How Hydropower Operations Mitigate Flow Forecast Uncertainties to Maintain Grid Services in the Western U.S.

Abstract Hydropower facilities represent a key electricity generating resource in the U.S. Western Interconnection. These facilities rely upon forecasts of inflow when scheduling releases to generate electricity. However, hydropower operations represented in bulk power systems models do not reflect uncertainty in inflow forecasts. This study aims to evaluate how inflow forecast uncertainties impact hydropower generation and revenues at the scale of an entire power grid at a spatial scale relevant to power system modeling. The question is critical and timely as more flexibility is called upon to integrate other technologies without understanding the flexibility already exercised. New advances are needed to represent hydropower contributions under operational uncertainty at the interconnection scale. Our contribution includes the development of consistent and coincident medium‐range (0–7 days) inflow forecasts and a generic hydropower scheduler, Forecast‐Informed Scheduler for Hydropower (FIScH), that captures non‐powered water management objectives and constraints and allows for varying electricity prices. This scheduler was applied at 242 hydropower facilities representing 86% of the conventional nameplate capacity in the Western Interconnection. Hydropower revenues were examined for schedules developed using three sets of inflow forecasts with differing levels of accuracy over a 20‐year period from 2000 to 2019. In aggregate, we find that annual hydropower revenue decreases 0.08% when using more skillful forecasts, and 0.11% when using baseline persistence forecasts as compared to revenue using perfect forecasts. Regional and interannual results were more varied and ranged between −1 and 4%. The translation of improved forecast skill into higher revenues is non‐linear and varies regionally, with larger revenue changes on the west coast and smaller responses across the interior western U.S. Overall, we demonstrate that scheduling mostly alleviates the impact of inflow forecast errors on hydropower revenue. The study motivates the need for a more detailed evaluation into which specific hydrologic events impact hydropower scheduling and revenue at the system scale.