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Related Experiment Videos

Optimization under variability and uncertainty: a case study for NOx emissions control for a gasification system.

Jianjun Chen1, H Christopher Frey

  • 1Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Campus Box 7908, Raleigh, North Carolina 27695-7908, USA.

Environmental Science & Technology
|January 27, 2005
PubMed
Summary

New methods distinguish between variability and uncertainty in process optimization, offering significant cost savings for Integrated Gasification Combined Cycle systems. Properly managing these factors can yield millions in annual benefits through improved design and dynamic control.

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Area of Science:

  • Process engineering
  • Optimization techniques
  • Environmental control

Background:

  • Integrated Gasification Combined Cycle (IGCC) systems face challenges in NOx emissions control.
  • Existing optimization methods often do not clearly distinguish between process variability and uncertainty.
  • This distinction is crucial for effective resource allocation and design decisions.

Purpose of the Study:

  • To develop and apply novel methods for process technology optimization that differentiate between variability and uncertainty.
  • To quantify the economic benefits of reducing uncertainty and managing variability in IGCC systems.
  • To compare the efficacy of different stochastic optimization approaches.

Main Methods:

  • Application of existing stochastic optimization (SO) and stochastic programming (SP) methods.

Related Experiment Videos

  • Demonstration of a coupled stochastic optimization and programming method.
  • Implementation of a two-dimensional stochastic programming method.
  • Case study analysis focused on NOx control in IGCC systems.

    • Main Results:

    • Reducing uncertainty before final design can yield an expected annual benefit of $240,000.
    • Dynamic process control, by addressing variability, can achieve annual savings of $1,000,000.
    • Distinctive treatment of variability and uncertainty in a case study estimated a mean annual benefit of $700,000 for dynamic process control, with a 95% confidence interval of $500,000 to $940,000.

    Conclusions:

    • Distinguishing between variability and uncertainty provides significant economic advantages in process optimization.
    • The developed methods are particularly valuable for large-scale projects where design improvements lead to substantial cost savings.
    • These approaches enhance decision-making for complex systems like IGCC, optimizing resource commitment and operational efficiency.