Optimized Operation Strategy of Desulfurization Wastewater Treatment System Based on KFCM

In order to reduce the energy consumption of the thermal power unit desulfurization wastewater treatment system, energy efficiency analysis of the system operation data and optimization search of the key parameters of the desulfurization wastewater are carried out, and an optimal operation strategy based on fuzzy clustering method is proposed, with lower wastewater treatment energy consumption as the objective function, and the fuzzy C-mean clustering method based on kernel is used to cluster the historical data with similar feature groups, and the clustering center is used as the optimization variable, and the optimal solution is obtained by iterative calculation. The historical operating data of FGD wastewater treatment system of a power plant in Hubei Province are analyzed. Compared with the actual operation, the actual optimal reference state under this condition can reduce the energy consumption by at least $11.7 \%$ under the premise of ensuring that the desulfurization wastewater meets the emission index, thus improving the economy of the plant and the system operation efficiency. The results show that this operation optimization strategy can be used to build a working condition library of desulfurization wastewater treatment system and provide optimization guidance.