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.

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.

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.

Power system robustness against high impact low probability events is becoming a major concern. About 90% of US power outages reported in the last three decades are due to Hurricanes and tropical storms. Various works of literature are focused on modelling the resilience framework against hurricanes. To depict distinct phases of a system response during these disturbances, an aggregated trapezoid model is derived from the conventional trapezoid model and proposed in this work. The model is analytically investigated for transmission system performance, based on which resiliency metrics are developed for the same.A probabilistic-based Monte Carlo Simulations (MCS) approach has been proposed in this work to incorporate the stochastic nature of the power system and hurricane uncertainty. Furthermore, the system's resilience to hurricanes is evaluated on the modified reliability test system (RTS), which is provided in this work, by performing steady-state and dynamic security assessment incorporating protection modelling and corrective action schemes using the Siemens Power System Simulator for Engineering (PSS®E) software. Based on the results of steady-state (both deterministic and stochastic approach) and dynamic (both deterministic and stochastic approach) analysis, resilience metrics are quantified. Finally, this work highlights the interdependency of operational and infrastructure resilience as they cannot be considered discrete characteristics of the system.
The objective of this work is to incorporate dynamic analysis and stochasticity in the resilience evaluation for a wind penetrated power system.

The past few years have witnessed a significant growth of distributed energy resources (DERs) in power systems at the customer level. Such growth challenges the traditional centralized model of conventional synchronous generation, making a transition to a decentralized network with a significant increase of DERs. This decentralized network requires a paradigm change in modeling distribution systems in more detail to maintain the reliability and efficiency while accommodating a high level of DERs. Accurate models of distribution feeders, including the secondary network, loads, and DER components must be developed and validated for system planning and operation and to examine the distribution system performance. In this work, a detailed model of an actual feeder with high penetration of DERs from an electrical utility in Arizona is developed. For the primary circuit, distribution transformers, and cables are modeled. For the secondary circuit, actual conductors to each house, as well as loads and photovoltaic (PV) units at each premise are represented. An automated tool for secondary network topology construction for load feeder topology assignation is developed. The automated tool provides a more accurate feeder topology for power flow calculation purposes. The input data for this tool consists of parcel geographic information system (GIS) delimitation data, and utility secondary feeder topology database. Additionally, a highly automated, novel method to enhance the accuracy of utility distribution feeder models to capture their performance by matching simulation results with corresponding field measurements is presented. The method proposed uses advanced metering infrastructure (AMI) voltage and derived active power measurements at the customer level, data acquisition systems (DAS) measurements at the feeder-head, in conjunction with an AC optimal power flow (ACOPF) to estimate customer active and reactive power consumption over a time horizon, while accounting for unmetered loads. The method proposed estimates both voltage magnitude and angle for each phase at the unbalanced distribution substation. The accuracy of the method developed by comparing the time-series power flow results obtained from the enhancement algorithm with OpenDSS results and with the field measurements available. The proposed approach seamlessly manages the data available from the optimization procedure through the final model verification.

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.

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.‎

Voltage Source Converters (VSCs) have been widely used in grid-connected applications with Distributed Energy Resource (DER) and Electric Vehicle (EV) applications. Replacement of traditional thyristors with Silicon/Silicon-Carbide based active switches provides full control capability to the converters and allows bidirectional power flow between the source and active loads. In this study, advanced control strategies for DER inverters and EV traction inverters will be explored.Chapter 1 gives a brief introduction to State-of-the-Art of VSC control strategies and summarizes the existing challenges in different applications. Chapter 2 presents multiple advanced control strategies of grid-connected DER inverters. Various grid support functions have been implemented in simulations and hardware experiments under both normal and abnormal operating conditions. Chapter 3 proposes an automated design and optimization process of a robust H-infinity controller to address the stability issue of grid-connected inverters caused by grid impedance variation. The principle of the controller synthesis is to select appropriate weighting functions to shape the systems closed-loop transfer function and to achieve robust stability and robust performance. An optimal controller will be selected by using a 2-Dimensional Pareto Front. Chapter 4 proposes a high-performance 4-layer communication architecture to facilitate the control of a large distribution network with high Photovoltaic (PV) penetration. Multiple strategies have been implemented to address the challenges
of coordination between communication and system control and between different communication protocols, which leads to a boost in the communication efficiency and makes the architecture highly scalable, adaptive, and robust. Chapter 5 presents the control strategies of a traditional Modular Multilevel Converter (MMC) and a novel Modular Isolated Multilevel Converter (MIMC) in grid-connected and variable speed drive applications. The proposed MIMC is able to achieve great size reduction for the submodule capacitors since the fundamental and double-line frequency voltage ripple has been cancelled. Chapter 6 shows a detailed hardware and controller design for a 48 V Belt-driven Starter Generator (BSG) inverter using automotive gate driver ICs and microcontroller. The inverter prototype has reached a power density of 333
W/inch3, up to 200 A phase current and 600 Hz output frequency.

Power systems are transforming into more complex and stressed systems each day. These stressed conditions could lead to a slow decline in the power grid's voltage profile and sometimes lead to a partial or total blackout. This phenomenon can be identified by either solving a power flow problem or using measurement-based real-time monitoring algorithms. The first part of this thesis focuses on proposing a robust power flow algorithm for ill-conditioned systems. While preserving the stable nature of the fixed point (FP) method, a novel distributed FP equation is proposed to calculate the voltage at each bus. The proposed algorithm's performance is compared with existing methods, showing that the proposed method can correctly find the solutions when other methods cannot work due to high condition number matrices. It is also empirically shown that the FP algorithm is more robust to bad initialization points. The second part of this thesis focuses on identifying the voltage instability phenomenon using real-time monitoring algorithms. This work proposes a novel distributed measurement-based monitoring technique called voltage stability index (VSI). With the help of PMUs and communication of voltage phasors between neighboring buses, the processors embedded at each bus in the smart grid perform simultaneous online computations of VSI. VSI enables real-time identification of the system's critical bus with minimal communication infrastructure. Its benefits include interpretability, fast computation, and low sensitivity to noisy measurements. Furthermore, this work proposes the ``local static-voltage stability index" (LS-VSI) that removes the minimal communication requirement in VSI by requiring only one PMU at the bus of interest. LS-VSI also solves the issue of Thevenin equivalent parameter estimation in the presence of noisy measurements. Unlike VSI, LS-VSI incorporates the ZIP load models and load tap changers (LTCs) and successfully identifies the bifurcation point considering ZIP loads' impact on voltage stability. Both VSI and LS-VSI are useful to monitor the voltage stability margins in real-time using the PMU measurements from the field. However, they cannot indicate the onset of voltage emergency situations. The proposed LD-VSI uses the dynamic measurements of the power system to identify the onset of a voltage emergency situation with an alarm. Compared to existing methods, it is shown that it is more robust to PMU measurement noise and can also identify the voltage collapse point while the existing methods have issues with the same.

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.