Deploying E3’s RESERVE Tool to Enable Advanced Operation of Clean Grids

Abstract

Energy and Environmental Economics, Inc. (E3) developed an open-source machine learning model, RESERVE, for deriving ancillary services timeseries in deeply decarbonized electricity grids. E3 used a bespoke PLEXOS production simulation model of the California Independent System Operator’s (CAISO) balancing area to validate RESERVE’s ability to enable production cost, greenhouse gas emissions (GHG), and renewable energy curtailment savings. These savings were modeled by comparing PLEXOS cases with RESERVE’s outputs to PLEXOS cases with CAISO’s incumbent reserve product in the Western Energy Imbalance Market (EIM)’s 15-minute market. E3 also tested cases with solar operating flexibly to provide reserves. E3 found that, in a 2030 modeling year, using RESERVE and flexible solar enabled significant production cost, GHG and curtailment savings versus the incumbent CAISO method in cases with low penetrations of lithium-ion batteries. However, with the full 14 gigawatts (about 30% of peak CAISO demand) of 4-hour lithium-ion batteries that are expected to be installed by 2030, these savings approach zero due to batteries saturating ancillary services markets. E3 also found significant savings under a 2019 benchmarking year.