Development of an intelligent decision support system for air pollution control at coal-fired power plants

Air pollution from power plants is responsible for some of the most pressing environmental problems today. Much research has been done on pollution control for power plants. Contemporary approaches to pollution control often take advantage of computer technology, but research on use of expert systems for power plant management is scarce. In this study an expert system was developed to assist power plant decision makers in selecting an economical and efficient pollution control system that meets new stringent emission standards. The study will also provide the key design parameters for such a system. A fuzzy relation model and a Gaussian dispersion model were integrated into this expert system. Using the fuzzy relation model, the system can quickly select feasible control methods according to the desired removal efficiency. The system will then identify the most cost effective control strategy according to economic considerations provided by users. To assess and ensure effectiveness of the selected method, ambient air quality is simulated using the Gaussian dispersion model and compared with required standards. The developed system was applied to a case study. The results generated show that the system is able to consider the trade-offs between environmental requirement and economic objective, decrease the possibility of pollutant risk, and help the power plant reduce environmental-related capital and operation costs.