Opportunities for Joint Water–Energy Management: Sensitivity of the 2010 Western U.S. Electricity Grid Operations to Climate Oscillations

Abstract

The increasing interconnectedness of energy and water systems makes it important to understand how interannual variations in water availability—and climate oscillations—could potentially impact the electric grid operations. The authors assess the vulnerability of the current western U.S. grid to historical climate variability using multiple energy and water system models. A 55-yr-long natural water availability benchmark is combined with the 2010 level of water demand from an integrated assessment model to drive a large-scale water management model over the western United States. The regulated flow at hydropower and thermoelectric power plants is then translated into boundary conditions for electricity generation in a production cost model. This analysis focuses on assessing regional interdependencies and the impact of interannual changes in water availability on power system operations, including reliability, cost, and carbon emissions. Results for August grid operations—when stress on the grid is often highest—show a range of sensitivity in production cost (–8% to +11%) and carbon emissions (–7% to +11%), as well as a 1-in-10 chance that electricity demand will exceed estimated supply. The authors also show that operating costs are lower under neutral El Niño–Southern Oscillation (ENSO) conditions than under other ENSO phases; carbon emissions are highest under La Niña conditions, especially in California; and the risk of brownouts may be higher under neutral and negative ENSO conditions. These results help characterize the grid’s performance under historical climate variations, are useful for seasonal and multiyear planning of joint water–electricity management, and can be used to support impact, adaptation, and vulnerability analyses.

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

“…Given the prevalence of forecast application, as suggested by this study, improved dam and reservoir models that represent intelligent operator response to anticipated reservoir inflows over seasonally-varying horizons should contribute to a better understanding of hydrological stressors on energy and food security that are increasingly linked to large-scale hydrological models (e.g., Van Vliet al al. 2016, Wada et al 2016Voisin et al 2013b;Hejazi et al 2015, Voisin et al, 2018.…”

The Greater Mekong's Climate‐Water‐Energy Nexus: How ENSO‐Triggered Regional Droughts Affect Power Supply and CO2 Emissions

“…Something that all these studies have in common is a boundary drawn at the interconnection between water and power systems. And yet, it is only by placing dams and thermoelectric plants in a broader water‐energy context that we can fully understand how water availability affects power systems behavior, especially during heat waves and droughts (Voisin et al., 2018). From a modeling perspective, this means coupling hydrologic models with power system models representing the broad spectrum of decisions made at the grid scale—for example, commitment of generating units, electricity generation and transmission.…”

“…ENSO, for instance, affects temperature, rainfall, and hydropower supply in several regions (Chiew & McMahon, 2002;Ng et al, 2017), so one would expect ENSO-driven droughts to modify the energy generation mix or increase the risks of power shortfalls. With the only exception of Voisin et al (2018), this hypothesis has not been tested. Since teleconnections represent one of the physical mechanisms upon which seasonal hydrometeorological forecasts are issued, verifying the hypothesis would allow us to predict grid operations and design contingency measures.…”

Drought and climate change impacts on cooling water shortages and electricity prices in Great Britain

“…However, very few studies have applied probabilistic methods and risk assessment approaches 18,19 to assess the impacts of low flows across large spatial domains on associated power plant outages 3,[20][21][22] , and the subsequent economic consequences for energy markets and consumers. A probabilistic approach better explores the uncertainties in future climate and hydrological model projections and can properly characterize the spatial and temporal heterogeneity of natural hazards such as droughts.…”