Dynamic Locational Marginal Emissions Via Implicit Differentiation

Locational marginal emissions rates (LMEs) estimate the rate of change in due to a small demand transmission network, and are an important metric for assessing impact various energy policies or interventions. In this work, we develop new method computing LMEs electricity system via implicit differentiation. The is model agnostic; it can compute any convex optimization-based dispatch model, including some complex models employed by operators real systems. particular, lets us derive dynamic models, i.e., with temporal constraints such as ramping storage. Using data from U.S. system, validate proposed against state-of-the-art merit-order-based show that incorporating improves accuracy 8.2%. Finally, use simulations on realistic 240-bus WECC demonstrate flexibility tool importance constraints. Namely, static exhibit normalized average RMS deviation 28.40%, implying essential accurately modeling rates.