Date of Graduation
Spring 5-14-2020
Document Access
Project/Capstone - Global access
Degree Name
Master of Science in Environmental Management (MSEM)
College/School
College of Arts and Sciences
Department/Program
Environmental Management
First Advisor
Amalia Kokkinaki
Abstract
In the event of a hurricane, electricity is the most important utility as it provides heat, water, food, light, communication, and medical care to communities. Research predicts an increase in frequency and strength of hurricanes with time due to climate change, which requires communities and electric utility companies to be prepared for the inevitable. This paper assesses existing methods of hurricane preparation and restoration of the electric power grid in hurricane prone locations with regards to the electric utility companies and electric distribution systems. In this study, I perform a comparative analysis between different methods of planning and forecasting electrical power outages for a hurricane event. Previous research analyzes single models and methods, where this paper compares the many different models and methods to synthesize the most promising results for electric utility companies to implement. Results from this study indicate that hardening the electrical grid and optimizing the electrical forecast models with more promising variables (Estimated maximum wind speed, duration of high winds, previous outages, and tree densities) and model types (General Additive Models and Bayesian Additive Regression Tree models) will reduce response and recovery time of the electrical grid after a hurricane. This study is important as it will guide electrical utility companies on better methods to prepare and respond to hurricanes to facilitate fewer power outages and quicker recovery times after a hurricane, saving money and lives of affected communities and service areas.
Recommended Citation
Litalien, Zackary, "A review of methods to better predict and reduce the risk of hurricane damage to the energy sector" (2020). Master's Projects and Capstones. 1007.
https://repository.usfca.edu/capstone/1007