Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models

Research output: NRELTechnical Report

Abstract

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies - using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.
Original languageAmerican English
Number of pages53
DOIs
StatePublished - 2024

NREL Publication Number

  • NREL/TP-6A20-87161

Keywords

  • Annual Technology Baseline (ATB)
  • bottom-up cost modeling
  • capacity expansion modeling
  • component-level cost modeling
  • Cost and Scaling Model (CSM)
  • geospatial data science
  • geospatial supply curve modeling
  • Land-based Balance-of-System Systems Engineering (LandBOSSE) model
  • least-cost optimization for plant layout
  • location-specific wind plant layout
  • power sector modeling
  • Renewable Energy Deployment System (ReEDS) model
  • Renewable Energy Potential (reV) model
  • scenario analysis
  • siting constraints
  • technoeconomic analysis
  • turbine choice
  • wind energy
  • wind energy deployment projections
  • wind energy technical potential

Fingerprint

Dive into the research topics of 'Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models'. Together they form a unique fingerprint.

Cite this