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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