Evaluation Method for Advanced Acid Rain Compliance Technology

Abstract

Technological innovation in emissions control of acid rain precursors has made possible increasingly stringent control requirements for coal‐fired power plants. A key challenge for potential process adopters is evaluation of the uncertainties in performance and cost inherent in any new control technology. Uncertainties can be explicitly characterized using probabilistic modeling techniques such as Monte Carlo simulation. A robust approach to evaluating advanced systems is illustrated via a case study based on the fluidized bed copper oxide process. An engineering performance and cost model of this process was developed. Selected input parameters were assigned probability distributions based on data analysis and expert judgments. The model then was exercised in a probabilistic modeling environment. The modeling applications illustrate how uncertainty may be included in process evaluation. In particular, the likely cost savings and risks of a new technology compared to conventional technology can be estimated under varying design and uncertainty assumptions. The results can be used for decisions regarding process design trade‐offs, technology selection, and research planning in the face of uncertainty.