On the Convexity of Common Resource Adequacy and Capacity Accreditation Metrics

Many emerging capacity expansion optimization formulations implicitly presume the convexity (or concavity) of power system adequacy risk (or capacity accreditation) metrics. These assumptions have yet to be formally justified. We present concise mathematical proofs validating the claim for certain metrics (expected unserved energy and effective load carrying capability), but also provide simple invalidating counterexamples for others (loss-of-load expectation and equivalent firm capacity). Formulations built on non-convex (non-concave) metrics structurally undervalue candidate portfolio adequacy, and so cannot claim to produce least-cost expansion plans.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-03
DOI
https://doi.org/10.48550/arxiv.2611.04896
Primary Topic
Electric Power System Optimization
Type
preprint
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preprint

On the Convexity of Common Resource Adequacy and Capacity Accreditation Metrics

Gord Stephen
arXiv (Cornell University)
Electric Power System Optimization
preprint

On the Convexity of Common Resource Adequacy and Capacity Accreditation Metrics

Gord Stephen
preprint en

Abstract

Many emerging capacity expansion optimization formulations implicitly presume the convexity (or concavity) of power system adequacy risk (or capacity accreditation) metrics. These assumptions have yet to be formally justified. We present concise mathematical proofs validating the claim for certain metrics (expected unserved energy and effective load carrying capability), but also provide simple invalidating counterexamples for others (loss-of-load expectation and equivalent firm capacity). Formulations built on non-convex (non-concave) metrics structurally undervalue candidate portfolio adequacy, and so cannot claim to produce least-cost expansion plans.

arXiv (Cornell University)
Electric Power System Optimization
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On the Convexity of Common Resource Adequacy and Capacity Accreditation Metrics — Gord Stephen · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS