelter tube, which these fish occupy at rest during the day, paired with an electrical stimulus. A custom built and programmed robotic system presents the electrical stimulus to the fish, slides the shelter tube requiring them to follow, and records video of their movements. I trained the electric fish of the genus Sternopygus was trained to respond to a resistive stimulus on this apparatus in 2 days. The motion detection algorithm correctly identifies the responses 91% of the time, with a false positive rate of only 4%. This system allows for a large number of trials, decreasing the amount of time needed to determine behavioral electroreception thresholds. This novel method enables the evaluation the evolutionary interplay between two conflicting sensory forces, social communication and navigation.
Resumo:
The South American electric knifefish, Brachyhypopomus gauderio, uses weakly electric fields to see and communicate in the dark. Only one study to date has investigated natural behavior in this species during the breeding season; this study proposed that B. guarerio has an exploded lek polygyny breeding system. To test this hypothesis, artificial marshes simulating the native vegetation, temperature, and water conductivities of the South American subtropics were created to study seasonal variation in associative behavior of B. gauderio during the breeding and non-breeding seasons. Mark/recapture methods were used to keep track of individual fish and their dispersion inside the experimental designs. The experimental design proved to be extremely successful at eliciting reproduction. Differences were found in seasonal variations of social behaviors between adult and juvenile populations. Although no apparent sex. differences in movement patterns were found during the breeding season; a trend for male-male aversion was found, suggesting male-male avoidance as a possible strategy guiding aspects of social behaviors in this species. Further, movement may be a tactic for mate seeking as the individuals who moved the most during the breeding season obtained the most opposite sex interactions. These findings support the exploded lek polygyny model. Social interactions are subject to complex regulation by social, physiologic and ecological factors; the extent to which these associations are repeatable may provide novel insights on the evolution of sociality as it has been shaped by natural selection.
Resumo:
Taken together, the six nations of Central America count a population of roughly 40 million people and an energy market equal in size to that of Colombia, sufficient to benefit from economies of scale. The region has traditionally been a net importer of hydrocarbons, and hydroelectricity has dominated electric generation. But more recently, thermoelectric generation (diesel and fuel oil) has greatly increased as a percentage of the regional generation market. Progress has been made across the region’s electric sector, beginning with reforms in the 1990s and the 1996 signing of a regional treaty aimed at the development of a regional energy integration project – the Central American Electrical Interconnection System, or SIEPAC. A fundamental SIEPAC goal is to set up a regional electric market and a regulatory system. Indeed, after many years of development, SIEPAC is poised to open a new chapter in Central America’s electric infrastructure and market. But this new era must contend with critical issues such as the need to consolidate the regional electric market, political issues surrounding the venture, and security concerns. Moreover, local conflicts, in different degrees, have become priorities for policymakers, and these are possible barriers to completing the project. The goals of the SIEPAC project and of deepening the broader electric integration process are possible if national and regional decision makers understand that cooperative decision making will produce better results than separate national decision making. Enhanced regional understanding and cooperative decision making, combined with an effort to reorient the terminology and dialogue vis-à-vis energy efficiency in Central America, form the core recommendations of this paper.
Resumo:
Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.
Resumo:
Sexually-selected communication signals can be used by competing males to settle contests without incurring the costs of fighting. The ability to dynamically regulate the signal in a context-dependent manner can further minimize the costs of male aggressive interactions. Such is the case in the gymnotiform fish Brachyhypopomus gauderio, which, by coupling its electric organ discharge (EOD) waveform to endocrine systems with circadian, seasonal, and behavioral drivers, can regulate its signal to derive the greatest reproductive benefit. My dissertation research examined the functional role of the EOD plasticity observed in male B. gauderio and the physiological mechanisms that regulate the enhanced male EOD. To evaluate whether social competition drives the EOD changes observed during male-male interactions, I manipulated the number of males in breeding groups to create conditions that exemplified low and high competition and measured their EOD and steroid hormone levels. My results showed that social competition drives the enhancement of the EOD amplitude of male B. gauderio. In addition, changes in the EOD of males due to changes in their social environment were paralleled by changes in the levels of androgens and cortisol. I also examined the relationship between body size asymmetry, EOD waveform parameters, and aggressive physical behaviors during male-male interactions in B. gauderio, in order to understand more fully the role of EOD waveforms as reliable signals. While body size was the best determinant of dominance in male B. gauderio, EOD amplitude reliably predicted body condition, a composite of length and weight, for fish in good body condition. To further characterize the mechanisms underlying the relationship between male-male interactions and EOD plasticity, I identified the expression of the serotonin receptor 1A, a key player in the regulation of aggressive behavior, in the brains of B. gauderio. I also identified putative regulatory regions in this receptor in B. gauderio and other teleost fish, highlighting the presence of additional plasticity. In conclusion, male-male competition seems to be a strong selective driver in the evolution of the male EOD plasticity in B. gauderio via the regulatory control of steroid hormones and the serotonergic system.
Resumo:
This paper for the first time discusses a computational study of using magneto-electric (ME) nanoparticles to artificially stimulate the neural activity deep in the brain. The new technology provides a unique way to couple electric signals in the neural network to the magnetic dipoles in the nanoparticles with the purpose to enable a non-invasive approach. Simulations of the effect of ME nanoparticles for non-invasively stimulating the brain of a patient with Parkinson’s Disease to bring the pulsed sequences of the electric field to the levels comparable to those of healthy people show that the optimized values for the concentration of the 20-nm nanoparticles (with the magneto-electric (ME) coefficient of 100 V cm21 Oe21 in the aqueous solution) is 36106 particles/cc, and the frequency of the externally applied 300-Oe magnetic field is 80 Hz.
Resumo:
Simulations suggest that photomixing in resonant laser-assisted field emission could be used to generate and detect signals from DC to 100 THz. It is the objective of this research to develop a system to efficiently couple the microwave signals generated on an emitting tip by optical mixing. Four different methods for coupling are studied. Tapered Goubau line is found to be the most suitable. Goubau line theory is reviewed, and programs are written to determine loss on the line. From this, Goubau tapers are designed that have a 1:100 bandwidth. These tapers are finally simulated using finite difference time domain, to find the optimum design parameters. Tapered Goubau line is an effective method for coupling power from the field emitting tip. It has large bandwidth, and acceptable loss. Another important consideration is that it is the easiest to manufacture of the four possibilities studied, an important quality for any prototype.
Resumo:
Sexually-selected communication signals can be used by competing males to settle contests without incurring the costs of fighting. The ability to dynamically regulate the signal in a context-dependent manner can further minimize the costs of male aggressive interactions. Such is the case in the gymnotiform fish Brachyhypopomus gauderio, which, by coupling its electric organ discharge (EOD) waveform to endocrine systems with circadian, seasonal, and behavioral drivers, can regulate its signal to derive the greatest reproductive benefit. My dissertation research examined the functional role of the EOD plasticity observed in male B. gauderio and the physiological mechanisms that regulate the enhanced male EOD. To evaluate whether social competition drives the EOD changes observed during male-male interactions, I manipulated the number of males in breeding groups to create conditions that exemplified low and high competition and measured their EOD and steroid hormone levels. My results showed that social competition drives the enhancement of the EOD amplitude of male B. gauderio. In addition, changes in the EOD of males due to changes in their social environment were paralleled by changes in the levels of androgens and cortisol. I also examined the relationship between body size asymmetry, EOD waveform parameters, and aggressive physical behaviors during male-male interactions in B. gauderio, in order to understand more fully the role of EOD waveforms as reliable signals. While body size was the best determinant of dominance in male B. gauderio, EOD amplitude reliably predicted body condition, a composite of length and weight, for fish in good body condition. To further characterize the mechanisms underlying the relationship between male-male interactions and EOD plasticity, I identified the expression of the serotonin receptor 1A, a key player in the regulation of aggressive behavior, in the brains of B. gauderio. I also identified putative regulatory regions in this receptor in B. gauderio and other teleost fish, highlighting the presence of additional plasticity. In conclusion, male-male competition seems to be a strong selective driver in the evolution of the male EOD plasticity in B. gauderio via the regulatory control of steroid hormones and the serotonergic system.
Resumo:
Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.
Resumo:
This thesis presents a system for visually analyzing the electromagnetic fields of the electrical machines in the energy conversion laboratory. The system basically utilizes the finite element method to achieve a real-time effect in the analysis of electrical machines during hands-on experimentation. The system developed is a tool to support the student's understanding of the electromagnetic field by calculating performance measures and operational concepts pertaining to the practical study of electrical machines. Energy conversion courses are fundamental in electrical engineering. The laboratory is conducted oriented to facilitate the practical application of the theory presented in class, enabling the student to use electromagnetic field solutions obtained numerically to calculate performance measures and operating characteristics. Laboratory experiments are utilized to help the students understand the electromagnetic concepts by the use of this visual and interactive analysis system. In this system, this understanding is accomplished while hands-on experimentation takes place in real-time.
Resumo:
Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.