Geospatial sensitivity of transmission-constrained ACOPF to generator retirement

Abstract

The US faces a growing resource adequacy challenge: new loads are being added at unprecedented scale while aging generating assets are being retired. In transmission-constrained grids, it is difficult to determine which units can be safely retired and which cannot be retired and instead require lifetime extensions until new generation can be built. Historically, this analysis was prohibitively time consuming. Transmission-constrained AC optimal power flow (ACOPF) is computationally intensive, and a thorough comparison and prioritization of generators could require hundreds or thousands of scenarios. We present an HPC-enabled framework that enables computation and geospatial mapping of the effects of generator retirement in terms of voltage magnitude and angle effects in the steady state. Specifically, our framework detects the effects of generator retirement using a simple k-nearest-neighbors model and a voltage-class-adjusted neighbor model. We demonstrate the results on over 8,000 generator retirement scenarios for a 70,000-bus transmission-constrained synthetic grid.