Observations on the Optimality Tolerance in the CAISO 33% RPS Model.

摘要

In 2008 Governor Schwarzenegger of California issued an executive order requiring that 33 percent of all electricity in the state in the year 2020 should come from renewable resources such as wind, solar, geothermal, biomass, and small hydroelectric facilities. This 33% renewable portfolio standard (RPS) was further codified and signed into law by Governor Brown in 2011. To assess the market impacts of such a requirement, the California Public Utilities Commission (CPUC) initiated a study to quantify the cost, risk, and timing of achieving a 33% RPS by 2020. The California Independent System Operator (CAISO) was contracted to manage this study. The production simulation model used in this study was developed using the PLEXOS software package, which allows energy planners to optimize long-term system planning decisions under a wide variety of system constraints. In this note we describe our observations on varying the optimality tolerance in the CAISO 33% RPS model. In particular, we observe that changing the optimality tolerance from .05% to .5% leads to solutions over 5 times faster, on average, producing very similar solutions with a negligible difference in overall distance from optimality.