Assessing Capacity Accreditation Choice on Resource Mix Outcomes

However, there is limited understanding of the relative advantages and disadvantages of these methods, as well as how the choice of accreditation method influences resource capacity value

(and, by extension, the resource buildout and resulting adequacy of the system). This paper explores the relationship between capacity expansion and resource adequacy in long-term planning, focusing on the evaluation of various capacity accreditation methodologies in a system with high renewable and storage penetration. It examines the Effective Load Carrying

Capability (ELCC), Marginal Reliability Impact (MRI), Equivalent Firm Capacity (EFC), and

Critical Periods Capacity Factor (CPCF) capacity accreditation methodologies as it pertains to wind resources. To accomplish this, it leverages a round-trip workflow that iterates between a capacity expansion model (CEM) and a resource adequacy (RA) model: the initial CEM run applies generic wind capacity assumptions, and a subsequent run updates the expansion plan using capacity values derived from RA results.

Key findings highlight the variability in capacity values derived from different methodologies in a system with high renewable and storage penetration. The way a capacity accreditation methodology is defined (such as whether it is first brought to criterion, or which underlying risk metric is used) can have a substantial impact on the resulting capacity accreditation values.

Expected Unserved Energy (EUE)-based capacity accreditation metrics are more consistent than those calculated using Loss of Load Expectation (LOLE) or Loss of Load Hours (LOLH), and computing values from the original system rather than after bringing it to criterion further reduces variability across capacity accreditation methodologies. Results also indicate that system‑wide capacity values for wind may fail to provide appropriate signals to the capacity expansion model regarding spatial differences in wind resource availability. This lack of coordination at times may lead to investments in wind resources located in areas less favorable from a resource adequacy perspective. Regional capacity values may help alleviate this incomplete linkage, and directly accounting for stress periods identified by the RA model within the capacity expansion process could further strengthen the connection between models. The results of this analysis can inform planning engineers in their selection of capacity accreditation methods and reduce iteration between models.