Control strategy for the combustion optimization for waste-to-energy incineration plant

Falconi, Franco; Guillard, Hervé; Capitaneanu, Stefan; Raïssi, Tarek

doi:10.1016/j.ifacol.2020.12.125

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…Watanabe et al [154] adopted a feedback control strategy with a fixed time window to achieve stability control. Furthermore, Falconi et al [155] introduced a stable closed-loop control system based on a linear quadratic regulator, verifying its effectiveness through simulation experiments.…”

Section: Siso Control (1) Furnace Temperature (Ft)mentioning

confidence: 99%

An Overview of Artificial Intelligence Application for Optimal Control of Municipal Solid Waste Incineration Process

Tang,

Wang,

Xia

et al. 2024

Sustainability

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Artificial intelligence (AI) has found widespread application across diverse domains, including residential life and product manufacturing. Municipal solid waste incineration (MSWI) represents a significant avenue for realizing waste-to-energy (WTE) objectives, emphasizing resource reuse and sustainability. Theoretically, AI holds the potential to facilitate optimal control of the MSWI process in terms of achieving minimal pollution emissions and maximal energy efficiency. However, a noticeable shortage exists in the current research of the review literature concerning AI in the field of WTE, particularly MSWI, hindering a focused understanding of future development directions. Consequently, this study conducts an exhaustive survey of AI applications for optimal control, categorizing them into four fundamental aspects: modeling, control, optimization, and maintenance. Timeline diagrams depicting the evolution of AI technologies in the MSWI process are presented to offer an intuitive visual representation. Each category undergoes meticulous classification and description, elucidating the shortcomings and challenges inherent in current research. Furthermore, the study articulates the future development trajectory of AI applications within the four fundamental categories, underscoring the contribution it makes to the field of MSWI and WTE.

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Section: Siso Control (1) Furnace Temperature (Ft)mentioning

confidence: 99%

An Overview of Artificial Intelligence Application for Optimal Control of Municipal Solid Waste Incineration Process

Tang,

Wang,

Xia

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…The possible reason for the rebound of water vapour at 2.8 m to 7 m to be occurred is the further breakdown of remaining H2 molecules to formed H2O [24]. There are also possibilities of accumulation of water vapour at the incinerator wall and drips back to the grate to be react again [28].…”

Section: Water Vapour Mass Fraction Under Different Air Inlet Tempera...mentioning

confidence: 99%

Sustainable Energy from Waste: A Feasibility Study in Miri, Malaysia

Chua,

Hashim,

Downmore

et al. 2023

Ind. Domest. Waste Manag.

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The growth of urban populations, industrialization, and economic development has led to a surge in solid waste production. When local recycling infrastructure falls short, much of this waste ends up in landfills, causing environmental and social challenges. This study aims to assess the feasibility of converting municipal solid waste (MSW) into energy, with a focus on combustion chamber modeling in Miri, Sarawak. Data on MSW composition are obtained from secondary sources. Ansys Fluent software is used to model the combustion chamber, and simulations are conducted to explore temperature, turbulence, and species distribution. MSW composition illustrates higher substantial fractions, with 39.8% being food waste, followed by 20.7% plastic/rubber. Calorific values range from 4652 kJ/kg for food waste to 32564 kJ/kg for plastic/rubber. Combustion simulations result in maximum flue gas temperatures of 1500 °C, 1200 °C, and 1800 °C under varying air inlet conditions. Turbulence intensities on the grate range from 125% to 174% for these air inlet configurations. The study concludes that moisture content significantly affects calorific value and heat generation during combustion. Higher turbulence intensities lead to increased reaction rates and heat generation, improving the energy efficiency of the process.

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Performance Improvement of Waste to Energy Plant by Stepped Cyclic Operation of RAM Feeder

Srivastava,

Syal

2024

Proceedings of 5th International Conference on Resources and Environmental Research—ICRER 2023

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Control strategy for the combustion optimization for waste-to-energy incineration plant

Cited by 7 publications

References 8 publications

An Overview of Artificial Intelligence Application for Optimal Control of Municipal Solid Waste Incineration Process

An Overview of Artificial Intelligence Application for Optimal Control of Municipal Solid Waste Incineration Process

Sustainable Energy from Waste: A Feasibility Study in Miri, Malaysia

Performance Improvement of Waste to Energy Plant by Stepped Cyclic Operation of RAM Feeder

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