ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
ABSTRACT
This dissertation introduces a real-time topology monitoring scheme for power systems intended to provide enhanced situational awareness during major system disturbances. The topology monitoring scheme requires accurate real-time topology information to be effective. This scheme is supported by advances in transmission line outage detection based on data-mining phasor measurement unit (PMU) measurements.
A network flow analysis scheme is proposed to track changes in user defined minimal cut sets within the system. This work introduces a new algorithm used to update a previous network flow solution after the loss of a single system branch. The proposed new algorithm provides a significantly decreased solution time that is desired in a real- time environment. This method of topology monitoring can provide system operators with visual indications of potential problems in the system caused by changes in topology.
This work also presents a method of determining all singleton cut sets within a given network topology called the one line remaining (OLR) algorithm. During operation, if a singleton cut set exists, then the system cannot withstand the loss of any one line and still remain connected. The OLR algorithm activates after the loss of a transmission line and determines if any singleton cut sets were created. These cut sets are found using properties of power transfer distribution factors and minimal cut sets.
The topology analysis algorithms proposed in this work are supported by line outage detection using PMU measurements aimed at providing accurate real-time topology information. This process uses a decision tree (DT) based data-mining approach to characterize a lost tie line in simulation. The trained DT is then used to analyze PMU measurements to detect line outages. The trained decision tree was applied to real PMU measurements to detect the loss of a 500 kV line and had no misclassifications.
The work presented has the objective of enhancing situational awareness during significant system disturbances in real time. This dissertation presents all parts of the proposed topology monitoring scheme and justifies and validates the methodology using a real system event.
This dissertation introduces a real-time topology monitoring scheme for power systems intended to provide enhanced situational awareness during major system disturbances. The topology monitoring scheme requires accurate real-time topology information to be effective. This scheme is supported by advances in transmission line outage detection based on data-mining phasor measurement unit (PMU) measurements.
A network flow analysis scheme is proposed to track changes in user defined minimal cut sets within the system. This work introduces a new algorithm used to update a previous network flow solution after the loss of a single system branch. The proposed new algorithm provides a significantly decreased solution time that is desired in a real- time environment. This method of topology monitoring can provide system operators with visual indications of potential problems in the system caused by changes in topology.
This work also presents a method of determining all singleton cut sets within a given network topology called the one line remaining (OLR) algorithm. During operation, if a singleton cut set exists, then the system cannot withstand the loss of any one line and still remain connected. The OLR algorithm activates after the loss of a transmission line and determines if any singleton cut sets were created. These cut sets are found using properties of power transfer distribution factors and minimal cut sets.
The topology analysis algorithms proposed in this work are supported by line outage detection using PMU measurements aimed at providing accurate real-time topology information. This process uses a decision tree (DT) based data-mining approach to characterize a lost tie line in simulation. The trained DT is then used to analyze PMU measurements to detect line outages. The trained decision tree was applied to real PMU measurements to detect the loss of a 500 kV line and had no misclassifications.
The work presented has the objective of enhancing situational awareness during significant system disturbances in real time. This dissertation presents all parts of the proposed topology monitoring scheme and justifies and validates the methodology using a real system event.
ContributorsWerho, Trevor Nelson (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald (Committee member) / Hedman, Kory (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
With the status of nuclear proliferation around the world becoming more and more complex, nuclear forensics methods are needed to restrain the unlawful usage of nuclear devices. Lithium-ion batteries are present ubiquitously in consumer electronic devices nowadays. More importantly, the materials inside the batteries have the potential to be used as neutron detectors, just like the activation foils used in reactor experiments. Therefore, in a nuclear weapon detonation incident, these lithium-ion batteries can serve as sensors that are spatially distributed.
In order to validate the feasibility of such an approach, Monte Carlo N-Particle (MCNP) models are built for various lithium-ion batteries, as well as neutron transport from different fission nuclear weapons. To obtain the precise battery compositions for the MCNP models, a destructive inductively coupled plasma mass spectrometry (ICP-MS) analysis is utilized. The same battery types are irradiated in a series of reactor experiments to validate the MCNP models and the methodology. The MCNP nuclear weapon radiation transport simulations are used to mimic the nuclear detonation incident to study the correlation between the nuclear reactions inside the batteries and the neutron spectra. Subsequently, the irradiated battery activities are used in the SNL-SAND-IV code to reconstruct the neutron spectrum for both the reactor experiments and the weapon detonation simulations.
Based on this study, empirical data show that the lithium-ion batteries have the potential to serve as widely distributed neutron detectors in this simulated environment to (1) calculate the nuclear device yield, (2) differentiate between gun and implosion fission weapons, and (3) reconstruct the neutron spectrum of the device.
In order to validate the feasibility of such an approach, Monte Carlo N-Particle (MCNP) models are built for various lithium-ion batteries, as well as neutron transport from different fission nuclear weapons. To obtain the precise battery compositions for the MCNP models, a destructive inductively coupled plasma mass spectrometry (ICP-MS) analysis is utilized. The same battery types are irradiated in a series of reactor experiments to validate the MCNP models and the methodology. The MCNP nuclear weapon radiation transport simulations are used to mimic the nuclear detonation incident to study the correlation between the nuclear reactions inside the batteries and the neutron spectra. Subsequently, the irradiated battery activities are used in the SNL-SAND-IV code to reconstruct the neutron spectrum for both the reactor experiments and the weapon detonation simulations.
Based on this study, empirical data show that the lithium-ion batteries have the potential to serve as widely distributed neutron detectors in this simulated environment to (1) calculate the nuclear device yield, (2) differentiate between gun and implosion fission weapons, and (3) reconstruct the neutron spectrum of the device.
ContributorsZhang, Taipeng (Author) / Holbert, Keith E. (Thesis advisor) / Karady, George G. (Committee member) / Qin, Jiangchao (Committee member) / Metzger, Robert (Committee member) / Arizona State University (Publisher)
Created2017