Matching Items (3)
Description
The flexibility in power system networks is not fully modeled in existing real-time contingency analysis (RTCA) and real-time security-constrained economic dispatch (RT SCED) applications. Thus, corrective transmission switching (CTS) is proposed in this dissertation to enable RTCA and RT SCED to take advantage of the flexibility in the transmission system in a practical way.
RTCA is first conducted to identify critical contingencies that may cause violations. Then, for each critical contingency, CTS is performed to determine the beneficial switching actions that can reduce post-contingency violations. To reduce computational burden, fast heuristic algorithms are proposed to generate candidate switching lists. Numerical simulations performed on three large-scale realistic power systems (TVA, ERCOT, and PJM) demonstrate that CTS can significantly reduce post-contingency violations. Parallel computing can further reduce the solution time.
RT SCED is to eliminate the actual overloads and potential post-contingency overloads identified by RTCA. Procedure-A, which is consistent with existing industry practices, is proposed to connect RTCA and RT SCED. As CTS can reduce post-contingency violations, higher branch limits, referred to as pseudo limits, may be available for some contingency-case network constraints. Thus, Procedure-B is proposed to take advantage of the reliability benefits provided by CTS. With the proposed Procedure-B, CTS can be modeled in RT SCED implicitly through the proposed pseudo limits for contingency-case network constraints, which requires no change to existing RT SCED tools. Numerical simulations demonstrate that the proposed Procedure-A can effectively eliminate the flow violations reported by RTCA and that the proposed Procedure-B can reduce most of the congestion cost with consideration of CTS.
The system status may be inaccurately estimated due to false data injection (FDI) cyber-attacks, which may mislead operators to adjust the system improperly and cause network violations. Thus, a two-stage FDI detection (FDID) approach, along with several metrics and an alert system, is proposed in this dissertation to detect FDI attacks. The first stage is to determine whether the system is under attack and the second stage would identify the target branch. Numerical simulations demonstrate the effectiveness of the proposed two-stage FDID approach.
RTCA is first conducted to identify critical contingencies that may cause violations. Then, for each critical contingency, CTS is performed to determine the beneficial switching actions that can reduce post-contingency violations. To reduce computational burden, fast heuristic algorithms are proposed to generate candidate switching lists. Numerical simulations performed on three large-scale realistic power systems (TVA, ERCOT, and PJM) demonstrate that CTS can significantly reduce post-contingency violations. Parallel computing can further reduce the solution time.
RT SCED is to eliminate the actual overloads and potential post-contingency overloads identified by RTCA. Procedure-A, which is consistent with existing industry practices, is proposed to connect RTCA and RT SCED. As CTS can reduce post-contingency violations, higher branch limits, referred to as pseudo limits, may be available for some contingency-case network constraints. Thus, Procedure-B is proposed to take advantage of the reliability benefits provided by CTS. With the proposed Procedure-B, CTS can be modeled in RT SCED implicitly through the proposed pseudo limits for contingency-case network constraints, which requires no change to existing RT SCED tools. Numerical simulations demonstrate that the proposed Procedure-A can effectively eliminate the flow violations reported by RTCA and that the proposed Procedure-B can reduce most of the congestion cost with consideration of CTS.
The system status may be inaccurately estimated due to false data injection (FDI) cyber-attacks, which may mislead operators to adjust the system improperly and cause network violations. Thus, a two-stage FDI detection (FDID) approach, along with several metrics and an alert system, is proposed in this dissertation to detect FDI attacks. The first stage is to determine whether the system is under attack and the second stage would identify the target branch. Numerical simulations demonstrate the effectiveness of the proposed two-stage FDID approach.
ContributorsLi, Xingpeng (Author) / Hedman, Kory (Thesis advisor) / Heydt, Gerald (Committee member) / Vittal, Vijay (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics
1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies
2. A systematic approach to n-1-1 analysis for power system security as-sessment
To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.
Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.
1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies
2. A systematic approach to n-1-1 analysis for power system security as-sessment
To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.
Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.
ContributorsMitra, Parag (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2016
Description
Reliable and secure operation of bulk power transmission system components is an important aspect of electric power engineering. Component failures in a transmission network can lead to serious consequences and impact system reliability. The operational health of the transmission assets plays a crucial role in determining the reliability of an electric grid. To achieve this goal, scheduled maintenance of bulk power system components is an important activity to secure the transmission system against unanticipated events. This thesis identifies critical transmission elements in a 500 kV transmission network utilizing a ranking strategy.
The impact of the failure of transmission assets operated by a major utility company in the Southwest United States on its power system network is studied. A methodology is used to quantify the impact and subsequently rank transmission assets in decreasing order of their criticality. The analysis is carried out on the power system network using a node breaker model and steady state analysis. The light load case of spring 2019, peak load case of summer 2023 and two intermediate load cases have been considered for the ranking. The contingency simulations and power flow studies have been carried out using a commercial power flow study software package, Positive Sequence Load Flow (PSLF). The results obtained from PSLF are analyzed using Matlab to obtain the desired ranking. The ranked list of transmission assets will enable asset managers to identify the assets that have the most significant impact on the overall power system network performance. Therefore, investment and maintenance decisions can be made effectively. A conclusion along with a recommendation for future work is also provided in the thesis.
The impact of the failure of transmission assets operated by a major utility company in the Southwest United States on its power system network is studied. A methodology is used to quantify the impact and subsequently rank transmission assets in decreasing order of their criticality. The analysis is carried out on the power system network using a node breaker model and steady state analysis. The light load case of spring 2019, peak load case of summer 2023 and two intermediate load cases have been considered for the ranking. The contingency simulations and power flow studies have been carried out using a commercial power flow study software package, Positive Sequence Load Flow (PSLF). The results obtained from PSLF are analyzed using Matlab to obtain the desired ranking. The ranked list of transmission assets will enable asset managers to identify the assets that have the most significant impact on the overall power system network performance. Therefore, investment and maintenance decisions can be made effectively. A conclusion along with a recommendation for future work is also provided in the thesis.
ContributorsBhandari, Harsh Nandlal (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2019