Acid Gas Removal Unit in Waste-to-energy Plants: Data-driven Models for Advanced Control

Flue gas cleaning is a crucial step in waste-to-energy (WtE) plants that process municipal solid waste. This paper analyzes the acid gas removal line of an Italian WtE plant, based on the injection of dry sorbents (calcium hydroxide Ca(OH)2 and sodium bicarbonate NaHCO3) for the abatement of hydrogen chloride, HCl. The aim of the study is to develop different data-driven models for the description of the acid gas treatment process with the final goal of implementing them in model-based controllers for optimizing the feed rate of alkaline reactants thus minimizing solid waste production. System identification and validation techniques have been applied to process data. Different input-output and state-space models are identified with the optimization of related model orders and validated on different routine data. The comparison of two system models (sequential and holistic) evidenced the importance of measuring additional internal variables to maintain a low system order. Anyway, results appear reliable and promising for control purposes, making possible different modeling approaches and control structures.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-07
DOI
https://doi.org/10.5281/zenodo.8093893
Primary Topic
Tree-ring climate responses
Type
article
Field-Weighted Citation Impact
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article

Acid Gas Removal Unit in Waste-to-energy Plants: Data-driven Models for Advanced Control

Zenodo (CERN European Organization for Nuclear Research)
Tree-ring climate responses
article

Acid Gas Removal Unit in Waste-to-energy Plants: Data-driven Models for Advanced Control

article en

Abstract

Flue gas cleaning is a crucial step in waste-to-energy (WtE) plants that process municipal solid waste. This paper analyzes the acid gas removal line of an Italian WtE plant, based on the injection of dry sorbents (calcium hydroxide Ca(OH)2 and sodium bicarbonate NaHCO3) for the abatement of hydrogen chloride, HCl. The aim of the study is to develop different data-driven models for the description of the acid gas treatment process with the final goal of implementing them in model-based controllers for optimizing the feed rate of alkaline reactants thus minimizing solid waste production. System identification and validation techniques have been applied to process data. Different input-output and state-space models are identified with the optimization of related model orders and validated on different routine data. The comparison of two system models (sequential and holistic) evidenced the importance of measuring additional internal variables to maintain a low system order. Anyway, results appear reliable and promising for control purposes, making possible different modeling approaches and control structures.

Zenodo (CERN European Organization for Nuclear Research)
University of Pisa (IT)
Industry, innovation and infrastructure
Openalex Percentile: Top 100%
Tree-ring climate responses
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