Intelligent Combustion Control in Waste-to-Energy Facilities: Enhancing Efficiency and Reducing Emissions Using AI and IoT

Autor: Dongmin Shin, Jaeho Lee, Jihoon Son, Yongkeun Yun, Yoonchan Song, Jaeman Song
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Energies, Vol 17, Iss 18, p 4634 (2024)
Druh dokumentu: article
ISSN: 1996-1073
DOI: 10.3390/en17184634
Popis: Expanding waste-to-energy (WtE) facilities is difficult, and with tightening incineration regulations, improvements in WtE facility operations are required to dispose of waste that is increasing by an average of 4.8% annually. To achieve this, an intelligent combustion control (ICC) system was studied using digital technologies such as the Internet of Things and artificial intelligence to improve the operation of WtE facilities. The ICC system in this study is composed of three modules: perception, decision, and control. Perception: collecting and visualizing digital data on the operating status of WtE facilities; Decision: using AI to propose optimal operation methods; Control: automatically controlling the WtE facility according to the AI-suggested optimization methods. The ICC system was applied to the “G” WtE facility, a solid waste WtE facility operating in Gyeonggi province, Republic of Korea, and the digital data collected over six months showed high quality, with low delay and a data loss rate of only 0.12%. Additionally, in January 2024, the ICC system was used to automatically control the second forced draft fan and induced draft fan over a four-day period. As a result, the incinerator flue gas temperature decreased by 0.66%, steam flow rate improved by 2.41%, power generation increased by 3.09%, CO emissions were reduced by 60.72%, and NOx emissions decreased by 7.33%. Future research will expand the ICC system to include the automatic control of the first forced draft fan and the operation time of the stoker.
Databáze: Directory of Open Access Journals
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