2026-09-20T05:12:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1449262022-08-30T03:53:37Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Kirtley Jr., James L.
Pérez-Arriaga, Ignacio J.
Barbar, Marc
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-08-29T16:21:27Z
2022-08-29T16:21:27Z
2022-05
2022-06-21T19:15:54.432Z
https://hdl.handle.net/1721.1/144926
0000-0002-9192-1731
Decision-making under uncertainty is required in a multiplicity of situations in power system operation and capacity expansion planning. This thesis investigates the drivers and impact of uncertainty on power system infrastructure planning and proposes several methods to design and operate a power system at granular modeling level. The focus of the thesis is on Emerging Markets and Developing Economy countries, specifically India and Nigeria. However, the work presented in this document can be adapted to other situations, in the power sector or elsewhere, that share similar traits. Moreover, incorporating uncertainty in generalized optimization models often yields inaccurate results due to the lack of precision in representing the problem. This thesis carefully examines a set of situations and presents appropriate decision-making under uncertainty frameworks that yield meaningful results. The thesis is divided into three parts: drivers of uncertainty, the impact of uncertainty, and accounting for uncertainty in electricity resource design, with applications to Emerging Markets and Developing Economy countries.
Ph.D.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
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http://rightsstatements.org/page/InC-EDU/1.0/
Decision-making under uncertainty for electric power system operation and expansion planning
Thesis
application/pdf
Doctoral
Doctor of Philosophy
Publication
unknown
unknown
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<Abstract>Decision-making under uncertainty is required in a multiplicity of situations in power system operation and capacity expansion planning. This thesis investigates the drivers and impact of uncertainty on power system infrastructure planning and proposes several methods to design and operate a power system at granular modeling level. The focus of the thesis is on Emerging Markets and Developing Economy countries, specifically India and Nigeria. However, the work presented in this document can be adapted to other situations, in the power sector or elsewhere, that share similar traits. Moreover, incorporating uncertainty in generalized optimization models often yields inaccurate results due to the lack of precision in representing the problem. This thesis carefully examines a set of situations and presents appropriate decision-making under uncertainty frameworks that yield meaningful results. The thesis is divided into three parts: drivers of uncertainty, the impact of uncertainty, and accounting for uncertainty in electricity resource design, with applications to Emerging Markets and Developing Economy countries.</Abstract>
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