A State-of-the-World Decomposition Approach to Dynamics and Uncertainty in Electric Utility Generation Expansion Planning

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Abstract
Dynamics and uncertainty are central to electric utility generation expansion planning, but are difficult to handle explicitly. A state-of-the-world decomposition approach is introduced that solves the dynamic probabilistic generation expansion problem using simple static deterministic solution techniques. The main problem is decomposed into a set of static deterministic problems. Each problem represents a distinct state-of-the-world (i.e., a time and outcome scenario) and is solved individually using a new dynamic programming procedure. The problems are linked through Lagrange multipliers that are determined iteratively and that can be interpreted as “shadow” fixed costs. Consequently, one difficult problem is replaced with many easy ones. The solution obtained represents the minimum discounted expected cost generation expansion plan. It reflects the importance of future conditions in current decisions and the utility's ability to respond to the resolution of uncertainties over time.

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