Research on Low-carbon Operation Optimization Control of Coal-fired Units Based on Improved Genetic Algorithm

To achieve carbon emission reduction during the operation of coal-fired units, a parameter calculation model was established considering the carbon emission reduction intensity, and the influence of the change of multiple parameters such as exhaust temperature on the carbon emission reduction intensity of coal-fired units was analyzed. The model was applied to the carbon emission reduction analysis during the operation of a 300MW coal-fired unit under three working conditions of 60%, 75% and 90% load rate, and five parameters such as exhaust temperature were selected as optimization variables. A multi-objective optimization model with carbon emission and operation cost as optimization objectives was established, and the improved genetic algorithm was used to solve the problem. The results show that the boiler side controllable operation parameters are higher, the multi-objective operation control optimization method is better than the single objective optimization, and the optimization effect is more significant with the increase of load rate.