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- Genre: Masters Thesis
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
With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For Twitter data extraction, we developed a multi-threaded application which seamlessly extracts, cleans and stores millions of tweets matching our keywords from Twitter Streaming API. For keyword extraction, we used topics and perspectives which were extracted using n-grams techniques and later approved by our social scientists. After the data is extracted, we aggregate the tweet contents that belong to every user on a weekly basis. Finally, we applied linear and logistic regression using SLEP, an open source sparse learning package to compute weekly score for users and mapping them to one of the 27 organizations on a radical or counter radical scale. Since, we are mapping users to organizations on a weekly basis, we are able to track user's behavior and important new events that triggered shifts among users between organizations. This thesis study can further be extended to identify topics and organization specific influential users and new users from various social media platforms like Facebook, YouTube etc. can easily be mapped to existing organizations on a radical or counter-radical scale.
ContributorsPoornachandran, Sathishkumar (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Woodward, Mark (Committee member) / Arizona State University (Publisher)
Created2013
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
The past few decades have seen a consistent growth of distributed PV sources. Distributed PV, like other DG sources, can be located at or near load centers and provide benefits which traditional generation may lack. However, distribution systems were not designed to accommodate such power generation sources as these sources might lead to operational as well as power quality issues. A high penetration of distributed PV resources may lead to bi-directional power flow resulting in voltage swells, increased losses and overloading of conductors. Voltage unbalance is a concern in distribution systems and the effect of single-phase residential PV systems on voltage unbalance needs to be explored. Furthermore, the islanding of DGs presents a technical hurdle towards the seamless integration of DG sources with the electricity grid. The work done in this thesis explores two important aspects of grid inte-gration of distributed PV generation, namely, the impact on power quality and anti-islanding. A test distribution system, representing a realistic distribution feeder in Arizona is modeled to study both the aforementioned aspects. The im-pact of distributed PV on voltage profile, voltage unbalance and distribution sys-tem primary losses are studied using CYMDIST. Furthermore, a PSCAD model of the inverter with anti-island controls is developed and the efficacy of the anti-islanding techniques is studied. Based on the simulations, generalized conclusions are drawn and the problems/benefits are elucidated.
ContributorsMitra, Parag (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
Data mining is increasing in importance in solving a variety of industry problems. Our initiative involves the estimation of resource requirements by skill set for future projects by mining and analyzing actual resource consumption data from past projects in the semiconductor industry. To achieve this goal we face difficulties like data with relevant consumption information but stored in different format and insufficient data about project attributes to interpret consumption data. Our first goal is to clean the historical data and organize it into meaningful structures for analysis. Once the preprocessing on data is completed, different data mining techniques like clustering is applied to find projects which involve resources of similar skillsets and which involve similar complexities and size. This results in "resource utilization templates" for groups of related projects from a resource consumption perspective. Then project characteristics are identified which generate this diversity in headcounts and skillsets. These characteristics are not currently contained in the data base and are elicited from the managers of historical projects. This represents an opportunity to improve the usefulness of the data collection system for the future. The ultimate goal is to match the product technical features with the resource requirement for projects in the past as a model to forecast resource requirements by skill set for future projects. The forecasting model is developed using linear regression with cross validation of the training data as the past project execution are relatively few in number. Acceptable levels of forecast accuracy are achieved relative to human experts' results and the tool is applied to forecast some future projects' resource demand.
ContributorsBhattacharya, Indrani (Author) / Sen, Arunabha (Thesis advisor) / Kempf, Karl G. (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Rapid technology scaling, the main driver of the power and performance improvements of computing solutions, has also rendered our computing systems extremely susceptible to transient errors called soft errors. Among the arsenal of techniques to protect computation from soft errors, Control Flow Checking (CFC) based techniques have gained a reputation of effective, yet low-cost protection mechanism. The basic idea is that, there is a high probability that a soft-fault in program execution will eventually alter the control flow of the program. Therefore just by making sure that the control flow of the program is correct, significant protection can be achieved. More than a dozen techniques for CFC have been developed over the last several decades, ranging from hardware techniques, software techniques, and hardware-software hybrid techniques as well. Our analysis shows that existing CFC techniques are not only ineffective in protecting from soft errors, but cause additional power and performance overheads. For this analysis, we develop and validate a simulation based experimental setup to accurately and quantitatively estimate the architectural vulnerability of a program execution on a processor micro-architecture. We model the protection achieved by various state-of-the-art CFC techniques in this quantitative vulnerability estimation setup, and find out that software only CFC protection schemes (CFCSS, CFCSS+NA, CEDA) increase system vulnerability by 18% to 21% with 17% to 38% performance overhead. Hybrid CFC protection (CFEDC) increases vulnerability by 5%, while the vulnerability remains almost the same for hardware only CFC protection (CFCET); notwithstanding the hardware overheads of design cost, area, and power incurred in the hardware modifications required for their implementations.
ContributorsRhisheekesan, Abhishek (Author) / Shrivastava, Aviral (Thesis advisor) / Colbourn, Charles Joseph (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
Description
Insulation aging monitoring is widely used to evaluate the operating condition of power equipment. One important monitoring method is detecting partial discharges (PD). PD is a localized breakdown of dielectric and its characteristics can give information about the insulation aging. Most existing test methods cannot identify different kinds of defects. Also, the practical application of PD detection in most existing test methods is restricted by weak PD signals and strong electric field disturbance from surroundings. In order to monitor aging situation in detail, types of PDs are important features to take into account. To classify different types of PDs, pulse sequence analysis (PSA) method is advocated to analyze PDs in the rod-plane model. This method can reflect cumulative effects of PDs, which are always ignored when only measuring PD value. It also shows uniform characteristics when different kinds of detecting system are utilized. Moreover, it does not need calibration. Analysis results from PSA show highly consistent distribution patterns for the same type of PDs and significant differences in the distribution patterns among types of PDs. Furthermore, a new method to detect PD signals using fiber bragg grating (FBG) based PD sensor is studied in this research. By using a piezoelectric ceramic transducer (PZT), small PD signals can be converted to pressure signal and then converted to an optical wavelength signal with FBG. The optical signal is isolated from the electric field; therefore its attenuation and anti-jamming performance will be better than traditional methods. Two sensors, one with resonant frequency of 42.7 kHz and the other 300 kHz, were used to explore the performance of this testing system. However, there were issues with the sensitivity of the sensors of these devices and the results have been communicated with the company. These devices could not give the results at the same level of accuracy as the conventional methods.
ContributorsCui, Longfei (Author) / Gorur, Ravi (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document.
ContributorsMurugesan, Veerakumar (Author) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013