Off-campus Michigan Tech users: To download campus access theses or dissertations, please use the following button to log in with your Michigan Tech ID and password: log in to proxy server

Non-Michigan Tech users: Please talk to your librarian about requesting this thesis or dissertation through interlibrary loan.

Date of Award


Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy in Electrical Engineering (PhD)

Administrative Home Department

Department of Electrical and Computer Engineering

Advisor 1

Wayne W. Weaver

Advisor 2

Chee-Wooi Ten

Committee Member 1

Gordon G. Parker

Committee Member 2

Yunting Liu


The disruption of extreme weather events can significantly impact on the operation of nation's critical infrastructures. With the growing trend of extreme weather events, evaluating hazard effects of wind storms on power distribution systems becomes increasingly important for disaster preparedness and fast responses in utilities. These catastrophic events disable critical paths of electricity overhead infrastructure, resulting in extended power outages and loss of critical services. There has been a national push to improve system resilience. A disrupted infrastructure should provide robust reconfigurable paths that can quickly restore power from mainstream or distributed energy resources to make power temporarily available for the critical services in the aftermath of a disaster.

This dissertation discusses a novel decision support tool for service power restoration. The tool includes a probabilistic wind storm models for the study region by mining all storm events recorded in the Hurricane Database (HURDAT) from the National Hurricane Center of the National Oceanic and Atmospheric Administration (NHC-NOAA). In addition, a simulation approach is presented to evaluate the impacts of wind storms over the power distribution system under different levels of hazards using a random storm trajectory generator and Geographic Information System (GIS) data. This simulation approach can be used for operation process of the autonomous restoration but can also be used for system planning of future high-impact, low-probability (HILP) events.

The modeling of pre-, during, and post-disaster infrastructure is also presented. These models characterizes the landfall and impact of a storm. Graph representation is utilized to establish the network properties, and Generalized Stochastic Petri Net (GSPN) was used as a feasible tool for power service restoration purpose. The uncertainty of communication availability due to disruption of the catastrophic events is also discussed.

Extensive studies for the Puerto Rico's electrical distribution system indicates that the proposed tool effectively estimate the number of affected customers and load loss due to a wind storm impact. In addition, illustrative examples with several case scenarios are presented to validate the feasibility of the proposed tool.