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Description
The uncertainty and variability associated with stochastic resources, such as wind and solar, coupled with the stringent reliability requirements and constantly changing system operating conditions (e.g., generator and transmission outages) introduce new challenges to power systems. Contemporary approaches to model reserve requirements within the conventional security-constrained unit commitment (SCUC) models may not be satisfactory with increasing penetration levels of stochastic resources; such conventional models pro-cure reserves in accordance with deterministic criteria whose deliverability, in the event of an uncertain realization, is not guaranteed. Smart, well-designed reserve policies are needed to assist system operators in maintaining reliability at least cost.
Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements.
This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures.
Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements.
This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures.
ContributorsSinghal, Nikita Ghanshyam (Author) / Hedman, Kory W (Thesis advisor) / Vittal, Vijay (Committee member) / Sankar, Lalitha (Committee member) / Pal, Anamitra (Committee member) / Arizona State University (Publisher)
Created2018
Description
After a major disturbance, the power system response is highly dependent on protection schemes and system dynamics. Improving power systems situational awareness requires proper and simultaneous modeling of both protection schemes and dynamic characteristics in power systems analysis tools. Historical information and ex-post analysis of blackouts reaffirm the critical role of protective devices in cascading events, thereby confirming the necessity to represent protective functions in transient stability studies. This dissertation is aimed at studying the importance of representing protective relays in power system dynamic studies. Although modeling all of the protective relays within transient stability studies may result in a better estimation of system behavior, representing, updating, and maintaining the protection system data becomes an insurmountable task. Inappropriate or outdated representation of the relays may result in incorrect assessment of the system behavior. This dissertation presents a systematic method to determine essential relays to be modeled in transient stability studies. The desired approach should identify protective relays that are critical for various operating conditions and contingencies. The results of the transient stability studies confirm that modeling only the identified critical protective relays is sufficient to capture system behavior for various operating conditions and precludes the need to model all of the protective relays. Moreover, this dissertation proposes a method that can be implemented to determine the appropriate location of out-of-step blocking relays. During unstable power swings, a generator or group of generators may accelerate or decelerate leading to voltage depression at the electrical center along with generator tripping. This voltage depression may cause protective relay mis-operation and unintentional separation of the system. In order to avoid unintentional islanding, the potentially mis-operating relays should be blocked from tripping with the use of out-of-step blocking schemes. Blocking these mis-operating relays, combined with an appropriate islanding scheme, help avoid a system wide collapse. The proposed method is tested on data from the Western Electricity Coordinating Council. A triple line outage of the California-Oregon Intertie is studied. The results show that the proposed method is able to successfully identify proper locations of out-of-step blocking scheme.
ContributorsHedman, Mojdeh Khorsand (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Pal, Anamitra (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
In order to meet the world’s growing energy need, it is necessary to create a reliable, robust, and resilient electric power grid. One way to ensure the creation of such a grid is through the extensive use of synchrophasor technology that is based on devices called phasor measurement units (PMUs), and their derivatives, such as μPMUs. Global positioning system (GPS) time-synchronized wide-area monitoring, protection, and control enabled by PMUs has opened up new ways in which the power grid can tackle the problems it faces today. However, with implementation of new technologies comes new challenges, and one of those challenges when it comes to PMUs is the misuse of GPS as a method to obtain a time reference.The use of GPS in PMUs is very intuitive as it is a convenient method to time stamp electrical signals, which in turn helps provide an accurate snapshot of the performance of the PMU-monitored section of the grid. However, GPS is susceptible to different types of signal interruptions due to natural (such as weather) or unnatural (jamming, spoofing) causes. The focus of this thesis is on demonstrating the practical feasibility of GPS spoofing attacks on PMUs, as well as developing novel countermeasures for them.
Prior research has demonstrated that GPS spoofing attacks on PMUs can cripple power system operation. The research conducted here first provides an experimental evidence of the feasibility of such an attack using commonly available digital radios known as software defined radio (SDR). Next, it introduces a new countermeasure against such attacks using GPS signal redundancy and low power long range (LoRa) spread spectrum modulation technique. The proposed approach checks the integrity of the GPS signal at remote locations and compares the data with the PMU’s current output. This countermeasure is a steppingstone towards developing a ready-to-deploy system that can provide an instant solution to the GPS spoofing detection problem for PMUs already placed in the power grid.
ContributorsSaadedeen, Fakhri G (Author) / Pal, Anamitra (Thesis advisor) / Sankar, Lalitha (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2021
Description
Fault detection is an integral part for power systems as without its proper study, analysis and mitigation, people will not be able to power the various appliances and equipment required in all aspects of life. One such type of fault which is very criticalin an electrical cable but very difficult to spot is incipient fault. These momentary faults are observed for very short periods however, if it persists, this would lead to consequences like insulation wear-off and even, power outages. With the advent of
machine learning in the power systems fraternity, this paper also uses a new and updated Active Learning algorithm to detect incipient fault data from a simulated test case. The objective of the paper is to detect the fault data accurately using this new and precise method. For purposes of data collection and training of the model, MATLAB Simulink and Python programming has been used respectively.
ContributorsGhosh, Kinjal (Author) / Weng, Yang (Thesis advisor) / Pal, Anamitra (Committee member) / Hedman, Mojdeh K (Committee member) / Arizona State University (Publisher)
Created2023
Description
Energy is one of the wheels on which the modern world runs. Therefore, standards and limits have been devised to maintain the stability and reliability of the power grid. This research shows a simple methodology for increasing the amount of Inverter-based Renewable Generation (IRG), which is also known as Inverter-based Resources (IBR), for that considers the voltage and frequency limits specified by the Western Electricity Coordinating Council (WECC) Transmission Planning (TPL) criteria, and the tie line power flow limits between the area-under-study and its neighbors under contingency conditions. A WECC power flow and dynamic file is analyzed and modified in this research to demonstrate the performance of the methodology. GE's Positive Sequence Load Flow (PSLF) software is used to conduct this research and Python was used to analyze the output data.
The thesis explains in detail how the system with 11% of IRG operated before conducting any adjustments (addition of IRG) and what procedures were modified to make the system run correctly. The adjustments made to the dynamic models are also explained in depth to give a clearer picture of how each adjustment affects the system performance. A list of proposed IRG units along with their locations were provided by SRP, a power utility in Arizona, which were to be integrated into the power flow and dynamic files. In the process of finding the maximum IRG penetration threshold, three sensitivities were also considered, namely, momentary cessation due to low voltages, transmission vs. distribution connected solar generation, and stalling of induction motors. Finally, the thesis discusses how the system reacts to the aforementioned modifications, and how IRG penetration threshold gets adjusted with regards to the different sensitivities applied to the system.
The thesis explains in detail how the system with 11% of IRG operated before conducting any adjustments (addition of IRG) and what procedures were modified to make the system run correctly. The adjustments made to the dynamic models are also explained in depth to give a clearer picture of how each adjustment affects the system performance. A list of proposed IRG units along with their locations were provided by SRP, a power utility in Arizona, which were to be integrated into the power flow and dynamic files. In the process of finding the maximum IRG penetration threshold, three sensitivities were also considered, namely, momentary cessation due to low voltages, transmission vs. distribution connected solar generation, and stalling of induction motors. Finally, the thesis discusses how the system reacts to the aforementioned modifications, and how IRG penetration threshold gets adjusted with regards to the different sensitivities applied to the system.
ContributorsAlbhrani, Hashem A M H S (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith E. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2020
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