Mississippi State University
Date of Degree
Dissertation - Open Access
Industrial and system Engineering
Doctor of Philosophy (Ph.D)
James Worth Bagley College of Engineering
Department of Industrial and Systems Engineering
In this study, increasing electricity demand requires considerable attention to increasing the diversity of power generation. Alternative energy can produce heating and power systems and thermal storage. Our objective and every organization’s objectives are to minimize its energy consumption cost under electricity demand uncertainty. In rural areas, heat and power availability and stability are also crucial. Combined heat and power have proven their effectiveness as a subsequent to Electricity. This paper identified four criteria and eleven sub-criteria to determine the most appropriate structure location for combined heat and power in the rural community. The Bayesian Network technology has been applied to analyze these criteria comprehensively. A case study including multiple sites across the Mississippi state was used to validate the proposed approach, and propagation and sensitivity analysis were used to evaluate performance. Results showed the summarized eleven criteria proposed Bayesian Network approach could aid location selection for Combined heat and power location in the rural area. Supplementary, the created model can support decision-makers to select the best alternatives under different electricity demand variability levels.
United States Protection Agency , Mississippi State University, University of Business and Technology , Saudi Arabia Cultural Mission
Battawi, Abdullah Hassan, "Bayesian network development and validation for siting selection" (2022). Theses and Dissertations. 5614.