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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- All Subjects: Optimization
- Creators: Ayyanar, Raja
Description
As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D; infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today unit commitment models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that uses a large penetration of variable renewable resources. A stochastic mixed integer linear program for day-ahead unit commitment is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational complexities, a Benders' decomposition approach is utilized. The commitment schedule was validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution. For this test case, there were few deviations to power imports, 0.007% of solar was curtailed, no load shedding occurred in the main-grid, and 1.70% load shedding occurred in the microgrid.
ContributorsHytowitz, Robin Broder (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
Substation ground system insures safety of personnel, which deserves considerable attentions. Basic substation safety requirement quantities include ground grid resistance, mesh touch potential and step potential, moreover, optimal design of a substation ground system should include both safety concerns and ground grid construction cost. In the purpose of optimal designing the ground grid in the accurate and efficient way, an application package coded in MATLAB is developed and its core algorithm and main features are introduced in this work.
To ensure accuracy and personnel safety, a two-layer soil model is applied instead of the uniform soil model in this research. Some soil model parameters are needed for the two-layer soil model, namely upper-layer resistivity, lower-layer resistivity and upper-layer thickness. Since the ground grid safety requirement is considered under the earth fault, the value of fault current and fault duration time are also needed.
After all these parameters are obtained, a Resistance Matrix method is applied to calculate the mutual and self resistance between conductor segments on both the horizontal and vertical direction. By using a matrix equation of the relationship of mutual and self resistance and unit current of the conductor segments, the ground grid rise can be calculated. Green's functions are applied to calculate the earth potential at a certain point produced by horizontal or vertical line of current. Furthermore, the three basic ground grid safety requirement quantities: the mesh touch potential in the worst case point can be obtained from the earth potential and ground grid rise; the step potential can be obtained from two points' earth potential difference; the grid resistance can be obtained from ground grid rise and fault current.
Finally, in order to achieve ground grid optimization problem more accurate and efficient, which includes the number of meshes in the horizontal grid and the number of vertical rods, a novel two-step hybrid genetic algorithm-pattern search (GA-PS) optimization method is developed. The Genetic Algorithm (GA) is used first to search for an approximate starting point, which is used by the Pattern Search (PS) algorithm to find the final optimal result. This developed application provides an optimal grid design meeting all safety constraints. In the cause of the accuracy of the application, the touch potential, step potential, ground potential rise and grid resistance are compared with these produced by the industry standard application WinIGS and some theoretical ground grid model.
In summary, the developed application can solve the ground grid optimization problem with the accurate ground grid modeling method and a hybrid two-step optimization method.
To ensure accuracy and personnel safety, a two-layer soil model is applied instead of the uniform soil model in this research. Some soil model parameters are needed for the two-layer soil model, namely upper-layer resistivity, lower-layer resistivity and upper-layer thickness. Since the ground grid safety requirement is considered under the earth fault, the value of fault current and fault duration time are also needed.
After all these parameters are obtained, a Resistance Matrix method is applied to calculate the mutual and self resistance between conductor segments on both the horizontal and vertical direction. By using a matrix equation of the relationship of mutual and self resistance and unit current of the conductor segments, the ground grid rise can be calculated. Green's functions are applied to calculate the earth potential at a certain point produced by horizontal or vertical line of current. Furthermore, the three basic ground grid safety requirement quantities: the mesh touch potential in the worst case point can be obtained from the earth potential and ground grid rise; the step potential can be obtained from two points' earth potential difference; the grid resistance can be obtained from ground grid rise and fault current.
Finally, in order to achieve ground grid optimization problem more accurate and efficient, which includes the number of meshes in the horizontal grid and the number of vertical rods, a novel two-step hybrid genetic algorithm-pattern search (GA-PS) optimization method is developed. The Genetic Algorithm (GA) is used first to search for an approximate starting point, which is used by the Pattern Search (PS) algorithm to find the final optimal result. This developed application provides an optimal grid design meeting all safety constraints. In the cause of the accuracy of the application, the touch potential, step potential, ground potential rise and grid resistance are compared with these produced by the industry standard application WinIGS and some theoretical ground grid model.
In summary, the developed application can solve the ground grid optimization problem with the accurate ground grid modeling method and a hybrid two-step optimization method.
ContributorsZhang, Qianzhi (Author) / Tylavsky, Daniel (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
The high R/X ratio of typical distribution systems makes the system voltage vulnerable to active power injection from the distributed energy resources (DERs). Moreover, the intermittent and uncertain nature of the DER generation brings new challenges to voltage management. As guided by the previous IEEE standard 1547-2003, most of the existing photovoltaic (PV) systems in the real distribution networks are equipped with conventional inverters, which only allow the PV systems to operate at unity power factor to generate active power. To utilize the voltage control capability of the existing PV systems following the guideline of the revised IEEE standard 1547-2018, this dissertation proposes a two-stage stochastic optimization strategy aimed at optimally placing the PV smart inverters with Volt-VAr capability among the existing PV systems for distribution systems with high PV penetration to mitigate voltage violations. PV smart inverters are fast-response devices compared to conventional voltage control devices in the distribution system. Historically, distribution system planning and operation studies are mainly based on quasi-static simulation, which ignores system dynamic transitions between static solutions. However, as high-penetration PV systems are present in the distribution system, the fast transients of the PV smart inverters cannot be ignored. A detailed dynamic model of the PV smart inverter with Volt-VAr control capability is developed as a dynamic link library (DLL) in OpenDSS to validate the system voltage stability with autonomous control of the optimally placed PV smart inverters. Static and dynamic verification is conducted on an actual 12.47 kV, 9 km-long Arizona utility feeder that serves residential customers. To achieve fast simulation and accommodate more complex PV models with desired accuracy and efficiency, an integrative dynamic simulation framework for OpenDSS with adaptive step size control is proposed. Based on the original fixed-step size simulation framework in OpenDSS, the proposed framework adds a function in the OpenDSS main program to adjust its step size to meet the minimum step size requirement from all the PV inverters in the system. Simulations are conducted using both the original and the proposed framework to validate the proposed simulation framework.
ContributorsChen, Mengxi (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Thesis advisor) / Hedman, Mojdeh (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2023