Retail electricity costs and emissions incentives are misaligned for commercial and industrial power consumers
Fletcher T. Chapin, Akshay K. Rao, Adhithyan Sakthivelu, Carson I. Tucker, Eres David, Casey S. Chen, Erin Musabandesu, Meagan S. Mauter

TL;DR
This paper presents a detailed spatiotemporal analysis of U.S. electricity costs and emissions, revealing significant misalignments in incentives for commercial and industrial consumers that hinder effective electrification and carbon reduction.
Contribution
It develops a comprehensive dataset and time series approximation methods to compare cost and emission incentives, uncovering spatial and temporal heterogeneity and misalignments in existing tariffs.
Findings
Significant spatial and temporal heterogeneity in incentives.
Tariffs often incentivize more carbon-intensive electricity use.
Site selection critically influences costs and emissions.
Abstract
Electrification is contributing to substantial growth in U.S. commercial and industrial loads, but the cost and Scope 2 carbon emission implications of this load growth are opaque for both power consumers and utilities. This work describes a unique spatiotemporally resolved data set of U.S. electricity costs and emissions and applies time series approximation methods to quantify the alignment of electricity cost and emission incentives for large commercial and industrial consumers. We present a comprehensive spatiotemporal dataset of U.S. price-based demand response (i.e., tariff) and incentive-based demand response programs, enabling direct comparison to previously published marginal emission factor, average emission factor, and day-ahead market prices. We resolved the structural incompatibility and fragmentation of these datasets by developing time series approximations of discrete…
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Taxonomy
TopicsSmart Grid Energy Management · Integrated Energy Systems Optimization · Energy Load and Power Forecasting
