Metrics for assessing the economic impacts of power sector climate and clean electricity policies

Abstract

Abstract Modeling tools are increasingly used to inform and evaluate proposed power sector climate and clean electricity policies such as renewable portfolio and clean electricity standards, carbon pricing, emissions caps, and tax incentives. However, claims about economic and environmental impacts often lack transparency and may be based on incomplete metrics that can obscure differences in policy design. This paper examines model-based metrics used to assess the economic efficiency impacts of prospective electric sector policies. The appropriateness of alternative metrics varies by context, model, audience, and application, depending on the prioritization of comprehensiveness, measurability, transparency, and credible precision. This paper provides guidance for the modeling community on calculating and communicating cost metrics and for consumers of model outputs on interpreting these economic indicators. Using an illustrative example of clean electricity standards in the US power sector, model outputs highlight strengths and limitations of different cost metrics. Transformations of power systems with lower-carbon resources and zero-marginal-cost generation may entail shifts in when and where system costs are incurred, and given how these changes may not be appropriately reflected in metrics that were commonly reported in the past such as wholesale energy prices, showing a decomposition of system costs across standard reporting categories could be a more robust reporting practice. Ultimately, providing better metrics is only one element in a portfolio of transparency-related practices, and although it is insufficient by itself, such reporting can help to move dialogues in more productive directions and encourage better modeling practices.