Endogenizing Probabilistic Resource Adequacy Risks in Deterministic Capacity Expansion Models
In this work, we demonstrate how power system capacity expansion models can understate the stochastic effects of thermal outages when considering resource availabilities on an hourly expected value basis, yielding system designs with multiple orders of magnitude more shortfall risk than stated adequacy targets. We develop a novel approximation approach to efficiently endogenize awareness of this risk in a deterministic, linear capacity expansion framework. We compare this approach to exogenous tuning of an energy reserve margin, the leading alternative method to compensate for unmodeled probabilistic shortfall risk. Empirical results from a test system show that the new endogenous method cost-effectively meets all regional reliability targets with a single optimization solve, and produces a near-identical system design as the incumbent method without the need for repeated re-optimizations to find an appropriate reserve level. The endogenous method may also use iterative re-optimizations to further improve solution quality, although these incremental benefits were modest in the system studied.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Strategic Programs Office
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 2449695
- Report Number(s):
- NREL/CP-6A40-89583; MainId:90362; UUID:53336690-bc6e-4066-9be5-de8e8594e30a; MainAdminId:73936
- Resource Relation:
- Conference: Presented at the 2024 18th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 24-26 June 2024, Auckland, New Zealand
- Country of Publication:
- United States
- Language:
- English
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