U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Improving Projections of Future Hydropower Changes in the Western United States
Published: March 22, 2019
Posted: May 23, 2019

Integrated modeling system with a new, process-based hydropower module accounts for both electric grid operations and environmental constraints.

The Science
Hydropower currently accounts for more than one-quarter of the electricity produced in the western United States, so there is considerable interest in understanding how this resource may evolve under changing environmental conditions. Previous estimates of future hydropower generation have generally been based either on statistical relationships deduced from historical hydropower production or on simplified process-based models. In this study, researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory enhanced a large-scale river-routing and water management model with a process-based hydropower module that accounts for reservoir operation constraints, grid operation constraints, and hydrometeorological simulation biases. The results of the study are generally consistent with previous assessments of how hydropower generation may change in the future, but with slightly weaker seasonal shifts and reduced uncertainties.

The Impact
By adding operational constraints on hydropower generation and using a two-step multiscale calibration, the approach used in this study produces more accurate projections of future hydropower changes in the western United States, which will be of value to regional power system planners. The design of the model, with explicit attention to operational constraints, also provides a platform for further exploration of coupled energy and water system dynamics.

Summary
In this study, the authors enhanced an integrated hydrological model (MOSART-WM) with an enhanced process-based hydropower module to predict future hydropower generation. The new module addresses several commonly underrepresented constraints, including (1) ecological spills, (2) penstock constraints to provide flexibility in electricity operations, and (3) biases in hydrometeorological simulations. By evaluating projections based on two radiative forcing scenarios (RCP4.5 and RCP8.5) and ten downscaled global Earth system models, the authors found that (1) potential hydropower generation is not projected to change substantially on an annual time scale in most of the study region; (2) at the seasonal time scale, systematic shifting of generation patterns can be observed in snowmelt-dominated regions; and (3) including more complex operations and constraints tends to reduce uncertainties, especially at the seasonal time scale. In the Pacific Northwest, where hydropower is the dominant electricity source, the predicted future shift in hydropower generation toward the spring season is about 10% lower than in regression-based projections. These results demonstrate the value of using a multisector, multiscale modeling approach to investigate complex system dynamics under time-evolving boundary conditions.

Contacts (BER PM)
Bob Vallario
Multisector Dynamics
bob.vallario@science.doe.gov

(PI Contact)
Nathalie Voisin
Pacific Northwest National Laboratory
nathalie.voisin@pnnl.gov

Ian Kraucunas
Pacific Northwest National Laboratory
ian.kraucunas@pnnl.gov

Funding
The integrated hydrologic simulations were conducted under the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory. The regional analysis and writing of the paper were supported by the U.S. Department of Energy, Office of Science, as part of the Multisector Dynamics, Earth and Environmental Modeling Program.

Publications
Zhou, T., N. Voisin, and T. Fu, “Non-stationary hydropower generation projections constrained by environmental and electricity grid operations over the western United States.” Environmental Research Letters 13(7):074035 (2018). [DOI: 10.1088/1748-9326/aad19f]

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Multisector Dynamics (formerly Integrated Assessment)

Division: SC-23 BER

 

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