Optimal electric utility generation expansion under uncertainty
This thesis presents a new approach to electric utility generation expansion planning under uncertainty. A comprehensive probabilistic model of the problem is formulated that focuses on the important strategic issues, including demand, technological and regulatory uncertainties, long-term generation expansion dynamics, and technological and regulatory constraints. Then, a four-part algorithm is described for finding the minimum feasible discounted expected cost generation expansion plan. The first and fundamental component of the algorithm is a dynamic programming procedure which addresses an elementary generation expansion subproblem that is unconstrained, static, and deterministic. Second, a primal-dual procedure is used to address a static, deterministic subproblem with capacity, energy, and capacity factor constraints. Third, a recursive technique is introduced to address a static, unconstrained subproblem that includes the effects of unscheduled outages. Finally, a decomposition technique is introduced to bridge the gap between the static subproblems and the dynamic, probabilistic generation expansion problem.
- OSTI ID:
- 6456589
- Resource Relation:
- Other Information: Thesis (Ph. D.)
- Country of Publication:
- United States
- Language:
- English
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