Can Carbon-Aware Electric Load Shifting Reduce Emissions? An Equilibrium-Based Analysis

Abstract

An increasing number of electric loads, such as hydrogen producers or data centers, can be characterized as carbon-sensitive, meaning that they are willing to adapt the timing and/or location of their electricity usage in order to minimize carbon footprints. However, the emission reduction efforts of these carbon-sensitive loads rely on carbon intensity information such as average carbon emissions, and it is unclear whether load shifting based on these signals effectively reduces carbon emissions. To address this open question, we design a carbon-aware equilibrium model, which expands the commonly used equilibrium model for standard (carbon-agnostic) electricity market clearing to include carbon-sensitive consumers that adapt their consumption based on average carbon emission signals and carbon costs. This analysis represents an idealized situation for carbon-sensitive consumers, where their carbon preferences are reflected directly in the market clearing, and contrasts with current practice, where carbon emission signals only become known to consumers a posteriori (i.e., after the market has already been cleared). Furthermore, we extend our model to consider temporal load shifting and time-varying maximum renewable generations. We employ illustrative three-bus examples and numerical simulations on the IEEE RTS-GMLC system to reveal the limitations of the widely adopted average carbon emission signal for guiding carbon emission reduction. Our model offers a novel perspective for evaluating the effectiveness of different carbon signals and contributes to new carbon signal design.