Data-driven Models for Advanced Control of Acid Gas Treatment in Waste-to-energy Plants

This paper presents a study of identification and validation data-driven models for the description acid gas treatment process, key step flue cleaning in waste-to-energy plants. The removal line an Italian plant, based on injection hydrated lime, Ca(OH)2, abatement hydrogen chloride, HCl, is investigated. final goal to minimize feed rate reactant needed achieve required HCl performance, also reducing as consequence production solid process residues. Process data are collected during dedicated plant tests carried out by imposing Generalized Binary Noise (GBN) sequences flow Ca(OH)2. Various input-output state-space identified with success, related model orders optimized. then validated different datasets routine operation. proposed modeling approach appears reliable promising control purposes, once implemented into advanced model-based structures.