A NOVEL METHOD ON MOBILE ENERGY STORAGE SYSTEM ALLOCATION TO ENHANCE THE ELECTRIC DISTRIBUTION SYSTEM RESILIENCE
| dc.contributor.advisor | Ko, Seok-Bum | |
| dc.contributor.committeeMember | Karki, Rajesh | |
| dc.contributor.committeeMember | Chen, Li | |
| dc.creator | Sadeghi, Mohamad | |
| dc.date.accessioned | 2025-01-10T20:21:56Z | |
| dc.date.available | 2025-01-10T20:21:56Z | |
| dc.date.copyright | 2024 | |
| dc.date.created | 2024-12 | |
| dc.date.issued | 2025-01-10 | |
| dc.date.submitted | December 2024 | |
| dc.date.updated | 2025-01-10T20:21:56Z | |
| dc.description.abstract | Electrical energy is one of the most important needs of modern societies. Extreme weather events, e.g., wind storms, typhoons, and hurricanes, are occurring with increasing intensity and causing complete or partial power outages. These weather-related events are usually ignored in reliability-based studies. Hence, resilience studies are needed to create a more realistic plan for electric grids. There are several solutions to a more resilient distribution system with different categories. Recently, energy storage systems have come to more attention to enhance distribution system resilience. A standard state-of-the-art planning method for stationary ES units is a two-stage stochastic MILP that treats ES units as stationary resources. The planning tool's complexity would be even more if the ES units were mobile. Existing solution techniques, such as Benders' decomposition, generally perform poorly when applied to two-stage stochastic mixed-integer problems with binary recourse decisions. Hence, this study will suggest the graph-based method to address the MESS unit allocation problem to overcome that computational difficulty. The graph-based technique will turn the allocation problem into a graph, with MESS units assigned to different paths in the graph. The graph-based technique, unlike Benders' decomposition, does not make use of the underlying optimization's two-stage structure and does not separate the first- and second-stage decisions. Different reward values will be assigned to different buses at different time steps, which will be represented as the nodes in the graph. Each MESS unit will find the path with the most reward through the nodes in the graph considering the time that it takes the MESS unit to move from one bus to another because of their physical distance in the real world. Next, the suggested method’s accuracy will be tested by comparing results to the conventional MILP solver results. Lastly, resilience improvement will be measured in different scenarios and results will be compared in distribution systems benefiting “Mobile Energy Storage Systems” and “Stationary Energy Storage Systems” to investigate the mobility advantage of energy storage systems. Moreover, energy storage battery limitations will be discussed shortly and the limitation impact on grid resilience improvement will be calculated and compared to limitless battery capacity energy storage system units. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10388/16407 | |
| dc.language.iso | en | |
| dc.subject | High Impact Low Probability | |
| dc.subject | Mobile Energy Storage System | |
| dc.subject | Mixed Integer Linear Programming | |
| dc.subject | Value of Lost Load | |
| dc.title | A NOVEL METHOD ON MOBILE ENERGY STORAGE SYSTEM ALLOCATION TO ENHANCE THE ELECTRIC DISTRIBUTION SYSTEM RESILIENCE | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Electrical and Computer Engineering | |
| thesis.degree.discipline | Electrical Engineering | |
| thesis.degree.grantor | University of Saskatchewan | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.Sc.) |