Matching Items (108)
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- All Subjects: Electrical Engineering
- Creators: Vittal, Vijay
Description
At present, almost 70% of the electric energy in the United States is produced utilizing fossil fuels. Combustion of fossil fuels contributes CO2 to the atmosphere, potentially exacerbating the impact on global warming. To make the electric power system (EPS) more sustainable for the future, there has been an emphasis on scaling up generation of electric energy from wind and solar resources. These resources are renewable in nature and have pollution free operation. Various states in the US have set up different goals for achieving certain amount of electrical energy to be produced from renewable resources. The Southwestern region of the United States receives significant solar radiation throughout the year. High solar radiation makes concentrated solar power and solar PV the most suitable means of renewable energy production in this region. However, the majority of the projects that are presently being developed are either residential or utility owned solar PV plants. This research explores the impact of significant PV penetration on the steady state voltage profile of the electric power transmission system. This study also identifies the impact of PV penetration on the dynamic response of the transmission system such as rotor angle stability, frequency response and voltage response after a contingency. The light load case of spring 2010 and the peak load case of summer 2018 have been considered for analyzing the impact of PV. If the impact is found to be detrimental to the normal operation of the EPS, mitigation measures have been devised and presented in the thesis. Commercially available software tools/packages such as PSLF, PSS/E, DSA Tools have been used to analyze the power network and validate the results.
ContributorsPrakash, Nitin (Author) / Heydt, Gerald T. (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
Continuous monitoring in the adequate temporal and spatial scale is necessary for a better understanding of environmental variations. But field deployments of molecular biological analysis platforms in that scale are currently hindered because of issues with power, throughput and automation. Currently, such analysis is performed by the collection of large sample volumes from over a wide area and transporting them to laboratory testing facilities, which fail to provide any real-time information. This dissertation evaluates the systems currently utilized for in-situ field analyses and the issues hampering the successful deployment of such bioanalytial instruments for environmental applications. The design and development of high throughput, low power, and autonomous Polymerase Chain Reaction (PCR) instruments, amenable for portable field operations capable of providing quantitative results is presented here as part of this dissertation. A number of novel innovations have been reported here as part of this work in microfluidic design, PCR thermocycler design, optical design and systems integration. Emulsion microfluidics in conjunction with fluorinated oils and Teflon tubing have been used for the fluidic module that reduces cross-contamination eliminating the need for disposable components or constant cleaning. A cylindrical heater has been designed with the tubing wrapped around fixed temperature zones enabling continuous operation. Fluorescence excitation and detection have been achieved by using a light emitting diode (LED) as the excitation source and a photomultiplier tube (PMT) as the detector. Real-time quantitative PCR results were obtained by using multi-channel fluorescence excitation and detection using LED, optical fibers and a 64-channel multi-anode PMT for measuring continuous real-time fluorescence. The instrument was evaluated by comparing the results obtained with those obtained from a commercial instrument and found to be comparable. To further improve the design and enhance its field portability, this dissertation also presents a framework for the instrumentation necessary for a portable digital PCR platform to achieve higher throughputs with lower power. Both systems were designed such that it can easily couple with any upstream platform capable of providing nucleic acid for analysis using standard fluidic connections. Consequently, these instruments can be used not only in environmental applications, but portable diagnostics applications as well.
ContributorsRay, Tathagata (Author) / Youngbull, Cody (Thesis advisor) / Goryll, Michael (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2013
Description
Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can be divided into two parts. The first part of this dissertation focuses on developing a more accurate network model for TEP study. First, a mixed-integer linear programming (MILP) based TEP model is proposed for solving multi-stage TEP problems. Compared with previous work, the proposed approach reduces the number of variables and constraints needed and improves the computational efficiency significantly. Second, the AC power flow model is applied to TEP models. Relaxations and reformulations are proposed to make the AC model based TEP problem solvable. Third, a convexified AC network model is proposed for TEP studies with reactive power and off-nominal bus voltage magnitudes included in the model. A MILP-based loss model and its relaxations are also investigated. The second part of this dissertation investigates the uncertainty modeling issues in the TEP problem. A two-stage stochastic TEP model is proposed and decomposition algorithms based on the L-shaped method and progressive hedging (PH) are developed to solve the stochastic model. Results indicate that the stochastic TEP model can give a more accurate estimation of the annual operating cost as compared to the deterministic TEP model which focuses only on the peak load.
ContributorsZhang, Hui (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Thesis advisor) / Mittelmann, Hans D (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2013
Description
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The fluorescence enhancement by a single Noble metal sphere is separated into excitation/absorption enhancement and the emission quantum yield enhancement. Incorporating the classical model of molecular spontaneous emission into the excitation/absorption transition, the excitation enhancement is calculated rigorously by electrodynamics in the frequency domain. The final formula for the excitation enhancement contains two parts: the primary field enhancement calculated from the Mie theory, and a derating factor due to the backscattering field from the molecule. When compared against a simplified model that only involves the primary Mie theory field calculation, this more rigorous model indicates that the excitation enhancement near the surface of the sphere is quenched severely due to the back-scattering field from the molecule. The degree of quenching depends in part on the bandwidth of the illumination because the presence of the sphere induces a red-shift in the absorption frequency of the molecule and at the same time broadens its spectrum. Monochromatic narrow band illumination at the molecule's original (unperturbed) resonant frequency yields large quenching. For the more realistic broadband illumination scenario, we calculate the final enhancement by integrating over the excitation/absorption spectrum. The numerical results indicate that the resonant illumination scenario overestimates the quenching and therefore would underestimate the total excitation enhancement if the illumination has a broader bandwidth than the molecule. Combining the excitation model with the exact Electrodynamical theory for emission, the complete realistic model demonstrates that there is a potential for significant fluorescence enhancement only for the case of a low quantum yield molecule close to the surface of the sphere. General expressions of the fluorescence enhancement for arbitrarily-shaped metal antennas are derived. The finite difference time domain method is utilized for analyzing these complicated antenna structures. We calculate the total excitation enhancement for the two-sphere dimer. Although the enhancement is greater in this case than for the single sphere, because of the derating effects the total enhancement can never reach the local field enhancement. In general, placing molecules very close to a plasmonic antenna surface yields poor enhancement because the local field is strongly affected by the molecular self-interaction with the metal antenna.
ContributorsZhang, Zhe (Author) / Diaz, Rodolfo E (Thesis advisor) / Lim, Derrick (Thesis advisor) / Pan, George (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the rapid growth of power systems and the concomitant technological advancements, the goal of achieving smart grids is no longer a vision but a foreseeable reality. Hence, the existing grids are undergoing infrastructural modifications to achieve the diverse characteristics of a smart grid. While there are many subjects associated with the operation of smart grids, this dissertation addresses two important aspects of smart grids: increased penetration of renewable resources, and increased reliance on sensor systems to improve reliability and performance of critical power system components. Present renewable portfolio standards are changing both structural and performance characteristics of power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. The present study investigates the impact of increased penetration of PV systems on steady state performance as well as transient stability of a large power system which is a portion of the Western U.S. interconnection. Utility scale and residential rooftop PVs are added to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance. With increased penetration of the renewable energy resources, and with the current loading scenario, more transmission system components such as transformers and circuit breakers are subject to increased stress and overloading. This research work explores the feasibility of increasing system reliability by applying condition monitoring systems to selected circuit breakers and transformers. A very important feature of smart grid technology is that this philosophy decreases maintenance costs by deploying condition monitoring systems that inform the operator of impending failures; or the approach can ameliorate problematic conditions. A method to identify the most critical transformers and circuit breakers with the aid of contingency ranking methods is presented in this study. The work reported in this dissertation parallels an industry sponsored study in which a considerable level of industry input and industry reported concerns are reflected.
ContributorsEftekharnejad, Sara (Author) / Heydt, Gerald (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Si, Jennie (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis presents a new technique to develop an air-conditioner (A/C) compressor single phase induction motor model for use in an electro-magnetic transient program (EMTP) simulation tool. The method developed also has the capability to represent multiple units of the component in a specific three-phase distribution feeder and investigate the phenomenon of fault-induced delayed voltage recovery (FIDVR) and the cause of motor stalling. The system of differential equations representing the single phase induction motor model is developed and formulated. Implicit backward Euler method is applied to numerically integrate the stator currents that are to be drawn from the electric network. The angular position dependency of the rotor shaft is retained in the inductance matrix associated with the model to accurately capture the dynamics of the motor loads. The equivalent circuit of the new model is interfaced with the electric network in the EMTP. The dynamic response of the motor when subjected to faults at different points on voltage waveform has been studied using the EMTP simulator. The mechanism and the impacts of motor stalling need to be explored with multiple units of the detailed model connected to a realistic three-phase distribution system. The model developed can be utilized to assess and improve the product design of compressor motors by air-conditioner manufacturers. Another critical application of the model would be to examine the impacts of asymmetric transmission faults on distribution systems to investigate and develop mitigation measures for the FIDVR problem.
ContributorsLiu, Yuan (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
Description
Today, the electric power system faces new challenges from rapid developing technology and the growing concern about environmental problems. The future of the power system under these new challenges needs to be planned and studied. However, due to the high degree of computational complexity of the optimization problem, conducting a system planning study which takes into account the market structure and environmental constraints on a large-scale power system is computationally taxing. To improve the execution time of large system simulations, such as the system planning study, two possible strategies are proposed in this thesis. The first one is to implement a relative new factorization method, known as the multifrontal method, to speed up the solution of the sparse linear matrix equations within the large system simulations. The performance of the multifrontal method implemented by UMFAPACK is compared with traditional LU factorization on a wide range of power-system matrices. The results show that the multifrontal method is superior to traditional LU factorization on relatively denser matrices found in other specialty areas, but has poor performance on the more sparse matrices that occur in power-system applications. This result suggests that multifrontal methods may not be an effective way to improve execution time for large system simulation and power system engineers should evaluate the performance of the multifrontal method before applying it to their applications. The second strategy is to develop a small dc equivalent of the large-scale network with satisfactory accuracy for the large-scale system simulations. In this thesis, a modified Ward equivalent is generated for a large-scale power system, such as the full Electric Reliability Council of Texas (ERCOT) system. In this equivalent, all the generators in the full model are retained integrally. The accuracy of the modified Ward equivalent is validated and the equivalent is used to conduct the optimal generation investment planning study. By using the dc equivalent, the execution time for optimal generation investment planning is greatly reduced. Different scenarios are modeled to study the impact of fuel prices, environmental constraints and incentives for renewable energy on future investment and retirement in generation.
ContributorsLi, Nan (Author) / Tylavsky, Daniel J (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
Description
A distributed-parameter model is developed for a pressurized water reactor (PWR) in order to analyze the frequency behavior of the nuclear reactor. The model is built based upon the partial differential equations describing heat transfer and fluid flow in the reactor core. As a comparison, a multi-lump reactor core model with five fuel lumps and ten coolant lumps using Mann's model is employed. The derivations of the different transfer functions in both models are also presented with emphasis on the distributed parameter. In order to contrast the two models, Bode plots of the transfer functions are generated using data from the Palo Verde Nuclear Generating Station. Further, a detailed contradistinction between these two models is presented. From the comparison, the features of both models are presented. The distributed parameter model has the ability to offer an accurate transfer function at any location throughout the reactor core. In contrast, the multi-lump parameter model can only provide the average value in a given region (lump). Also, in the distributed parameter model only the feedback according to the specific location under study is incorporated into the transfer function; whereas the transfer functions derived from the multi-lump model contain the average feedback effects happening all over the reactor core.
ContributorsZhang, Taipeng (Author) / Holbert, Keith E. (Thesis advisor) / Vittal, Vijay (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2012
Description
Harsh environments have conditions that make collecting scientific data difficult with existing commercial-off-the-shelf technology. Micro Electro Mechanical Systems (MEMS) technology is ideally suited for harsh environment characterization and operation due to the wide range of materials available and an incredible array of different sensing techniques while providing small device size, low power consumption, and robustness. There were two main objectives of the research conducted. The first objective was to design, fabricate, and test novel sensors that measure the amount of exposure to ionizing radiation for a wide range of applications including characterization of harsh environments. Two types of MEMS ionizing radiation dosimeters were developed. The first sensor was a passive radiation-sensitive capacitor-antenna design. The antenna's emitted frequency of peak-intensity changed as exposure time to radiation increased. The second sensor was a film bulk acoustic-wave resonator, whose resonant frequency decreased with increasing ionizing radiation exposure time. The second objective was to develop MEMS sensor systems that could be deployed to gather scientific data and to use that data to address the following research question: do temperature and/or conductivity predict the appearance of photosynthetic organisms in hot springs. To this end, temperature and electrical conductivity sensor arrays were designed and fabricated based on mature MEMS technology. Electronic circuits and the software interface to the electronics were developed for field data collection. The sensor arrays utilized in the hot springs yielded results that support the hypothesis that temperature plays a key role in determining where the photosynthetic organisms occur. Additionally, a cold-film fluidic flow sensor was developed, which is suitable for near-boiling temperature measurement. Future research should focus on (1) developing a MEMS pH sensor array with integrated temperature, conductivity, and flow sensors to provide multi-dimensional data for scientific study and (2) finding solutions to biofouling and self-calibration, which affects sensor performance over long-term deployment.
ContributorsOiler, Jonathon (Author) / Yu, Hongyu (Thesis advisor) / Anbar, Ariel (Committee member) / Hartnett, Hilairy (Committee member) / Scannapieco, Evan (Committee member) / Timmes, Francis (Committee member) / Arizona State University (Publisher)
Created2013