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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
Description
The computation of the fundamental mode in structural moment frames provides valuable insight into the physical response of the frame to dynamic or time-varying loads. In standard practice, it is not necessary to solve for all n mode shapes in a structural system; it is therefore practical to limit the system to some determined number of r significant mode shapes. Current building codes, such as the American Society of Civil Engineers (ASCE), require certain class of structures to obtain 90% effective mass participation as a way to estimate the accuracy of a solution for base shear motion. A parametric study was performed from the collected data obtained by the analysis of a large number of framed structures. The purpose of this study was the development of rules for the required number of r significant modes to meet the ASCE code requirements. The study was based on the implementation of an algorithm and a computer program developed in the past. The algorithm is based on Householders Transformations, QR Factorization, and Inverse Iteration and it extracts a requested s (s<< n) number of predominate mode shapes and periods. Only the first r (r < s) of these modes are accurate. To verify the accuracy of the algorithm a variety of building frames have been analyzed using the commercially available structural software (RISA 3D) as a benchmark. The salient features of the algorithm are presented briefly in this study.
ContributorsGrantham, Jonathan (Author) / Fafitis, Apostolos (Thesis advisor) / Attard, Thomas (Committee member) / Houston, Sandra (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2014
Description
Access control is necessary for information assurance in many of today's applications such as banking and electronic health record. Access control breaches are critical security problems that can result from unintended and improper implementation of security policies. Security testing can help identify security vulnerabilities early and avoid unexpected expensive cost in handling breaches for security architects and security engineers. The process of security testing which involves creating tests that effectively examine vulnerabilities is a challenging task. Role-Based Access Control (RBAC) has been widely adopted to support fine-grained access control. However, in practice, due to its complexity including role management, role hierarchy with hundreds of roles, and their associated privileges and users, systematically testing RBAC systems is crucial to ensure the security in various domains ranging from cyber-infrastructure to mission-critical applications. In this thesis, we introduce i) a security testing technique for RBAC systems considering the principle of maximum privileges, the structure of the role hierarchy, and a new security test coverage criterion; ii) a MTBDD (Multi-Terminal Binary Decision Diagram) based representation of RBAC security policy including RHMTBDD (Role Hierarchy MTBDD) to efficiently generate effective positive and negative security test cases; and iii) a security testing framework which takes an XACML-based RBAC security policy as an input, parses it into a RHMTBDD representation and then generates positive and negative test cases. We also demonstrate the efficacy of our approach through case studies.
ContributorsGupta, Poonam (Author) / Ahn, Gail-Joon (Thesis advisor) / Collofello, James (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2014
Description
The semiconductor field of Photovoltaics (PV) has experienced tremendous growth, requiring curricula to consider ways to promote student success. One major barrier to success students may face when learning PV is the development of misconceptions. The purpose of this work was to determine the presence and prevalence of misconceptions students may have for three PV semiconductor phenomena; Diffusion, Drift and Excitation. These phenomena are emergent, a class of phenomena that have certain characteristics. In emergent phenomena, the individual entities in the phenomena interact and aggregate to form a self-organizing pattern that can be observed at a higher level. Learners develop a different type of misconception for these phenomena, an emergent misconception. Participants (N=41) completed a written protocol. The pilot study utilized half of these protocols (n = 20) to determine the presence of both general and emergent misconceptions for the three phenomena. Once the presence of both general and emergent misconceptions was confirmed, all protocols (N=41) were analyzed to determine the presence and prevalence of general and emergent misconceptions, and to note any relationships among these misconceptions (full study). Through written protocol analysis of participants' responses, numerous codes emerged from the data for both general and emergent misconceptions. General and emergent misconceptions were found in 80% and 55% of participants' responses, respectively. General misconceptions indicated limited understandings of chemical bonding, electricity and magnetism, energy, and the nature of science. Participants also described the phenomena using teleological, predictable, and causal traits, indicating participants had misconceptions regarding the emergent aspects of the phenomena. For both general and emergent misconceptions, relationships were observed between similar misconceptions within and across the three phenomena, and differences in misconceptions were observed across the phenomena. Overall, the presence and prevalence of both general and emergent misconceptions indicates that learners have limited understandings of the physical and emergent mechanisms for the phenomena. Even though additional work is required, the identification of specific misconceptions can be utilized to enhance semiconductor and PV course content. Specifically, changes can be made to curriculum in order to limit the formation of misconceptions as well as promote conceptual change.
ContributorsNelson, Katherine G (Author) / Brem, Sarah K. (Thesis advisor) / Mckenna, Ann F (Thesis advisor) / Hilpert, Jonathan (Committee member) / Honsberg, Christiana (Committee member) / Husman, Jenefer (Committee member) / Arizona State University (Publisher)
Created2014
Description
Renewable portfolio standards prescribe for penetration of high amounts of re-newable energy sources (RES) that may change the structure of existing power systems. The load growth and changes in power flow caused by RES integration may result in re-quirements of new available transmission capabilities and upgrades of existing transmis-sion paths. Construction difficulties of new transmission lines can become a problem in certain locations. The increase of transmission line thermal ratings by reconductoring using High Temperature Low Sag (HTLS) conductors is a comparatively new technology introduced to transmission expansion. A special design permits HTLS conductors to operate at high temperatures (e.g., 200oC), thereby allowing passage of higher current. The higher temperature capability increases the steady state and emergency thermal ratings of the transmission line. The main disadvantage of HTLS technology is high cost. The high cost may place special emphasis on a thorough analysis of cost to benefit of HTLS technology im-plementation. Increased transmission losses in HTLS conductors due to higher current may be a disadvantage that can reduce the attractiveness of this method. Studies described in this thesis evaluate the expenditures for transmission line re-conductoring using HTLS and the consequent benefits obtained from the potential decrease in operating cost for thermally limited transmission systems. Studies performed consider the load growth and penetration of distributed renewable energy sources according to the renewable portfolio standards for power systems. An evaluation of payback period is suggested to assess the cost to benefit ratio of HTLS upgrades. The thesis also considers the probabilistic nature of transmission upgrades. The well-known Chebyshev inequality is discussed with an application to transmission up-grades. The Chebyshev inequality is proposed to calculate minimum payback period ob-tained from the upgrades of certain transmission lines. The cost to benefit evaluation of HTLS upgrades is performed using a 225 bus equivalent of the 2012 summer peak Arizona portion of the Western Electricity Coordi-nating Council (WECC).
ContributorsTokombayev, Askhat (Author) / Heydt, Gerald T. (Thesis advisor) / Sankar, Lalitha (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2014
Description
A cerebral aneurysm is an abnormal ballooning of the blood vessel wall in the brain that occurs in approximately 6% of the general population. When a cerebral aneurysm ruptures, the subsequent damage is lethal damage in nearly 50% of cases. Over the past decade, endovascular treatment has emerged as an effective treatment option for cerebral aneurysms that is far less invasive than conventional surgical options. Nonetheless, the rate of successful treatment is as low as 50% for certain types of aneurysms. Treatment success has been correlated with favorable post-treatment hemodynamics. However, current understanding of the effects of endovascular treatment parameters on post-treatment hemodynamics is limited. This limitation is due in part to current challenges in in vivo flow measurement techniques. Improved understanding of post-treatment hemodynamics can lead to more effective treatments. However, the effects of treatment on hemodynamics may be patient-specific and thus, accurate tools that can predict hemodynamics on a case by case basis are also required for improving outcomes.Accordingly, the main objectives of this work were 1) to develop computational tools for predicting post-treatment hemodynamics and 2) to build a foundation of understanding on the effects of controllable treatment parameters on cerebral aneurysm hemodynamics. Experimental flow measurement techniques, using particle image velocimetry, were first developed for acquiring flow data in cerebral aneurysm models treated with an endovascular device. The experimental data were then used to guide the development of novel computational tools, which consider the physical properties, design specifications, and deployment mechanics of endovascular devices to simulate post-treatment hemodynamics. The effects of different endovascular treatment parameters on cerebral aneurysm hemodynamics were then characterized under controlled conditions. Lastly, application of the computational tools for interventional planning was demonstrated through the evaluation of two patient cases.
ContributorsBabiker, M. Haithem (Author) / Frakes, David H (Thesis advisor) / Adrian, Ronald (Committee member) / Caplan, Michael (Committee member) / Chong, Brian (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Aluminum alloys and their composites are attractive materials for applications requiring high strength-to-weight ratios and reasonable cost. Many of these applications, such as those in the aerospace industry, undergo fatigue loading. An understanding of the microstructural damage that occurs in these materials is critical in assessing their fatigue resistance. Two distinct experimental studies were performed to further the understanding of fatigue damage mechanisms in aluminum alloys and their composites, specifically fracture and plasticity. Fatigue resistance of metal matrix composites (MMCs) depends on many aspects of composite microstructure. Fatigue crack growth behavior is particularly dependent on the reinforcement characteristics and matrix microstructure. The goal of this work was to obtain a fundamental understanding of fatigue crack growth behavior in SiC particle-reinforced 2080 Al alloy composites. In situ X-ray synchrotron tomography was performed on two samples at low (R=0.1) and at high (R=0.6) R-ratios. The resulting reconstructed images were used to obtain three-dimensional (3D) rendering of the particles and fatigue crack. Behaviors of the particles and crack, as well as their interaction, were analyzed and quantified. Four-dimensional (4D) visual representations were constructed to aid in the overall understanding of damage evolution. During fatigue crack growth in ductile materials, a plastic zone is created in the region surrounding the crack tip. Knowledge of the plastic zone is important for the understanding of fatigue crack formation as well as subsequent growth behavior. The goal of this work was to quantify the 3D size and shape of the plastic zone in 7075 Al alloys. X-ray synchrotron tomography and Laue microdiffraction were used to non-destructively characterize the volume surrounding a fatigue crack tip. The precise 3D crack profile was segmented from the reconstructed tomography data. Depth-resolved Laue patterns were obtained using differential-aperture X-ray structural microscopy (DAXM), from which peak-broadening characteristics were quantified. Plasticity, as determined by the broadening of diffracted peaks, was mapped in 3D. Two-dimensional (2D) maps of plasticity were directly compared to the corresponding tomography slices. A 3D representation of the plastic zone surrounding the fatigue crack was generated by superimposing the mapped plasticity on the 3D crack profile.
ContributorsHruby, Peter (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, the chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor several parameters simultaneously: the intercept, slope(s), and the error standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that the number of observations within a sample has on the performance of the proposed method is investigated. The proposed method was also compared to the T^2 method discussed in Kang and Albin (2000) for multivariate, polynomial, and nonlinear profiles. A simulation study shows that overall the proposed P-value method performs satisfactorily for different profile types.
ContributorsAdibi, Azadeh (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Thesis advisor) / Li, Jing (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solar power generation is the most promising technology to transfer energy consumption reliance from fossil fuel to renewable sources. Concentrated solar power generation is a method to concentrate the sunlight from a bigger area to a smaller area. The collected sunlight is converted more efficiently through two types of technologies: concentrated solar photovoltaics (CSPV) and concentrated solar thermal power (CSTP) generation. In this thesis, these two technologies were evaluated in terms of system construction, performance characteristics, design considerations, cost benefit analysis and their field experience. The two concentrated solar power generation systems were implemented with similar solar concentrators and solar tracking systems but with different energy collecting and conversion components: the CSPV system uses high efficiency multi-junction solar cell modules, while the CSTP system uses a boiler -turbine-generator setup. The performances are calibrated via the experiments and evaluation analysis.
ContributorsJin, Zhilei (Author) / Hui, Yu (Thesis advisor) / Ayyanar, Raja (Committee member) / Rodriguez, Armando (Committee member) / Arizona State University (Publisher)
Created2013