One of the most critical factors affecting boiler efficiency and hazardous-gas-emission reduction is the volume of excess air mixed with fuel.A knowledge-based approach is proposed to model the efficiency of a 320-MW ...One of the most critical factors affecting boiler efficiency and hazardous-gas-emission reduction is the volume of excess air mixed with fuel.A knowledge-based approach is proposed to model the efficiency of a 320-MW natural-gas-fired steam power plant in Isfahan,Iran by applying fuzzy-modelling techniques to control the boiler efficiency.This model is based on fuel and air entering the boiler.First,the fuzzy-model structure is identified by applying the fuzzy rules obtained from an experienced human operator.The proposed method is then optimized using a genetic algorithm to increase the fuzzy-model accuracy.The results indicate that,by applying a genetic algorithm,the precision of the proposed fuzzy model increases.The error between the actual efficiency of the plant and the output efficiency of the proposed model is low.This model is developed by applying the fuzzy rules and modelling-related calculations.Finally,to optimize the efficiency of the boiler,a fuzzy proportional-integral controller is designed.The closed-loop control simulations are run by applying both the proposed controller and the manual controller to demonstrate the influence of the suggested method.The simulation outcomes indicate that the recommended controller adjusts the excess-air percentage correctly and increases the unit efficiency by 0.70%,significantly reducing fuel consumption.展开更多
文摘One of the most critical factors affecting boiler efficiency and hazardous-gas-emission reduction is the volume of excess air mixed with fuel.A knowledge-based approach is proposed to model the efficiency of a 320-MW natural-gas-fired steam power plant in Isfahan,Iran by applying fuzzy-modelling techniques to control the boiler efficiency.This model is based on fuel and air entering the boiler.First,the fuzzy-model structure is identified by applying the fuzzy rules obtained from an experienced human operator.The proposed method is then optimized using a genetic algorithm to increase the fuzzy-model accuracy.The results indicate that,by applying a genetic algorithm,the precision of the proposed fuzzy model increases.The error between the actual efficiency of the plant and the output efficiency of the proposed model is low.This model is developed by applying the fuzzy rules and modelling-related calculations.Finally,to optimize the efficiency of the boiler,a fuzzy proportional-integral controller is designed.The closed-loop control simulations are run by applying both the proposed controller and the manual controller to demonstrate the influence of the suggested method.The simulation outcomes indicate that the recommended controller adjusts the excess-air percentage correctly and increases the unit efficiency by 0.70%,significantly reducing fuel consumption.
