Quantifying the impact of furnace heat transfer parameter uncertainties on the thermodynamic simulations of a biomass retrofit. (1st January 2023)

• Record Type: Journal Article
• Authors: De Meulenaere, Roeland; Coppitters, Diederik; Maertens, Tim; Contino, Francesco; Blondeau, Julien
• Is Part Of: Thermal science and engineering progress. Volume 37(2023)
• Publication Date: 2023-01-01
• Subjects: Biomass -- Uncertainty quantification -- Thermodynamics -- Exergy -- Retrofit -- Furnace exit gas temperature; Heat engineering -- Periodicals; Heat engineering; Thermodynamics; Periodicals; 621.402
• DOI: 10.1016/j.tsep.2022.101592
• Languages: English
• ISSNs: 2451-9049

Abstract

Abstract: High-fidelity thermodynamic simulation software is available to perform detailed simulations of power plants. However, these models depend on many operating parameters the user must characterize to assess the power plant performances. Unfortunately, most parameters are underdetermined by experience: the validation of the model using field measurements does not allow for the complete determination of all parameters, notwithstanding the unavoidable uncertainties of the measurements themselves. These limitations can result in a drastic mismatch between simulated and actual performance and lead to biased, suboptimal decision-making. To address these limitations, we performed Uncertainty Quantification on key furnace heat transfer parameters to predict the thermodynamic performance of coal-fired power plants retrofitted to biomass (co-)firing under uncertain operating conditions. We used a high-fidelity Thermoflex® model to simulate the thermodynamic performance of the power plant, and we adopted Polynomial Chaos Expansion to perform Uncertainty Quantification in a computationally-efficient manner. Finally, we evaluated the effect of various fractions of biomass in the fuel (from 0 to 100%) on the performance, which provides additional information in the decision-making process during the retrofit of the power plant. The results illustrate that the uncertainty on the non-uniform radiant flux factor dominates the uncertainty on the power, efficiency and flue gas temperature, meaning that efforts should aim at reducing the epistemic uncertainty on the radiative heat flux in the boiler. Increasing the biomass fraction results in a decrease in the gross power and gross efficiency. The mean Furnace Exit Gas Temperature remains relatively stable, but reaches a minimum value at 60% biomass co-firing. In conclusion, Polynomial Chaos Expansion allows for a computationally-efficient probabilistic assessment of non-validated operational conditions, such as a fuel switch, in high-fidelity models for thermal power plants. Future work will focus on extending the number of uncertain parameters. Highlights: Uncertainty quantification was applied to a high-fidelity thermal power plant model. The uncertainty on the performance increases with an increasing biomass fraction. The gross power and gross efficiency decrease with an increasing biomass fraction. The Furnace Exit Gas Temperature is minimal at 60% biomass co-firing.