Probabilistic Performance, Environmental, and Economic Evaluation of an Advanced Coal Gasification System

INTRODUCTION The acid rain provisions of the 1990 Clean Air Act Amendments (CAAA) provide new incentives for the development of power generation technology with low SO 2 emissions. Detailed evaluations of possible NO x and air toxics emission limits also are required by the CAAA in the next few years. Furthermore, reauthorization of other key environmental legislation, such as the Clean Water Act and RCRA, will be considered by Congress in the 1990s. Thus, an increasingly multi-pollutant and multi-media approach to waste minimization will be required. If coal is to continue to supply the major electricity needs for the U.S., there is a need for new coal-based power generation technologies that can comfortably comply with both current and possible future environmental regulations. Coal gasification systems are a promising approach for clean and efficient coal-based power generation. Integrated coal gasification combined cycle (IGCC) systems are capable of high thermal efficiencies, correspondingly reduced CO 2 emissions, and low emissions of acid rain precursors (i.e. SO 2 and NO x) compared to conventional coal-combustion based technologies. IGCC systems also are characterized by low particle emissions and potentially lower solid waste production than conventional coal-fired power plants with flue gas desulfurization and comparable sulfur removal efficiencies. However, there is still limited experience with IGCC systems, and many promising concepts have not yet been demonstrated in full-size and integrated plants. The uncertain nature of limited performance and cost data for first generation systems, coupled with uncertainties associated with alternative process configurations, suggests a strong need for systematic analysis of uncertainty in evaluating the risks and potential pay-offs of alternative concepts. To explicitly represent uncertainties in IGCC systems, a probabilistic modeling approach has been developed and applied. This approach features: (1) development of sufficiently detailed engineering models of performance, emissions, and cost; (2) implementation of the models in a probabilistic modeling environment; (3) development of quantitative representations of uncertainties in specific model parameters based on literature review, data analysis, and elicitation of technical judgments from experts; and (4) modeling applications for cost estimating, risk assessment, and research planning. An advanced IGCC system featuring hot gas cleanup technology is analyzed and evaluated. The evaluation here focuses in particular on control of NO x emissions from an air-blown gasifier-based system with hot gas cleanup. Results will illustrate the types of insights provided by a probabilistic method for evaluating advanced process technologies.