Decision-making under uncertainty for electric power system operation and expansion planning

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.