The author of this document has limited its availability to on-campus or logged-in CSUSB users only.

Off-campus CSUSB users: To download restricted items, please log in to our proxy server with your MyCoyote username and password.

Date of Award


Document Type

Restricted Project: Campus only access

Degree Name

Master of Science in Computer Science


School of Computer Science and Engineering

First Reader/Committee Chair

Amir Ghasemkhani


The Phasor Measurement Units commonly referred to as PMUs is a tool for collecting fine-grained measurements in power systems ranging from phase angles, current flows and voltage levels. The valuable insight derived from analyzing such extensive amounts of data plays an important role in monitoring, controlling and securing the power systems. However, analyzing vast amounts of constantly changing data collected through PMUs becomes challenging over time. Hence, there is a pressing need to create an effective visualization platform by employing modern web technologies such as Flask Python coupled with HTML/CSS web development programs. This visualization framework aims at simplifying readings through interactive illustrative designs, portraying aspects like time-series plots, and utilizing modern machine learning algorithms specifically designed for identifying anomalies in the system measurements. The practicality of the proposed framework will be corroborated by utilizing real-world PMU data obtained from U.S. western interconnections. The proposed monitoring framework will be useful in automatically analyzing PMU data while delivering vital insights about how power systems operate across various operating conditions.