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Machine Learning Applications for Dynamic Security Assessment in presence of Renewable Generation and Load Induced Variability

Abstract Large-scale blackouts that have occurred across North America in the past few decades have paved the path for substantial amount of research in the field of security assessment of the grid. With the aid of advanced technology such as phasor measurement units (PMUs), considerable work has been done involving voltage stability analysis and power system dynamic behavior analysis to ensure security and reliability of the grid. Online dynamic security assessment (DSA) analysis has been developed and applied in several power system control centers. Existing applications of DSA are limited by the assumption of simplistic load profiles, which often considers a normative day to represent an entire year. To overcome these aforementioned challenges, t... (more)
Created Date 2019
Contributor NATH, ANUBHAV (Author) / PAL, ANAMITRA (Advisor) / HOLBERT, KEITH (Committee member) / WU, MENG (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering
Type Masters Thesis
Extent 99 pages
Language English
Note Masters Thesis Electrical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis