Risk-Based Capacity Accreditation of Resource-Colocated Large Loads in Capacity Markets

TL;DR

This paper introduces a risk-based capacity accreditation method for resource-colocated large loads, integrating generation and storage to improve reliability assessment in capacity markets.

Contribution

It develops a convex optimization framework based on ELCC to accurately evaluate the combined reliability of colocated resources, advancing capacity accreditation techniques.

Findings

Effective load carrying capability (ELCC) used for reliability assessment

Convex optimization minimizes reliability risk

Applied to a hydrogen manufacturing facility with renewable resources

Abstract

We study capacity accreditation of resource-colocated large loads, defined as large demands such as data center and manufacturing loads colocated with behind-the-meter generation and storage resources, synchronously connected to the bulk power system, and capable of participating in the wholesale electricity market as an integrated unit. Because the accredited capacity of a resource portfolio is not equal to the sum of its individual resources' capacity values, we adopt a risk-based capacity accreditation framework to evaluate the combined reliability contribution of colocated resources. Grounded in the effective load carrying capability (ELCC) metric, the proposed capacity accreditation employs a convex optimization engine that jointly dispatches colocated resources to minimize reliability risk. We apply the developed methodology to a hydrogen manufacturing facility with colocated renewable generation, storage, and fuel cell resources.