Due to complex process mechanism

frequently changeable inlet flue gas indices induced by upstream coking conditions

and severe interference of process unknowns

it is difficult to determine process indices by traditional exact mathematical models for the first domestic coking flue gas desulfurization and denitration integrated unit. A case-based reasoning method was proposed to optimize indices of the coking flue gas denitration process. Meanwhile

abrupt change of some correlation description indices

which was caused by coke oven reversion

may lead to deviation from results because single feature was used to describe current working condition in traditional case reuse method. A case retrieval and reuse method was further proposed from principal component regression multiple case fusion. The results of numerical simulation and application in the coking plant show that this method can appropriately obtain operating parameter settings at different characteristic conditions

effectively control NOx outlet concentration within process specification

and greatly reduce power consumption of the equipment.