Description
As the share of variable renewable energy generation in the power system increases, there is a growing need for flexible resources to balance the resulting variability. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely

As the share of variable renewable energy generation in the power system increases, there is a growing need for flexible resources to balance the resulting variability. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to fill this balancing role for some time. Accordingly, accurate production cost modeling of the operational parameters of gas turbines will be increasingly crucial as these units are relied on more heavily for flexibility. This thesis explores the impact of three additional parameters—start-up profiles/costs, run-up rates, and forced outage rates—in the production cost modeling of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the publicly available National Renewable Energy Laboratory’s 118 bus test system, the study examines how higher the increase in parameter modeling affects outcomes such as the number of start-ups and shut-downs, ramping, total generation costs for open-cycle gas turbines, and system-wide costs in three variable renewable energy penetration scenarios. The outcome of replacing certain conventional generation units with newer and more flexible combustion turbines is also examined. The results suggest the importance of detailed parameter modeling and continued research on the formulation of production cost models for flexible generation resources such as combustion turbines.
Reuse Permissions
  • Downloads
    PDF (1.7 MB)
    Download count: 3

    Details

    Title
    • Assessing the Impact of Increased Parameter Modeling of Combustion Turbines in a Grid with Varying Renewable Energy Penetration Using PLEXOS
    Contributors
    Date Created
    2023
    Resource Type
  • Text
  • Collections this item is in
    Note
    • Partial requirement for: M.S., Arizona State University, 2023
    • Field of study: Electrical Engineering

    Machine-readable links