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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- Creators: Ayyanar, Raja
Description
There has been a significant growth in the distributed energy resources (DERs) connected to the distribution networks in recent years. For a distribution system with a high penetration of DERs, a detailed modeling and representation of the distribution network is needed to accurately assess its steady-state and dynamic behavior. In this dissertation, a field-validated model for a real sub-transmission and distribution network is developed, including one of the feeders modeled with the secondary network and loads and solar PV units at their household/user location. A procedure is developed combining data from various sources such as the utility database, geoinformation data, and field measurements to create an accurate network model.
Applying a single line to ground fault to the detailed distribution feeder model, a high voltage swell, with potentially detrimental impacts on connected equipment, is shown in one of the non-faulted phases of the feeder. The reason for this voltage swell is analyzed in detail. It is found that with appropriate control the solar PV units on the feeder can reduce the severity of the voltage swell, but not entirely eliminate it.
For integrated studies of the transmission-distribution (T&D) network, a T&D co-simulation framework is developed, which is capable of power flow as well as dynamic simulations, and supports unbalanced modeling and disturbances in the distribution as well as the sub-transmission system. The power flow co-simulation framework is developed as a module that can be run on a cloud-based platform.
Using the developed framework, the T&D system response is studied for balanced and unbalanced faults on the distribution and sub-transmission system. For some faults the resultant loss of generation can potentially lead to the entire feeder tripping due to high unbalance at the substation. However, it is found that advanced inverter controls may improve the response of the distribution feeders to the faults. The dissertation also highlights the importance of modeling the secondary network for both steady-state and dynamic studies. Lastly, a preliminary investigation is conducted to include different dynamic elements such as grid-forming inverters in a T&D network simulation.
ContributorsThakar, Sushrut (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Thesis advisor) / Hedman, Mojdeh (Committee member) / Ramapuram Matavalam, Amarsagar Reddy (Committee member) / Arizona State University (Publisher)
Created2023
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
Wide Bandgap Semiconductor Based Electric Vehicle Charging Systems: Modeling, Magnetics, and Control
Description
Adhering to an ever-increasing demand for innovation in the field of onboard electric vehicle (EV) charging, several technical aspects pertaining to the design and performance enhancement of integrated multi-port charger topologies are discussed in this study. This study also elucidates various research challenges pertaining to each module of the topology and elucidates technically validated solutions for each.Firstly, targeting the input side totempole power factor corrector (TPFC) circuit, a novel digital filter based Active Mitigation Scheme (AMS) is proposed to curb the third harmonic component, along with a novel discretized sampling-based robust control scheme. Experimental verification of these techniques yields an enhanced Total Harmonic Distortion (THD) of 1.68%, enhanced efficiency of 98.1% and resultant power factor of 0.998 (lag).
Further, focusing on the bidirectional CLLC based DC/DC converter topology, a general harmonic approximation (GHA) based secondary side turnoff current minimization technique is discussed. Numerous fabrication and design-based constraints and correlations for parametric modelling of high frequency planar transformer (HFPT) are explained with analytical and 3D Finite Element Analysis (FEA) findings. Further, characterization of the plant transfer function of all-inclusive CLLC model is described along with hybrid Sliding Mode Control (SMC) based control scheme. The steady state experimental results at 1kW rated load show a peak efficiency of 98.49%, while the quantification of dynamic response portray a settling time reduction of 46.4% and an over/undershoot reduction of 33%.
Further, comprehensive modeling of triple active bridge (TAB) DC/DC converter topology is presented with special focus on the control scheme and decoupling capabilities to independently regulate the output bridges. With an objective to reduce the overall losses and to add a dimension of controllability, a three-loop control scheme is proposed with power flow optimization. Inculcating the benefits of multiport and resonant topologies, a comprehensive multi-variable loss optimization study of a Triple Active C^3 L^3 (TAC^3L^3) converter is discussed. The performance of eight different hybrid modulation schemes is compared with respect to the developed global loss minimization objective function. Experimental validations for various loading conditions are presented for a wide-gain bidirectional operation (400V/500-600V/24-28V), portraying a peak converter efficiency of 97.42%.
ContributorsChandwani, Ashwin Vijay (Author) / Mallik, Ayan (Thesis advisor) / Ayyanar, Raja (Thesis advisor) / Kannan, Arunanchala Mada (Committee member) / Hedman, Mojdeh (Committee member) / Arizona State University (Publisher)
Created2022
Description
In recent years, there has been an increasing need for effective voltage controls in power systems due to the growing complexity and dynamic nature of practical power grid operations. Deep reinforcement learning (DRL) techniques now have been widely explored and applied to various electric power operation analyses under different control structures. With massive data available from phasor measurement units (PMU), it is possible to explore the application of DRL to ensure that electricity is delivered reliably.For steady-state power system voltage regulation and control, this study proposed a novel deep reinforcement learning (DRL) based method to provide voltage control that can quickly remedy voltage violations under different operating conditions. Multiple types of devices, adjustable voltage ratio (AVR) and switched shunts, are considered as controlled devices. A modified deep deterministic policy gradient (DDPG) algorithm is applied to accommodate both the continuous and discrete control action spaces of different devices. A case study conducted on the WECC 240-Bus system validates the effectiveness of the proposed method.
System dynamic stability and performance after serious disturbances using DRL are further discussed in this study. A real-time voltage control method is proposed based on DRL, which continuously regulates the excitation system in response to system disturbances. Dynamic performance is considered by incorporating historical voltage data, voltage rate of change, voltage deviation, and regulation amount. A versatile transmission-level power system dynamic training and simulation platform is developed by integrating the simulation software PSS/E and a user-written DRL agent code developed in Python. The platform developed facilitates the training and testing of various power system algorithms and power grids in dynamic simulations with all the modeling capabilities available within PSS/E. The efficacy of the proposed method is evaluated based on the developed platform.
To enhance the controller's resilience in addressing communication failures, a dynamic voltage control method employing the Multi-agent DDPG algorithm is proposed. The algorithm follows the principle of centralized training and decentralized execution. Each agent has independent actor neural networks and critic neural networks. Simulation outcomes underscore the method’s efficacy, showcasing its capability in providing voltage support and handling communication failures among agents.
ContributorsWang, Yuling (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Pal, Anamitra (Committee member) / Hedman, Mojdeh (Committee member) / Arizona State University (Publisher)
Created2024