The invention discloses a grey wolf
algorithm flue gas
waste heat control method and
system introducing
exhaust gas temperature prediction constraint, and the method comprises the steps: firstly building a thermodynamic
simulation model of a
flue gas
waste heat system, collecting the working condition data of a unit in real time, and calibrating the model; under the targets of power supply
coal consumption minimization,
waste heat recovery rate maximization and the like, an
exhaust gas temperature prediction result is used as a dynamic constraint, a grey wolf optimization
algorithm is adopted to carry out multi-target optimization on parameters such as the opening degree of a
flue gas baffle, the
water supply distribution proportion of an
economizer and the
water flow of an
air heater, and multiple regression or a BP neural
network model is utilized to predict the
exhaust gas temperature. If the predicted value is lower than the safety
lower limit, dynamically adjusting the search direction to avoid an infeasible solution; and an optimization result is issued on line through a DCS
system, and closed-
loop control is realized. Compared with the prior art, on the premise that the safety of the exhaust gas temperature is guaranteed, the waste heat
utilization rate is remarkably increased, power supply
coal consumption is reduced, the capacity of adapting to different
coal qualities and load fluctuations in a self-learning mode is achieved, and the good
engineering application prospect is achieved.