Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Marufuzzaman, Mohammad
Committee Member
Ma, Junfeng
Committee Member
Bian, Linkan
Date of Degree
4-30-2021
Original embargo terms
Complete embargo for 6 months
Document Type
Graduate Thesis - Open Access
Major
Industrial and Systems Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Industrial and Systems Engineering
Abstract
Due to the growing number of diverse power systems disruptions, including extreme weather events, technical factors, and human factors, assessing and quantifying the resilience of electric power subsystems has become an indispensable step to develop an efficient strategic plan to enhance the resilience and reliability of these systems and to endure the diverse interruptions. In this study, factors and sub-factors that may have either direct or indirect impact on the resilience of biomass-based combined heat and power systems are identified, and the interdependencies among them are determined as well. A Bayesian network model is implemented to quantify the resilience of a bCHP system, and the results are analyzed by applying three different techniques, which are sensitivity analysis, forward propagation analysis, and backward propagation analysis.
Sponsorship
SACM
Recommended Citation
Alzahrani, Omar, "Development of a Bayesian network model for assessing the resilience of biomass-based combined heat and power system" (2021). Theses and Dissertations. 5075.
https://scholarsjunction.msstate.edu/td/5075