## 4 Conclusions  
The conversion from a base-load coal-fired power plant into an 80%-load biomass CHP will, as expected, result in a gross power decrease from 703 to 382 MW and a gross electric efficiency decrease from 45.4% to 30.8%, while the CHP efficiency increases from 41.5% to 65.3%. The uncertainty of these parameters stays more or less the same before and after the conversion. The steam quality indicators and furnace operation indicators also decrease after conversion, and all the related standard deviations decrease too, which shows that these parameters tend to be less uncertain for biomass than for coal combustion. Among the furnace parameters, the adiabatic flame temperature and the effective radiation temperature, however, show significant uncertainties and skewed probability distributions. This is a strong attention point in terms of boiler operation and maintenance. With the analysis of the Sobol' indices, it is shown that only 18 of the 242 input parameters for coal and 243 input parameters for biomass have a significant impact on the studied outputs, and 17 of the 18 impactful input parameters are the same for coal and biomass, but only 4 input parameters strongly dominate the impact on the uncertainties for coal outputs: carbon and hydrogen content of the fuel, LHV of the fuel, and the evaporator outlet temperature. For biomass, only 3 high impact input parameters are observed: carbon and hydrogen content of the fuel and LHV of the fuel. In this work, it is shown that the proposed methodology, combining expert judgment and SPCE for numerous unknown inputs and multiple outputs, can be used to assess the performances of complex thermodynamics systems under uncertainty. This method can be used to avoid a lack of information for high-fidelity simulation programs such as Thermoflex(r). If the retrofits of several similar power plants have to be modeled and simulated, the computational time can be drastically reduced after the first power plant is calculated because attention can be focused on the important input parameters, namely the input parameters with the highest Sobol' indices for the next power plants. In future works, the methodology should be applied to investigate the impact of daily and seasonal load changes on the performance of the power plant. Given the importance of the fuel characteristics, conversions to other bio-fuels, e-fuels, or their mixtures could also be investigated, including in other types of thermal assets that will play a role in future energy systems, such as combined cycles. Financial and carbon footprint aspects could be included as well in the KPIs. The use of stochastic processes could be investigated [47; 48]. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app131910751/s1](https://www.mdpi.com/article/10.3390/app131910751/s1)]([https://www.mdpi.com/article/10.3390/app131910751/s1](https://www.mdpi.com/article/10.3390/app131910751/s1)), The list of variable input parameters and the corresponding distributions for coal and biomass, all resulting data for coal and biomass, all resulting data of the LOOs and all the resulting Sobol indices, with supplementary graphs of the results. Conceptualization, R.D.M., D.C., A.S. and J.B.; Methodology, R.D.M., D.C., A.S. and J.B.; Software, R.D.M. and D.C.; Validation, R.D.M., D.C. and A.S.; Formal analysis, R.D.M., D.C. and A.S.; Investigation, R.D.M. and D.C.; Resources, R.D.M., A.S. and T.M. ; Data curation, R.D.M., D.C. and A.S.; Writing-original draft, R.D.M. and D.C.; Writing-review & editing, D.C., A.S. and J.B.; Visualization, R.D.M. and D.C.; Supervision, T.M. and J.B.; Project administration, R.D.M. ; Funding acquisition, J.B. All authors have read and agreed to the published version of the manuscript. This research was partly funded by the European Union's Horizon 2020 research and innovation program grant number 818349 and the Fonds de la Recherche Scientifique--FNRS [CR 40016260]. Not applicable.