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: Vittal, Vijay
Description
The fast growth of the power system industry and the increase in the usage of computerized management systems introduces more complexities to power systems operations. Although these computerized management systems help system operators manage power systems reliably and efficiently, they introduce the threat of cyber-attacks. In this regard, this dissertation focuses on the load-redistribution (LR) attacks, which cause overflows in power systems. Previous researchers have shown the possibility of launching undetectable LR attacks against power systems, even when protection schemes exist. This fact pushes researchers to develop detection mechanisms. In this thesis, real-time detection mechanisms are developed based on the fundamental knowledge of power systems, operation research, and machine learning. First, power systems domain insight is used to identify an underlying exploitable structure for the core problem of LR attacks. Secondly, a greedy algorithm’s ability to solve the identified structure to optimality is proved, which helps operators quickly find the best attack vector and the most sensitive buses for each target transmission asset. Then, two quantitative security indices are proposed and leveraged to develop a measurement threat analysis (MTA) tool. Finally, a machine learning-based classifier is used to enhance the MTA tool’s functionality in flagging tiny LR attacks and distinguishing them from measurement/forecasting errors. On the other hand, after acknowledging that an adversarial LR attack interferes with the system, establishing a corrective action is imperative to mitigate or remove the potential consequences of the attack. This dissertation proposes two corrective actions; the first one is developed based on the worst-case attack scenario, considering the information provided by the MTA tool. After The MTA tool flags an LR attack in the system, it should determine the primary target and other affected transmission assets, using which the operator can estimate the actual loads in the post-attack stage. This estimation is essential since the corresponding security constraints in the first corrective action model are modeled based on these loads. The second one is a robust optimization that considers various load scenarios. The functionality of this robust model does not depend on the information provided by the MTA tool and is more reliable.
ContributorsKaviani, Ramin (Author) / Hedman, Kory (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Mojdeh (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2022
Description
In recent years, with the increasing penetration of solar generation, the uncertainty and variability of the power system generation also have increased. Power systems always require a balance between generation and load. The generation of the conventional generators must be scheduled to meet the total net load of the system with the variability and uncertainty of the solar resources integrated. The ability to match generation to load requires certain flexibility of the conventional generation units as well as a flexible transmission network to deliver the power. In this work, given the generation flexibility primarily reflected in the ramping rates, as well as the minimum and maximum output of the generation units, the transmission network flexibility is assessed using the metric developed in this work.
The main topic of this thesis is the examination of the transmission system flexibility using time series power flows (TSPFs). First, a TSPFs program is developed considering the economic dispatch of all the generating stations, as well as the available ramping rate of each generating unit. The time series power flow spans a period of 24 hours with 5-minute time interval and hence includes 288 power flow snapshots. Every power flow snapshot is created based on the power system topology and the previous system state. These power flow snapshots are referred to as the base case power flow below.
Sensitivity analysis is then conducted by using the TSPFs program as a primary tool, by fixing all but one of the system changes which include: solar penetration, wires to wires interconnection, expected retirements of coal units and expected participation in the energy
imbalance market. The impact of each individual change can be evaluated by the metric developed in the following chapters.
The main topic of this thesis is the examination of the transmission system flexibility using time series power flows (TSPFs). First, a TSPFs program is developed considering the economic dispatch of all the generating stations, as well as the available ramping rate of each generating unit. The time series power flow spans a period of 24 hours with 5-minute time interval and hence includes 288 power flow snapshots. Every power flow snapshot is created based on the power system topology and the previous system state. These power flow snapshots are referred to as the base case power flow below.
Sensitivity analysis is then conducted by using the TSPFs program as a primary tool, by fixing all but one of the system changes which include: solar penetration, wires to wires interconnection, expected retirements of coal units and expected participation in the energy
imbalance market. The impact of each individual change can be evaluated by the metric developed in the following chapters.
ContributorsChen, Mengxi (Author) / Vittal, Vijay (Thesis advisor) / Hedman, Mojdeh Khorsand (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2019
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
Description
Due to the new and old challenges, modern-day market management systems continue to evolve, including market reformulations, introducing new market products, and proposing new frameworks for integrating distributed energy resources (DERs) into the wholesale markets. Overall, questions is regarding how to reflect these essential changes in the market models (design, reformulation, and coordination frameworks), design market-based incentive structures to adequately compensate participants for providing ancillary services, and assess these impacts on market settlements.First, this dissertation proposes the concept of securitized-LMP to solve the issue of how market participants should be compensated for providing N-1 reliability services. Then, pricing implications and settlements of three state-of-art market models are compared. The results show that with a more accurate representation of contingencies in the market models, N-1 grid security requirements are originally captured; thereby, the value of service provided by generators is reflected in the prices to achieve grid security.
Also, new flexible ramping product (FRP) designs are proposed for different market processes to (i) schedule day-ahead (DA) FRP awards that are more adaptive concerning the real-time (RT) 15-min net load changes, and (ii) address the FRP deployability issue in fifteen-minute market (FMM). The proposed market models performance with enhanced FRP designs is compared against the DA market and FMM models with the existing FRP design through a validation methodology based on California independent system operator (ISO) RT operation. The proposed FRP designs lead to less expected final RT operating cost, higher reliability, and fewer RT price spikes.
Finally, this dissertation proposes a distribution utility and ISO coordination framework to enable ISO to manage the wholesale market while preemptively not allowing aggregators to cause distribution system (DS) violations. To this end, this coordination framework architecture utilizes the statistical information obtained using different DS conditions and data-mining algorithms to predict the aggregators qualified maximum capacity. A validation phase considering Volt-VAr support provided by distributed PV smart inverters is utilized for evaluate the proposed model performance. The proposed model produces wholesale market awards for aggregators that fall within the DS operational limits and, consequently, will not impose reliable and safety issues for the DS.
ContributorsGhaljehei, Mohammad (Author) / Khorsand, Mojdeh (Thesis advisor) / Vittal, Vijay (Committee member) / Wu, Meng (Committee member) / Weng, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
With the increasing penetration levels of distributed energy resources along distribution feeders, the importance of load modeling has grown significantly and therefore it is important to have an accurate representation of the distribution system in the planning and operation studies. Although, currently, most of the power system studies are being done using positive sequence commercial software packages for computational convenience purposes, it comes at the cost of reduced accuracy when compared to the more accurate electromagnetic transient (EMT) simulators (but more computationally intensive). However, it is expected, that in the next several years, the use of EMT simulators for large-scale system studies would become a necessity to implement the ambitious renewable energy targets adopted by many countries across the world. Currently, the issue of developing more accurate EMT feeder and load models has yet to be addressed. Therefore, in the first phase of this work, an optimization algorithm to synthesize an EMT distribution feeder and load model has been developed by capturing the current transients when three-phase voltage measurements (obtained from a local utility) are played-in as input, from events such as sub-transmission faults, to the synthesized model. Using the developed algorithm, for the proposed feeder model, both the load composition and the load parameters have been estimated. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor (SPHIM) loads and three-phase induction motor loads.
In the second phase of this work, an analytical formulation of a 24 V EMT contactor is developed to trip the air conditioner EMT SPHIM load, in the feeder and load model developed in Phase 1 of this work, under low voltage conditions. Additionally, a new methodology is developed, to estimate and incorporate the trip and reconnection settings of the proposed EMT contactor model to trip, reconnect and stall the SPHIMs in a positive sequence simulator (PSLF) for single-line to ground faults. Also, the proposed methodology has been tested on a modified three-segment three-phase feeder model using a local utility’s practical feeder topological and loading information. Finally, the developed methodology is modified to accommodate three-phase faults in the system.
ContributorsNekkalapu, Sameer (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2022
Description
The electric power system (EPS) is an extremely complex system that has operational interdependencies with the water delivery and treatment system (WDTS). The term water-energy nexus is commonly used to describe the critical interdependencies that naturally exist between the EPS and water distribution systems (WDS). Presented in this work is a framework for simulating interactions between these two critical infrastructure systems in short-term and long-term time-scales. This includes appropriate mathematical models for system modeling and for optimizing control of power system operation with consideration of conditions in the WDS. Also presented is a complete methodology for quantifying the resilience of the two interdependent systems.
The key interdependencies between the two systems are the requirements of water for the cooling cycle of traditional thermal power plants as well as electricity for pumping and/or treatment in the WDS. While previous work has considered the dependency of thermoelectric generation on cooling water requirements at a high-level, this work considers the impact from limitations of cooling water into network simulations in both a short-term operational framework as well as in the long-term planning domain.
The work completed to set-up simulations in operational length time-scales was the development of a simulator that adequately models both systems. This simulation engine also facilitates the implementation of control schemes in both systems that take advantage of the knowledge of operating conditions in the other system. Initial steps for including the influence of anticipated water availability and water rights attainability within the combined generation and transmission expansion planning problem is also presented. Lastly, the framework for determining the infrastructural-operational resilience (IOR) of the interdependent systems is formulated.
Adequately modeling and studying the two systems and their interactions is becoming critically important. This importance is illustrated by the possibility of unforeseen natural or man-made events or by the likelihood of load increase in the systems, either of which has the risk of putting extreme stress on the systems beyond that experienced in normal operating conditions. Therefore, this work addresses these concerns with novel modeling and control/policy strategies designed to mitigate the severity of extreme conditions in either system.
The key interdependencies between the two systems are the requirements of water for the cooling cycle of traditional thermal power plants as well as electricity for pumping and/or treatment in the WDS. While previous work has considered the dependency of thermoelectric generation on cooling water requirements at a high-level, this work considers the impact from limitations of cooling water into network simulations in both a short-term operational framework as well as in the long-term planning domain.
The work completed to set-up simulations in operational length time-scales was the development of a simulator that adequately models both systems. This simulation engine also facilitates the implementation of control schemes in both systems that take advantage of the knowledge of operating conditions in the other system. Initial steps for including the influence of anticipated water availability and water rights attainability within the combined generation and transmission expansion planning problem is also presented. Lastly, the framework for determining the infrastructural-operational resilience (IOR) of the interdependent systems is formulated.
Adequately modeling and studying the two systems and their interactions is becoming critically important. This importance is illustrated by the possibility of unforeseen natural or man-made events or by the likelihood of load increase in the systems, either of which has the risk of putting extreme stress on the systems beyond that experienced in normal operating conditions. Therefore, this work addresses these concerns with novel modeling and control/policy strategies designed to mitigate the severity of extreme conditions in either system.
ContributorsZuloaga, Scott (Author) / Vittal, Vijay (Thesis advisor) / Zhang, Junshan (Committee member) / Mays, Larry (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2020
Description
Low frequency oscillations (LFOs) are recognized as one of the most challenging problems in electric grids as they limit power transfer capability and can result in system instability. In recent years, the deployment of phasor measurement units (PMUs) has increased the accessibility to time-synchronized wide-area measurements, which has, in turn, enabledthe effective detection and control of the oscillatory modes of the power system. This work assesses the stability improvements that can be achieved through the coordinated wide-area control of power system stabilizers (PSSs), static VAr compensators (SVCs), and supplementary damping controllers (SDCs) of high voltage DC (HVDC) lines, for damping electromechanical oscillations in a modern power system. The improved damping is achieved by designing different types of coordinated wide-area damping controllers (CWADC) that employ partial state-feedback. The first design methodology uses a linear matrix inequality (LMI)-based mixed H2/Hinfty control that is robust for multiple operating scenarios. To counteract the negative impact of communication failure or missing PMU measurements on the designed control, a scheme to identify the alternate set of feedback signals is proposed. Additionally, the impact of delays on the performance of the control design is investigated.
The second approach is motivated by the increasing popularity of artificial intelligence (AI) in enhancing the performance of interconnected power systems. Two different wide-area coordinated control schemes are developed using deep neural networks (DNNs) and deep reinforcement learning (DRL), while accounting for the uncertainties present in the power system. The DNN-CWADC learns to make control decisions using supervised learning; the training dataset consisting of polytopic controllers designed with the help of LMI-based mixed H2/Hinfty optimization. The DRL-CWADC learns to adapt to the system uncertainties based on its continuous interaction with the power system environment by employing
an advanced version of the state-of-the-art deep deterministic policy gradient (DDPG) algorithm referred to as bounded exploratory control-based DDPG (BEC-DDPG). The studies performed on a 29 machine, 127 bus equivalent model of theWestern Electricity Coordinating Council (WECC) system-embedded with different types of damping controls have demonstrated the effectiveness and robustness of the proposed CWADCs.
ContributorsGupta, Pooja (Author) / Pal, Anamitra (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Zhang, Junshan (Committee member) / Hedmnan, Mojdeh (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2021
Description
Ensuring reliable operation of large power systems subjected to multiple outages is a challenging task because of the combinatorial nature of the problem. Traditional methods of steady-state security assessment in power systems involve contingency analysis based on AC or DC power flows. However, power flow based contingency analysis is not fast enough to evaluate all contingencies for real-time operations. Therefore, real-time contingency analysis (RTCA) only evaluates a subset of the contingencies (called the contingency list), and hence might miss critical contingencies that lead to cascading failures.This dissertation proposes a new graph-theoretic approach, called the feasibility test (FT) algorithm, for analyzing whether a contingency will create a saturated or over-loaded cut-set in a meshed power network; a cut-set denotes a set of lines which if tripped separates the network into two disjoint islands. A novel feature of the proposed approach is that it lowers the solution time significantly making the approach viable for an exhaustive real-time evaluation of the system. Detecting saturated cut-sets in the power system is important because they represent the vulnerable bottlenecks in the network. The robustness of the FT algorithm is demonstrated on a 17,000+ bus model of the Western Interconnection (WI).
Following the detection of post-contingency cut-set saturation, a two-component methodology is proposed to enhance the reliability of large power systems during a series of outages. The first component combines the proposed FT algorithm with RTCA to create an integrated corrective action (iCA), whose goal is to secure the power system against post-contingency cut-set saturation as well as critical branch overloads. The second component only employs the results of the FT to create a relaxed corrective action (rCA) that quickly secures the system against saturated cut-sets.
The first component is more comprehensive than the second, but the latter is computationally more efficient. The effectiveness of the two components is evaluated based upon the number of cascade triggering contingencies alleviated, and the computation time. Analysis of different case-studies on the IEEE 118-bus and 2000-bus synthetic Texas systems indicate that the proposed two-component methodology enhances the scope and speed of power system security assessment during multiple outages.
ContributorsSen Biswas, Reetam (Author) / Pal, Anamitra (Thesis advisor) / Vittal, Vijay (Committee member) / Undrill, John (Committee member) / Wu, Meng (Committee member) / Zhang, Yingchen (Committee member) / Arizona State University (Publisher)
Created2021
Description
In recent years, the adoption of Distributed Energy Resources (DERs) in power systems has been increasing, driven by technological advancements, development of monitoring and control techniques, policy guidance among various countries, and the benefits DERs bring to the power system. These benefits include low-cost energy production, environmental sustainability promotion, and enhanced operational efficiency of the power system. For instance, demand response (DR) can alleviate pressure during peak load periods, while solar PV units and wind turbines with smart inverters can improve grid reliability through grid regulation based on IEEE Standard 1547. Despite the opportunities DERs present, their adoption also poses challenges. The growing reliance on renewable sources introduces uncertainty, variability, and intermittency, directly impacting system stability and efficiency. Addressing these challenges necessitates comprehensive research to enhance stability, improve system operations, and maximize resource utilization. This dissertation concentrates on two primary research areas: analyzing prosumer (consumers and producers, as one) consumption behavior and developing AC optimal power flow (ACOPF) models. Firstly, understanding prosumer consumption behavior is important for reducing DERs' uncertainty, particularly DR programs. This study employs a proposed probabilistic algorithm to analyze the causal relationships between prosumer consumption behavior and other factors. Two causal-oriented approaches are utilized to establish accurate prediction models and assess demand flexibility. Causal artificial intelligence facilitates intervention and counterfactual analyses of prosumers’ DR participation and consumption behavior. Finally, a Conditional Hidden Semi-Markov Model (CHSMM) is applied to model and predict household appliance electricity consumption, further enhancing understanding of prosumer behavior. Secondly, the dissertation investigates optimization models for efficient, cost-effective power system operation and resource utilization maximization. A convex two-stage socially-aware and risk-aware Second-Order Cone Programming (SOCP)-based ACOPF model is introduced to mitigate DER uncertainty, enhance PV energy utilization, and reduce operational costs. Additionally, a convex SOCP-based ACOPF model is presented for three-phase unbalanced distribution systems, incorporating the Q-V characteristics of PV units with smart inverters based on IEEE Standard 1547. This model enables the participation of PV units with smart inverters in grid voltage regulation, enhancing power system stability and achieving efficient, cost-effective operation.
ContributorsHe, Mingyue (Author) / Khorsand, Mojdeh (Thesis advisor) / Vittal, Vijay (Committee member) / Weng, Yang (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2024