  We consider the construction of renewable portfolios targeting specified
carbon-free (CFE) hourly performance scores. We work in a probabilistic
framework that uses a collection of simulation scenarios and imposes
probability constraints on achieving the desired CFE score. In our approach
there is a fixed set of available CFE generators and a given load customer who
seeks to minimize annual procurement costs. We illustrate results using a
realistic dataset of jointly calibrated solar and wind assets, and compare
different approaches to handling multiple loads.
