The Influence of Demand-Side Data Granularity on the Efficacy of 24/7 Carbon-Free Electricity Procurement

This study explores the system-level impacts of 24/7 CFE procurement in scenarios where electricity buyers are able to access granular supply-side data, i.e. hourly-granularity energy attribute certificates (EACs) produced by generators, but are unable to access granular data describing their own electricity demand. The study aims to answer the following questions:

• To what extent are the benefits of 24/7 CFE procurement lost or preserved if participating consumers match temporally granular CFE supply to estimated representations of their own demand?
• How do outcomes change across different possible demand profiles?
• How does the use of non-granular load profiles affect the accuracy of attributional emissions accounting?
• How consistent are findings across different electricity grids, technology portfolios, and matching targets?

In this study, we model procurement of 24/7 CFE by hypothetical commercial and industrial electricity consumers who can access their own consumption data at varying levels of granularity. We use a 24/7 CFE module implemented in the open-source GenX electricity system planning model to assess the impacts of this procurement on large-scale electricity sector outcomes, including total CO2 emissions and energy technology deployments. We also compare the ‘attributional’ emissions that would be calculated and reported by electricity consumers under a granular inventory accounting approach using estimated load profiles to those that would be calculated if the true hourly profile were known and calculate any discrepancies. 

Key findings of this study include the following:

• The system-level impacts of 24/7 CFE procurement are relatively consistent even when using an approximation of a consumer’s true demand profile.
  
• System-level emissions and generation impacts of 24/7 CFE procurement are very consistent across different possible demand-side representations and are much more sensitive to other factors including system conditions, matching targets, and technology availability.
• Costs for participating consumers exhibit minor variability across different demand-side representations, with no consistent direction.
• Participants’ incentives to procure nascent CFE generation and storage technologies are not significantly affected by use of estimated load profiles.
• Use of load profiles with different levels of granularity has very little impact on the accuracy of granular attributional emissions accounting; technology portfolios procured to match approximate profiles are very similar to those used to match the true demand.
• All of the above findings are consistent whether consumers pursue 100% 24/7 CFE matching or a lower target matching percentage.

Note: This study is published in the spirit of a working paper for public dissemination and has not been subject to peer review. Any final publications based on this report will be subject to further peer review and may be revised.

This project was supported by a grant from Google, Inc.