Date of Award

3-2024

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering

First Advisor

Amin Khodaei

Second Advisor

Mohammad Matin

Third Advisor

Rui Fan

Keywords

Data-driven models, Distribution networks, Load phase identification, Power systems, Transmission networks, Wildfire risk assessment

Abstract

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and vulnerability of power system to wildfires. This study presents a comprehensive data-driven framework that integrates a robust wildfire spread simulator and power flow analysis to assess metrics such as risk and vulnerability associated with transmission network components against grid-ignited wildfires. A 30-bus test system serves as the case study. Results suggest that this framework can support power system planners and operators in determining the optimal allocation of investments for resilience and risk mitigation strategies.

This research demonstrates how harnessing data, particularly from smart meters and robust simulation tools, can drive strategic decision-making in power system planning and operations, and contribute significantly towards a reliable and resilient energy future.

Copyright Date

3-2024

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Behrouz Sohrabi

Provenance

Received from ProQuest

File Format

application/pdf

Language

English (eng)

Extent

75 pgs

File Size

5.4 MB

Discipline

Energy

Download



Share

COinS