The invention relates to an electric dust removal
system optimization control method based on a
hybrid model. The optimization control method comprises a modeling method mixing electric dust removal
system mechanism and data, an electric dust removal
system variable working condition
energy consumption evaluation method and a system operation multi-parameter optimization method based on a group intelligent
algorithm; wherein through the modeling method mixing electric dust removal system mechanism and data, the particulate matter removal mechanism of the electric dust removal system is organically combined with the actual operation data, so that the accurate prediction of the outlet concentration under the variable working condition of the electric dust removal system is realized; throughthe electric dust removal system variable working condition
energy consumption evaluation method, the change rule of system
energy consumption under different parameters is obtained; and through the system operation multi-parameter optimization method based on a group intelligent
algorithm, the methods are combined to obtain the optimal energy injection strategy under the specific emission targetand the variable operation working condition. According to the method, the operation strategy of the electric dust removal system is innovated from the theory, the framework and the
algorithm layer, the problems of low model precision, even model mismatch, large energy consumption evaluation error, difficulty in operation parameter optimization and the like brought by the variable working condition, the multi-
electric field, the multi-pole matching mode and the like are solved, so that reliable energy-saving and efficient removal of particulate matters in industrial
flue gas is realized.