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Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

Author

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  • Svetlana Lawrence

    (Idaho National Laboratory, 1955 Fremont Ave., Idaho Falls, ID 83415, USA
    Department of Systems Engineering, Walter Scott, Jr. College of Engineering, Colorado State University, Fort Collins, CO 80523, USA)

  • Daniel R. Herber

    (Department of Systems Engineering, Walter Scott, Jr. College of Engineering, Colorado State University, Fort Collins, CO 80523, USA)

  • Kamran Eftekhari Shahroudi

    (Department of Systems Engineering, Walter Scott, Jr. College of Engineering, Colorado State University, Fort Collins, CO 80523, USA)

Abstract

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

Suggested Citation

  • Svetlana Lawrence & Daniel R. Herber & Kamran Eftekhari Shahroudi, 2025. "Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy," Energies, MDPI, vol. 18(8), pages 1-33, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2048-:d:1636017
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