Massachussets Institute of Technology. Cambridge (United States of America)
November 4th, 2019
Summary:
The recent spike in the frequency of hurricanes in Central America has severely damaged the conventional electrical grid. Notably, the government of Puerto Rico laid out a plan to reinvent its energy sector to improve its level of resiliency against natural disasters. Better planning and preparation can minimize the damage that needs to be repaired on time. For instance, when necessary facilities, such as hospitals, lose access to electricity, the ability to manage a displaced population after a hurricane is diminished. Computational planning tools allow policymakers and planners to take reliability metrics, resource constraints, interactions between off-grid and traditional grid-extension projects into account when designing contingency plans for the electric grid. The goal of this thesis is to explore the role of a hybrid decentralized structure of the electrical grid to improve the level of reliability through extraordinary circumstances. In this thesis, I develop algorithms that are shown via several case studies. Given the proper input data, these algorithms can provide insight into the technical feasibility of where to deploy microgrids given the existing infrastructure. This research emphasizes the need for granular spatial data at the distribution level to make better planning decisions.
Citation:
M. Barbar (2019), Resiliency and reliability planning of the electric grid in natural disaster affected areas. Massachussets Institute of Technology. Cambridge (United States of America).
